Quantitative AV-45 PET Imaging for Assessing Treatment Response to Lecanemab and Deep Cervical Lymphatic–Venous Anastomosis in Alzheimer’s Disease

Quantitative AV-45 PET Imaging for Assessing Treatment Response to Lecanemab and Deep Cervical Lymphatic–Venous Anastomosis in Alzheimer’s Disease | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Quantitative AV-45 PET Imaging for Assessing Treatment Response to Lecanemab and Deep Cervical Lymphatic–Venous Anastomosis in Alzheimer’s Disease LUQIANG jin, Xinyu Wang, Fahuan Song, Jie Hou, Yueqian Bi, Xuehua Wen, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8821582/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objectives This study aimed to validate the clinical utility of visual and software quantitative AV-45 PET analyses and to compare treatment effects between lecanemab and deep cervical lymphatic–venous anastomosis (dcLVA). Methods This retrospective cohort study included patients with AD who received 6 months of lecanemab therapy or dcLVA surgery between July 2024 and July 2025. AV-45 PET was performed 1 week before and 6 months after treatment. Standardized uptake value ratios (SUVRs) and Centiloid values (CLs) were obtained using visual and software-based quantitative analyses. Agreement between methods was assessed using Cohen’s kappa and intraclass correlation coefficients (ICC). Receiver operating characteristic (ROC) analysis evaluated diagnostic performance. Logistic regression analyses were conducted using an Informant Questionnaire on Cognitive Decline in the Elderly score ≥ 3.3 as the outcome. Results Baseline demographic, clinical, and imaging characteristics were comparable between groups (all P > 0.05). Visual AV-45 PET assessment showed good agreement with Centiloid-based quantification (kappa = 0.72; ICC = 0.663). ROC analysis identified ΔCL as the optimal imaging marker (area under the curve = 0.764, P = 0.026), with a cutoff of − 11.5%. ΔCL ≥ − 11.5% independently predicted cognitive decline in the lecanemab group (odds ratio = 10.281, 95% confidence interval = 1.289–82.005, P = 0.028). Cognitive decline occurred less frequently in the lecanemab group than in the dcLVA group (23.5% vs. 81.8%, P < 0.001). ΔCL differed significantly between groups ( P = 0.006), whereas ΔSUVR did not. Conclusions Visual and Centiloid-based AV-45 PET analyses show good concordance and clinical value for monitoring AD treatment response. ΔCL is a robust quantitative marker of lecanemab efficacy, which appears superior to dcLVA in reducing cerebral Aβ burden and delaying cognitive decline. AV-45 positron emission tomography Alzheimer’s disease lecanemab deep cervical lymphatic–venous anastomosis Centiloid scale Figures Figure 1 Highlights What are the main findings? AV-45 PET visual assessment and Centiloid-based quantification showed good concordance, with ΔCL emerging as the most sensitive imaging marker for monitoring treatment response to lecanemab in Alzheimer’s disease. Lecanemab significantly reduced cognitive decline and cerebral amyloid-β burden compared with deep cervical lymphatic–venous anastomosis, which showed limited pathological and clinical benefit. What are the implications of the main findings? The Centiloid change value (ΔCL) provides a robust, quantitative imaging biomarker for predicting cognitive outcomes and evaluating anti-amyloid therapeutic efficacy in clinical practice and trials. These findings support lecanemab as a more effective disease-modifying strategy than dcLVA and underscore the need for rigorous imaging-based endpoints when assessing alternative surgical interventions in Alzheimer’s disease. 1. Introduction Alzheimer’s disease (AD) is the most prevalent neurodegenerative disorder worldwide and a leading cause of cognitive impairment[ 1 ]. Currently, approximately 50 million individuals are affected by dementia globally, and this number is projected to triple by 2050 [ 2 ]. Clinically, AD is characterized by progressive cognitive decline and functional deterioration. Its hallmark neuropathological features include extracellular amyloid plaques formed by abnormal deposition of β-amyloid (Aβ) peptides and intracellular neurofibrillary tangles resulting from tau protein hyperphosphorylation [ 3 – 4 ]. These pathological processes ultimately lead to synaptic dysfunction, neuronal loss, and irreversible cognitive impairment, imposing a substantial medical, social, and economic burden on patients, caregivers, and healthcare systems. In recent years, Aβ-targeted pharmacotherapy and surgical approaches aimed at enhancing cerebral lymphatic clearance have emerged as major research directions in AD treatment. Lecanemab (BAN2401), a humanized immunoglobulin G1 (IgG1) monoclonal antibody, selectively binds soluble Aβ aggregates, reduces cerebral amyloid burden, and has demonstrated clinical efficacy in delaying cognitive decline in early-stage AD. Based on these findings, lecanemab has been approved for the treatment of mild AD and AD-related mild cognitive impairment (MCI) [ 5 – 8 ]. In parallel, deep cervical lymphatic–venous anastomosis (dcLVA) has been proposed as a novel microsurgical strategy to enhance lymphatic drainage by creating a bypass between cervical lymphatic vessels and the venous system. Preliminary studies suggest that dcLVA may facilitate systemic waste clearance, reduce Aβ accumulation, and improve cognitive function [ 9 – 12 ]. However, the therapeutic mechanism of dcLVA in AD remains largely speculative. Evidence supporting its long-term efficacy is limited, standardized surgical protocols are lacking, and data from large, multicenter randomized controlled trials (RCTs) are absent, warranting cautious clinical interpretation [ 13 ]. As a noninvasive molecular imaging modality, 18 F-florbetapir (AV-45) positron emission tomography/computed tomography (PET/CT) enables in vivo localization and quantification of cerebral Aβ deposition, substantially advancing the diagnostic and monitoring capabilities for AD. AV-45 PET plays a critical role in elucidating AD pathophysiology and in assessing the therapeutic effects of Aβ-targeted interventions [ 14 , 15 ]. Compared with conventional neuropsychological assessments, which rely on subjective scoring and may be influenced by inter-observer variability, AV-45 PET provides direct, objective, and quantitative measures of core AD pathology, thereby offering a robust imaging biomarker for treatment evaluation [ 16 ]. Nevertheless, to date, no studies have employed AV-45 PET to directly compare the therapeutic effects of lecanemab and dcLVA, nor has the differential impact of these two interventions on cerebral Aβ burden been quantitatively assessed using paired pre- and post-treatment imaging. Against this background, the present study aims to validate the clinical utility of AV-45 PET for evaluating treatment response in AD. By systematically analyzing changes in imaging parameters before and after treatment, we further seek to elucidate differences in therapeutic efficacy between lecanemab and dcLVA, thereby providing objective imaging evidence to support individualized treatment selection for patients with AD. 2. Materials and Methods 2.1. Study Participants Clinical data from patients with AD who were diagnosed and treated at the Department of Neurology and the Department of Lymphatic Surgery of our hospital between July 2024 and July 2025 were retrospectively collected. This study was approved by the Ethics Committee of our hospital (Ethics Approval No.: QT2026011). Owing to the retrospective nature of the study, the requirement for written informed consent was waived. All procedures were conducted in accordance with the Declaration of Helsinki and relevant regulations governing the protection of patient privacy and medical data. 2.2. Inclusion and Exclusion Criteria Inclusion criteria (1) Fulfillment of the diagnostic criteria for AD dementia according to the 2018 Alzheimer’s Disease Research Framework (AT(N) system) issued by the National Institute on Aging–Alzheimer’s Association (NIA–AA) [ 17 ]; (2) Completion of AV-45 PET scans 1 week before treatment initiation and 6 months after treatment, with image quality sufficient for quantitative analysis of Aβ deposition; (3) Clear receipt of either lecanemab treatment (completion of 12 infusions) or deep cervical lymphatic–venous anastomosis (dcLVA) surgery, with a standardized treatment protocol and complete follow-up data; (4) Age between 55 and 80 years, regardless of sex; (5) Availability of complete and traceable clinical data, including medical history, laboratory findings, and Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) scores. Exclusion criteria (1) Presence of other neurodegenerative disorders (e.g., frontotemporal dementia, dementia with Lewy bodies) or severe structural brain lesions (e.g., intracerebral hemorrhage, brain tumors); (2) History of cervical surgery, cervical lymphadenopathy, or lymphatic malformations that could interfere with dcLVA implementation or outcome assessment; (3) Occurrence of treatment-related adverse events, including amyloid-related imaging abnormalities detected by magnetic resonance imaging (MRI); (4) Concomitant use of other Aβ-targeted agents, psychotropic medications, or drugs that could confound treatment efficacy during the study period; (5) Poor-quality AV-45 PET images, missing imaging data, or incomplete follow-up precluding reliable efficacy evaluation. 2.3. Study Design This study employed a retrospective cohort design. Baseline demographic and clinical data—including age, sex, disease duration and comorbidities—were extracted from the hospital’s electronic medical record system. Baseline AV-45 PET/CT scans were obtained 1 week prior to treatment initiation. All patients underwent a standardized diagnostic workflow and were assigned to either the lecanemab treatment group (pharmacological group) or the dcLVA treatment group (surgical group) based on the therapeutic intervention received. Patients in the lecanemab group were administered lecanemab at a dose of 10 mg/kg every 2 weeks for a total duration of 6 months [ 18 ]. All dcLVA procedures were performed by the same neurosurgeon with more than 5 years of microsurgical experience to ensure procedural consistency and standardization. Follow-up AV-45 PET/CT imaging was conducted after 6 months of treatment, accompanied by comprehensive clinical assessment. Given the relatively small sample size of the dcLVA group and the associated risk of insufficient statistical power and model instability, analyses comparing AV-45 PET visual assessment with Centiloid-based quantification and identifying independent predictors of treatment response were restricted to the lecanemab group. 2.4. AV-45 PET/CT Scanning Protocol All PET/CT images were acquired using a Siemens Biograph 64 PET/CT scanner (Munich, Germany). The radiochemical purity of AV-45 exceeded 95%. Following intravenous administration of AV-45 at a dose of 3.7–5.55 MBq/kg, patients rested quietly for 40–60 min while avoiding head movement. CT acquisition parameters included a slice thickness of 1 mm, tube voltage of 120 kV, and automatic tube current modulation. PET data were acquired in three-dimensional mode for 20 min. Image reconstruction was performed using the ordered subset expectation maximization (OSEM) algorithm, and attenuation correction was applied using CT-derived attenuation maps. Image interpretation was conducted retrospectively and independently by two nuclear medicine physicians, each with more than 5 years of diagnostic experience, who were blinded to clinical information and treatment allocation. Inter-reader agreement was assessed using the intraclass correlation coefficient (ICC). In cases of significant disagreement, a third senior physician provided adjudication. For visual analysis, bilateral regions of interest (ROIs) were defined in the frontal, parietal, lateral temporal, medial temporal, and occipital cortices, as well as the posterior cingulate gyrus and precuneus. The cerebellar cortex served as the reference region for calculation of standardized uptake value ratios (SUVRs). For software-based quantitative analysis, the “Cerebral Neuroimaging Quantitative Analysis System(Shanghai, China)” was used for standardized image processing and computation of Centiloid values (CLs), with a CL ≤ 12 indicating the absence of pathological Aβ deposition [ 19 ]. The baseline AV-45 PET scan was defined as PET1, and the post-treatment scan as PET2. The percentage change in SUVR between scans was calculated as: ΔSUVR (%) = [(SUVR 2 − SUVR 1 ) / SUVR 1 ] ⋅ 100% Negative values indicate reduced Aβ deposition, whereas positive values indicate increased deposition. The change in Centiloid value between scans was defined as ΔCL. 2.5. IQCODE Assessment Cognitive status was evaluated using the IQCODE following completion of the standardized treatment period. Assessments were conducted by neurologists who were blinded to PET imaging results. The interviewees were primary caregivers who had provided care for at least 6 months and had contact with the patient for a minimum of 10 h per week. The IQCODE comprises 26 items, each rated on a five-point scale according to perceived cognitive change (1 = markedly improved, 5 = markedly declined), with higher scores indicating greater cognitive impairment. The mean item score was calculated for each patient, and a mean score ≥ 3.3 was used as the predefined threshold for significant cognitive decline [ 20 ]. 