Diffusion-Weighted Magnetic Resonance Imaging of the Gallbladder in Acute Cholecystitis: Diagnostic Performance Compared to Histopathological Findings

Diffusion-Weighted Magnetic Resonance Imaging of the Gallbladder in Acute Cholecystitis: Diagnostic Performance Compared to Histopathological Findings | 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 Diffusion-Weighted Magnetic Resonance Imaging of the Gallbladder in Acute Cholecystitis: Diagnostic Performance Compared to Histopathological Findings Ivan Arsic, Søren Rafael Rafaelsen, Konstantina Foufa, Rasa Mikalone, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8018195/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 Purpose: To evaluate the diagnostic performance of gallbladder (GB) wall diffusion restriction on MRCP with diffusion-weighted imaging (DWI) for diagnosing acute cholecystitis (AC), with histopathological findings as the reference standard, and to assess the added value of GB wall thickness and interobserver agreement. Methods: In this retrospective multicenter study, 270 patients underwent MRCP with DWI followed by cholecystectomy within seven days. Three experienced abdominal radiologists independently assessed GB wall diffusion restriction and measured GB wall thickness. Diagnostic accuracy was calculated for DWI, GB wall thickness, and a combined model compared to histopathology-confirmed AC diagnosis. Interobserver agreement was assessed with kappa and intraclass correlation. Subgroup analyses examined the influence of MRI-to-surgery interval and magnetic field strength. Results GB wall diffusion restriction showed high diagnostic accuracy, with sensitivity of 94%, specificity 84%, PPV 77%, and NPV 96% (AUC 0.89). Sensitivity was 100% for surgery performed within 24 hours, but declined with longer intervals. GB wall thickness alone reached an optimal cutoff at 4.3 mm (sensitivity 84%, specificity 72%). The combined model slightly increased AUC (0.92) without significant improvement over DWI alone. Interobserver agreement was substantial for DWI (κ = 0.63) and good for wall thickness (ICC = 0.80). Diagnostic performance was similar across 1.5T and 3.0T field strengths (p = 0.23). Conclusion GB wall diffusion restriction on MRCP with DWI is a reproducible and accurate marker for AC diagnosis. GB wall thickness adds information but only modestly affects overall accuracy. DWI is a robust imaging marker that could be integrated into diagnostic algorithms for suspected AC. Acute cholecystitis Gallbladder Diffusion-weighted imaging MRI MRCP Diagnostic accuracy Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Acute cholecystitis (AC), a common gastrointestinal condition associated with gallstone disease, is typically diagnosed through a combination of clinical findings, inflammatory markers, and ultrasonography (US), according to the 2018 Tokyo guidelines ( 1 ). However, US findings alone, such as gallbladder (GB) wall thickening, pericholecystic fluid, and sludge, show variable sensitivity (37.5–91%) and specificity (83–95%), leading to diagnostic uncertainty that may result in missed cases, delayed treatment, complications, and higher morbidity ( 2 , 3 ). Magnetic resonance cholangiopancreatography (MRCP), a non-invasive method for imaging the biliary tract, can serve as an alternative, offering high diagnostic accuracy without the use of ionizing radiation or contrast agents. In this context, diffusion-weighted imaging (DWI), an additional magnetic resonance imaging (MRI) technique that identifies inflammation and edema through restricted diffusion, has become a promising tool for diagnosing AC. The potential of MRI, including DWI, in diagnosing AC is emphasized by a study from Wang et al., which reported a sensitivity of 83% to 92% and a specificity of 68% to 70% in a cohort of 83 patients ( 4 ). Tomizawa et al. reported a sensitivity of 90.9%, further highlighting the promising potential of DWI in AC diagnosis despite being based on only 11 patients ( 5 ). The present study was conducted to evaluate the diagnostic performance of DWI compared to histopathological findings in a large group of patients undergoing cholecystectomy. We hypothesized that DWI has high diagnostic accuracy for histopathology-confirmed AC and evaluated the added value of including GB wall thickness with DWI. Hence, the aims were to: ( 1 ) Assemble retrospective MRCP exams with DWI and histopathology data; ( 2 ) compare the diagnostic accuracy of DWI, GB wall thickness, and a combined model, with histology as reference; ( 3 ) analyze inter-reader variability for DWI-based AC classification and GB wall thickness; and ( 4 ) investigate subgroup effects of field strength and MRI-to-surgery time interval. Methods Study Design and Setting This retrospective multicenter study was conducted in collaboration between the Departments of Radiology at Viborg Regional Hospital, Regional Hospital Gødstrup Herning, and the University Hospital of Southern Denmark, Aabenraa. The study adhered to the principles of the Declaration of Helsinki and was approved by the Danish National Committee on Health Research Ethics (Case No. 2401317, Document No. 2956684). Because of its retrospective nature, the requirement for informed consent was waived. All study procedures complied with applicable institutional and national regulations for research ethics and data protection. Patient Selection and Clinical Data Patients aged 18 years and older who underwent MRCP, including DWI, for suspected biliary obstruction or inflammation between May 1, 2022, and May 1, 2024, were identified from the Radiology Information System (RIS) and Picture Archiving and Communication System (PACS). Data on cholecystectomy and histopathology were obtained from the electronic patient records. Inclusion required cholecystectomy within seven days of MRCP and complete imaging and pathology datasets, as described below. Patients with delayed surgery or missing data were excluded. Body mass index (BMI) was recorded at admission and categorized into three groups: underweight (BMI < 18.5 kg/m²), normal weight (BMI 18.5–24.9 kg/m²), and overweight (BMI ≥ 25 kg/m²). Imaging Technique Routine MRCP with added DWI was performed on 1.5T Siemens Magnetom Avanto, Sola, and Aera systems, as well as 3.0T Siemens Magnetom Vida systems. MRCP was conducted following the standard protocols: Viborg Regional Hospital (T2 coronal and axial, axial T2 fat-suppressed, coronal T2 3D TSE); Regional Hospital Gødstrup Herning (T2 coronal and axial, axial T2 True FISP, coronal T2 SPACE); and University Hospital of Southern Denmark, Aabenraa (coronal and axial T2 True FISP, coronal T2 3D TSE). All DWI acquisitions used b-values of 0, 400, and 800 s/mm². For the 1.5T systems, DWI parameters included: repetition time, 6000–7500 ms; echo time, 53–78 ms; flip angle, 90°; slice thickness/spacing, 5.0–6.0/6.0–7.8 mm; bandwidth, 1812–1960 Hz/pixel; field of view, 248 × 368 to 338 × 420 mm; acquisition matrix, 184 × 192 to 192–368 (reconstructed); 40 slices; coverage area approximately 200 mm; and acquisition time, 3 minutes and 52 seconds. In the 3.0T systems, DWI parameters included: repetition time, 3000–8600 ms; echo time, 51–56 ms; flip angle, 90°; slice thickness/spacing, 5.0/6.0 mm; bandwidth, 2442 Hz/pixel; field of view, 306 × 380 to 308 × 380 mm; acquisition matrix, 146 × 192 to 128–268 (reconstructed); 40 slices; coverage area approximately 200 mm; and acquisition time, 2 min 31 s. Two patients were scanned on a GE Signa Voyager 1.5T using similar abdominal DWI settings (average acquisition time of three minutes). Imaging Evaluation Three abdominal radiologists (two with eight years and one with 17 years of post-certification experience) independently reviewed all MRCP with DWI datasets, blinded to clinical, pathological, and other imaging findings. Qualitative assessment of the GB wall diffusion restriction was performed without quantitative measurements of ADC values. For this study, diffusion restriction was defined as high signal intensity of the GB wall compared to normal liver on DWI b = 800 images, with corresponding low signal intensity on the apparent diffusion coefficient (ADC) map. Diffusion restriction was evaluated in three anatomical regions of the GB (fundus, corpus, and infundibulum). A diagnosis of AC was considered present if any part of the GB wall showed diffusion restriction. Interobserver agreement on the assessment of diffusion restriction was measured using Cohen’s kappa statistic, with κ values interpreted as follows: 0.81, excellent agreement. For analysis of the diagnostic accuracy, any discrepancies were resolved through consensus. The GB wall thickness (mm) was measured perpendicular to the wall on the coronal T2-weighted sequence at its thickest point. For analysis, the mean of three observers was used as the GB wall-thickness variable. Inter-reader reliability was evaluated using the intraclass correlation coefficient (ICC) with 95% confidence intervals (CI). Histopathological Evaluation Histopathology was used as the reference standard for comparison with GB wall diffusion restriction. Board-certified pathologists assessed specimens using standard protocols ( 6 ), including macroscopic evaluation of GB size, wall thickness, surface integrity, mucosal changes, and gallstones. Microscopic examination graded inflammation. Chronic cholecystitis was defined by lymphocytes, plasma cells, and eosinophils, and AC by additional neutrophilic infiltration. Ulceration, necrosis, and fibrosis were recorded when present. Final diagnoses were categorized as acute or chronic cholecystitis and coded according to the SNOMED morphology system (e.g., M41000 = AC). The acute group included these entities: AC (M41000), acute suppurative cholecystitis (M41100), fibrinous cholecystitis (M41200), gangrenous cholecystitis (M41300), acute ulcerative cholecystitis (M41400), phlegmonous cholecystitis (M41600), emphysematous cholecystitis (M41740), chronic active cholecystitis (M42100), chronic active inflammation (M40001), inflammation with fibrinoid necrosis (M43005), ulcerative inflammation (M54730), and necrotizing inflammation (M40700). The chronic group included: chronic cholecystitis (M40000), xanthogranulomatous cholecystitis (M40400), follicular inflammation (M43080), fibrosis (M49000), chronic inactive inflammation (M43009), and granulomatous inflammation (M38000). Statistical analysis Descriptive statistics were used to display the characteristics of the study population. Normally distributed data are presented as mean ± standard deviation (SD), while non-normally distributed data are reported as median with interquartile range (IQR). Categorical variables are expressed as counts and percentages. