Multimodality Imaging Characterization of Perugini Scintigraphic Grades in Transthyretin Amyloid Cardiomyopathy: a single center experience

Multimodality Imaging Characterization of Perugini Scintigraphic Grades in Transthyretin Amyloid Cardiomyopathy: a single center experience | 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 Multimodality Imaging Characterization of Perugini Scintigraphic Grades in Transthyretin Amyloid Cardiomyopathy: a single center experience Paulius Bucius, Evelina Zarambaite, Kornelija Lušaitė, Matas Streckis, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8838252/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 10 You are reading this latest preprint version Abstract Background Transthyretin amyloid cardiomyopathy (ATTR-CM) has undergone a shift towards non-invasive diagnostics using bone tracer scintigraphy with Perugini grading. While both grades 2 and 3 are considered diagnostic, potential phenotypic differences between these groups remain uncertain. We aimed to evaluate the diagnostic yield of technetium-99m pyrophosphate (99mTc-PYP) scintigraphy and to compare clinical and multimodality imaging characteristics across scintigraphic grades in a single-center cohort. Methods We retrospectively reviewed all patients who underwent 99mTc-PYP scintigraphy for suspected cardiac amyloidosis between 2018 and 2025. Patients with confirmed ATTR-CM were stratified by Perugini grade (grade 2 vs. grade 3). Clinical features, biomarkers, electrocardiography, echocardiography, and cardiac magnetic resonance (CMR) parameters were compared. Correlations between scintigraphic grade, imaging markers, and biomarkers were assessed. Results Among 302 scans, 101 (33.4%) demonstrated myocardial uptake. Fifty-three patients were diagnosed with ATTR-CM, including 8 (15.1%) with grade 2 and 45 (84.9%) with grade 3 uptake. Grade 3 patients exhibited worse functional status, shorter 6-minute walk distance, and higher troponin I levels. Echocardiography showed greater maximal wall thickness, lower left ventricular ejection fraction, and worse global longitudinal strain. In the subset with CMR (N = 38), grade 3 patients (N = 30) had significantly higher left ventricular mass index, extracellular volume fraction, right ventricular free wall thickness, and more frequent right ventricular involvement. Perugini grade correlated strongly with left ventricular mass index (r = 0.61, p < 0.01) and extracellular volume (r = 0.53, p < 0.01), and moderately with troponin I (r = 0.55) and B-type natriuretic peptide (r = 0.36, p < 0.05). Grade 1 uptake was not associated with subsequent ATTR-CM diagnosis. Conclusions Non-invasive scintigraphy provides effective detection of ATTR-CM in a referral population. Although grades 2 and 3 both meet diagnostic criteria, grade 3 uptake is associated with greater myocardial amyloid burden, more advanced structural remodeling, and worse functional impairment. In our cohort, Perugini grade appears to reflect disease severity rather than serving solely as a binary diagnostic marker. Figures Figure 1 Background Transthyretin amyloid cardiomyopathy (ATTR-CM) has become an increasingly recognized cause of heart failure with preserved ejection fraction. Historically, its diagnosis relied on endomyocardial biopsy, the risks and limited availability of which often outweighed the potential clinical benefit, especially given the historical lack of specific treatments. However, with the validation of a non-invasive, nuclear medicine-based diagnostic approach [1, 2] and the increasing availability of disease-modifying agents [3–5], the paradigm has shifted towards the identification of early signs of the disease [6]. The interpretation of scintigraphic studies is based on the Perugini grading system, a visual scoring method comparing myocardial uptake to the surrounding ribcage. Current guidelines classify grade 2 and grade 3 uptake as positive for TTR amyloidosis, provided that the presence of monoclonal gammopathy has been excluded. While both grade 2 and grade 3 are diagnostic, there is ongoing debate regarding phenotypic and prognostic differences between these two groups [7, 8]. In this study, we present a 7-year single-center experience in diagnosing ATTR-CM. We aim to describe the volume of disease detection through 99mTc-PYP scintigraphy, as well as the clinical and imaging characteristics of our patient population. Furthermore, we sought to explore the clinical and imaging implications of the scintigraphic grading system by subdividing patients according to Perugini grade and comparing their phenotypes. Methods In this study we reviewed all 99mTc pyrophosphate (PYP) scintigraphy scans performed for suspected cardiac amyloidosis at Lithuanian University of Health Sciences Hospital Kauno Klinikos. Clinical and imaging data temporally closest to the scintigraphy scan were used for further analysis. The local ethics committee approved the study and it was performed according to the declaration of Helsinki. 