2.6. Statistical Analyses Statistical analyses were performed using SPSS software (version 27.0; IBM Corp., Armonk, NY, USA). Continuous variables are presented as mean ± standard deviation (SD) or median with interquartile range (IQR), as appropriate. Agreement between visual assessment and quantitative imaging parameters was evaluated using Cohen’s kappa coefficient. Receiver operating characteristic (ROC) curve analysis was performed to assess diagnostic performance, with calculation of the area under the curve (AUC). Univariate binary logistic regression analyses were conducted using semi-quantitative parameters derived from visual assessment and quantitative metrics obtained from software-based analysis as independent variables. Variables demonstrating significance in univariate analysis were subsequently entered into multivariate binary logistic regression models to identify independent predictors of cognitive decline as defined by the IQCODE threshold. Categorical variables were compared using Fisher’s exact test, and continuous variables were compared using the Mann–Whitney U test. All statistical tests were two-sided, and a P value < 0.05 was considered statistically significant. 3. Results 3.1. Baseline Characteristics of Study Participants Between July 2024 and July 2025, a total of 327 patients were initially screened, including 80 patients in the lecanemab treatment group and 247 patients in the dcLVA surgical group. Of these, 47 patients (34 in the lecanemab group and 13 in the dcLVA group) met all inclusion and exclusion criteria and completed the required follow-up, and were therefore included in the final analysis. The final cohort comprised 21 men and 26 women, with a mean age of 68.4 ± 9.1 years. Baseline demographic characteristics, disease duration, comorbidities, concomitant AD–approved medications, and baseline AV-45 PET imaging parameters were comparable between the two treatment groups. No statistically significant differences were observed between groups for any baseline variable (all P > 0.05), indicating good baseline comparability (Table 1 ). Table 1 Baseline characteristics of patients Characteristics Lecanemab Treatment Group (n = 34) dcLVA Treatment Group (n = 13) Age (years) 69.3 ± 9.3 65.8 ± 8.1 Sex, n (%) - Men 17 (50.0) 4 (30.8) - Women 17 (50.0) 9 (69.2) Disease duration (years) 2.47 ± 1.05 3.08 ± 1.32 Underlying diseases, n (%) - Hypertension 8 (23.5) 5 (38.4) - Diabetes mellitus 3 (8.8) 1 (7.7) - Coronary heart disease 1 (2.9) 0 (0.0) Concomitant AD-approved drugs at baseline, n (%) 19 (55.9) 10 (76.9) Baseline AV-45 PET parameters - SUVR 1 Frontal lobe 1.41 ± 0.46 1.52 ± 0.32 - SUVR 1 Parietal lobe 1.38 ± 0.43 1.54 ± 0.49 - SUVR 1 Lateral temporal lobe 1.35 ± 0.42 1.38 ± 0.21 - SUVR 1 Medial temporal lobe 1.13 ± 0.41 1.13 ± 0.19 - SUVR 1 Posterior cingulate gyrus 1.44 ± 0.45 1.39 ± 0.23 - SUVR 1 Precuneus 1.41 ± 0.49 1.49 ± 0.48 - SUVR 1 Occipital lobe 1.50 ± 0.51 1.64 ± 0.32 - SUVR 1 Cerebellum 0.95 ± 0.21 0.92 ± 0.17 - Centiloid value (CL 1 ) 22.8 ± 36.9 20.1 ± 36.7 Note: Continuous variables are presented as mean ± standard deviation. SUVR₁ and CL₁ represent baseline semi-quantitative AV-45 PET parameters. SUVR₁ values were calculated using the cerebellar cortex as the reference region for each specified ROI. AD, Alzheimer’s disease; dcLVA, deep cervical lymphatic–venous anastomosis; PET, positron emission tomography; SUVR, standardized uptake value ratio; ROI, region of interest. 3.2. Consistency and Diagnostic Efficacy of AV-45 PET Visual Analysis and Centiloid Value Assessment After 6 months of standardized treatment, 8 patients (23.5%) in the lecanemab treatment group and 9 patients (81.8%) in the dcLVA treatment group had an IQCODE score ≥ 3.3 indicating significant cognitive decline. In the lecanemab treatment group, agreement between AV-45 PET visual assessment and Centiloid-based quantification for evaluating cerebral Aβ deposition (negative: CL ≤ 12; weakly positive: 12 < CL < 30; positive: CL ≥ 30) was substantial. The Cohen’s kappa coefficient was 0.72 (95% confidence interval [CI]: 0.50–0.94), and the ICC was 0.663, indicating good consistency between the two assessment methods. ROC curve analysis was performed in the lecanemab treatment group to evaluate the diagnostic performance of ΔSUVR across different brain regions and ΔCL for predicting cognitive decline. The optimal cutoff values, corresponding sensitivities, specificities, AUCs, and 95% CIs are summarized in Table 2 . Among all parameters examined, ΔCL demonstrated the highest diagnostic performance, with an AUC of 0.764 ( P = 0.026) and an optimal cutoff value of − 11.5%. The ROC curves illustrating the comparative diagnostic performance of AV-45 PET–derived parameters, including ΔCL and regional ΔSUVR measures, are shown in Fig. 1 . Table 2 Optimal cutoff values of relevant parameters calculated by ROC curve analysis and Youden Index in the lecanemab treatment group Parameter Cutoff Value Sensitivity (%) Specificity (%) AUC P Value 95% CI ΔSUVR Frontal lobe −18.5% 87.5 42.3 0.618 0.320 (0.407–0.829) ΔSUVR Parietal lobe −9.5% 62.5 88.5 0.733 0.049* (0.520–0.947) ΔSUVR Medial temporal lobe −2.5% 50.0 76.9 0.589 0.453 (0.346–0.832) ΔSUVR Lateral temporal lobe −1.5% 62.5 69.2 0.630 0.273 (0.387–0.872) ΔSUVR Posterior cingulate gyrus −1% 50.0 76.9 0.562 0.598 (0.336–0.789) ΔSUVR Precuneus −7.5% 50.0 73.1 0.538 0.745 (0.296–0.781) ΔSUVR Occipital lobe −13% 50.0 84.6 0.659 0.180 (0.416–0.901) ΔSUVR Cerebellum −1% 50.0 65.4 0.514 0.903 (0.266–0.762) ΔCL −11.5% 75.0 84.6 0.764 0.026* (0.558–0.971) AD, Alzheimer’s disease; AUC, area under the curve; CI, confidence interval; ΔCL, Centiloid change value; ΔSUVR, standardized uptake value ratio change rates (A,B) ROC curves of regional standardized uptake value ratio change rates (ΔSUVR) across multiple cortical regions, including the frontal, parietal, lateral temporal, medial temporal, posterior cingulate, precuneus, occipital cortex, and cerebellum. (C) ROC curves comparing the diagnostic performance of the Centiloid change value (ΔCL) with representative regional ΔSUVR parameters. ΔCL demonstrated superior diagnostic accuracy for predicting cognitive decline, as reflected by a higher area under the curve (AUC). Cognitive decline was defined as an Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) score ≥ 3.3. ROC-derived cutoff values, sensitivities, specificities, AUCs, and 95% confidence intervals are provided in Table 2 . 3.3 Logistic Regression Analysis of AV-45 PET Parameters for Predicting Cognitive Decline in AD Patients Treated with Lecanemab Univariate binary logistic regression analysis was performed with cognitive decline, defined as an IQCODE score ≥ 3.3, as the dependent variable. In patients treated with lecanemab monotherapy, a ΔCL ≥ − 11.5% was significantly associated with an increased risk of cognitive decline (odds ratio [OR] = 10.000, 95% CI: 1.585–63.097, P = 0.014) (Table 3 ). To further control for potential confounding factors and identify independent predictors, variables with P < 0.10 in the univariate analysis (including ΔSUVR in the precuneus ≥ − 7.5% and ΔSUVR in the posterior cingulate gyrus ≥ − 1%), as well as clinically relevant covariates (age, sex, underlying diseases, and concomitant AD–approved medications), were entered into a multivariate binary logistic regression model. After adjustment, ΔCL ≥ − 11.5% remained independently associated with cognitive decline in patients receiving lecanemab monotherapy (adjusted OR = 10.281, 95% CI: 1.289–82.005, P = 0.028). No regional ΔSUVR parameter retained statistical significance in the multivariate model. Table 3 Univariate and Multivariate Logistic Regression Analyses Predicting Cognitive Decline in the Lecanemab Treatment Group Variables Univariate Analysis Multivariate Analysis OR 95% CI P Value OR 95% CI P Value Age 0.514 0.101–2.614 0.423 1.202 0.154–9.368 0.861 Sex 2.200 0.371–13.038 0.385 2.280 0.278–18.709 0.443 Underlying diseases 8.333 0.644–107.851 0.105 - - - Disease duration 1.350 0.258–7.072 0.722 - - - Concomitant AD-approved drugs at baseline 1.429 0.281–7.261 0.667 - - - ΔSUVR Frontal lobe ≥ − 18.5% 4.375 0.466–41.067 0.196 - - - ΔSUVR Parietal lobe ≥ − 9.5% 3.750 0.716–19.644 0.118 - - - ΔSUVR Medial temporal lobe ≥ − 2.5% 1.167 0.239–5.698 0.849 - - - ΔSUVR Lateral temporal lobe ≥ − 1.5% 1.667 0.328–8.462 0.538 - - - ΔSUVR Posterior cingulate gyrus ≥ − 1% 1.167 0.239–5.698 0.849 1.324 0.082–21.348 0.843 ΔSUVR Precuneus ≥ − 7.5% 0.625 0.127–3.081 0.065 0.561 0.037–8.566 0.678 ΔSUVR Occipital lobe ≥ − 13% 1.105 0.179–6.821 0.914 - - - ΔSUVR Cerebellum≥-1% 0.397 0.070–2.243 0.296 - - - ΔCL ≥ − 11.5% 10.000 1.585–63.097 0.014* 10.281 1.289–82.005 0.028* AD, Alzheimer’s disease; CI, confidence interval; ΔCL, Centiloid change value; ΔSUVR, standardized uptake value ratio change rates; OR, odds ratio. 3.4 Comparison of Therapeutic Outcomes Between Lecanemab and dcLVA Surgery After 6 months of standardized treatment, therapeutic outcomes between the lecanemab treatment group and the dcLVA surgical group were compared using both clinical and AV-45 PET–based measures. For clinical outcomes, cognitive decline was defined as an IQCODE score ≥ 3.3. Fisher’s exact test demonstrated that the proportion of patients experiencing cognitive decline was significantly lower in the lecanemab group than in the dcLVA group (23.5% vs. 81.8%), indicating a markedly reduced risk of cognitive deterioration in patients treated with lecanemab ( P < 0.001). For imaging outcomes, no significant differences were observed between groups in the distribution of AV-45 PET visual assessment categories or in regional ΔSUVR. In contrast, a significant intergroup difference was detected for the change in ΔCL. Mann–Whitney U testing showed that ΔCL differed significantly between the lecanemab and dcLVA groups ( U = 337.0, Z = 2.759, P = 0.006), with a moderate effect size (r = 0.40). The lecanemab group exhibited a greater reduction in cerebral Aβ burden, whereas the dcLVA group showed a tendency toward increased Aβ deposition (Table 4 ). Table 4 Comparison of Clinical and AV-45 PET Outcomes Between the Lecanemab Monotherapy Group and the dcLVA Treatment Group Outcome Type Indicators Lecanemab Treatment Group (n = 34) dcLVA Treatment Group (n = 13) Test Statistic P Value Clinical outcome IQCODE score ≥ 3.3 (significant cognitive decline) 8 (23.5%) 9 (81.8%) - < 0.001* AV-45 PET outcomes ΔSUVR Frontal lobe (%) −6.47 ± 40.38 −1 (− 28.00, 15.50) U = 263 0.318 ΔSUVR Parietal lobe (%) −13.5 ± 35.43 −1 (− 24.00, 33.00) U = 241.5 0.626 ΔSUVR Lateral temporal lobe (%) −4.41 ± 29.95 −4 (− 16.00, 19.50) U = 258.0 0.379 ΔSUVR Medial temporal lobe (%) −5.44 ± 33.09 −4 (− 30.00, 7.50) U = 229.5 0.840 ΔSUVR Posterior cingulate gyrus (%) −0.06 ± 37.79 −2 (− 19.50, 11.00) U = 252.5 0.454 ΔSUVR Precuneus (%) −0.26 ± 34.31 −2 (− 17.50, 26.50) U = 242.0 0.617 ΔSUVR Occipital lobe (%) −1.53 ± 32.80 −1 (− 21.50, 9.50) U = 215.5 0.896 ΔSUVR Cerebellum (%) 3.32 ± 31.05 −4 (− 20.00, 8.50) U = 209.0 0.775 ΔCL (%) −0.44 ± 150.55 13 (− 15.50, 168.00) U = 337.0 0.006* Notes: 1. Categorical data are presented as n (%). Continuous variables are expressed as mean ± standard deviation for the lecanemab group and as median (interquartile range, IQR) for the dcLVA group, reflecting distributional differences and sample size. 2. ΔSUVR and ΔCL represent percentage changes between baseline and post-treatment scans. Negative ΔCL values indicate reduced amyloid-β deposition, whereas positive values indicate increased deposition. 