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the curve (AUC) were calculated for GB wall diffusion restriction, GB wall thickness, and a combined logistic model of both, using histopathology as reference. Logistic regression analyzed wall thickness as a continuous variable, with the optimal cutoff determined using Youden’s J index. Receiver operating characteristic (ROC) curves were compared using the DeLong method. Interobserver agreement was assessed with Cohen’s and Fleiss’ kappa for evaluations of GB wall diffusion restriction, and ICC with 95% CI for quantitative wall thickness measurements. All analyses were two-sided, and p < 0.05 indicated significance. STATA BE version 19 (StataCorp, Texas, USA) was used for the statistical analyses. Results Two hundred seventy patients referred for MRCP with DWI and subsequently undergoing cholecystectomy were included in the study (Fig. 1 ). The baseline demographics and clinical characteristics are shown in Table 1 . Most patients were overweight, and the prevalence of AC was higher in men than in women across BMI categories. No patients in this cohort were underweight. Table 1 Patient demographics and baseline clinical characteristics, including age, sex distribution, histopathology-confirmed AC, and BMI categories. Characteristic Women (n = 152) Men (n = 118) Total (n = 270) p-value Age, mean (range), years 47.2 (18–85) 56.6 (19–85) – Histopathology confirmed AC, n (%) 40 (26.3) 58 (49.2) 98 (36.3) 0.00018 BMI category, n (AC, %) – Normal weight (18.5–24.9 kg/m 2 ) 22 (8 AC, 36.4%) 19 (9 AC, 47.4%) 41 – Overweight (≥ 25 kg/m 2 ) 130 (32 AC, 24.6%) 99 (49 AC, 49.5%) 229 Illustrative cases To demonstrate the DWI spectrum, two cases are presented. A 74-year-old man with acute right upper quadrant pain and elevated inflammatory markers had US without signs of AC, but MRCP with DWI showed GB wall diffusion restriction, consistent with AC (Fig. 2 A, B). A 27-year-old woman with similar symptoms had no US signs of AC, and MRCP with DWI showed no restriction (wall thickness 5 mm), consistent with chronic cholecystitis (Fig. 2 C, D). Both patients underwent cholecystectomy within 24 h, and histopathology confirmed the AC diagnoses. Diagnostic accuracy of MRI diffusion restriction of the GB wall for diagnosing AC (Table 2 ) Table 2 Diagnostic performance of GB wall diffusion restriction on MRI in relation to MRI-to-cholecystectomy time interval, including sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) with 95% confidence intervals (CI). P-values are provided for comparisons across the three subgroups; (*) indicates a significant PPV decrease with longer intervals. Interval n Sensitivity % (95% CI) Specificity % (95% CI) PPV % (95% CI) NPV % (95% CI) Overall 270 94 (87–98) 84 (77–89) 77 (68–84) 96 (91–99) ≤ 24 hours 50 100 (87–100) 83 (63–95) 87 (69–96) 100 (83–100) 24–72 hours 152 93.7 (85–98) 83 (74–90) 80 (69–88) 95 (87–99) > 72 hours 68 77.8 (40–97) 85 (73–93) 44 (20–70) 96 (87–100) p-value 0.056 0.966 0.003 (*) 0.578 Consensus DWI readings of GB wall diffusion restriction, compared with histopathology, showed a sensitivity of 94% (95% CI: 87–98%), specificity of 84% (95% CI: 77–89%), PPV of 77% (95% CI: 68–84%), and NPV of 96% (95% CI: 91–99%). The AUC was 0.89, indicating excellent diagnostic accuracy. Sensitivity reached 100% (95% CI: 87–100%) when the interval between DWI and cholecystectomy was ≤ 24 hours, but decreased to 77.8% (95% CI: 40–97%) after more than 72 hours; however, this change was not statistically significant (p = 0.056). Specificity and NPV remained stable (p = 0.97 and 0.58), while PPV significantly declined with longer intervals (87% vs. 44%, p = 0.003) (Table 2 ). Diagnostic accuracy of MRI GB wall thickness for the diagnosis of AC (Table 3 ) Table 3 Diagnostic performance of GB wall thickness at different cutoffs (≥ 4, ≥ 5, and ≥ 6 mm, and ≥ 4.3 mm from Youden’s J index) compared to histopathological diagnosis of AC. Values are shown as percentages. Cutoff GB wall thickness Sensitivity % Specificity % PPV % NPV % Accuracy % ≥ 4 mm 89.8 65.1 59.5 91.8 74.1 ≥ 5 mm 73.5 77.9 65.5 83.8 76.3 ≥ 6 mm 56.1 88.4 73.3 77.9 76.7 ≥ 4.3 mm 83.7 72.1 63.1 88.6 76.3 To assess the diagnostic performance of GB wall thickness as a standalone parameter, the mean thickness measured by three radiologists was compared with histopathology as the reference standard for AC. Diagnostic accuracy was evaluated at three clinically relevant thresholds (≥ 4 mm, ≥ 5 mm, and ≥ 6 mm). When analyzing GB wall thickness as a continuous variable, logistic regression showed a sharp increase in the likelihood of histopathology-confirmed AC between 4 and 6 mm (Fig. 3 ). The clinical cutoffs of 4, 5, and 6 mm demonstrated progressively higher specificity but lower sensitivity (Table 3 ). The statistically optimal cutoff, identified by Youden’s J index, was 4.3 mm, offering the best balance between sensitivity (83.7%) and specificity (72.1%) (Fig. 3 ). Combined MRI diagnostic model – GB wall diffusion restriction combined with wall thickness To evaluate whether adding morphologic information enhances diagnostic accuracy, a combined logistic regression model was applied that included both GB wall diffusion restriction and mean GB wall thickness. While diffusion restriction alone achieved an AUC of 0.89 and GB wall thickness alone an AUC of 0.87, the combined model resulted in a higher AUC of 0.92 (Fig. 4 ). Using a probability cutoff of 0.5 (corresponding to a GB wall thickness of about 6.1 mm), the combined model achieved a sensitivity of 94%, specificity of 84%, PPV of 77%, and NPV of 96%. Although these results demonstrate the highest numerical accuracy, a formal comparison of ROC curves (DeLong test) revealed no significant difference between the combined model and DWI alone (p = 0.76). Interobserver Agreement To assess the level of agreement in evaluating GB wall diffusion restriction, Fleiss’ kappa was calculated based on individual radiologist assessments (Yes/No) across 270 cases. All three radiologists agreed in 196 cases (72.6%). Fleiss’ kappa was 0.63, indicating substantial agreement. Pairwise Cohen’s kappa values ranged from 0.55 to 0.70, reflecting moderate to considerable reliability (Fig. 5 ). Interobserver agreement for quantitative measurements of GB wall thickness on MRI among the three radiologists showed an ICC of 0.80 (95% CI: 0.77–0.84), indicating good reliability for MRI-based measurements. Impact of Magnetic Field Strength The diagnostic accuracy of GB wall diffusion restriction compared to histopathology was also evaluated based on magnetic field strength (Table 4 ). At 1.5T (n = 240), DWI achieved a sensitivity of 96% (95% CI: 89–99), specificity of 83% (95% CI: 76–89), PPV of 77% (95% CI: 69–85), and NPV of 97% (95% CI: 92–99). At 3.0T (n = 30), sensitivity was lower at 75% (95% CI: 35–97), while specificity remained similar at 86% (95% CI: 65–97), with PPV of 67% (95% CI: 30–93), and NPV of 90% (95% CI: 70–99). Although the point estimates indicated lower sensitivity at 3.0T, statistical analysis revealed no significant differences between 1.5T and 3.0T in sensitivity (p = 0.23) or specificity (p = 0.77). The interval from DWI to cholecystectomy was comparable between 1.5T and 3.0T examinations (mean 56 vs. 50.5 hours, p = 0.92). The average MRCP exam time, including DWI, was 34 minutes at 1.5T and 24 minutes at 3.0T. Table 4 Diagnostic performance of GB wall diffusion restriction at different magnetic field strengths (1.5T and 3.0T). Values are presented as percentages with 95% confidence intervals (CI). Magnetic field strength Number of patients Sensitivity Specificity PPV NPV 1.5T 240 (88.9%) 96% (95% CI: 89–99) 83% (95% CI: 76–89) 77% (95% CI: 69–85) 97% (95% CI: 92–99) 3.0T 30 (11.1%) 75% (95% CI: 35–97) 86% (95% CI: 65–97) 67% (95% CI: 30–93) 90% (95% CI: 70–99) Discussion This multicenter retrospective study indicated that GB wall diffusion restriction on DWI is a highly accurate diagnostic marker of AC when compared with histopathology as the reference standard. DWI demonstrated excellent sensitivity and NPV. It offers improved diagnostic performance compared with GB wall thickness alone, supporting its role as a reliable tool for ruling out AC in acute clinical scenarios. To our knowledge, this is the most extensive published study directly comparing MRCP with DWI and GB wall thickness to histopathology in patients undergoing cholecystectomy, thereby improving robustness and external validity compared to earlier series. Diagnostic performance of DWI with assessment of diffusion restriction Our findings align with and expand on previous research. Tomizawa et al. reported a sensitivity of 91% in 11 patients with GB wall diffusion restriction, while Wang et al. observed a sensitivity of 83–92% in 83 patients, though with lower specificity (68–70%) ( 4 , 5 ). Gupta et al. found that diffusion restriction in the pericholecystic hepatic tissue had significantly lower sensitivity (30–40%) in a cohort of 153 patients, compared to our study, although specificity remained moderate (75–84%) for differentiating between acute and chronic cholecystitis ( 7 ). Their use of b-values of 0 and 600 s/mm² with breath-hold axial DWI may have decreased sensitivity for subtle diffusion restriction compared to our use of b = 800 s/mm². Higher b-values enhance the contrast between inflamed and non-inflamed tissue, likely explaining the higher sensitivity observed in our cohort. Supporting this, Wang et al. (2015) found that high signal intensity on DWI (b-values of 1000 s/mm²) was an independent indicator of AC ( 4 ). In contrast, ADC values did not significantly distinguish between acute and chronic cases. Overall, these findings support the use of qualitative assessment of diffusion restriction as a practical diagnostic approach, especially in time-sensitive clinical situations. Timing between imaging and surgery is another crucial factor affecting accuracy. Sensitivity remained at 100% when surgery took place within 24 hours of imaging, but dropped to 78% when surgery was delayed beyond 72 hours, along with a notable decrease in PPV. This pattern likely reflects disease progression, with early edema showing clear diffusion restriction, while later fibrotic or necrotic stages obscure signal changes. However, in some cases, spontaneous resolution may also occur. These timing effects correspond with the variability in performance