99mTc-PYP scintigraphy All scintigraphy scans were performed using 99mTc-pyrophosphate (PYP scan) on a hybrid SPECT/CT scanner with 16-slice diagnostic CT (AnyScan, Mediso Medical Imaging Systems, Budapest, Hungary). Anterior and posterior planar views were obtained at 1 and 3 hours after tracer injection. Where available, single-photon emission tomography (SPECT) (early scan) and fusion images with computed tomography (SPECT/CT) (delayed scan) were used for confirmation of myocardial uptake (Fig. 1 ). All scans with clinically reported cardiac uptake (Perugini grade ≥ 1)[9] were independently reviewed by an experienced reader and re-graded for the purposes of this study. All patients underwent systematic evaluation for monoclonal gammopathy using serum and urine immunofixation and serum free light chain assays[1]. ECG analysis ECG recordings for all subjects diagnosed with ATTR-CM were reviewed by a cardiologist for the presence of red flags, conduction abnormalities and QRS width. Low voltage ECG was defined as either QRS amplitude < 10 mm in all precordial or < 5 mm in all limb leads. Pseudo-infarction pattern was defined as QS waves in leads V1-V3. Automatic analysis was used for determination of QRS width. Echocardiography Echocardiographic studies were available in all patients and were performed within 3 months of the 99mTc-PYP scintigraphy scan. Two-dimensional echocardiography was performed according to recommendation from European Association of Cardiovascular imaging[10]. Two experienced echocardiographers with either Philips “EPIQ 7” or “Affinity 70” machines. Archived images were analyzed offline using TomTec Imaging Systems (Unterschleissheim, Germany) software. Maximal wall thickness (MWT) was measured from parasternal long axis view. Left ventricular ejection fraction (LVEF) was measured using Simpson’s method from apical two- and four-chamber views. Same views were used for measuring left atrial volume index. LV global longitudinal strain (GLS) was determined from apical two-, three-, and four-chamber views using in-built applications. GLS values are reported as absolute values throughout the manuscript. Other parameters were measured directly from the acquired images. CMR analysis Due to limited availability, contraindications and poor image quality in some scans, CMR was only available in 38 patients. All CMR examinations were performed within 4 months of the 99mTc-PYP scintigraphy scan. CMR scans were performed on a 3.0-T magnetic resonance imaging scanner (MAGNETOM Skyra, Siemens Healthcare, Erlangen, Germany) with an 18-channel cardiac coil. CINE images were acquired using balanced steady-state free precession sequence in long axes (2-, 3-, 4-chamber views) and a short axis stack with an expiratory breathhold and retrospective ECG gating. For T1 mapping, an ECG-gated single-shot modified Look-Locker inversion recovery (MOLLI) sequence with a 5(3)3 acquisition scheme was used. T1 mapping images were acquired in three short axis slices (basal, mid-ventricular and apical) pre-contrast and 15 minutes after contrast injection (0.1 mmol/l Gadobutrol [Gadovist]. Late gadolinium enhancement (LGE) sequences were acquired 10 minutes after contrast injection. CMR images were analyzed with CMR post-processing software MEDIS Suite (Medis Medical Imaging, Leiden, The Netherlands) by a blinded observer. Standard volumetric techniques were used to determine LV and right ventricular (RV) volumes, as well as LVEF, RV ejection fraction (RVEF) and LV myocardial mass (LVM) parameters [11]. All volumetric parameters were indexed to body surface area. Short-axis CINE images were used for measuring maximal free wall thickness of the RV (RVFWT). Native T1 values were determined by delineating mid-myocardial layer of each myocardial segment. Hematocrit level for each patient was determined from a venous blood sample that was drawn immediately before the scan. A region of interest was drawn in the blood pool of pre- and post-contrast T1 mapping images to create an ECV map. ECV values were calculated by measuring ECV in mid-myocardial layer of basal and mid-ventricular septum and then averaging the two results. Statistical analysis Results are presented as either means ± standard deviations (SD) or absolute numbers with percentages. Study population was divided into two groups according to Perugini grade of PYP scan. Student’s T test was used for normally distributed and Mann-Whitney U-test for abnormally distributed parameters. Fisher’s exact test was used to compare categorical data, given small group sizes and low expected cell counts. Correlation analyses were performed by using Pearson (r) or Spearman correlation coefficient (rho), according to data distribution. Analyses were performed using SPSS version 22 (IBM, Chicago, IL, USA). Results A total of 302 PYP scans were performed at our institution between 2018 and 2025. Of these, 101 (33.4%) patients demonstrated myocardial uptake. The uptake was distributed according to the Perugini grading system as follows: grade 1 (n = 48, 47.5% of positive scans), grade 2 (n = 8, 7.9%), and grade 3 (n = 45, 44.6%). Two patients with grade 2 uptake were confirmed to have AL amyloidosis and were excluded from the analysis. The remaining 53 patients with confirmed ATTR-CM comprised the final study cohort. This ATTR-CM population consisted of 8 (15.1%) patients with grade 2 uptake and 45 (84.9%) patients with grade 3 uptake. All patients (n = 53) were symptomatic and/or had echocardiographic features suggestive of amyloid cardiomyopathy. Genetic analysis was performed in every patient and identified variant-type ATTR-CM in 2 (3.8%) and wild-type ATTR-CM in 51 (96.2%) patients. The yearly distribution and diagnostic method for the cohort are presented in Table 1 . To evaluate differences in disease presentation, the ATTR-CM cohort was stratified into Grade 2 (n = 8) and Grade 3 (n = 45) groups. The association between these scan grades and key clinical and imaging parameters was then assessed. To contextualize the diagnostic performance of scintigraphy, we additionally reviewed patients with Perugini grade 1 uptake. None of the grade 1 patients progressed to diagnosed ATTR-CM during available follow-up (median 28.0 months (IQR, 12.0–45.0 months). SPECT-CT imaging was available in 27 (56% of all grade 1 scans) cases and showed myocardial uptake in only 3 (11.1%) of these patients. The other 24 showed blood-pool uptake which was reported as myocardial uptake on planar imaging. Table 1 