3. Statistical comparisons were performed using Fisher’s exact test for categorical variables and the Mann–Whitney U test for continuous variables. P < 0.05 was considered statistically significant. dcLVA, deep cervical lymphatic–venous anastomosis; ΔCL, Centiloid change value; ΔSUVR, standardized uptake value ratio change rates. 4. Discussion At present, available treatments for AD–related dementia primarily provide symptomatic relief and do not halt the underlying neurodegenerative process [ 21 ]. Growing evidence suggests that reducing cerebral Aβ deposition may delay disease progression, positioning both amyloid-targeted disease-modifying therapies and interventions aimed at enhancing cerebral lymphatic clearance as key areas of contemporary AD research [ 22 ]. However, direct comparative evidence evaluating the pathological and clinical effects of these two therapeutic strategies remains limited. As a noninvasive molecular imaging modality, AV-45 PET offers objective, reproducible, and quantitative assessment of cerebral Aβ burden, enabling direct evaluation of treatment effects on the core pathology of AD [ 14 , 23 ]. Leveraging these advantages, the present study represents, to our knowledge, the first investigation to directly compare the effects of lecanemab and dcLVA surgery on Aβ clearance and cognitive outcomes using AV-45 PET imaging. In this retrospective cohort, patients receiving 6 months of standardized lecanemab therapy or dcLVA surgery underwent paired AV-45 PET scans before and after treatment. Our findings demonstrated substantial agreement between visual AV-45 PET assessment and software-based quantitative analysis in the lecanemab group (kappa = 0.72; ICC = 0.663), supporting the complementary value of these two approaches in clinical evaluation. Importantly, ROC analysis identified the ΔCL as the imaging parameter with the highest diagnostic performance, and multivariate logistic regression confirmed ΔCL ≥ − 11.5% as an independent predictor of cognitive decline. These results are consistent with accumulating evidence linking Aβ burden to cognitive deterioration [ 6 , 9 , 24 ]. Notably, the relatively large standard deviation observed for ΔCL in the lecanemab group likely reflects inter-individual variability in treatment response, as well as statistical dispersion related to modest sample size. Future studies with larger cohorts and the adoption of advanced harmonization strategies, such as the multi-reference region correction and image harmonization framework proposed by Shekari et al. [ 25 ], may help reduce variability and enhance the stability of quantitative PET metrics. In contrast to lecanemab, dcLVA surgery demonstrated limited efficacy in both clinical and pathological domains. The proportion of patients experiencing significant cognitive decline was markedly higher in the dcLVA group than in the lecanemab group (81.8% vs. 23.5%, P < 0.001). At the imaging level, although regional ΔSUVR values did not differ significantly between groups, the dcLVA group exhibited a positive ΔCL, indicating an overall increase in cerebral Aβ burden. This contrasted with the greater Aβ reduction observed in the lecanemab group and resulted in a statistically significant intergroup difference in global amyloid clearance ( P = 0.006, r = 0.40). These findings suggest that dcLVA surgery may not effectively intervene in the core amyloid pathology of AD. Our results align with the prospective cohort study by Chen eta al. [ 26 ], in which most caregivers reported inconsistent symptomatic improvement following dcLVA surgery, accompanied by no significant changes in cerebrospinal fluid Aβ42 levels. Conversely, Ma et al. [ 11 ] reported short-term clinical improvement following dcLVA; however, their conclusions were based on a limited 3-month follow-up and lacked pathological endpoints such as Aβ imaging, restricting inference regarding long-term disease modification. Collectively, current evidence underscores substantial uncertainty surrounding the therapeutic efficacy of dcLVA, emphasizing the need for well-designed, multi-center RCTs with extended follow-up and robust pathological outcome measures [ 27 , 28 ]. To enhance the reliability of quantitative PET analysis, this study excluded patients with abnormally elevated AV-45 uptake in the cerebellar gray matter, defined as values exceeding the cohort mean plus two standard deviations. As the reference region for SUVR calculation, the cerebellar cortex is assumed to be free of Aβ pathology and metabolically stable. Violation of this assumption can introduce systematic underestimation of cortical Aβ burden by inflating the SUVR denominator. Simulation data from Shekari et al. [ 25 ], indicate that such bias may reach nearly 9% in Centiloid units, substantially compromising intergroup comparisons. Although the underlying causes of abnormal cerebellar uptake remain unclear, future studies integrating high-resolution PET/MR imaging may further improve the accuracy and generalizability of Aβ PET quantification. Several limitations warrant consideration. First, the relatively small sample size, particularly in the dcLVA group, may increase susceptibility to type II error. Second, the retrospective design introduces potential selection bias. Third, the absence of long-term follow-up limits evaluation of sustained efficacy and safety. Prospective, large-scale, multicenter RCTs incorporating longitudinal imaging and multimodal biomarkers, such as cerebrospinal fluid Aβ42 and phosphorylated tau, are needed to validate and extend these findings. 5. Conclusions Visual AV-45 PET assessment and Centiloid-based quantification demonstrate good concordance and robust diagnostic performance in evaluating treatment response in AD. A ΔCL ≥ − 11.5% serves as a key quantitative indicator of lecanemab efficacy and an independent predictor of cognitive decline. Compared with dcLVA surgery, lecanemab shows superior effectiveness in reducing cerebral Aβ burden and delaying cognitive deterioration in patients with Alzheimer’s disease. Abbreviations AD Alzheimer’s disease Aβ amyloid-β AUC area under the curve AV-45 18 F-florbetapir CL Centiloid value CT computed tomography dcLVA deep cervical lymphatic–venous anastomosis ICC intraclass correlation coefficient IgG1 immunoglobulin G1 IQCODE Informant Questionnaire on Cognitive Decline in the Elderly IQR interquartile range MCI mild cognitive impairment MCI-AD mild cognitive impairment due to Alzheimer’s disease MRI magnetic resonance imaging NIA–AA National Institute on Aging–Alzheimer’s Association OSEM ordered subset expectation maximization OR odds ratio PET positron emission tomography PET/CT positron emission tomography/computed tomography ROC receiver operating characteristic ROI region of interest RR reference region SD standard deviation SUVR standardized uptake value ratio ΔCL change in Centiloid value ΔSUVR change in standardized uptake value ratio Declarations Funding: This research was funded by grants from the National Natural Science Founda tion of China (no. 82001862), Zhejiang Provincial Natural Science Foundation (no. LQ24H180010). Acknowledgments We would like to thank and express our gratitude to Editage for editorial assistance. References Zhang J, Zhang Y, Wang J, Xia Y, Zhang J, Chen L. Recent advances in Alzheimer's disease: Mechanisms, clinical trials and new drug development strategies [J]. Signal Transduct Target Therapy. 2024;9(1):211. Estimation of the global prevalence of dementia. in 2019 and forecasted prevalence in 2050: an analysis for the Global Burden of Disease Study 2019 [J]. Lancet Public Health. 2022;7(2):e105–25. Scheltens P, De Strooper B, Kivipelto M, Holstege H, Chételat G, Teunissen CE, et al. Alzheimer's disease [J]. Lancet. 2021;397(10284):1577–90. Heneka MT, Morgan D, Jessen F. Passive anti-amyloid β immunotherapy in Alzheimer's disease-opportunities and challenges [J]. Lancet. 2024;404(10468):2198–208. Arroyo-Pacheco N, Sarmiento-Blanco S, Vergara-Cadavid G, Castro-Leones M, Contreras-Puentes. N.Monoclonal therapy with lecanemab in the treatment of mild Alzheimer's disease: A systematic review and meta-analysis [J]. Ageing Res Rev. 2025;104:102620. van Dyck CH, Swanson CJ, Aisen P, Bateman RJ, Chen C, Gee M, et al. Lecanemab in Early Alzheimer's Disease [J]. N Engl J Med. 2023;388(1):9–21. The Lancet. Lecanemab for Alzheimer's disease: tempering hype and hope [J]. Lancet. 2022;400(10367):1899. Jucker M, Walker LC. Alzheimer's disease: From immunotherapy to immunoprevention [J]. Cell. 2023;186(20):4260–70. Tang C, Zheng X, Li H, Wang B, Zheng Y, Song W, et al. Deep cervical lymphatic-venous anastomosis in dementia: a clinical and mechanistic evaluation [J]. International Journal of Surgery; 2025. Li X, Zhang C, Fang Y, Xin M, Shi J, Zhang Z, et al. Promising outcomes 5 weeks after a surgical cervical shunting procedure to unclog cerebral lymphatic systems in a patient with Alzheimer's disease [J]. Gen Psychiatry. 2024;37(3):e101641. Ma X, Wang F, Wang G, Zhao M, Zheng Y, Guo Y, et al. A surgical therapy for Alzheimer's disease with lymphaticovenular anastomosis [J]. J Alzheimer's Disease Rep. 2025;9:25424823251384244. Da Mesquita S, Louveau A, Vaccari A, Smirnov I, Cornelison RC, Kingsmore KM, et al. Functional aspects of meningeal lymphatics in ageing and Alzheimer's disease [J]. Nature. 2018;560(7717):185–91. Xie F, Ye Y, Hao J, Liu H, Richard SA, He S. Surgical advances in the treatment of Alzheimer's disease: A comprehensive review [J]. J Alzheimers Dis. 2025;107(3):899–909. Villemagne VL, Doré V, Burnham SC, Masters CL, Rowe CC. Imaging tau and amyloid-β proteinopathies in Alzheimer disease and other conditions [J]. Nat Reviews Neurol. 2018;14(4):225–36. Zhao Z, Wang J, Wang Y, Liu X, He K, Guo Q, et al. 18F-AV45 PET and MRI Reveal the Influencing Factors of Alzheimer's Disease Biomarkers in Subjective Cognitive Decline Population [J]. J Alzheimers Dis. 2023;93(2):585–94. Shi Z, Fu LP, Zhang N, Zhao X, Liu S, Zuo C, et al. Amyloid PET in Dementia Syndromes: A Chinese Multicenter Study [J]. J Nucl Med. 2020;61(12):1814–9. Jack CR Jr, Bennett DA, Blennow K, Carrillo MC, Dunn B, Haeberlein SB, et al. NIA-AA Research Framework: Toward a biological definition of Alzheimer's disease [J]. Volume 14. Alzheimer's & Dementia; 2018. pp. 535–62. 4. Swanson CJ, Zhang Y, Dhadda S, Wang J, Kaplow J, Lai RYK, et al. A randomized, double-blind, phase 2b proof-of-concept clinical trial in early Alzheimer's disease with lecanemab, an anti-Aβ protofibril antibody [J]. Volume 13. Alzheimer's Research & Therapy; 2021. p. 80. 1. Karran E, De Strooper B. The amyloid hypothesis in Alzheimer disease: new insights from new therapeutics [J]. Nat Rev Drug Discovery. 2022;21(4):306–18. Burton JK, Stott DJ, McShane R, Noel-Storr AH, Swann-Price RS, Quinn TJ. Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) for the early detection of dementia across a variety of healthcare settings [J]. The Cochrane Database of Systematic Reviews, 2021, 7(7): Cd011333. Long JM, Holtzman DM. Alzheimer Disease: An Update on Pathobiology and Treatment Strategies [J]. Cell. 2019;179(2):312–39. Horie K, Barthélemy NR, Sato C. Bateman RJ.CSF tau microtubule binding region identifies tau tangle and clinical stages of Alzheimer's disease [J]. Brain. 2021;144(2):515–27. Zhang QZ, Yilihamu N, Li YB, Li XH, Qin YD. Simple Synthesis of [(18)F] AV-45 and its Clinical Application in the Diagnosis of Alzheimer's Disease [J]. Curr Med Chem. 2024;31(10):1278–88. Sperling RA, Donohue MC, Raman R, Rafii MS, Johnson K, Masters CL, et al. Trial of Solanezumab in Preclinical Alzheimer's Disease [J]. N Engl J Med. 2023;389(12):1096–107. Shekari M, Vállez García D, Collij LE, Altomare D, Heeman F, Pemberton H, et al. Stress testing the Centiloid: Precision and variability of PET quantification of amyloid pathology [J]. Volume 20. Alzheimer's & Dementia; 2024. pp. 5102–13. 8. Chen JY, Zhao DW, Yin Y, Gui L, Chen X, Wang XM, et al. Deep cervical lymphovenous anastomosis (LVA) for Alzheimer's disease: microsurgical procedure in a prospective cohort study [J]. Int J Surg. 2025;111(7):4211–21. Chen Q, Wen Q, Zhong T, Liu J, Gao H. Deep cervical lymphaticovenous anastomosis for Alzheimer's disease: A narrative review [J]. Volume 21. Alzheimer's & Dementia; 2025. p. e71038. 12. Wang H, Levey A, Wang G. Lymphatic-venous anastomosis surgery for Alzheimer's disease [J]. Gen Psychiatry. 