across imaging modalities described in the meta-analysis by Kiewiet et al., and emphasize the importance of incorporating the potential influence of imaging-to-surgery intervals in future research ( 8 ). Gallbladder wall thickness In our cohort, GB wall thickness was confirmed as a proper auxiliary parameter, with an optimal cutoff of 4,3 mm identified using Youden’s J index. This aligns with the Tokyo Guidelines 2018 and previous MR studies by Jung et al. and Omiya et al. ( 1 , 3 , 9 ). Lower thresholds maximize sensitivity and NPV, while higher thresholds increase specificity and PPV. However, wall thickening is not specific for AC and can occur in chronic cholecystitis or systemic conditions such as cirrhosis, renal failure, or heart failure ( 10 – 12 ). Therefore, GB wall thickness is best considered a supplementary marker that should be evaluated in conjunction with DWI and clinical findings, rather than as a standalone criterion. Combined diagnostic model Combining wall thickness with DWI diffusion restriction slightly increased the area under the ROC curve (0.92 vs. 0.89) for DWI alone, and the 83,7% sensitivity for GB wall thickness alone, but this difference was not statistically significant. Interestingly, the optimal cutoff for GB wall thickness differed between models. When analyzed as a single parameter, Youden’s J index identified 4.3 mm as the optimal threshold. In contrast, within the combined model, a probability cutoff of 0.5 corresponded to approximately 6.1 mm. This discrepancy likely reflects the dominant contribution of DWI in the logistic regression model, where wall thickness only provides limited incremental value and therefore requires a higher threshold to influence classification. These findings emphasize that DWI captures the principal pathophysiological features of AC, while wall thickness adds only modest diagnostic information. However, GB wall thickness remains a readily available marker with reasonable accuracy when DWI is not feasible. Clinically, this indicates that DWI may be enough as a primary imaging parameter, especially in urgent situations. However, prospective validation studies are necessary before it can be widely adopted. Interobserver agreement Reproducibility is crucial for clinical translation. In this study, the interobserver agreement for diffusion restriction assessment was substantial (Fleiss κ = 0.63), similar to that reported for CT in previous studies (κ 0.55–0.64) ( 13 ), whereas wall-thickness measurements showed good reliability (ICC = 0.80), exceeding the agreement typically reported for US (κ 0.54–0.71) ( 14 ). Part of this variability may be explained by differences in measurement strategies, for example assessing the maximum wall thickness versus applying standardized measurements at predefined GB sites. Moreover, the κ values reported here align with those found in MRI-based studies of hepatobiliary diseases, where values between 0.60 and 0.75 are generally seen reflecting substantial agreement ( 7 ). The relatively high reproducibility of DWI diffusion restriction interpretation suggests that it is well-suited for routine clinical use, particularly in cases where diagnostic certainty directly impacts surgical decisions. Effect of magnetic field strength Diagnostic performance showed no statistically significant differences across different field strengths. At 1.5T, sensitivity reached 96% and NPV was 97%, while at 3.0T, sensitivity was lower (75%), but specificity stayed similar (86%). Although these differences were not statistically significant, the small sample size of patients at 3.0T (n = 30) resulted in a wide CI. Previous studies have also shown no consistent differences between 1.5T and 3.0T for hepatobiliary imaging, including DWI and MRCP ( 15 ). Notably, 3.0T provided shorter acquisition times (24 vs. 34 minutes), which could improve workflow efficiency. Overall, these results suggest that both field strengths are clinically viable; however, a trend toward higher sensitivity at 1.5T warrants further research. One possible explanation for the lower sensitivity at 3.0T is greater motion and susceptibility artifacts, which may obscure subtle GB wall diffusion restriction and warrant further study. Strengths and limitations The study has several strengths. This is the largest histopathology-verified DWI cohort in AC to date, used a multicenter design, implemented a standardized DWI protocol using both 1.5 and 3.0T with consistent b-values, and had blinded evaluations by experienced radiologists. However, it also has some limitations that should be considered. These include a retrospective design, lack of quantitative diffusion analysis (such as ADC or radiomics), small subgroup sizes—especially at 3.0T—and variability in the time between imaging and surgery. Intravenous contrast was not administered in the present study, however, its use is generally indicated in cases with a clinical suspicion of malignancy ( 16 ). Our cohort included only patients who underwent MRI and subsequent cholecystectomy. In clinical practice, MRI is also performed in suspected AC cases managed conservatively or with other diagnoses. Hence, our present study may overestimate diagnostic accuracy, particularly PPV, compared with a future implementation in clinical practice. Moreover, MRI is costly and may not be readily available in the acute setting in all institutions. The retrospective design and small subgroup sizes without randomization of field strength may limit the generalizability of the findings, and the lack of quantitative diffusion analysis presents a potential area for future research. Given the time-sensitive nature of the condition, abbreviated MRI protocols with reduced and faster sequences may provide valuable diagnostic support in cases of suspected AC. Future perspectives Future research could combine qualitative DWI with quantitative metrics such as ADC values, radiomic profiling, or texture analyses to enhance specificity and predictive accuracy. Multicenter prospective studies with standardized imaging-to-surgery intervals are necessary to verify reproducibility and broader applicability. Additionally, integrating imaging features with clinical and biochemical data could improve predictive models that not only aid in diagnosis but also support surgical risk assessment and perioperative planning. Importantly, future studies should also directly compare DWI with US in the diagnosis of AC. These studies would determine whether DWI can supplement or even replace US, which is currently the primary modality but has inconsistent reproducibility and operator dependence. Conclusion This retrospective multicenter study showed that GB wall diffusion restriction on DWI has excellent sensitivity and NPV for diagnosing AC, and with greater reproducibility than GB wall thickness. GB wall thickness provided additional information but did not significantly improve diagnostic accuracy beyond DWI alone. While further prospective studies are needed, these findings suggest that MRCP with DWI could be incorporated into diagnostic algorithms for suspected AC, with interpretation influenced by the clinical context and surgical timing. Declarations Author Contribution A, B, I, and J wrote the main manuscript text and prepared the figures. All authors participated in the project, including MRI image evaluation, data entry in REDCap, and providing clinical input from radiology, pathology, and surgery. All authors reviewed the manuscript. References Yokoe M, Hata J, Takada T, Strasberg SM, Asbun HJ, Wakabayashi G, et al. Tokyo Guidelines 2018: diagnostic criteria and severity grading of acute cholecystitis (with videos). J Hepatobiliary Pancreat Sci. 2018;25(1):41–54. Thampy R, Khan A, Zaki IH. Acalculous cholecystitis in hospitalized patients with hematological malignancies and the prognostic significance of sonographic gallbladder findings. J Ultrasound Med. 2019;38(1):51–61. Jung SE, Lee JM, Lee K. Gallbladder wall thickening: MR imaging and pathologic correlation with emphasis on layered pattern. Eur Radiol. 2005;15(4):694–701. Wang A. Utility of diffusion-weighted MRI for differentiating acute from chronic cholecystitis. 2015. Tomizawa M, Shinozaki F, Tanaka S. Diffusion-weighted whole-body magnetic resonance imaging with background body signal suppression/T2 image fusion for the diagnosis of acute cholecystitis. Exp Ther Med. 2017;14(1):730–4. Abraham S. Gallbladder and Extrahepatic Biliary System. In: Westra WH, Hruban RH, Phelps TH, Isacson C, editors. Surgical Pathology Dissection: An Illustrated Guide. 2 ed. New York: Springer-Verlag; 2003. p. 102–5. Gupta A, LeBedis CA, Uyeda J, Qureshi MM, Anderson SW, Soto JA. Diffusion-weighted imaging of the pericholecystic hepatic parenchyma for distinguishing acute and chronic cholecystitis. Emerg Radiol. 2018;25(1):7–11. Kiewiet JJ, Leeuwenburgh MM, Bipat S, Bossuyt PM, Stoker J, Boermeester MA. A systematic review and meta-analysis of diagnostic performance of imaging in acute cholecystitis. Radiology. 2012;264(3):708–20. Omiya K, Hiramatsu K, Kato T, Shibata Y, Yoshihara M, Aoba T, et al. Preoperative MRI for predicting pathological changes associated with surgical difficulty during laparoscopic cholecystectomy for acute cholecystitis. BJS Open. 2020;4(5):1137–45. van Breda Vriesman AC, Engelbrecht MR, Smithuis RH, Puylaert JB. Diffuse gallbladder wall thickening: differential diagnosis. AJR Am J Roentgenol. 2007;188(2):495–501. Pedrosa I, Casanova R, Rodriguez R, et al. MR imaging of acute and chronic gallbladder disease. Radiographics. 2008;28(6):1741–54. Yeh BM, Liu PS, Soto JA, Corvera CA, Hussain HK. MR imaging and CT of the biliary tract. Radiology. 2009;250(2):420–37. Chang W-C, Sun Y, Wu E-H, Kim SY, Wang ZJ, Huang G-S, et al. CT Findings for Detecting the Presence of Gangrenous Ischemia in Cholecystitis. AJR Am J Roentgenol. 2016;207(2):302–9. Van Roekel D, LeBedis CA, Santos J, Paul D, Qureshi MM, Kasotakis G, et al. Cholecystitis: association between ultrasound findings and surgical outcomes. Clinical Radiology. 2022;77(5):360–7. Sato M, Kurita Y, Sakai E, Watanabe S, Sanada H, Shimizu T, et al. Computed diffusion- weighted magnetic resonance imaging with high b-values in the diagnosis of gallbladder lesions. Abdominal Radiology (NY). 2022;47(9):3278–89. Choi IY, Cha SH, Yeom SK, Lee SW, Chung HH, Je BK, et al. Diagnosis of acute cholecystitis: value of contrast agent in the gallbladder and cystic duct on Gd-EOB-DTPA enhanced MR cholangiography. Clinical Imaging. 2014;38(2):174–8. Additional Declarations No competing interests reported. 