Yearly Distribution and Mode of Diagnosis (N = 53). Year Number diagnosed Biopsy – N (%) Non-invasive – N (%) 2018 1 1 (100%) 0 (0.0%) 2019 4 2 (50%) 2 (50%) 2020 2 0 (0.0%) 2 (100%) 2021 4 0 (0.0%) 4 (100%) 2022 2 1 (50%) 1 (50%) 2023 13 1 (7.7%) 12 (92.3%) 2024 12 2 (16.6%) 10 (83.4%) 2025 15 1 (6.7%) 14 (93.3%) Total 53 8 (15.1%) 45 (84.9%) Clinical and echocardiographic characteristics Baseline clinical and echocardiographic characteristics are presented in Table 2 and Table 3 , respectively. The average age at diagnosis was 78 years (77.8 ± 4.9 in Grade 2 vs. 78.2 ± 6.6 in Grade 3; p = 0.862), and 69.8% of the cohort was male (50% vs. 73%; p = 0.309). Common "red flag" conditions such as spinal stenosis (p = 0.761), carpal tunnel syndrome (p = 0.297), and atrial fibrillation (p = 0.533) were prevalent in the cohort, with no significant difference between the groups. While ECG features associated with cardiac amyloidosis (low voltage and pseudoinfarction patterns) were common in both groups, pacemaker implantation occurred only in Grade 3 patients (22.2%), although this difference did not reach statistical significance. Functionally, Grade 3 patients had significantly worse NYHA functional class (p = 0.028) and shorter 6-minute walk test distance (298 ± 110 m vs. 366 ± 38 m; p = 0.039). This was accompanied by significantly higher cardiac troponin I levels (0.099 ± 0.09 mcg/l vs. 0.025 ± 0.009 mcg/l; p < 0.001). Differences in BNP did not reach statistical significance (139 ± 82 vs 332 ± 341; p = 0.12). Table 3 Comparison of echocardiographic parameters between Grade 2 and Grade 3 groups (N = 53). Abbreviations: LVEF = left ventricular ejection fraction; LV GLS = left ventricular global longitudinal strain; MWT = maximal wall thickness; LAVi = left atrial volume index; E/e′ = ratio of early mitral inflow velocity to early diastolic mitral annular velocity; S′ = systolic tricuspid annular velocity; PAT = pulmonary acceleration time; LVEDDi = left ventricular end diastolic diameter index. ^Calculated using Fisher's Exact Test (2–sided) Grade 2 (N – 8) Grade 3 (N – 45) P value LVEF (%) 53.8 ± 2.3 49.1 ± 8.2 0.003 LV GLS (%) 16.0 ± 4.6 12.5 ± 3.9 0.037 MWT (mm) 14.6 ± 2.3 16.9 ± 2.2 0.009 LVEDDi (mm/m2) 24.7 ± 1.4 24.3 ± 2.6 0.460 LAVi (ml/m2) 48.2 ± 15.1 51.5 ± 16.1 0.62 E/e’ 14.8 ± 3.4 17.6 ± 5.7 0.186 S’ (cm/s) 12.8 ± 2.4 9.7 ± 3.1 0.01 PAT (ms) 106 ± 12.6 94 ± 15.6 0.06 Pericardial effusion 0 (0) 10 (22.2) 0.325^ Apical sparing 4 (50) 40/45 (88.9) 0.021^ Table 4 Comparison of CMR parameters between Grade 2 and Grade 3 groups (N = 38). Abbreviations: LVEDVi = left ventricular end diastolic volume index; LVSVi = left ventricular stroke volume index; LVEF = left ventricular ejection fraction; RVEDVi = right ventricular end–diastolic volume index; RVSVi = right ventricular stroke volume index; RVEF = right ventricular ejection fraction; LAAi = left atrial area index; LVMi = left ventricular mass index; ECV = extracellular volume fraction, RVFWT = right ventricular free wall thickness; ^ calculated using Fisher's Exact Test (2–sided) Feature Grade 2 (N – 8) Grade 3 (N – 30) P value LVEDVi (ml/m2) 79.4 ± 17.2 88.2 ± 18.3 0.26 LVSVi (ml/m2) 42.8 ± 8.7 46.3 ± 9.7 0.39 LVEF (%) 54.7 ± 9.86 53.0 ± 7.9 0.643 RVEDVi (ml/m2) 69.2 ± 19.9 78.0 ± 24.5 0.386 RVSVi (ml/m2) 41.6 ± 9.1 43.9 ± 10.7 0.606 RVEF (%) 61.6 ± 10 58.2 ± 11.2 0.462 RVFWT (mm) 4.0 ± 1.4 6.2 ± 1.6 0.001 RV-LGE (N(%)) 3 (37.5%) 28 (93.3%) 0.002^ LAAi (cm2/m2) 16.2 ± 3.5 16.5 ± 2.3 0.81 LVMi (g/m2) 68.1 ± 16.7 106.0 ± 22.2 < 0.001 ECV (%) 35.1 ± 4.1 45.2 ± 7.8 < 0.001 Myocardial T1 (ms) 1348 ± 45.9 1386 ± 53.1 0.069 Echocardiographic analysis revealed that Grade 3 patients had a more severe cardiac phenotype, characterized by significantly higher MWT (16.9 ± 2.2 mm vs. 14.6 ± 2.3 mm; p = 0.009), lower LVEF (49.1 ± 8.2% vs. 53.8 ± 2.3%; p = 0.003), and worse GLS (12.5 ± 3.9% vs. 16.0 ± 4.6%; p = 0.037), as well as higher rates of apical sparing (50% vs 88.9%, p = 0.021). Indexed left atrial volume (LAVi) was similar between the groups. CMR data The Grade 3 group demonstrated significantly higher LVMi (106.0 ± 22.2 g/m²) compared to the Grade 2 group (68.1 ± 16.7 g/m²; p < 0.001). Despite this significant difference in mass, all other volumetric parameters were similar between the groups. Regarding myocardial tissue characteristics, pre-contrast T1 mapping values showed a trend towards being higher in the Grade 3 group (1386 ± 53.1 ms vs. 1348 ± 45.9 ms for Grade 2; p = 0.069). Furthermore, extracellular volume (ECV) was significantly higher in the Grade 3 cohort (45.2 ± 7.8%) compared to the Grade 2 cohort (35.1 ± 4.4%; p < 0.001). Among those with CMR data, Grade 3 patients (N = 30) had higher RVFWT (6.2 ± 1.6 vs. 4.0 ± 1.4 mm, p = 0.001) and more frequent RV involvement, as determined by the presence of LGE (28/30; 93.3% vs. 3/8; 37.5% in Grade 2, p = 0.002). Correlation analysis Correlation analyses were performed to assess relationships among Perugini grade, clinical variables, and imaging parameters. Correlation parameters are presented in Table 5 . Perugini grade demonstrated strong, significant correlations with LVMi (r = 0.608, p < 0.01) and ECV (r = 0.530, p < 0.01). It also correlated significantly with cardiac biomarkers, including Troponin I (r = 0.549, p < 0.01) and BNP (r = 0.355, p < 0.05). Table 5 Correlation Matrix of Key Clinical, Imaging, and Biomarker Parameters (N = 53 for clinical characteristics and echocardiographic data, N = 38 for CMR parameters). Data represent Pearson's correlation coefficient (r), except for correlations with Perugini Grade, which use Spearman's correlation coefficient. * p < 0.05 ** p < 0.01. Abbreviations: 6MWT = 6 Variable Troponin I BNP 6MWT GLS (echo) MWT (echo) LVMi (CMR) ECV