2025;38(3):e102062. Supplementary Files floatimage2.png Graphical Abstract Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8821582","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":588764479,"identity":"ddbb499f-fa45-4484-86e9-a1e9381dffaf","order_by":0,"name":"LUQIANG jin","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5ElEQVRIiWNgGAWjYBACxmbG9g8SFWz1bOyNjQ8SKmqI0NLO3MZgcYYvgZ/ncLPBgzPHiLCGn72NobJNLkFyRnqb5MMWZsI6mJsZ2x7cbDPLMzhzsK0isYGNgb+9O4GgXwxnnEsrNjje2HYjcYcMg8SZsxsIaWmQlig7xrgBaMuNxDNsDAYSuURo+cP2n3HDjcS2gsQ2ZqK0tElItLElzpyR2MZArJZmA4kzbMb8PAebJRLOHOMh6BfD/uMPHwCjUo6Nvf3hxx8VNXL87b0EtDSgCfDgVQ4C8gRVjIJRMApGwSgAAEk+T9sp+D5qAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0009-0005-8094-0952","institution":"Cancer Center, Department of Nuclear Medicine, Zhejiang Provincial People's Hospital(Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China","correspondingAuthor":true,"prefix":"","firstName":"LUQIANG","middleName":"","lastName":"jin","suffix":""},{"id":588764480,"identity":"f5629b46-ccfa-421f-9583-b23f1e4d8ab9","order_by":1,"name":"Xinyu Wang","email":"","orcid":"","institution":"Cancer Center, Department of Nuclear Medicine, Zhejiang Provincial People's Hospital(Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China","correspondingAuthor":false,"prefix":"","firstName":"Xinyu","middleName":"","lastName":"Wang","suffix":""},{"id":588764481,"identity":"3d67ee79-cc1c-4f7b-8678-8273340e695f","order_by":2,"name":"Fahuan Song","email":"","orcid":"","institution":"Cancer Center, Department of Nuclear Medicine, Zhejiang Provincial People's Hospital(Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China","correspondingAuthor":false,"prefix":"","firstName":"Fahuan","middleName":"","lastName":"Song","suffix":""},{"id":588764482,"identity":"918973e0-49db-4500-91fb-3e829f77747e","order_by":3,"name":"Jie Hou","email":"","orcid":"","institution":"Cancer Center, Department of Radiology, Zhejiang Provincial People's Hospital(Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China","correspondingAuthor":false,"prefix":"","firstName":"Jie","middleName":"","lastName":"Hou","suffix":""},{"id":588764483,"identity":"4652f14b-e857-4a79-935d-16d9d8010ede","order_by":4,"name":"Yueqian Bi","email":"","orcid":"","institution":"Heze Rongjun Youfu Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yueqian","middleName":"","lastName":"Bi","suffix":""},{"id":588764484,"identity":"69fbc33b-052d-4826-9198-eb1e434be5a3","order_by":5,"name":"Xuehua Wen","email":"","orcid":"","institution":"Cancer Center, Department of Radiology, Zhejiang Provincial People's Hospital(Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China","correspondingAuthor":false,"prefix":"","firstName":"Xuehua","middleName":"","lastName":"Wen","suffix":""},{"id":588764485,"identity":"71d7ddaf-bda5-401a-b55b-93c08915f844","order_by":6,"name":"Xu Wang","email":"","orcid":"","institution":"Center for Rehabilitation Medicine, Department of Neurology, Zhejiang Provincial People's Hospital(Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China","correspondingAuthor":false,"prefix":"","firstName":"Xu","middleName":"","lastName":"Wang","suffix":""},{"id":588764486,"identity":"f72ae40b-455d-4f1a-992f-98796e735774","order_by":7,"name":"Fangyuan Lai","email":"","orcid":"","institution":"Center for Plastic \u0026 Reconstructive Surgery, Department of Hand \u0026 Reconstructive Surgery, Zhejiang Provincial People's Hospital(Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China","correspondingAuthor":false,"prefix":"","firstName":"Fangyuan","middleName":"","lastName":"Lai","suffix":""},{"id":588764487,"identity":"5f16f9c0-6ef4-4abb-a063-7b91f595e8cc","order_by":8,"name":"Aiping Cheng","email":"","orcid":"https://orcid.org/0000-0003-4642-4426","institution":"Cancer Center, Department of Nuclear Medicine, Zhejiang Provincial People's Hospital(Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China","correspondingAuthor":false,"prefix":"","firstName":"Aiping","middleName":"","lastName":"Cheng","suffix":""}],"badges":[],"createdAt":"2026-02-08 12:47:37","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8821582/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8821582/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102736337,"identity":"55ca0ad7-f583-4614-a0c6-1d441a7de88e","added_by":"auto","created_at":"2026-02-16 06:25:21","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":81703,"visible":true,"origin":"","legend":"\u003cp\u003e(A,B) ROC curves of regional standardized uptake value ratio change rates (ΔSUVR) across multiple cortical regions, including the frontal, parietal, lateral temporal, medial temporal, posterior cingulate, precuneus, occipital cortex, and cerebellum. (C) ROC curves comparing the diagnostic performance of the Centiloid change value (ΔCL) with representative regional ΔSUVR parameters. ΔCL demonstrated superior diagnostic accuracy for predicting cognitive decline, as reflected by a higher area under the curve (AUC).\u003c/p\u003e\n\u003cp\u003eCognitive decline was defined as an Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) score ≥3.3. ROC-derived cutoff values, sensitivities, specificities, AUCs, and 95% confidence intervals are provided in Table 2.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8821582/v1/2d832f45797afdc210021cf9.png"},{"id":103506637,"identity":"850a9ae9-536b-489b-98c5-a2e88b7cd32c","added_by":"auto","created_at":"2026-02-26 13:38:19","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1103728,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8821582/v1/124f8b08-d2dd-4860-a2f1-44c6389b6a0e.pdf"},{"id":102736333,"identity":"9f5abeff-00b2-4f01-a6b9-6d16af0e72fc","added_by":"auto","created_at":"2026-02-16 06:25:18","extension":"png","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":613538,"visible":true,"origin":"","legend":"\u003cp\u003eGraphical Abstract\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8821582/v1/f4b508749fc473767ffa562c.png"}],"financialInterests":"","formattedTitle":"Quantitative AV-45 PET Imaging for Assessing Treatment Response to Lecanemab and Deep Cervical Lymphatic–Venous Anastomosis in Alzheimer’s Disease","fulltext":[{"header":"Highlights","content":"\u003cp\u003eWhat are the main findings?\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e AV-45 PET visual assessment and Centiloid-based quantification showed good concordance, with \u0026Delta;CL emerging as the most sensitive imaging marker for monitoring treatment response to lecanemab in Alzheimer\u0026rsquo;s disease.\u003c/li\u003e\n \u003cli\u003e\u0026nbsp;Lecanemab significantly reduced cognitive decline and cerebral amyloid-\u0026beta; burden compared with deep cervical lymphatic\u0026ndash;venous anastomosis, which showed limited pathological and clinical benefit.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eWhat are the implications of the main findings?\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e The Centiloid change value (\u0026Delta;CL) provides a robust, quantitative imaging biomarker for predicting cognitive outcomes and evaluating anti-amyloid therapeutic efficacy in clinical practice and trials.\u003c/li\u003e\n \u003cli\u003eThese findings support lecanemab as a more effective disease-modifying strategy than dcLVA and underscore the need for rigorous imaging-based endpoints when assessing alternative surgical interventions in Alzheimer\u0026rsquo;s disease.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"1. Introduction","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eAlzheimer\u0026rsquo;s disease (AD) is the most prevalent neurodegenerative disorder worldwide and a leading cause of cognitive impairment[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Currently, approximately 50\u0026nbsp;million individuals are affected by dementia globally, and this number is projected to triple by 2050 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Clinically, AD is characterized by progressive cognitive decline and functional deterioration. Its hallmark neuropathological features include extracellular amyloid plaques formed by abnormal deposition of β-amyloid (Aβ) peptides and intracellular neurofibrillary tangles resulting from tau protein hyperphosphorylation [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. These pathological processes ultimately lead to synaptic dysfunction, neuronal loss, and irreversible cognitive impairment, imposing a substantial medical, social, and economic burden on patients, caregivers, and healthcare systems.\u003c/p\u003e \u003cp\u003eIn recent years, Aβ-targeted pharmacotherapy and surgical approaches aimed at enhancing cerebral lymphatic clearance have emerged as major research directions in AD treatment. Lecanemab (BAN2401), a humanized immunoglobulin G1 (IgG1) monoclonal antibody, selectively binds soluble Aβ aggregates, reduces cerebral amyloid burden, and has demonstrated clinical efficacy in delaying cognitive decline in early-stage AD. Based on these findings, lecanemab has been approved for the treatment of mild AD and AD-related mild cognitive impairment (MCI) [\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In parallel, deep cervical lymphatic\u0026ndash;venous anastomosis (dcLVA) has been proposed as a novel microsurgical strategy to enhance lymphatic drainage by creating a bypass between cervical lymphatic vessels and the venous system. Preliminary studies suggest that dcLVA may facilitate systemic waste clearance, reduce Aβ accumulation, and improve cognitive function [\u003cspan additionalcitationids=\"CR10 CR11\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. However, the therapeutic mechanism of dcLVA in AD remains largely speculative. Evidence supporting its long-term efficacy is limited, standardized surgical protocols are lacking, and data from large, multicenter randomized controlled trials (RCTs) are absent, warranting cautious clinical interpretation [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAs a noninvasive molecular imaging modality, \u003csup\u003e18\u003c/sup\u003eF-florbetapir (AV-45) positron emission tomography/computed tomography (PET/CT) enables \u003cem\u003ein vivo\u003c/em\u003e localization and quantification of cerebral Aβ deposition, substantially advancing the diagnostic and monitoring capabilities for AD. AV-45 PET plays a critical role in elucidating AD pathophysiology and in assessing the therapeutic effects of Aβ-targeted interventions [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Compared with conventional neuropsychological assessments, which rely on subjective scoring and may be influenced by inter-observer variability, AV-45 PET provides direct, objective, and quantitative measures of core AD pathology, thereby offering a robust imaging biomarker for treatment evaluation [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Nevertheless, to date, no studies have employed AV-45 PET to directly compare the therapeutic effects of lecanemab and dcLVA, nor has the differential impact of these two interventions on cerebral Aβ burden been quantitatively assessed using paired pre- and post-treatment imaging.\u003c/p\u003e \u003cp\u003eAgainst this background, the present study aims to validate the clinical utility of AV-45 PET for evaluating treatment response in AD. By systematically analyzing changes in imaging parameters before and after treatment, we further seek to elucidate differences in therapeutic efficacy between lecanemab and dcLVA, thereby providing objective imaging evidence to support individualized treatment selection for patients with AD.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study Participants\u003c/h2\u003e \u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eClinical data from patients with AD who were diagnosed and treated at the Department of Neurology and the Department of Lymphatic Surgery of our hospital between July 2024 and July 2025 were retrospectively collected. This study was approved by the Ethics Committee of our hospital (Ethics Approval No.: QT2026011). Owing to the retrospective nature of the study, the requirement for written informed consent was waived. All procedures were conducted in accordance with the Declaration of Helsinki and relevant regulations governing the protection of patient privacy and medical data.