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. 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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-8018195","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":545757037,"identity":"f4d6180c-bcd7-4604-ad04-1b98d3fe8df8","order_by":0,"name":"Ivan Arsic","email":"","orcid":"","institution":"Regionshospitalet Viborg","correspondingAuthor":false,"prefix":"","firstName":"Ivan","middleName":"","lastName":"Arsic","suffix":""},{"id":545757038,"identity":"89b072c3-f3ea-43c8-97b4-a3d209fde3e4","order_by":1,"name":"Søren Rafael Rafaelsen","email":"","orcid":"","institution":"University Hospital of Southern Denmark, Vejle","correspondingAuthor":false,"prefix":"","firstName":"Søren","middleName":"Rafael","lastName":"Rafaelsen","suffix":""},{"id":545757039,"identity":"5bfdf705-43bb-4e12-98b3-4414617c8441","order_by":2,"name":"Konstantina Foufa","email":"","orcid":"","institution":"University Hospital of Southern Denmark, Aabenraa","correspondingAuthor":false,"prefix":"","firstName":"Konstantina","middleName":"","lastName":"Foufa","suffix":""},{"id":545757040,"identity":"62904e83-6fee-4459-ac07-6577bfc3a084","order_by":3,"name":"Rasa Mikalone","email":"","orcid":"","institution":"Regionshospitalet Viborg","correspondingAuthor":false,"prefix":"","firstName":"Rasa","middleName":"","lastName":"Mikalone","suffix":""},{"id":545757041,"identity":"063be655-e272-4cca-839a-4d6095ebe7b2","order_by":4,"name":"Lotte Skeldal","email":"","orcid":"","institution":"Regionshospitalet Viborg","correspondingAuthor":false,"prefix":"","firstName":"Lotte","middleName":"","lastName":"Skeldal","suffix":""},{"id":545757042,"identity":"07abdd9d-38d6-47d6-96b1-f1c5859842f0","order_by":5,"name":"Martina Kuga","email":"","orcid":"","institution":"Regionshospitalet Viborg","correspondingAuthor":false,"prefix":"","firstName":"Martina","middleName":"","lastName":"Kuga","suffix":""},{"id":545757043,"identity":"00f58d34-a76f-482e-9035-64fe6faca35f","order_by":6,"name":"Marie Skrydstrup","email":"","orcid":"","institution":"Regional Hospital Gødstrup, Herning","correspondingAuthor":false,"prefix":"","firstName":"Marie","middleName":"","lastName":"Skrydstrup","suffix":""},{"id":545757044,"identity":"f91c3ba1-0b69-4fd6-b00e-df8ac27bcaa3","order_by":7,"name":"Samuel Kilian Rodriguez Dreis","email":"","orcid":"","institution":"University Hospital of Southern Denmark, Aabenraa","correspondingAuthor":false,"prefix":"","firstName":"Samuel","middleName":"Kilian Rodriguez","lastName":"Dreis","suffix":""},{"id":545757045,"identity":"0f90c6e9-13d4-4517-823f-664040a32e43","order_by":8,"name":"Michael Festersen Nielsen","email":"","orcid":"","institution":"Regional Hospital Horsens","correspondingAuthor":false,"prefix":"","firstName":"Michael","middleName":"Festersen","lastName":"Nielsen","suffix":""},{"id":545757046,"identity":"722d8797-a08d-44c0-96b6-736b32a16e1a","order_by":9,"name":"Jens Brøndum Frøkjær","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAlElEQVRIiWNgGAWjYBACxgYehg8fQKwzJGhhnDmDJC0MDDyMs3lI0sLc3nuw2XbPHQa+MweIdVjPucTmnGfPGCTPNhCrZUaO+eOcA4cZDM4T6zDG+W8Mmy1I0zKDx7CZAaSFeIf15CU29hw4zCNJtPcN288ebPhx4LAc35kEYrVAncNDpHogkCde6SgYBaNgFIxYAACuaS5eRXfeAQAAAABJRU5ErkJggg==","orcid":"","institution":"Aalborg University Hospital","correspondingAuthor":true,"prefix":"","firstName":"Jens","middleName":"Brøndum","lastName":"Frøkjær","suffix":""}],"badges":[],"createdAt":"2025-11-03 10:53:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8018195/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8018195/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":96159510,"identity":"1a092744-cd11-420b-b620-3ec5e730bf25","added_by":"auto","created_at":"2025-11-18 08:42:16","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1150941,"visible":true,"origin":"","legend":"","description":"","filename":"Anonymisedmanuscript.docx","url":"https://assets-eu.researchsquare.com/files/rs-8018195/v1/646faef7f815a31459607a00.docx"},{"id":96159509,"identity":"a7d88f7f-5c0d-41f7-8858-7432b216ac25","added_by":"auto","created_at":"2025-11-18 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08:42:16","extension":"html","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":79592,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8018195/v1/2becd8b66fa647fcb35271b3.html"},{"id":96159511,"identity":"aa9c6a9b-c510-4b7e-b9e7-dfc81c452514","added_by":"auto","created_at":"2025-11-18 08:42:16","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":447401,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of patient selection. Out of 2,433 patients who underwent MRCP with DWI, 270 met the inclusion criteria by having had a cholecystectomy within 7 days, while one patient was excluded due to the absence of the B800 DWI sequence. The final study population was divided into two groups based on the presence or absence of gallbladder wall diffusion restriction, and this division was correlated with histopathological diagnosis.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8018195/v1/c3087d6db27b25fa8faeb687.jpeg"},{"id":96159516,"identity":"26930feb-717b-42f0-bcf1-ebcaa2c98878","added_by":"auto","created_at":"2025-11-18 08:42:16","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1569363,"visible":true,"origin":"","legend":"\u003cp\u003eA 74-year-old man presented with acute right upper quadrant pain and elevated inflammatory markers. (A) Axial DWI (b=800 s/mm²) demonstrates hyperintense gallbladder wall signal (black arrows). (B) Corresponding ADC map shows hypointense signal (white arrows), consistent with diffusion restriction due to acute cholecystitis confirmed by histopathology.\u003c/p\u003e\n\u003cp\u003eA 27-year-old woman presented with acute right upper quadrant pain and elevated inflammatory markers. (C) Axial DWI (b=800 s/mm²) shows no hyperintense signal in the 5 mm thick gallbladder wall (black arrows). (D) The corresponding ADC map demonstrates preserved signal without evidence of diffusion restriction (white arrows), consistent with chronic cholecystitis confirmed by histopathology.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8018195/v1/dfa5c3f8654f098653a88c1c.jpeg"},{"id":96249937,"identity":"8a90840c-acef-4657-80f2-1ca5105b482b","added_by":"auto","created_at":"2025-11-19 07:36:48","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":424327,"visible":true,"origin":"","legend":"\u003cp\u003eLogistic regression curve showing the probability of histopathology-confirmed AC based on gallbladder wall thickness. Vertical lines indicate clinical thresholds of 4, 5, and 6 mm, with the optimal cutoff identified by Youden’s J index (about 4.3 mm; 95% CI: 3.9–4.7 mm) marked on the graph.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8018195/v1/520337b49eb130357a1f43dc.jpeg"},{"id":96252216,"identity":"1c25977b-0d14-4cf3-9af4-6748cae93f6f","added_by":"auto","created_at":"2025-11-19 07:40:40","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":492136,"visible":true,"origin":"","legend":"\u003cp\u003eReceiver operating characteristic (ROC) curves for diagnosing AC with diffusion-weighted imaging (DWI), gallbladder (GB) wall thickness, and the combined model. The areas under the curve (AUC) were 0.892 (95% CI: 0.85–0.93) for DWI, 0.868 (95% CI: 0.82–0.91) for GB wall thickness, and 0.916 (95% CI: 0.88–0.95) for the combined model.\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8018195/v1/842bf39fd8eed43b369086ea.jpeg"},{"id":96159519,"identity":"83a20ae1-8dd9-434e-bb0c-a7943cf708e9","added_by":"auto","created_at":"2025-11-18 08:42:16","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":716882,"visible":true,"origin":"","legend":"\u003cp\u003eInterobserver agreement for gallbladder wall diffusion restriction assessment. Cohen’s kappa values are shown for each pair of radiologists (R1 vs R2, R1 vs R3, R2 vs R3), and Fleiss’ kappa indicates overall agreement among all three readers. Reference lines indicate thresholds for moderate (0.41–0.60), substantial (≥0.61), and almost perfect agreement (≥0.81).\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8018195/v1/fcded64d51db4eb4553bca40.jpeg"},{"id":97136261,"identity":"c6ad2c08-d084-4b04-905e-d220a3e8d89d","added_by":"auto","created_at":"2025-12-01 09:56:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4651568,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8018195/v1/6617c5d9-adb4-47a7-ac83-6b70d53f1df2.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Diffusion-Weighted Magnetic Resonance Imaging of the Gallbladder in Acute Cholecystitis: Diagnostic Performance Compared to Histopathological Findings","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAcute cholecystitis (AC), a common gastrointestinal condition associated with gallstone disease, is typically diagnosed through a combination of clinical findings, inflammatory markers, and ultrasonography (US), according to the 2018 Tokyo guidelines (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). However, US findings alone, such as gallbladder (GB) wall thickening, pericholecystic fluid, and sludge, show variable sensitivity (37.5\u0026ndash;91%) and specificity (83\u0026ndash;95%), leading to diagnostic uncertainty that may result in missed cases, delayed treatment, complications, and higher morbidity (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Magnetic resonance cholangiopancreatography (MRCP), a non-invasive method for imaging the biliary tract, can serve as an alternative, offering high diagnostic accuracy without the use of ionizing radiation or contrast agents. In this context, diffusion-weighted imaging (DWI), an additional magnetic resonance imaging (MRI) technique that identifies inflammation and edema through restricted diffusion, has become a promising tool for diagnosing AC. The potential of MRI, including DWI, in diagnosing AC is emphasized by a study from Wang et al., which reported a sensitivity of 83% to 92% and a specificity of 68% to 70% in a cohort of 83 patients (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Tomizawa et al. reported a sensitivity of 90.9%, further highlighting the promising potential of DWI in AC diagnosis despite being based on only 11 patients (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe present study was conducted to evaluate the diagnostic performance of DWI compared to histopathological findings in a large group of patients undergoing cholecystectomy. We hypothesized that DWI has high diagnostic accuracy for histopathology-confirmed AC and evaluated the added value of including GB wall thickness with DWI. Hence, the aims were to: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) Assemble retrospective MRCP exams with DWI and histopathology data; (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) compare the diagnostic accuracy of DWI, GB wall thickness, and a combined model, with histology as reference; (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) analyze inter-reader variability for DWI-based AC classification and GB wall thickness; and (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) investigate subgroup effects of field strength and MRI-to-surgery time interval.