Perugini grade 0.549** 0.355* -0.307* -0.270 0.315* 0.608** 0.530** Troponin I - 0.140 -0.084 -0.332* 0.081 0.321 0.414* BNP - -0.242 -0.492** 0.518** 0.478** 0.357* 6MWT - 0.301* -0.108 -0.144 -0.066 GLS (echo) - -0.597** -0.547** - 0.339* MWT (echo) - 0.692** -0.019 LVMi (CMR) - 0.553** Minute Walk Test; BNP = B–type Natriuretic Peptide; ECV = Extracellular Volume; GLS = Global Longitudinal Strain; LVMi = Left Ventricular Mass Index; MWT = Maximal Wall Thickness. Negative correlations with GLS reflect worsening myocardial function, as GLS values are reported as absolute values BNP, as a marker of neurohormonal stress, showed significant correlations with structural and functional parameters, including a strong positive correlation with increased cardiac mass, as measured by both echocardiographic MWT (r = 0.518, p < 0.01) and CMR-derived LVMi (r = 0.478, p < 0.01). It was also significantly correlated with myocardial infiltration, as quantified by ECV (r = 0.357, p < 0.05). Functionally, higher BNP levels were strongly correlated with worse myocardial function (lower absolute GLS, r = -0.492, p < 0.01). There was, however, no significant correlation between BNP and Troponin I (r = 0.140) or functional capacity (6MWT, r = -0.242). Troponin I levels were significantly correlated with a key marker of infiltration – ECV (r = 0.414, p < 0.05). It was also significantly correlated with markers of cardiac function – GLS (-0.332, p < 0.05) and RVEF (-0.425, p < 0.05). However, there was no statistical association with echo-derived MWT (r = 0.081) or CMR-derived LVMi (r = 0.321). Furthermore, troponin did not correlate with neurohormonal stress (BNP, r = 0.14) or functional capacity (6MWT, r = -0.084). As expected, echocardiographic and CMR parameters of mass (MWT and LVMi) were highly correlated (r = 0.692, p < 0.01). Discussion In this single-center study, we describe a 7-year experience with the diagnosis of ATTR-CM in a Lithuanian referral center. Our data demonstrate a substantial increase in diagnostic yield following adoption of the non-invasive diagnostic algorithm and highlight important clinical and imaging differences between patients with Perugini grade 2 and grade 3 myocardial uptake. While both grades fulfill current diagnostic criteria for ATTR-CM, we have found important differences in myocardial involvement, with higher scintigraphic uptake reflecting more advanced structural and functional disease. Taken together, these findings support the interpretation of Perugini scintigraphic grade as a marker of myocardial amyloid burden and phenotypic disease severity, rather than a purely binary diagnostic variable. Diagnostic yield Approximately one third of all 99mTc-PYP scans demonstrated myocardial uptake on planar imaging; however, nearly half of these were graded as equivocal or grade 1, and none of these patients were ultimately diagnosed with ATTR-CM. SPECT-CT imaging clarified that most grade 1 cases represented blood-pool activity rather than true myocardial tracer uptake, underscoring the limitations of planar imaging alone and reinforcing current guideline recommendations for SPECT/CT confirmation [12]. This finding is in-line with previous reports that grade 1 patients have favourable outcomes[13, 14]. The overall diagnostic yield of ≥grade 2 uptake was approximately 15%, consistent with prior reports from referral populations [14, 15], supporting the effectiveness of targeted scintigraphic screening in patients with clinical or echocardiographic suspicion of amyloid cardiomyopathy. Circulating biomarkers Circulating biomarkers demonstrated distinct and complementary associations with imaging findings. BNP correlated strongly with markers of myocardial remodeling and functional impairment, including echocardiographic maximal wall thickness, CMR-derived LV mass index, and impaired longitudinal systolic function. In contrast, troponin I correlated with Perugini grade and extracellular volume fraction (ECV), but not with myocardial bulk parameters. Notably, BNP and troponin I did not correlate with each other, underscoring their reflection of different pathophysiological processes. This dissociation is biologically plausible. Troponin release in ATTR-CM likely reflects ongoing myocardial injury driven by amyloid infiltration, microvascular dysfunction, direct cytotoxic effects, and increased wall stress at the cellular level [16, 17]. Natriuretic peptides, by contrast, predominantly reflect hemodynamic consequences of increased myocardial stiffness and chamber pressure overload [18]. Similar findings were reported by Morioka et al., who observed higher troponin levels in patients with greater histological amyloid burden despite comparable natriuretic peptide levels and myocardial mass [19]. Collectively, these findings support a multi-marker approach to staging: Troponin I appears to reflect the extent of infiltration and active toxicity, whereas BNP reflects the hemodynamic consequence of that infiltration. Perugini grade and disease severity In our cohort, patients with Perugini grade 3 uptake presented with a significantly more advanced clinical profile than those with grade 2. These patients had worse NYHA functional class, lower exercise tolerance, worse troponin I levels and a higher prevalence of conduction system disease – specifically wider QRS intervals and a greater need for pacemaker implantation. Structural imaging mirrored this clinical decline: echocardiography showed increased MWT and lower LVEF, while CMR confirmed a higher amyloid burden through increased LVMi, RVFWT, and expanded ECV. Additionally, both CMR and echocardiography confirmed near-universal RV involvement in Grade 3 patients with CMR data. RV involvement in ATTRM-CM was studied in