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Inclusion and Exclusion Criteria\u003c/h2\u003e \u003cp\u003e \u003cstrong\u003eInclusion criteria\u003c/strong\u003e \u003cp\u003e(1) Fulfillment of the diagnostic criteria for AD dementia according to the 2018 Alzheimer\u0026rsquo;s Disease Research Framework (AT(N) system) issued by the National Institute on Aging\u0026ndash;Alzheimer\u0026rsquo;s Association (NIA\u0026ndash;AA) [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]; (2) Completion of AV-45 PET scans 1 week before treatment initiation and 6 months after treatment, with image quality sufficient for quantitative analysis of Aβ deposition; (3) Clear receipt of either lecanemab treatment (completion of 12 infusions) or deep cervical lymphatic\u0026ndash;venous anastomosis (dcLVA) surgery, with a standardized treatment protocol and complete follow-up data; (4) Age between 55 and 80 years, regardless of sex; (5) Availability of complete and traceable clinical data, including medical history, laboratory findings, and Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) scores.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eExclusion criteria\u003c/strong\u003e \u003cp\u003e(1) Presence of other neurodegenerative disorders (e.g., frontotemporal dementia, dementia with Lewy bodies) or severe structural brain lesions (e.g., intracerebral hemorrhage, brain tumors); (2) History of cervical surgery, cervical lymphadenopathy, or lymphatic malformations that could interfere with dcLVA implementation or outcome assessment; (3) Occurrence of treatment-related adverse events, including amyloid-related imaging abnormalities detected by magnetic resonance imaging (MRI); (4) Concomitant use of other Aβ-targeted agents, psychotropic medications, or drugs that could confound treatment efficacy during the study period; (5) Poor-quality AV-45 PET images, missing imaging data, or incomplete follow-up precluding reliable efficacy evaluation.\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Study Design\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThis study employed a retrospective cohort design. Baseline demographic and clinical data\u0026mdash;including age, sex, disease duration and comorbidities\u0026mdash;were extracted from the hospital\u0026rsquo;s electronic medical record system. Baseline AV-45 PET/CT scans were obtained 1 week prior to treatment initiation. All patients underwent a standardized diagnostic workflow and were assigned to either the lecanemab treatment group (pharmacological group) or the dcLVA treatment group (surgical group) based on the therapeutic intervention received. Patients in the lecanemab group were administered lecanemab at a dose of 10 mg/kg every 2 weeks for a total duration of 6 months [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. All dcLVA procedures were performed by the same neurosurgeon with more than 5 years of microsurgical experience to ensure procedural consistency and standardization. Follow-up AV-45 PET/CT imaging was conducted after 6 months of treatment, accompanied by comprehensive clinical assessment. Given the relatively small sample size of the dcLVA group and the associated risk of insufficient statistical power and model instability, analyses comparing AV-45 PET visual assessment with Centiloid-based quantification and identifying independent predictors of treatment response were restricted to the lecanemab group.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. AV-45 PET/CT Scanning Protocol\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eAll PET/CT images were acquired using a Siemens Biograph 64 PET/CT scanner (Munich, Germany). The radiochemical purity of AV-45 exceeded 95%. Following intravenous administration of AV-45 at a dose of 3.7\u0026ndash;5.55 MBq/kg, patients rested quietly for 40\u0026ndash;60 min while avoiding head movement. CT acquisition parameters included a slice thickness of 1 mm, tube voltage of 120 kV, and automatic tube current modulation. PET data were acquired in three-dimensional mode for 20 min. Image reconstruction was performed using the ordered subset expectation maximization (OSEM) algorithm, and attenuation correction was applied using CT-derived attenuation maps. Image interpretation was conducted retrospectively and independently by two nuclear medicine physicians, each with more than 5 years of diagnostic experience, who were blinded to clinical information and treatment allocation. Inter-reader agreement was assessed using the intraclass correlation coefficient (ICC). In cases of significant disagreement, a third senior physician provided adjudication.\u003c/p\u003e \u003cp\u003eFor visual analysis, bilateral regions of interest (ROIs) were defined in the frontal, parietal, lateral temporal, medial temporal, and occipital cortices, as well as the posterior cingulate gyrus and precuneus. The cerebellar cortex served as the reference region for calculation of standardized uptake value ratios (SUVRs).\u003c/p\u003e \u003cp\u003eFor software-based quantitative analysis, the \u0026ldquo;Cerebral Neuroimaging Quantitative Analysis System(Shanghai, China)\u0026rdquo; was used for standardized image processing and computation of Centiloid values (CLs), with a CL\u0026thinsp;\u0026le;\u0026thinsp;12 indicating the absence of pathological Aβ deposition [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. The baseline AV-45 PET scan was defined as PET1, and the post-treatment scan as PET2. The percentage change in SUVR between scans was calculated as:\u003c/p\u003e \u003cp\u003eΔSUVR (%) = [(SUVR\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;\u0026minus;\u0026thinsp;SUVR\u003csub\u003e1\u003c/sub\u003e) / SUVR\u003csub\u003e1\u003c/sub\u003e] \u0026sdot; 100%\u003c/p\u003e \u003cp\u003eNegative values indicate reduced Aβ deposition, whereas positive values indicate increased deposition. The change in Centiloid value between scans was defined as ΔCL.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. IQCODE Assessment\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eCognitive status was evaluated using the IQCODE following completion of the standardized treatment period. Assessments were conducted by neurologists who were blinded to PET imaging results. The interviewees were primary caregivers who had provided care for at least 6 months and had contact with the patient for a minimum of 10 h per week. The IQCODE comprises 26 items, each rated on a five-point scale according to perceived cognitive change (1\u0026thinsp;=\u0026thinsp;markedly improved, 5\u0026thinsp;=\u0026thinsp;markedly declined), with higher scores indicating greater cognitive impairment. The mean item score was calculated for each patient, and a mean score\u0026thinsp;\u0026ge;\u0026thinsp;3.3 was used as the predefined threshold for significant cognitive decline [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Statistical Analyses\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eStatistical analyses were performed using SPSS software (version 27.0; IBM Corp., Armonk, NY, USA). Continuous variables are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) or median with interquartile range (IQR), as appropriate. Agreement between visual assessment and quantitative imaging parameters was evaluated using Cohen\u0026rsquo;s kappa coefficient. Receiver operating characteristic (ROC) curve analysis was performed to assess diagnostic performance, with calculation of the area under the curve (AUC). Univariate binary logistic regression analyses were conducted using semi-quantitative parameters derived from visual assessment and quantitative metrics obtained from software-based analysis as independent variables. Variables demonstrating significance in univariate analysis were subsequently entered into multivariate binary logistic regression models to identify independent predictors of cognitive decline as defined by the IQCODE threshold. Categorical variables were compared using Fisher\u0026rsquo;s exact test, and continuous variables were compared using the Mann\u0026ndash;Whitney \u003cem\u003eU\u003c/em\u003e test. All statistical tests were two-sided, and a \u003cem\u003eP\u003c/em\u003e value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Baseline Characteristics of Study Participants\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eBetween July 2024 and July 2025, a total of 327 patients were initially screened, including 80 patients in the lecanemab treatment group and 247 patients in the dcLVA surgical group. Of these, 47 patients (34 in the lecanemab group and 13 in the dcLVA group) met all inclusion and exclusion criteria and completed the required follow-up, and were therefore included in the final analysis. The final cohort comprised 21 men and 26 women, with a mean age of 68.4\u0026thinsp;\u0026plusmn;\u0026thinsp;9.1 years. Baseline demographic characteristics, disease duration, comorbidities, concomitant AD\u0026ndash;approved medications, and baseline AV-45 PET imaging parameters were comparable between the two treatment groups. No statistically significant differences were observed between groups for any baseline variable (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05), indicating good baseline comparability (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics of patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLecanemab Treatment Group (n\u0026thinsp;=\u0026thinsp;34)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003edcLVA Treatment Group (n\u0026thinsp;=\u0026thinsp;13)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69.3\u0026thinsp;\u0026plusmn;\u0026thinsp;9.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65.8\u0026thinsp;\u0026plusmn;\u0026thinsp;8.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Men\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (50.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (30.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Women\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (50.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (69.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDisease duration (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.47\u0026thinsp;\u0026plusmn;\u0026thinsp;1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.08\u0026thinsp;\u0026plusmn;\u0026thinsp;1.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUnderlying diseases, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Hypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (23.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (38.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Diabetes mellitus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (8.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (7.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Coronary heart disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (2.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eConcomitant AD-approved drugs at baseline, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (55.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (76.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBaseline AV-45 PET parameters\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- SUVR\u003csub\u003e1\u003c/sub\u003e Frontal lobe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- SUVR\u003csub\u003e1\u003c/sub\u003e Parietal lobe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- SUVR\u003csub\u003e1\u003c/sub\u003e Lateral temporal lobe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- SUVR\u003csub\u003e1\u003c/sub\u003e Medial temporal lobe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- SUVR\u003csub\u003e1\u003c/sub\u003e Posterior cingulate gyrus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- SUVR\u003csub\u003e1\u003c/sub\u003e Precuneus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- SUVR\u003csub\u003e1\u003c/sub\u003e Occipital lobe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- SUVR\u003csub\u003e1\u003c/sub\u003e Cerebellum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Centiloid value (CL\u003csub\u003e1\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.8\u0026thinsp;\u0026plusmn;\u0026thinsp;36.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.1\u0026thinsp;\u0026plusmn;\u0026thinsp;36.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eNote: Continuous variables are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation. SUVR₁ and CL₁ represent baseline semi-quantitative AV-45 PET parameters. SUVR₁ values were calculated using the cerebellar cortex as the reference region for each specified ROI.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eAD, Alzheimer\u0026rsquo;s disease; dcLVA, deep cervical lymphatic\u0026ndash;venous anastomosis; PET, positron emission tomography; SUVR, standardized uptake value ratio; ROI, region of interest.