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Design and Setting\u003c/h2\u003e\u003cp\u003e This retrospective multicenter study was conducted in collaboration between the Departments of Radiology at Viborg Regional Hospital, Regional Hospital G\u0026oslash;dstrup Herning, and the University Hospital of Southern Denmark, Aabenraa. The study adhered to the principles of the Declaration of Helsinki and was approved by the Danish National Committee on Health Research Ethics (Case No. 2401317, Document No. 2956684). Because of its retrospective nature, the requirement for informed consent was waived. All study procedures complied with applicable institutional and national regulations for research ethics and data protection.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003ePatient Selection and Clinical Data\u003c/h3\u003e\n\u003cp\u003ePatients aged 18 years and older who underwent MRCP, including DWI, for suspected biliary obstruction or inflammation between May 1, 2022, and May 1, 2024, were identified from the Radiology Information System (RIS) and Picture Archiving and Communication System (PACS). Data on cholecystectomy and histopathology were obtained from the electronic patient records. Inclusion required cholecystectomy within seven days of MRCP and complete imaging and pathology datasets, as described below. Patients with delayed surgery or missing data were excluded. Body mass index (BMI) was recorded at admission and categorized into three groups: underweight (BMI\u0026thinsp;\u0026lt;\u0026thinsp;18.5 kg/m\u0026sup2;), normal weight (BMI 18.5\u0026ndash;24.9 kg/m\u0026sup2;), and overweight (BMI\u0026thinsp;\u0026ge;\u0026thinsp;25 kg/m\u0026sup2;).\u003c/p\u003e\n\u003ch3\u003eImaging Technique\u003c/h3\u003e\n\u003cp\u003eRoutine MRCP with added DWI was performed on 1.5T Siemens Magnetom Avanto, Sola, and Aera systems, as well as 3.0T Siemens Magnetom Vida systems. MRCP was conducted following the standard protocols: Viborg Regional Hospital (T2 coronal and axial, axial T2 fat-suppressed, coronal T2 3D TSE); Regional Hospital G\u0026oslash;dstrup Herning (T2 coronal and axial, axial T2 True FISP, coronal T2 SPACE); and University Hospital of Southern Denmark, Aabenraa (coronal and axial T2 True FISP, coronal T2 3D TSE).\u003c/p\u003e\u003cp\u003eAll DWI acquisitions used b-values of 0, 400, and 800 s/mm\u0026sup2;. For the 1.5T systems, DWI parameters included: repetition time, 6000\u0026ndash;7500 ms; echo time, 53\u0026ndash;78 ms; flip angle, 90\u0026deg;; slice thickness/spacing, 5.0\u0026ndash;6.0/6.0\u0026ndash;7.8 mm; bandwidth, 1812\u0026ndash;1960 Hz/pixel; field of view, 248 \u0026times; 368 to 338 \u0026times; 420 mm; acquisition matrix, 184 \u0026times; 192 to 192\u0026ndash;368 (reconstructed); 40 slices; coverage area approximately 200 mm; and acquisition time, 3 minutes and 52 seconds. In the 3.0T systems, DWI parameters included: repetition time, 3000\u0026ndash;8600 ms; echo time, 51\u0026ndash;56 ms; flip angle, 90\u0026deg;; slice thickness/spacing, 5.0/6.0 mm; bandwidth, 2442 Hz/pixel; field of view, 306 \u0026times; 380 to 308 \u0026times; 380 mm; acquisition matrix, 146 \u0026times; 192 to 128\u0026ndash;268 (reconstructed); 40 slices; coverage area approximately 200 mm; and acquisition time, 2 min 31 s.\u003c/p\u003e\u003cp\u003eTwo patients were scanned on a GE Signa Voyager 1.5T using similar abdominal DWI settings (average acquisition time of three minutes).\u003c/p\u003e\n\u003ch3\u003eImaging Evaluation\u003c/h3\u003e\n\u003cp\u003e Three abdominal radiologists (two with eight years and one with 17 years of post-certification experience) independently reviewed all MRCP with DWI datasets, blinded to clinical, pathological, and other imaging findings. Qualitative assessment of the GB wall diffusion restriction was performed without quantitative measurements of ADC values. For this study, diffusion restriction was defined as high signal intensity of the GB wall compared to normal liver on DWI b\u0026thinsp;=\u0026thinsp;800 images, with corresponding low signal intensity on the apparent diffusion coefficient (ADC) map. Diffusion restriction was evaluated in three anatomical regions of the GB (fundus, corpus, and infundibulum). A diagnosis of AC was considered present if any part of the GB wall showed diffusion restriction. Interobserver agreement on the assessment of diffusion restriction was measured using Cohen\u0026rsquo;s kappa statistic, with κ values interpreted as follows: \u0026lt;0.20 indicating poor agreement; 0.21\u0026ndash;0.40, fair; 0.41\u0026ndash;0.60, moderate; 0.61\u0026ndash;0.80, good; and \u0026gt;\u0026thinsp;0.81, excellent agreement. For analysis of the diagnostic accuracy, any discrepancies were resolved through consensus.\u003c/p\u003e\u003cp\u003eThe GB wall thickness (mm) was measured perpendicular to the wall on the coronal T2-weighted sequence at its thickest point. For analysis, the mean of three observers was used as the GB wall-thickness variable. Inter-reader reliability was evaluated using the intraclass correlation coefficient (ICC) with 95% confidence intervals (CI).\u003c/p\u003e\n\u003ch3\u003eHistopathological Evaluation\u003c/h3\u003e\n\u003cp\u003eHistopathology was used as the reference standard for comparison with GB wall diffusion restriction. Board-certified pathologists assessed specimens using standard protocols (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e), including macroscopic evaluation of GB size, wall thickness, surface integrity, mucosal changes, and gallstones. Microscopic examination graded inflammation. Chronic cholecystitis was defined by lymphocytes, plasma cells, and eosinophils, and AC by additional neutrophilic infiltration. Ulceration, necrosis, and fibrosis were recorded when present. Final diagnoses were categorized as acute or chronic cholecystitis and coded according to the SNOMED morphology system (e.g., M41000\u0026thinsp;=\u0026thinsp;AC).\u003c/p\u003e\u003cp\u003eThe acute group included these entities: AC (M41000), acute suppurative cholecystitis (M41100), fibrinous cholecystitis (M41200), gangrenous cholecystitis (M41300), acute ulcerative cholecystitis (M41400), phlegmonous cholecystitis (M41600), emphysematous cholecystitis (M41740), chronic active cholecystitis (M42100), chronic active inflammation (M40001), inflammation with fibrinoid necrosis (M43005), ulcerative inflammation (M54730), and necrotizing inflammation (M40700).\u003c/p\u003e\u003cp\u003eThe chronic group included: chronic cholecystitis (M40000), xanthogranulomatous cholecystitis (M40400), follicular inflammation (M43080), fibrosis (M49000), chronic inactive inflammation (M43009), and granulomatous inflammation (M38000).\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eDescriptive statistics were used to display the characteristics of the study population. Normally distributed data are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD), while non-normally distributed data are reported as median with interquartile range (IQR). Categorical variables are expressed as counts and percentages. Sensitivity, specificity, positive predictive value (PPV), negative predictive value\u003c/p\u003e\u003cp\u003e(NPV), and area under the curve (AUC) were calculated for GB wall diffusion restriction, GB wall thickness, and a combined logistic model of both, using histopathology as reference. Logistic regression analyzed wall thickness as a continuous variable, with the optimal cutoff determined using Youden\u0026rsquo;s J index. Receiver operating characteristic (ROC) curves were compared using the DeLong method. Interobserver agreement was assessed with Cohen\u0026rsquo;s and Fleiss\u0026rsquo; kappa for evaluations of GB wall diffusion restriction, and ICC with 95% CI for quantitative wall thickness measurements. All analyses were two-sided, and p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicated significance. STATA BE version 19 (StataCorp, Texas, USA) was used for the statistical analyses.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eTwo hundred seventy patients referred for MRCP with DWI and subsequently undergoing cholecystectomy were included in the study (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The baseline demographics and clinical characteristics are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Most patients were overweight, and the prevalence of AC was higher in men than in women across BMI categories. No patients in this cohort were underweight.\u003c/p\u003e\u003cp\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\u003ePatient demographics and baseline clinical characteristics, including age, sex distribution, histopathology-confirmed AC, and BMI categories.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\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\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWomen (n\u0026thinsp;=\u0026thinsp;152)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMen (n\u0026thinsp;=\u0026thinsp;118)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;270)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep-value\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, mean (range), years\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e47.2 (18\u0026ndash;85)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e56.6 (19\u0026ndash;85)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHistopathology confirmed AC, n (%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e40 (26.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e58 (49.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e98 (36.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.00018\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBMI category, n (AC, %)\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ndash; Normal weight (18.5\u0026ndash;24.9 kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22 (8 AC, 36.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19 (9 AC, 47.