a large SPECT-based study by Porcari et al. [20]. They showed that some degree of RV involvement is a universal finding in ATTR-CM patients on SPECT. However, patients with diffuse RV involvement had a more severe clinical profile, as evidenced by multiple imaging and biomarker parameters. They also found that diffuse RV involvement was correlated with higher Perugini grades. Our cohort showed a strong correlation between RVEF and troponin I values, further supporting the idea that RV involvement tracks with increased amyloid load and likely reflects a transition from predominantly LV-focused disease to a diffuse cardiomyopathy. Importantly, the phenotypic differences that we have observed do not translate to prognostic difference of Perugini grade 2 and 3 patients in past large-scale studies [20, 21]. It has been argued that quantification of Perugini grades can be confounded by competitive radiotracer uptake from surrounding soft-tissue, thus higher visual grades may not reflect higher cardiac uptake but rather a decrease in bone uptake [22]. However, recent studies on semi-quantitative scintigraphic parameters have shown associations with more severe disease profile and worse outcomes [23, 24]. In this context, our findings suggest that higher scintigraphic grade reflects a more advanced structural involvement without translating into measurable difference in prognosis. Survival in ATTR-CM is influenced by multiple competing factors, including age, comorbidities, referral patterns, and treatment, which may obscure biological gradients detectable by detailed imaging and biomarker assessment. It is also possible that past a certain point myocardial infiltration primarily drives functional and biventricular involvement, rather than incremental mortality risk. Limitations This study has several limitations. Its retrospective, single-center design and relatively small number of Grade 2 patients limit statistical power and generalizability. However, this likely reflects real-world referral patterns. CMR data were not available for all patients, potentially introducing selection bias related to availability, contraindications, or image quality. BNP values were available, but NT-proBNP was not, precluding application of established staging systems. Finally, outcome data were not analyzed, preventing direct assessment of the prognostic implications of Perugini grade differences. These findings should not be interpreted as demonstrating prognostic differences between Perugini grades. Conclusion In conclusion, while Perugini grade 2 and grade 3 myocardial uptake on PYP scan, both satisfy non-invasive diagnostic criteria for ATTR-CM, they are associated with distinct clinical and imaging phenotypes. Our cohort shows that higher PYP uptake reflects greater myocardial amyloid burden, more advanced functional impairment, and increased biomarkers of cardiac injury. Abbreviations ATTR CM–Transthyretin amyloid cardiomyopathy BNP B–type natriuretic peptide CMR Cardiac magnetic resonance CT Computed tomography ECG Electrocardiogram ECV Extracellular volume GLS Global longitudinal strain LV Left ventricular LVEF Left ventricular ejection fraction LVMi Left ventricular mass index MWT Maximal wall thickness NYHA New York Heart Association RVFWT Right ventricular free wall thickness SD Standard deviation SPECT Single–photon emission computed tomography SPECT/CT Single–photon emission computed tomography/computed tomography TTR Transthyretin Declarations Competing interests The authors declare no competing interest. Conflict of interest The authors declare no conflict of interest. Ethical approval The study was approved by the Kaunas regional bioethics committee (Reference Nr. BE-2-50). Consent to participate Informed consent was obtained from all individual participants included in the study. Dataset availability The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Author contributions Conceptualization, E.E., D.V., data collection, E.Z., M.S, P.B., G.S., writing of original draft, P.B., review and editing, E.E., A.K., T.L, A.J., J.P. All authors have read and agreed to the published version of the manuscript. Acknowledgements Not applicable. References Garcia-Pavia P, Rapezzi C, Adler Y, Arad M, Basso C, Brucato A, et al. Diagnosis and treatment of cardiac amyloidosis: a position statement of the ESC Working Group on Myocardial and Pericardial Diseases. Eur Heart J. 2021 Apr 21;42(16):1554–68. Gillmore JD, Maurer MS, Falk RH, Merlini G, Damy T, Dispenzieri A, et al. Nonbiopsy Diagnosis of Cardiac Transthyretin Amyloidosis. Circulation. 2016 Jun 14;133(24):2404–12. Gillmore JD, Judge DP, Cappelli F, Fontana M, Garcia-Pavia P, Gibbs S, et al. 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Porcari A, Fontana M, Canepa M, Biagini E, Cappelli F, Gagliardi C, et al. Clinical and Prognostic Implications of Right Ventricular Uptake on Bone Scintigraphy in Transthyretin Amyloid Cardiomyopathy. Circulation. 2024 Apr 9;149(15):1157–68. Sheikh A, Achten A, Aimo A, Razvi Y, Mansell J, Rauf MU, et al. Myocardial Amyloid Burden in Transthyretin Amyloidosis. JACC. 2025 Nov; Koeckerling D, Reddy RK, Eichhorn C, Braun V, Ahmad Y, Howard JP, et al. Echocardiographic risk stratification in light chain and transthyretin amyloidosis: a meta-analysis. European Heart Journal Open. 2025 Jul 4;5(4). Hutt DF, Fontana M, Burniston M, Quigley A-M, Petrie A, Ross JC, et al. Prognostic utility of the Perugini grading of 99mTc-DPD scintigraphy in transthyretin (ATTR) amyloidosis and its relationship with skeletal muscle and soft tissue amyloid. Eur Heart J Cardiovasc Imaging. 2017 Dec 1;18(12):1344–50. Scully PR, Morris E, Patel KP, Treibel TA, Burniston M, Klotz E, et al. DPD Quantification in Cardiac Amyloidosis. JACC Cardiovasc Imaging. 