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Consistency and Diagnostic Efficacy of AV-45 PET Visual Analysis and Centiloid Value Assessment\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eAfter 6 months of standardized treatment, 8 patients (23.5%) in the lecanemab treatment group and 9 patients (81.8%) in the dcLVA treatment group had an IQCODE score\u0026thinsp;\u0026ge;\u0026thinsp;3.3 indicating significant cognitive decline. In the lecanemab treatment group, agreement between AV-45 PET visual assessment and Centiloid-based quantification for evaluating cerebral Aβ deposition (negative: CL\u0026thinsp;\u0026le;\u0026thinsp;12; weakly positive: 12\u0026thinsp;\u0026lt;\u0026thinsp;CL\u0026thinsp;\u0026lt;\u0026thinsp;30; positive: CL\u0026thinsp;\u0026ge;\u0026thinsp;30) was substantial. The Cohen\u0026rsquo;s kappa coefficient was 0.72 (95% confidence interval [CI]: 0.50\u0026ndash;0.94), and the ICC was 0.663, indicating good consistency between the two assessment methods.\u003c/p\u003e \u003cp\u003eROC curve analysis was performed in the lecanemab treatment group to evaluate the diagnostic performance of ΔSUVR across different brain regions and ΔCL for predicting cognitive decline. The optimal cutoff values, corresponding sensitivities, specificities, AUCs, and 95% CIs are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Among all parameters examined, ΔCL demonstrated the highest diagnostic performance, with an AUC of 0.764 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.026) and an optimal cutoff value of \u0026minus;\u0026thinsp;11.5%. The ROC curves illustrating the comparative diagnostic performance of AV-45 PET\u0026ndash;derived parameters, including ΔCL and regional ΔSUVR measures, are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eOptimal cutoff values of relevant parameters calculated by ROC curve analysis and Youden Index in the lecanemab treatment group\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCutoff Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSensitivity (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSpecificity (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAUC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔSUVR Frontal lobe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;18.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e87.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e42.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.618\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(0.407\u0026ndash;0.829)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔSUVR Parietal lobe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;9.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e62.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e88.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.733\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.049*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(0.520\u0026ndash;0.947)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔSUVR Medial temporal lobe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;2.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e76.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.589\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.453\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(0.346\u0026ndash;0.832)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔSUVR Lateral temporal lobe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;1.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e62.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e69.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.630\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(0.387\u0026ndash;0.872)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔSUVR Posterior cingulate gyrus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e76.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.562\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.598\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(0.336\u0026ndash;0.789)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔSUVR Precuneus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;7.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e73.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.538\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.745\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(0.296\u0026ndash;0.781)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔSUVR Occipital lobe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;13%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e84.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.659\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(0.416\u0026ndash;0.901)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔSUVR Cerebellum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e65.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.514\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.903\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(0.266\u0026ndash;0.762)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔCL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;11.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e75.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e84.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.764\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.026*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(0.558\u0026ndash;0.971)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eAD, Alzheimer\u0026rsquo;s disease; AUC, area under the curve; CI, confidence interval; ΔCL, Centiloid change value; ΔSUVR, standardized uptake value ratio change rates\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e(A,B) ROC curves of regional standardized uptake value ratio change rates (ΔSUVR) across multiple cortical regions, including the frontal, parietal, lateral temporal, medial temporal, posterior cingulate, precuneus, occipital cortex, and cerebellum. (C) ROC curves comparing the diagnostic performance of the Centiloid change value (ΔCL) with representative regional ΔSUVR parameters. ΔCL demonstrated superior diagnostic accuracy for predicting cognitive decline, as reflected by a higher area under the curve (AUC).\u003c/p\u003e \u003cp\u003eCognitive decline was defined as an Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) score\u0026thinsp;\u0026ge;\u0026thinsp;3.3. ROC-derived cutoff values, sensitivities, specificities, AUCs, and 95% confidence intervals are provided in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cem\u003e3.3 Logistic Regression Analysis of AV-45 PET Parameters for Predicting Cognitive Decline in AD Patients Treated with Lecanemab\u003c/em\u003e \u003c/p\u003e \u003cp\u003eUnivariate binary logistic regression analysis was performed with cognitive decline, defined as an IQCODE score\u0026thinsp;\u0026ge;\u0026thinsp;3.3, as the dependent variable. In patients treated with lecanemab monotherapy, a ΔCL\u0026thinsp;\u0026ge;\u0026thinsp;\u0026minus;\u0026thinsp;11.5% was significantly associated with an increased risk of cognitive decline (odds ratio [OR]\u0026thinsp;=\u0026thinsp;10.000, 95% CI: 1.585\u0026ndash;63.097, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.014) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). To further control for potential confounding factors and identify independent predictors, variables with P\u0026thinsp;\u0026lt;\u0026thinsp;0.10 in the univariate analysis (including ΔSUVR in the precuneus\u0026thinsp;\u0026ge;\u0026thinsp;\u0026minus;\u0026thinsp;7.5% and ΔSUVR in the posterior cingulate gyrus\u0026thinsp;\u0026ge;\u0026thinsp;\u0026minus;\u0026thinsp;1%), as well as clinically relevant covariates (age, sex, underlying diseases, and concomitant AD\u0026ndash;approved medications), were entered into a multivariate binary logistic regression model. After adjustment, ΔCL\u0026thinsp;\u0026ge;\u0026thinsp;\u0026minus;\u0026thinsp;11.5% remained independently associated with cognitive decline in patients receiving lecanemab monotherapy (adjusted OR\u0026thinsp;=\u0026thinsp;10.281, 95% CI: 1.289\u0026ndash;82.005, P\u0026thinsp;=\u0026thinsp;0.028). No regional ΔSUVR parameter retained statistical significance in the multivariate model.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate and Multivariate Logistic Regression Analyses Predicting Cognitive Decline in the Lecanemab Treatment Group\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eUnivariate Analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eMultivariate Analysis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.514\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.101\u0026ndash;2.614\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.423\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.202\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.154\u0026ndash;9.368\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.861\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.371\u0026ndash;13.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.385\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.278\u0026ndash;18.709\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.443\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnderlying diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.333\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.644\u0026ndash;107.851\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisease duration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.350\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.258\u0026ndash;7.072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.722\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConcomitant AD-approved drugs at baseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.429\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.281\u0026ndash;7.261\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.667\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔSUVR Frontal lobe\u0026thinsp;\u0026ge;\u0026thinsp;\u0026minus;\u0026thinsp;18.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.466\u0026ndash;41.067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.196\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔSUVR Parietal lobe\u0026thinsp;\u0026ge;\u0026thinsp;\u0026minus;\u0026thinsp;9.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.750\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.716\u0026ndash;19.644\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔSUVR Medial temporal lobe\u0026thinsp;\u0026ge;\u0026thinsp;\u0026minus;\u0026thinsp;2.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.239\u0026ndash;5.698\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.849\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔSUVR Lateral temporal lobe\u0026thinsp;\u0026ge;\u0026thinsp;\u0026minus;\u0026thinsp;1.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.667\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.328\u0026ndash;8.462\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.538\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔSUVR Posterior cingulate gyrus\u0026thinsp;\u0026ge;\u0026thinsp;\u0026minus;\u0026thinsp;1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.239\u0026ndash;5.698\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.849\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.324\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.082\u0026ndash;21.348\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.843\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔSUVR Precuneus\u0026thinsp;\u0026ge;\u0026thinsp;\u0026minus;\u0026thinsp;7.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.625\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.127\u0026ndash;3.081\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.561\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.037\u0026ndash;8.566\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.678\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔSUVR Occipital lobe\u0026thinsp;\u0026ge;\u0026thinsp;\u0026minus;\u0026thinsp;13%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.179\u0026ndash;6.821\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.914\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔSUVR Cerebellum\u0026ge;-1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.397\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.070\u0026ndash;2.243\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.296\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔCL\u0026thinsp;\u0026ge;\u0026thinsp;\u0026minus;\u0026thinsp;11.