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ndash; Overweight (\u0026ge;\u0026thinsp;25 kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e130 (32 AC, 24.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e99 (49 AC, 49.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e229\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\n\u003ch3\u003eIllustrative cases\u003c/h3\u003e\n\u003cp\u003eTo demonstrate the DWI spectrum, two cases are presented. A 74-year-old man with acute right upper quadrant pain and elevated inflammatory markers had US without signs of AC, but MRCP with DWI showed GB wall diffusion restriction, consistent with AC (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA, B). A 27-year-old woman with similar symptoms had no US signs of AC, and MRCP with DWI showed no restriction (wall thickness 5 mm), consistent with chronic cholecystitis (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC, D). Both patients underwent cholecystectomy within 24 h, and histopathology confirmed the AC diagnoses.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eDiagnostic accuracy of MRI diffusion restriction of the GB wall for diagnosing AC (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e)\u003c/h2\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\u003eDiagnostic performance of GB wall diffusion restriction on MRI in relation to MRI-to-cholecystectomy time interval, including sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) with 95% confidence intervals (CI). P-values are provided for comparisons across the three subgroups; (*) indicates a significant PPV decrease with longer intervals.\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=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" 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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInterval\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003en\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSensitivity % (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSpecificity % (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePPV % (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNPV % (95% CI)\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\u003eOverall\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e270\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e94 (87\u0026ndash;98)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e84 (77\u0026ndash;89)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e77 (68\u0026ndash;84)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e96 (91\u0026ndash;99)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e\u0026le;\u0026thinsp;24 hours\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e100 (87\u0026ndash;100)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e83 (63\u0026ndash;95)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e87 (69\u0026ndash;96)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e100 (83\u0026ndash;100)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e24\u0026ndash;72 hours\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e152\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e93.7 (85\u0026ndash;98)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e83 (74\u0026ndash;90)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e80 (69\u0026ndash;88)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e95 (87\u0026ndash;99)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e\u0026gt;\u0026thinsp;72 hours\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e77.8 (40\u0026ndash;97)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e85 (73\u0026ndash;93)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e44 (20\u0026ndash;70)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e96 (87\u0026ndash;100)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ep-value\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\u003cp\u003e0.056\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.966\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.003 (*)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.578\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\u003eConsensus DWI readings of GB wall diffusion restriction, compared with histopathology, showed a sensitivity of 94% (95% CI: 87\u0026ndash;98%), specificity of 84% (95% CI: 77\u0026ndash;89%), PPV of 77% (95% CI: 68\u0026ndash;84%), and NPV of 96% (95% CI: 91\u0026ndash;99%). The AUC was 0.89, indicating excellent diagnostic accuracy. Sensitivity reached 100% (95% CI: 87\u0026ndash;100%) when the interval between DWI and cholecystectomy was \u0026le;\u0026thinsp;24 hours, but decreased to 77.8% (95% CI: 40\u0026ndash;97%) after more than 72 hours; however, this change was not statistically significant (p\u0026thinsp;=\u0026thinsp;0.056). Specificity and NPV remained stable (p\u0026thinsp;=\u0026thinsp;0.97 and 0.58), while PPV significantly declined with longer intervals (87% vs. 44%, p\u0026thinsp;=\u0026thinsp;0.003) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eDiagnostic accuracy of MRI GB wall thickness for the diagnosis of AC (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e)\u003c/h2\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\u003eDiagnostic performance of GB wall thickness at different cutoffs (\u0026ge;\u0026thinsp;4, \u0026ge;\u0026thinsp;5, and \u0026ge;\u0026thinsp;6 mm, and \u0026ge;\u0026thinsp;4.3 mm from Youden\u0026rsquo;s J index) compared to histopathological diagnosis of AC. Values are shown as percentages.\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=\"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=\"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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCutoff GB wall thickness\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSensitivity %\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSpecificity %\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePPV %\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNPV %\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eAccuracy %\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\u003e\u0026ge;\u0026thinsp;4 mm\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e89.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e65.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e59.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e91.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e74.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e\u0026ge;\u0026thinsp;5 mm\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e73.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e77.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e65.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e83.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e76.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e\u0026ge;\u0026thinsp;6 mm\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e56.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e88.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e73.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e77.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e76.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e\u0026ge;\u0026thinsp;4.3 mm\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e83.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e72.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e63.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e88.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e76.3\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\u003eTo assess the diagnostic performance of GB wall thickness as a standalone parameter, the mean thickness measured by three radiologists was compared with histopathology as the reference standard for AC. Diagnostic accuracy was evaluated at three clinically relevant thresholds (\u0026ge;\u0026thinsp;4 mm, \u0026ge;\u0026thinsp;5 mm, and \u0026ge;\u0026thinsp;6 mm). When analyzing GB wall thickness as a continuous variable, logistic regression showed a sharp increase in the likelihood of histopathology-confirmed AC between 4 and 6 mm (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The clinical cutoffs of 4, 5, and 6 mm demonstrated progressively higher specificity but lower sensitivity (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The statistically optimal cutoff, identified by Youden\u0026rsquo;s J index, was 4.3 mm, offering the best balance between sensitivity (83.7%) and specificity (72.1%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eCombined MRI diagnostic model \u0026ndash; GB wall diffusion restriction combined with wall thickness\u003c/h2\u003e\u003cp\u003eTo evaluate whether adding morphologic information enhances diagnostic accuracy, a combined logistic regression model was applied that included both GB wall diffusion restriction and mean GB wall thickness. While diffusion restriction alone achieved an AUC of 0.89 and GB wall thickness alone an AUC of 0.87, the combined model resulted in a higher AUC of 0.92 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Using a probability cutoff of 0.5 (corresponding to a GB wall thickness of about 6.1 mm), the combined model achieved a sensitivity of 94%, specificity of 84%, PPV of 77%, and NPV of 96%. Although these results demonstrate the highest numerical accuracy, a formal comparison of ROC curves (DeLong test) revealed no significant difference between the combined model and DWI alone (p\u0026thinsp;=\u0026thinsp;0.76).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eInterobserver Agreement\u003c/h2\u003e\u003cp\u003eTo assess the level of agreement in evaluating GB wall diffusion restriction, Fleiss\u0026rsquo; kappa was calculated based on individual radiologist assessments (Yes/No) across 270 cases. All three radiologists agreed in 196 cases (72.6%). Fleiss\u0026rsquo; kappa was 0.63, indicating substantial agreement. Pairwise Cohen\u0026rsquo;s kappa values ranged from 0.55 to 0.70, reflecting moderate to considerable reliability (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e Interobserver agreement for quantitative measurements of GB wall thickness on MRI among the three radiologists showed an ICC of 0.80 (95% CI: 0.77\u0026ndash;0.84), indicating good reliability for MRI-based measurements.