2020 Jun;13(6):1353–63. Rettl R, Duca F, Kronberger C, Binder C, Willixhofer R, Ermolaev N, et al. Prognostic implication of DPD quantification in transthyretin cardiac amyloidosis. Eur Heart J Cardiovasc Imaging. 2025 Jan 31;26(2):251–60. Harapoz M, Evans S, Geenty P, Kwok F, Stewart G, Taylor MS, et al. Correlation Between Quantitative Uptake of 99mTC-DPD and Echocardiographic Parameters in Cardiac ATTR: A Novel Follow-Up Strategy. Front Cardiovasc Med. 2021 Oct 15;8. Table 2 Table 2 is not available with this version. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 23 Apr, 2026 Reviews received at journal 19 Apr, 2026 Reviewers agreed at journal 28 Mar, 2026 Reviews received at journal 05 Mar, 2026 Reviewers agreed at journal 25 Feb, 2026 Reviewers agreed at journal 12 Feb, 2026 Reviewers invited by journal 12 Feb, 2026 Editor assigned by journal 11 Feb, 2026 Submission checks completed at journal 11 Feb, 2026 First submitted to journal 10 Feb, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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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-8838252","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":590114381,"identity":"ec1e69db-7235-46cf-8e98-a4ab57a944b9","order_by":0,"name":"Paulius Bucius","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4ElEQVRIie3PsQrCMBCA4RNBlyuugtK+wm2lID5LS6BTByfH4tTJWQrFh+gbnGQVXQsuFsHJwbFDB2MtqEPN6pAfksDBRxIAk+k/67GvdlKLAWbTZnbWmE8SYjPyfQ2BlqiknrjDPXGZxOCORSmxPqKz2RMEVTfx1hFxkEjw0pCklZyQThH9vIW4IQxURCCtlSITHTneniR+EawP6GQ6UjS39FsyYATdw7z0umD/INFbX2m3TYT6S6gmYTdxRyIvq2Vsu0Nxud/que1kIj/fZz8e1p74NeVu8CYmk8lk6u4BiTRUzc3lGUIAAAAASUVORK5CYII=","orcid":"","institution":"Lithuanian University of Health Sciences","correspondingAuthor":true,"prefix":"","firstName":"Paulius","middleName":"","lastName":"Bucius","suffix":""},{"id":590114382,"identity":"fe6a628b-8345-435f-bbe7-d35532ce8b0e","order_by":1,"name":"Evelina Zarambaite","email":"","orcid":"","institution":"Lithuanian University of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Evelina","middleName":"","lastName":"Zarambaite","suffix":""},{"id":590114383,"identity":"3b4419bf-e9ef-4acf-b4fe-e0b93a898c5d","order_by":2,"name":"Kornelija Lušaitė","email":"","orcid":"","institution":"Lithuanian University of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Kornelija","middleName":"","lastName":"Lušaitė","suffix":""},{"id":590114384,"identity":"07b2835f-b560-4efa-92e0-2b5446257959","order_by":3,"name":"Matas Streckis","email":"","orcid":"","institution":"Lithuanian University of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Matas","middleName":"","lastName":"Streckis","suffix":""},{"id":590114386,"identity":"3de6d00a-31b5-4b51-83a1-bce4714f2739","order_by":4,"name":"Arnas Karuzas","email":"","orcid":"","institution":"Lithuanian University of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Arnas","middleName":"","lastName":"Karuzas","suffix":""},{"id":590114388,"identity":"d67fbb51-01be-47a4-9e64-7f7ccdf0c92c","order_by":5,"name":"Jurgita Plisiene","email":"","orcid":"","institution":"Lithuanian University of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Jurgita","middleName":"","lastName":"Plisiene","suffix":""},{"id":590114391,"identity":"b6acdfd6-6927-4e73-917e-b3e29fb29cbc","order_by":6,"name":"Gintare Sakalyte","email":"","orcid":"","institution":"Lithuanian University of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Gintare","middleName":"","lastName":"Sakalyte","suffix":""},{"id":590114393,"identity":"4a03861b-8810-413e-a2d3-3a02ebf1350f","order_by":7,"name":"Tomas Lapinskas","email":"","orcid":"","institution":"Lithuanian University of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Tomas","middleName":"","lastName":"Lapinskas","suffix":""},{"id":590114395,"identity":"1eb8ea77-d236-4954-9da6-0533346ebf6d","order_by":8,"name":"Donatas Vajauskas","email":"","orcid":"","institution":"Lithuanian University of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Donatas","middleName":"","lastName":"Vajauskas","suffix":""},{"id":590114397,"identity":"defad725-30a7-426f-96fb-b6c61aca1cc8","order_by":9,"name":"Antanas Jankauskas","email":"","orcid":"","institution":"Lithuanian University of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Antanas","middleName":"","lastName":"Jankauskas","suffix":""},{"id":590114399,"identity":"8349e301-2715-4b18-8cc3-bf6e589c74ce","order_by":10,"name":"Egle Ereminiene","email":"","orcid":"","institution":"Lithuanian University of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Egle","middleName":"","lastName":"Ereminiene","suffix":""}],"badges":[],"createdAt":"2026-02-10 08:23:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8838252/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8838252/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102892599,"identity":"3b8d8bdf-2833-408d-8f42-10ac9b7fcad1","added_by":"auto","created_at":"2026-02-18 05:28:18","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":609553,"visible":true,"origin":"","legend":"\u003cp\u003eScintigraphy with 99mTc-pyrophosphate. Top row – planar SPECT images, bottom row – SPECT/CT fusion images. A and C – patient graded as Perugini grade 2. B and D – patient graded as Perugini grade 3.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8838252/v1/9370fdea782d643131bd70cc.png"},{"id":102963676,"identity":"3336753a-216a-4886-861c-853213d36284","added_by":"auto","created_at":"2026-02-19 04:19:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1643306,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8838252/v1/d51dfa61-51ab-4184-8de6-a2e0beb4f176.