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.585\u0026ndash;63.097\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.014*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.281\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.289\u0026ndash;82.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.028*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eAD, Alzheimer\u0026rsquo;s disease; CI, confidence interval; ΔCL, Centiloid change value; ΔSUVR, standardized uptake value ratio change rates; OR, odds ratio.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Comparison of Therapeutic Outcomes Between Lecanemab and dcLVA Surgery\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eAfter 6 months of standardized treatment, therapeutic outcomes between the lecanemab treatment group and the dcLVA surgical group were compared using both clinical and AV-45 PET\u0026ndash;based measures. For clinical outcomes, cognitive decline was defined as an IQCODE score\u0026thinsp;\u0026ge;\u0026thinsp;3.3. Fisher\u0026rsquo;s exact test demonstrated that the proportion of patients experiencing cognitive decline was significantly lower in the lecanemab group than in the dcLVA group (23.5% vs. 81.8%), indicating a markedly reduced risk of cognitive deterioration in patients treated with lecanemab (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). For imaging outcomes, no significant differences were observed between groups in the distribution of AV-45 PET visual assessment categories or in regional ΔSUVR. In contrast, a significant intergroup difference was detected for the change in ΔCL. Mann\u0026ndash;Whitney \u003cem\u003eU\u003c/em\u003e testing showed that ΔCL differed significantly between the lecanemab and dcLVA groups (\u003cem\u003eU\u003c/em\u003e\u0026thinsp;=\u0026thinsp;337.0, Z\u0026thinsp;=\u0026thinsp;2.759, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006), with a moderate effect size (r\u0026thinsp;=\u0026thinsp;0.40). The lecanemab group exhibited a greater reduction in cerebral Aβ burden, whereas the dcLVA group showed a tendency toward increased Aβ deposition (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of Clinical and AV-45 PET Outcomes Between the Lecanemab Monotherapy Group and the dcLVA Treatment Group\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutcome Type\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndicators\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLecanemab Treatment Group (n\u0026thinsp;=\u0026thinsp;34)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003edcLVA Treatment Group (n\u0026thinsp;=\u0026thinsp;13)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTest Statistic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClinical outcome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIQCODE score\u0026thinsp;\u0026ge;\u0026thinsp;3.3 (significant cognitive decline)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8 (23.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9 (81.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAV-45 PET outcomes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eΔSUVR Frontal lobe (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;6.47\u0026thinsp;\u0026plusmn;\u0026thinsp;40.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;1 (\u0026minus;\u0026thinsp;28.00, 15.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;263\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.318\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eΔSUVR Parietal lobe (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;13.5\u0026thinsp;\u0026plusmn;\u0026thinsp;35.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;1 (\u0026minus;\u0026thinsp;24.00, 33.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;241.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.626\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eΔSUVR Lateral temporal lobe (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;4.41\u0026thinsp;\u0026plusmn;\u0026thinsp;29.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;4 (\u0026minus;\u0026thinsp;16.00, 19.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;258.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.379\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eΔSUVR Medial temporal lobe (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;5.44\u0026thinsp;\u0026plusmn;\u0026thinsp;33.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;4 (\u0026minus;\u0026thinsp;30.00, 7.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;229.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.840\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eΔSUVR Posterior cingulate gyrus (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;0.06\u0026thinsp;\u0026plusmn;\u0026thinsp;37.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;2 (\u0026minus;\u0026thinsp;19.50, 11.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;252.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.454\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eΔSUVR Precuneus (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;0.26\u0026thinsp;\u0026plusmn;\u0026thinsp;34.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;2 (\u0026minus;\u0026thinsp;17.50, 26.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;242.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.617\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eΔSUVR Occipital lobe (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;1.53\u0026thinsp;\u0026plusmn;\u0026thinsp;32.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;1 (\u0026minus;\u0026thinsp;21.50, 9.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;215.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.896\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eΔSUVR Cerebellum (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.32\u0026thinsp;\u0026plusmn;\u0026thinsp;31.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;4 (\u0026minus;\u0026thinsp;20.00, 8.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;209.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.775\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eΔCL (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;0.44\u0026thinsp;\u0026plusmn;\u0026thinsp;150.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13 (\u0026minus;\u0026thinsp;15.50, 168.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;337.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.006*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eNotes: 1. Categorical data are presented as n (%). Continuous variables are expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation for the lecanemab group and as median (interquartile range, IQR) for the dcLVA group, reflecting distributional differences and sample size. 2. ΔSUVR and ΔCL represent percentage changes between baseline and post-treatment scans. Negative ΔCL values indicate reduced amyloid-β deposition, whereas positive values indicate increased deposition. 3. Statistical comparisons were performed using Fisher\u0026rsquo;s exact test for categorical variables and the Mann\u0026ndash;Whitney U test for continuous variables. \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003edcLVA, deep cervical lymphatic\u0026ndash;venous anastomosis; ΔCL, Centiloid change value; ΔSUVR, standardized uptake value ratio change rates.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eAt present, available treatments for AD\u0026ndash;related dementia primarily provide symptomatic relief and do not halt the underlying neurodegenerative process [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Growing evidence suggests that reducing cerebral Aβ deposition may delay disease progression, positioning both amyloid-targeted disease-modifying therapies and interventions aimed at enhancing cerebral lymphatic clearance as key areas of contemporary AD research [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. However, direct comparative evidence evaluating the pathological and clinical effects of these two therapeutic strategies remains limited. As a noninvasive molecular imaging modality, AV-45 PET offers objective, reproducible, and quantitative assessment of cerebral Aβ burden, enabling direct evaluation of treatment effects on the core pathology of AD [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Leveraging these advantages, the present study represents, to our knowledge, the first investigation to directly compare the effects of lecanemab and dcLVA surgery on Aβ clearance and cognitive outcomes using AV-45 PET imaging.\u003c/p\u003e \u003cp\u003eIn this retrospective cohort, patients receiving 6 months of standardized lecanemab therapy or dcLVA surgery underwent paired AV-45 PET scans before and after treatment. Our findings demonstrated substantial agreement between visual AV-45 PET assessment and software-based quantitative analysis in the lecanemab group (kappa\u0026thinsp;=\u0026thinsp;0.72; ICC\u0026thinsp;=\u0026thinsp;0.663), supporting the complementary value of these two approaches in clinical evaluation. Importantly, ROC analysis identified the ΔCL as the imaging parameter with the highest diagnostic performance, and multivariate logistic regression confirmed ΔCL\u0026thinsp;\u0026ge;\u0026thinsp;\u0026minus;\u0026thinsp;11.5% as an independent predictor of cognitive decline. These results are consistent with accumulating evidence linking Aβ burden to cognitive deterioration [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Notably, the relatively large standard deviation observed for ΔCL in the lecanemab group likely reflects inter-individual variability in treatment response, as well as statistical dispersion related to modest sample size. Future studies with larger cohorts and the adoption of advanced harmonization strategies, such as the multi-reference region correction and image harmonization framework proposed by Shekari et al. [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], may help reduce variability and enhance the stability of quantitative PET metrics.\u003c/p\u003e \u003cp\u003eIn contrast to lecanemab, dcLVA surgery demonstrated limited efficacy in both clinical and pathological domains. The proportion of patients experiencing significant cognitive decline was markedly higher in the dcLVA group than in the lecanemab group (81.8% vs. 23.5%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). At the imaging level, although regional ΔSUVR values did not differ significantly between groups, the dcLVA group exhibited a positive ΔCL, indicating an overall increase in cerebral Aβ burden. This contrasted with the greater Aβ reduction observed in the lecanemab group and resulted in a statistically significant intergroup difference in global amyloid clearance (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006, r\u0026thinsp;=\u0026thinsp;0.40). These findings suggest that dcLVA surgery may not effectively intervene in the core amyloid pathology of AD. Our results align with the prospective cohort study by Chen eta al. [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], in which most caregivers reported inconsistent symptomatic improvement following dcLVA surgery, accompanied by no significant changes in cerebrospinal fluid Aβ42 levels. Conversely, Ma et al. [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] reported short-term clinical improvement following dcLVA; however, their conclusions were based on a limited 3-month follow-up and lacked pathological endpoints such as Aβ imaging, restricting inference regarding long-term disease modification. Collectively, current evidence underscores substantial uncertainty surrounding the therapeutic efficacy of dcLVA, emphasizing the need for well-designed, multi-center RCTs with extended follow-up and robust pathological outcome measures [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo enhance the reliability of quantitative PET analysis, this study excluded patients with abnormally elevated AV-45 uptake in the cerebellar gray matter, defined as values exceeding the cohort mean plus two standard deviations. As the reference region for SUVR calculation, the cerebellar cortex is assumed to be free of Aβ pathology and metabolically stable. Violation of this assumption can introduce systematic underestimation of cortical Aβ burden by inflating the SUVR denominator. Simulation data from Shekari et al. [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], indicate that such bias may reach nearly 9% in Centiloid units, substantially compromising intergroup comparisons. Although the underlying causes of abnormal cerebellar uptake remain unclear, future studies integrating high-resolution PET/MR imaging may further improve the accuracy and generalizability of Aβ PET quantification.