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eImpact of Magnetic Field Strength\u003c/h2\u003e\u003cp\u003eThe diagnostic accuracy of GB wall diffusion restriction compared to histopathology was also evaluated based on magnetic field strength (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). At 1.5T (n\u0026thinsp;=\u0026thinsp;240), DWI achieved a sensitivity of 96% (95% CI: 89\u0026ndash;99), specificity of 83% (95% CI: 76\u0026ndash;89), PPV of 77% (95% CI: 69\u0026ndash;85), and NPV of 97% (95% CI: 92\u0026ndash;99). At 3.0T (n\u0026thinsp;=\u0026thinsp;30), sensitivity was lower at 75% (95% CI: 35\u0026ndash;97), while specificity remained similar at 86% (95% CI: 65\u0026ndash;97), with PPV of 67% (95% CI: 30\u0026ndash;93), and NPV of 90% (95% CI: 70\u0026ndash;99). Although the point estimates indicated lower sensitivity at 3.0T, statistical analysis revealed no significant differences between 1.5T and 3.0T in sensitivity (p\u0026thinsp;=\u0026thinsp;0.23) or specificity (p\u0026thinsp;=\u0026thinsp;0.77). The interval from DWI to cholecystectomy was comparable between 1.5T and 3.0T examinations (mean 56 vs. 50.5 hours, p\u0026thinsp;=\u0026thinsp;0.92). The average MRCP exam time, including DWI, was 34 minutes at 1.5T and 24 minutes at 3.0T.\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\u003eDiagnostic performance of GB wall diffusion restriction at different magnetic field strengths (1.5T and 3.0T). Values are presented as percentages with 95% confidence intervals (CI).\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=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" 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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMagnetic field strength\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNumber of patients\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\u003ePPV\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNPV\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\u003e1.5T\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e240 (88.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e96% (95% CI: 89\u0026ndash;99)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e83% (95% CI: 76\u0026ndash;89)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e77% (95% CI: 69\u0026ndash;85)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e97% (95% CI: 92\u0026ndash;99)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e3.0T\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30\u003c/p\u003e\u003cp\u003e(11.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e75% (95% CI: 35\u0026ndash;97)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e86% (95% CI: 65\u0026ndash;97)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e67% (95% CI: 30\u0026ndash;93)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e90% (95% CI: 70\u0026ndash;99)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis multicenter retrospective study indicated that GB wall diffusion restriction on DWI is a highly accurate diagnostic marker of AC when compared with histopathology as the reference standard. DWI demonstrated excellent sensitivity and NPV. It offers improved diagnostic performance compared with GB wall thickness alone, supporting its role as a reliable tool for ruling out AC in acute clinical scenarios. To our knowledge, this is the most extensive published study directly comparing MRCP with DWI and GB wall thickness to histopathology in patients undergoing cholecystectomy, thereby improving robustness and external validity compared to earlier series.\u003c/p\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eDiagnostic performance of DWI with assessment of diffusion restriction\u003c/h2\u003e\u003cp\u003eOur findings align with and expand on previous research. Tomizawa et al. reported a sensitivity of 91% in 11 patients with GB wall diffusion restriction, while Wang et al. observed a sensitivity of 83\u0026ndash;92% in 83 patients, though with lower specificity (68\u0026ndash;70%) (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Gupta et al. found that diffusion restriction in the pericholecystic hepatic tissue had significantly lower sensitivity (30\u0026ndash;40%) in a cohort of 153 patients, compared to our study, although specificity remained moderate (75\u0026ndash;84%) for differentiating between acute and chronic cholecystitis (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Their use of b-values of 0 and 600 s/mm\u0026sup2; with breath-hold axial DWI may have decreased sensitivity for subtle diffusion restriction compared to our use of b\u0026thinsp;=\u0026thinsp;800 s/mm\u0026sup2;. Higher b-values enhance the contrast between inflamed and non-inflamed tissue, likely explaining the higher sensitivity observed in our cohort. Supporting this, Wang et al. (2015) found that high signal intensity on DWI (b-values of 1000 s/mm\u0026sup2;) was an independent indicator of AC (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). In contrast, ADC values did not significantly distinguish between acute and chronic cases. Overall, these findings support the use of qualitative assessment of diffusion restriction as a practical diagnostic approach, especially in time-sensitive clinical situations.\u003c/p\u003e\u003cp\u003eTiming between imaging and surgery is another crucial factor affecting accuracy. Sensitivity remained at 100% when surgery took place within 24 hours of imaging, but dropped to 78% when surgery was delayed beyond 72 hours, along with a notable decrease in PPV. This pattern likely reflects disease progression, with early edema showing clear diffusion restriction, while later fibrotic or necrotic stages obscure signal changes. However, in some cases, spontaneous resolution may also occur. These timing effects correspond with the variability in performance across imaging modalities described in the meta-analysis by Kiewiet et al., and emphasize the importance of incorporating the potential influence of imaging-to-surgery intervals in future research (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eGallbladder wall thickness\u003c/h2\u003e\u003cp\u003eIn our cohort, GB wall thickness was confirmed as a proper auxiliary parameter, with an optimal cutoff of 4,3 mm identified using Youden\u0026rsquo;s J index. This aligns with the Tokyo Guidelines 2018 and previous MR studies by Jung et al. and Omiya et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Lower thresholds maximize sensitivity and NPV, while higher thresholds increase specificity and PPV. However, wall thickening is not specific for AC and can occur in chronic cholecystitis or systemic conditions such as cirrhosis, renal failure, or heart failure (\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Therefore, GB wall thickness is best considered a supplementary marker that should be evaluated in conjunction with DWI and clinical findings, rather than as a standalone criterion.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003eCombined diagnostic model\u003c/h2\u003e\u003cp\u003eCombining wall thickness with DWI diffusion restriction slightly increased the area under the ROC curve (0.92 vs. 0.89) for DWI alone, and the 83,7% sensitivity for GB wall thickness alone, but this difference was not statistically significant. Interestingly, the optimal cutoff for GB wall thickness differed between models. When analyzed as a single parameter, Youden\u0026rsquo;s J index identified 4.3 mm as the optimal threshold. In contrast, within the combined model, a probability cutoff of 0.5 corresponded to approximately 6.1 mm. This discrepancy likely reflects the dominant contribution of DWI in the logistic regression model, where wall thickness only provides limited incremental value and therefore requires a higher threshold to influence classification. These findings emphasize that DWI captures the principal pathophysiological features of AC, while wall thickness adds only modest diagnostic information. However, GB wall thickness remains a readily available marker with reasonable accuracy when DWI is not feasible. Clinically, this indicates that DWI may be enough as a primary imaging parameter, especially in urgent situations. However, prospective validation studies are necessary before it can be widely adopted.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003eInterobserver agreement\u003c/h2\u003e\u003cp\u003eReproducibility is crucial for clinical translation. In this study, the interobserver agreement for diffusion restriction assessment was substantial (Fleiss κ\u0026thinsp;=\u0026thinsp;0.63), similar to that reported for CT in previous studies (κ 0.55\u0026ndash;0.64) (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e), whereas wall-thickness measurements showed good reliability (ICC\u0026thinsp;=\u0026thinsp;0.80), exceeding the agreement typically reported for US (κ 0.54\u0026ndash;0.71) (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Part of this variability may be explained by differences in measurement strategies, for example assessing the maximum wall thickness versus applying standardized measurements at predefined GB sites. Moreover, the κ values reported here align with those found in MRI-based studies of hepatobiliary diseases, where values between 0.60 and 0.75 are generally seen reflecting substantial agreement (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). The relatively high reproducibility of DWI diffusion restriction interpretation suggests that it is well-suited for routine clinical use, particularly in cases where diagnostic certainty directly impacts surgical decisions.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003eEffect of magnetic field strength\u003c/h2\u003e\u003cp\u003eDiagnostic performance showed no statistically significant differences across different field strengths. At 1.5T, sensitivity reached 96% and NPV was 97%, while at 3.0T, sensitivity was lower (75%), but specificity stayed similar (86%). Although these differences were not statistically significant, the small sample size of patients at 3.0T (n\u0026thinsp;=\u0026thinsp;30) resulted in a wide CI. Previous studies have also shown no consistent differences between 1.5T and 3.0T for hepatobiliary imaging, including DWI and MRCP (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Notably, 3.0T provided shorter acquisition times (24 vs. 34 minutes), which could improve workflow efficiency. Overall, these results suggest that both field strengths are clinically viable; however, a trend toward higher sensitivity at 1.5T warrants further research. One possible explanation for the lower sensitivity at 3.0T is greater motion and susceptibility artifacts, which may obscure subtle GB wall diffusion restriction and warrant further study.