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Multimodality Imaging Characterization of Perugini Scintigraphic Grades in Transthyretin Amyloid Cardiomyopathy: a single center experience","fulltext":[{"header":"Background","content":"\u003cp\u003eTransthyretin amyloid cardiomyopathy (ATTR-CM) has become an increasingly recognized cause of heart failure with preserved ejection fraction. Historically, its diagnosis relied on endomyocardial biopsy, the risks and limited availability of which often outweighed the potential clinical benefit, especially given the historical lack of specific treatments. However, with the validation of a non-invasive, nuclear medicine-based diagnostic approach [1, 2] and the increasing availability of disease-modifying agents [3\u0026ndash;5], the paradigm has shifted towards the identification of early signs of the disease [6].\u003c/p\u003e \u003cp\u003eThe interpretation of scintigraphic studies is based on the Perugini grading system, a visual scoring method comparing myocardial uptake to the surrounding ribcage. Current guidelines classify grade 2 and grade 3 uptake as positive for TTR amyloidosis, provided that the presence of monoclonal gammopathy has been excluded. While both grade 2 and grade 3 are diagnostic, there is ongoing debate regarding phenotypic and prognostic differences between these two groups [7, 8].\u003c/p\u003e \u003cp\u003eIn this study, we present a 7-year single-center experience in diagnosing ATTR-CM. We aim to describe the volume of disease detection through 99mTc-PYP scintigraphy, as well as the clinical and imaging characteristics of our patient population. Furthermore, we sought to explore the clinical and imaging implications of the scintigraphic grading system by subdividing patients according to Perugini grade and comparing their phenotypes.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e In this study we reviewed all 99mTc pyrophosphate (PYP) scintigraphy scans performed for suspected cardiac amyloidosis at Lithuanian University of Health Sciences Hospital Kauno Klinikos. Clinical and imaging data temporally closest to the scintigraphy scan were used for further analysis. The local ethics committee approved the study and it was performed according to the declaration of Helsinki.\u003c/p\u003e \u003cp\u003e \u003cb\u003e99mTc-PYP scintigraphy\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAll scintigraphy scans were performed using 99mTc-pyrophosphate (PYP scan) on a hybrid SPECT/CT scanner with 16-slice diagnostic CT (AnyScan, Mediso Medical Imaging Systems, Budapest, Hungary). Anterior and posterior planar views were obtained at 1 and 3 hours after tracer injection. Where available, single-photon emission tomography (SPECT) (early scan) and fusion images with computed tomography (SPECT/CT) (delayed scan) were used for confirmation of myocardial uptake (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). All scans with clinically reported cardiac uptake (Perugini grade\u0026thinsp;\u0026ge;\u0026thinsp;1)[9] were independently reviewed by an experienced reader and re-graded for the purposes of this study. All patients underwent systematic evaluation for monoclonal gammopathy using serum and urine immunofixation and serum free light chain assays[1].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eECG analysis\u003c/h2\u003e \u003cp\u003eECG recordings for all subjects diagnosed with ATTR-CM were reviewed by a cardiologist for the presence of red flags, conduction abnormalities and QRS width. Low voltage ECG was defined as either QRS amplitude\u0026thinsp;\u0026lt;\u0026thinsp;10 mm in all precordial or \u0026lt;\u0026thinsp;5 mm in all limb leads. Pseudo-infarction pattern was defined as QS waves in leads V1-V3. Automatic analysis was used for determination of QRS width.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEchocardiography\u003c/h3\u003e\n\u003cp\u003eEchocardiographic studies were available in all patients and were performed within 3 months of the 99mTc-PYP scintigraphy scan. Two-dimensional echocardiography was performed according to recommendation from European Association of Cardiovascular imaging[10]. Two experienced echocardiographers with either Philips \u0026ldquo;EPIQ 7\u0026rdquo; or \u0026ldquo;Affinity 70\u0026rdquo; machines. Archived images were analyzed offline using TomTec Imaging Systems (Unterschleissheim, Germany) software.\u003c/p\u003e \u003cp\u003eMaximal wall thickness (MWT) was measured from parasternal long axis view. Left ventricular ejection fraction (LVEF) was measured using Simpson\u0026rsquo;s method from apical two- and four-chamber views. Same views were used for measuring left atrial volume index. LV global longitudinal strain (GLS) was determined from apical two-, three-, and four-chamber views using in-built applications. GLS values are reported as absolute values throughout the manuscript. Other parameters were measured directly from the acquired images.\u003c/p\u003e\n\u003ch3\u003eCMR analysis\u003c/h3\u003e\n\u003cp\u003eDue to limited availability, contraindications and poor image quality in some scans, CMR was only available in 38 patients. All CMR examinations were performed within 4 months of the 99mTc-PYP scintigraphy scan. CMR scans were performed on a 3.0-T magnetic resonance imaging scanner (MAGNETOM Skyra, Siemens Healthcare, Erlangen, Germany) with an 18-channel cardiac coil. CINE images were acquired using balanced steady-state free precession sequence in long axes (2-, 3-, 4-chamber views) and a short axis stack with an expiratory breathhold and retrospective ECG gating. For T1 mapping, an ECG-gated single-shot modified Look-Locker inversion recovery (MOLLI) sequence with a 5(3)3 acquisition scheme was used. T1 mapping images were acquired in three short axis slices (basal, mid-ventricular and apical) pre-contrast and 15 minutes after contrast injection (0.1 mmol/l Gadobutrol [Gadovist]. Late gadolinium enhancement (LGE) sequences were acquired 10 minutes after contrast injection.