\u003c/p\u003e \u003cp\u003eSeveral limitations warrant consideration. First, the relatively small sample size, particularly in the dcLVA group, may increase susceptibility to type II error. Second, the retrospective design introduces potential selection bias. Third, the absence of long-term follow-up limits evaluation of sustained efficacy and safety. Prospective, large-scale, multicenter RCTs incorporating longitudinal imaging and multimodal biomarkers, such as cerebrospinal fluid Aβ42 and phosphorylated tau, are needed to validate and extend these findings.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eVisual AV-45 PET assessment and Centiloid-based quantification demonstrate good concordance and robust diagnostic performance in evaluating treatment response in AD. A ΔCL\u0026thinsp;\u0026ge;\u0026thinsp;\u0026minus;\u0026thinsp;11.5% serves as a key quantitative indicator of lecanemab efficacy and an independent predictor of cognitive decline. Compared with dcLVA surgery, lecanemab shows superior effectiveness in reducing cerebral Aβ burden and delaying cognitive deterioration in patients with Alzheimer\u0026rsquo;s disease.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"0\" cellspacing=\"3\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAlzheimer\u0026rsquo;s disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eA\u0026beta;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eamyloid-\u0026beta;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAUC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003earea under the curve\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAV-45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003csup\u003e18\u003c/sup\u003eF-florbetapir\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCentiloid value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ecomputed tomography\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003edcLVA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003edeep cervical lymphatic\u0026ndash;venous anastomosis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eICC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eintraclass correlation coefficient\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eIgG1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eimmunoglobulin G1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eIQCODE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eInformant Questionnaire on Cognitive Decline in the Elderly\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eIQR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003einterquartile range\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003emild cognitive impairment\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMCI-AD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003emild cognitive impairment due to Alzheimer\u0026rsquo;s disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMRI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003emagnetic resonance imaging\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNIA\u0026ndash;AA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNational Institute on Aging\u0026ndash;Alzheimer\u0026rsquo;s Association\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eOSEM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eordered subset expectation maximization\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eodds ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePET\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003epositron emission tomography\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePET/CT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003epositron emission tomography/computed tomography\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eROC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ereceiver operating characteristic\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eROI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eregion of interest\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ereference region\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003estandard deviation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSUVR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003estandardized uptake value ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026Delta;CL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003echange in Centiloid value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026Delta;SUVR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003echange in standardized uptake value ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eThis research was funded by grants from the National Natural Science Founda tion of China (no. 82001862), Zhejiang Provincial Natural Science Foundation (no. LQ24H180010).\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e \u003cp\u003eWe would like to thank and express our gratitude to Editage for editorial assistance.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eZhang J, Zhang Y, Wang J, Xia Y, Zhang J, Chen L. Recent advances in Alzheimer's disease: Mechanisms, clinical trials and new drug development strategies [J]. Signal Transduct Target Therapy. 2024;9(1):211.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEstimation of the global prevalence of dementia. in 2019 and forecasted prevalence in 2050: an analysis for the Global Burden of Disease Study 2019 [J]. Lancet Public Health. 2022;7(2):e105\u0026ndash;25.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eScheltens P, De Strooper B, Kivipelto M, Holstege H, Ch\u0026eacute;telat G, Teunissen CE, et al. Alzheimer's disease [J]. 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A randomized, double-blind, phase 2b proof-of-concept clinical trial in early Alzheimer's disease with lecanemab, an anti-Aβ protofibril antibody [J]. Volume 13. Alzheimer's Research \u0026amp; Therapy; 2021. p. 80. 1.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKarran E, De Strooper B. The amyloid hypothesis in Alzheimer disease: new insights from new therapeutics [J]. Nat Rev Drug Discovery. 2022;21(4):306\u0026ndash;18.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBurton JK, Stott DJ, McShane R, Noel-Storr AH, Swann-Price RS, Quinn TJ. Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) for the early detection of dementia across a variety of healthcare settings [J]. The Cochrane Database of Systematic Reviews, 2021, 7(7): Cd011333.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLong JM, Holtzman DM. Alzheimer Disease: An Update on Pathobiology and Treatment Strategies [J]. Cell. 2019;179(2):312\u0026ndash;39.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHorie K, Barth\u0026eacute;lemy NR, Sato C. Bateman RJ.CSF tau microtubule binding region identifies tau tangle and clinical stages of Alzheimer's disease [J]. Brain. 2021;144(2):515\u0026ndash;27.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang QZ, Yilihamu N, Li YB, Li XH, Qin YD. Simple Synthesis of [(18)F] AV-45 and its Clinical Application in the Diagnosis of Alzheimer's Disease [J]. Curr Med Chem. 2024;31(10):1278\u0026ndash;88.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSperling RA, Donohue MC, Raman R, Rafii MS, Johnson K, Masters CL, et al. Trial of Solanezumab in Preclinical Alzheimer's Disease [J]. N Engl J Med. 2023;389(12):1096\u0026ndash;107.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShekari M, V\u0026aacute;llez Garc\u0026iacute;a D, Collij LE, Altomare D, Heeman F, Pemberton H, et al. Stress testing the Centiloid: Precision and variability of PET quantification of amyloid pathology [J]. Volume 20. Alzheimer's \u0026amp; Dementia; 2024. pp. 5102\u0026ndash;13. 8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen JY, Zhao DW, Yin Y, Gui L, Chen X, Wang XM, et al. Deep cervical lymphovenous anastomosis (LVA) for Alzheimer's disease: microsurgical procedure in a prospective cohort study [J]. Int J Surg. 2025;111(7):4211\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen Q, Wen Q, Zhong T, Liu J, Gao H. Deep cervical lymphaticovenous anastomosis for Alzheimer's disease: A narrative review [J]. Volume 21. Alzheimer's \u0026amp; Dementia; 2025. p. e71038. 12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang H, Levey A, Wang G. Lymphatic-venous anastomosis surgery for Alzheimer's disease [J]. Gen Psychiatry. 2025;38(3):e102062.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"AV-45 positron emission tomography, Alzheimer’s disease, lecanemab, deep cervical lymphatic–venous anastomosis, Centiloid scale","lastPublishedDoi":"10.21203/rs.3.rs-8821582/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8821582/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cdiv id=\"ASec1\" class=\"AbstractSection\"\u003e \u003cdiv class=\"Heading\"\u003eObjectives\u003c/div\u003e \u003cp\u003eThis study aimed to validate the clinical utility of visual and software quantitative AV-45 PET analyses and to compare treatment effects between lecanemab and deep cervical lymphatic\u0026ndash;venous anastomosis (dcLVA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"ASec2\" class=\"AbstractSection\"\u003e \u003cdiv class=\"Heading\"\u003eMethods\u003c/div\u003e \u003cp\u003eThis retrospective cohort study included patients with AD who received 6 months of lecanemab therapy or dcLVA surgery between July 2024 and July 2025. AV-45 PET was performed 1 week before and 6 months after treatment. Standardized uptake value ratios (SUVRs) and Centiloid values (CLs) were obtained using visual and software-based quantitative analyses. Agreement between methods was assessed using Cohen\u0026rsquo;s kappa and intraclass correlation coefficients (ICC). Receiver operating characteristic (ROC) analysis evaluated diagnostic performance. Logistic regression analyses were conducted using an Informant Questionnaire on Cognitive Decline in the Elderly score\u0026thinsp;\u0026ge;\u0026thinsp;3.3 as the outcome.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"ASec3\" class=\"AbstractSection\"\u003e \u003cdiv class=\"Heading\"\u003eResults\u003c/div\u003e \u003cp\u003eBaseline demographic, clinical, and imaging characteristics were comparable between groups (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Visual AV-45 PET assessment showed good agreement with Centiloid-based quantification (kappa\u0026thinsp;=\u0026thinsp;0.72; ICC\u0026thinsp;=\u0026thinsp;0.663). ROC analysis identified ΔCL as the optimal imaging marker (area under the curve\u0026thinsp;=\u0026thinsp;0.764, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.026), with a cutoff of \u0026minus;\u0026thinsp;11.5%. ΔCL\u0026thinsp;\u0026ge;\u0026thinsp;\u0026minus;\u0026thinsp;11.5% independently predicted cognitive decline in the lecanemab group (odds ratio\u0026thinsp;=\u0026thinsp;10.281, 95% confidence interval\u0026thinsp;=\u0026thinsp;1.289\u0026ndash;82.005, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.028). Cognitive decline occurred less frequently in the lecanemab group than in the dcLVA group (23.5% vs. 81.8%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). ΔCL differed significantly between groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006), whereas ΔSUVR did not.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"ASec4\" class=\"AbstractSection\"\u003e \u003cdiv class=\"Heading\"\u003eConclusions\u003c/div\u003e \u003cp\u003eVisual and Centiloid-based AV-45 PET analyses show good concordance and clinical value for monitoring AD treatment response. ΔCL is a robust quantitative marker of lecanemab efficacy, which appears superior to dcLVA in reducing cerebral Aβ burden and delaying cognitive decline.\u003c/p\u003e \u003c/div\u003e","manuscriptTitle":"Quantitative AV-45 PET Imaging for Assessing Treatment Response to Lecanemab and Deep Cervical Lymphatic–Venous Anastomosis in Alzheimer’s Disease","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-16 06:23:15","doi":"10.21203/rs.3.rs-8821582/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3f0da9d6-2752-4a86-888a-06692e8d0e1a","owner":[],"postedDate":"February 16th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-25T05:34:28+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-16 06:23:15","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8821582","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8821582","identity":"rs-8821582","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}