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\u003ch2\u003eStrengths and limitations\u003c/h2\u003e\u003cp\u003eThe study has several strengths. This is the largest histopathology-verified DWI cohort in AC to date, used a multicenter design, implemented a standardized DWI protocol using both 1.5 and 3.0T with consistent b-values, and had blinded evaluations by experienced radiologists. However, it also has some limitations that should be considered. These include a retrospective design, lack of quantitative diffusion analysis (such as ADC or radiomics), small subgroup sizes\u0026mdash;especially at 3.0T\u0026mdash;and variability in the time between imaging and surgery. Intravenous contrast was not administered in the present study, however, its use is generally indicated in cases with a clinical suspicion of malignancy (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Our cohort included only patients who underwent MRI and subsequent cholecystectomy. In clinical practice, MRI is also performed in suspected AC cases managed conservatively or with other diagnoses. Hence, our present study may overestimate diagnostic accuracy, particularly PPV, compared with a future implementation in clinical practice. Moreover, MRI is costly and may not be readily available in the acute setting in all institutions. The retrospective design and small subgroup sizes without randomization of field strength may limit the generalizability of the findings, and the lack of quantitative diffusion analysis presents a potential area for future research. Given the time-sensitive nature of the condition, abbreviated MRI protocols with reduced and faster sequences may provide valuable diagnostic support in cases of suspected AC.\u003c/p\u003e\u003cdiv id=\"Sec23\" class=\"Section3\"\u003e\u003ch2\u003eFuture perspectives\u003c/h2\u003e\u003cp\u003eFuture research could combine qualitative DWI with quantitative metrics such as ADC values, radiomic profiling, or texture analyses to enhance specificity and predictive accuracy. Multicenter prospective studies with standardized imaging-to-surgery intervals are necessary to verify reproducibility and broader applicability. Additionally, integrating imaging features with clinical and biochemical data could improve predictive models that not only aid in diagnosis but also support surgical risk assessment and perioperative planning. Importantly, future studies should also directly compare DWI with US in the diagnosis of AC. These studies would determine whether DWI can supplement or even replace US, which is currently the primary modality but has inconsistent reproducibility and operator dependence.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis retrospective multicenter study showed that GB wall diffusion restriction on DWI has excellent sensitivity and NPV for diagnosing AC, and with greater reproducibility than GB wall thickness. GB wall thickness provided additional information but did not significantly improve diagnostic accuracy beyond DWI alone. While further prospective studies are needed, these findings suggest that MRCP with DWI could be incorporated into diagnostic algorithms for suspected AC, with interpretation influenced by the clinical context and surgical timing.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eA, B, I, and J wrote the main manuscript text and prepared the figures. All authors participated in the project, including MRI image evaluation, data entry in REDCap, and providing clinical input from radiology, pathology, and surgery. All authors reviewed the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eYokoe M, Hata J, Takada T, Strasberg SM, Asbun HJ, Wakabayashi G, et al. Tokyo Guidelines 2018: diagnostic criteria and severity grading of acute cholecystitis (with videos). J Hepatobiliary Pancreat Sci. 2018;25(1):41\u0026ndash;54.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eThampy R, Khan A, Zaki IH. Acalculous cholecystitis in hospitalized patients with hematological malignancies and the prognostic significance of sonographic gallbladder findings. J Ultrasound Med. 2019;38(1):51\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJung SE, Lee JM, Lee K. Gallbladder wall thickening: MR imaging and pathologic correlation with emphasis on layered pattern. Eur Radiol. 2005;15(4):694\u0026ndash;701.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang A. Utility of diffusion-weighted MRI for differentiating acute from chronic cholecystitis. 2015.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTomizawa M, Shinozaki F, Tanaka S. Diffusion-weighted whole-body magnetic resonance imaging with background body signal suppression/T2 image fusion for the diagnosis of acute cholecystitis. Exp Ther Med. 2017;14(1):730\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAbraham S. Gallbladder and Extrahepatic Biliary System. In: Westra WH, Hruban RH, Phelps TH, Isacson C, editors. Surgical Pathology Dissection: An Illustrated Guide. 2 ed. New York: Springer-Verlag; 2003. p. 102\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGupta A, LeBedis CA, Uyeda J, Qureshi MM, Anderson SW, Soto JA. Diffusion-weighted imaging of the pericholecystic hepatic parenchyma for distinguishing acute and chronic cholecystitis. Emerg Radiol. 2018;25(1):7\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKiewiet JJ, Leeuwenburgh MM, Bipat S, Bossuyt PM, Stoker J, Boermeester MA. A systematic review and meta-analysis of diagnostic performance of imaging in acute cholecystitis. Radiology. 2012;264(3):708\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOmiya K, Hiramatsu K, Kato T, Shibata Y, Yoshihara M, Aoba T, et al. Preoperative MRI for predicting pathological changes associated with surgical difficulty during laparoscopic cholecystectomy for acute cholecystitis. BJS Open. 2020;4(5):1137\u0026ndash;45.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003evan Breda Vriesman AC, Engelbrecht MR, Smithuis RH, Puylaert JB. Diffuse gallbladder wall thickening: differential diagnosis. AJR Am J Roentgenol. 2007;188(2):495\u0026ndash;501.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePedrosa I, Casanova R, Rodriguez R, et al. MR imaging of acute and chronic gallbladder disease. Radiographics. 2008;28(6):1741\u0026ndash;54.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYeh BM, Liu PS, Soto JA, Corvera CA, Hussain HK. MR imaging and CT of the biliary tract. Radiology. 2009;250(2):420\u0026ndash;37.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChang W-C, Sun Y, Wu E-H, Kim SY, Wang ZJ, Huang G-S, et al. CT Findings for Detecting the Presence of Gangrenous Ischemia in Cholecystitis. AJR Am J Roentgenol. 2016;207(2):302\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVan Roekel D, LeBedis CA, Santos J, Paul D, Qureshi MM, Kasotakis G, et al. Cholecystitis: association between ultrasound findings and surgical outcomes. Clinical Radiology. 2022;77(5):360\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSato M, Kurita Y, Sakai E, Watanabe S, Sanada H, Shimizu T, et al. Computed diffusion- weighted magnetic resonance imaging with high b-values in the diagnosis of gallbladder lesions. Abdominal Radiology (NY). 2022;47(9):3278\u0026ndash;89.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChoi IY, Cha SH, Yeom SK, Lee SW, Chung HH, Je BK, et al. Diagnosis of acute cholecystitis: value of contrast agent in the gallbladder and cystic duct on Gd-EOB-DTPA enhanced MR cholangiography. Clinical Imaging. 2014;38(2):174\u0026ndash;8.\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":"Acute cholecystitis, Gallbladder, Diffusion-weighted imaging, MRI, MRCP, Diagnostic accuracy","lastPublishedDoi":"10.21203/rs.3.rs-8018195/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8018195/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose:\u003c/h2\u003e\u003cp\u003eTo evaluate the diagnostic performance of gallbladder (GB) wall diffusion restriction on MRCP with diffusion-weighted imaging (DWI) for diagnosing acute cholecystitis (AC), with histopathological findings as the reference standard, and to assess the added value of GB wall thickness and interobserver agreement.\u003c/p\u003e\u003ch2\u003eMethods:\u003c/h2\u003e\u003cp\u003eIn this retrospective multicenter study, 270 patients underwent MRCP with DWI followed by cholecystectomy within seven days. Three experienced abdominal radiologists independently assessed GB wall diffusion restriction and measured GB wall thickness. Diagnostic accuracy was calculated for DWI, GB wall thickness, and a combined model compared to histopathology-confirmed AC diagnosis. Interobserver agreement was assessed with kappa and intraclass correlation. Subgroup analyses examined the influence of MRI-to-surgery interval and magnetic field strength.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eGB wall diffusion restriction showed high diagnostic accuracy, with sensitivity of 94%, specificity 84%, PPV 77%, and NPV 96% (AUC 0.89). Sensitivity was 100% for surgery performed within 24 hours, but declined with longer intervals. GB wall thickness alone reached an optimal cutoff at 4.3 mm (sensitivity 84%, specificity 72%). The combined model slightly increased AUC (0.92) without significant improvement over DWI alone. Interobserver agreement was substantial for DWI (κ\u0026thinsp;=\u0026thinsp;0.63) and good for wall thickness (ICC\u0026thinsp;=\u0026thinsp;0.80). Diagnostic performance was similar across 1.5T and 3.0T field strengths (p\u0026thinsp;=\u0026thinsp;0.23).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eGB wall diffusion restriction on MRCP with DWI is a reproducible and accurate marker for AC diagnosis. GB wall thickness adds information but only modestly affects overall accuracy. DWI is a robust imaging marker that could be integrated into diagnostic algorithms for suspected AC.\u003c/p\u003e","manuscriptTitle":"Diffusion-Weighted Magnetic Resonance Imaging of the Gallbladder in Acute Cholecystitis: Diagnostic Performance Compared to Histopathological Findings","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-18 08:42:11","doi":"10.21203/rs.3.rs-8018195/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":"f8499631-8442-48ad-9650-56801f329738","owner":[],"postedDate":"November 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-28T03:23:37+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-18 08:42:11","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8018195","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8018195","identity":"rs-8018195","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}