\u003c/p\u003e \u003cp\u003eCMR images were analyzed with CMR post-processing software MEDIS Suite (Medis Medical Imaging, Leiden, The Netherlands) by a blinded observer. Standard volumetric techniques were used to determine LV and right ventricular (RV) volumes, as well as LVEF, RV ejection fraction (RVEF) and LV myocardial mass (LVM) parameters [11]. All volumetric parameters were indexed to body surface area. Short-axis CINE images were used for measuring maximal free wall thickness of the RV (RVFWT). Native T1 values were determined by delineating mid-myocardial layer of each myocardial segment. Hematocrit level for each patient was determined from a venous blood sample that was drawn immediately before the scan. A region of interest was drawn in the blood pool of pre- and post-contrast T1 mapping images to create an ECV map. ECV values were calculated by measuring ECV in mid-myocardial layer of basal and mid-ventricular septum and then averaging the two results.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eResults are presented as either means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviations (SD) or absolute numbers with percentages. Study population was divided into two groups according to Perugini grade of PYP scan. Student\u0026rsquo;s T test was used for normally distributed and Mann-Whitney U-test for abnormally distributed parameters. Fisher\u0026rsquo;s exact test was used to compare categorical data, given small group sizes and low expected cell counts. Correlation analyses were performed by using Pearson (r) or Spearman correlation coefficient (rho), according to data distribution. Analyses were performed using SPSS version 22 (IBM, Chicago, IL, USA).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 302 PYP scans were performed at our institution between 2018 and 2025. Of these, 101 (33.4%) patients demonstrated myocardial uptake. The uptake was distributed according to the Perugini grading system as follows: grade 1 (n\u0026thinsp;=\u0026thinsp;48, 47.5% of positive scans), grade 2 (n\u0026thinsp;=\u0026thinsp;8, 7.9%), and grade 3 (n\u0026thinsp;=\u0026thinsp;45, 44.6%). Two patients with grade 2 uptake were confirmed to have AL amyloidosis and were excluded from the analysis.\u003c/p\u003e \u003cp\u003eThe remaining 53 patients with confirmed ATTR-CM comprised the final study cohort. This ATTR-CM population consisted of 8 (15.1%) patients with grade 2 uptake and 45 (84.9%) patients with grade 3 uptake. All patients (n\u0026thinsp;=\u0026thinsp;53) were symptomatic and/or had echocardiographic features suggestive of amyloid cardiomyopathy. Genetic analysis was performed in every patient and identified variant-type ATTR-CM in 2 (3.8%) and wild-type ATTR-CM in 51 (96.2%) patients. The yearly distribution and diagnostic method for the cohort are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. To evaluate differences in disease presentation, the ATTR-CM cohort was stratified into Grade 2 (n\u0026thinsp;=\u0026thinsp;8) and Grade 3 (n\u0026thinsp;=\u0026thinsp;45) groups. The association between these scan grades and key clinical and imaging parameters was then assessed.\u003c/p\u003e \u003cp\u003eTo contextualize the diagnostic performance of scintigraphy, we additionally reviewed patients with Perugini grade 1 uptake. None of the grade 1 patients progressed to diagnosed ATTR-CM during available follow-up (median 28.0 months (IQR, 12.0\u0026ndash;45.0 months). SPECT-CT imaging was available in 27 (56% of all grade 1 scans) cases and showed myocardial uptake in only 3 (11.1%) of these patients. The other 24 showed blood-pool uptake which was reported as myocardial uptake on planar imaging.\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\u003eYearly Distribution and Mode of Diagnosis (N\u0026thinsp;=\u0026thinsp;53).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber diagnosed\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBiopsy \u0026ndash; N (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNon-invasive \u0026ndash; N (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (7.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (92.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (16.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (83.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (6.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14 (93.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e53\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e8 (15.1%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e45 (84.9%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eClinical and echocardiographic characteristics\u003c/h2\u003e \u003cp\u003eBaseline clinical and echocardiographic characteristics are presented in Table\u0026nbsp;2 and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3\u003c/span\u003e, respectively. The average age at diagnosis was 78 years (77.8\u0026thinsp;\u0026plusmn;\u0026thinsp;4.9 in Grade 2 vs. 78.2\u0026thinsp;\u0026plusmn;\u0026thinsp;6.6 in Grade 3; p\u0026thinsp;=\u0026thinsp;0.862), and 69.8% of the cohort was male (50% vs. 73%; p\u0026thinsp;=\u0026thinsp;0.309). Common \"red flag\" conditions such as spinal stenosis (p\u0026thinsp;=\u0026thinsp;0.761), carpal tunnel syndrome (p\u0026thinsp;=\u0026thinsp;0.297), and atrial fibrillation (p\u0026thinsp;=\u0026thinsp;0.533) were prevalent in the cohort, with no significant difference between the groups. While ECG features associated with cardiac amyloidosis (low voltage and pseudoinfarction patterns) were common in both groups, pacemaker implantation occurred only in Grade 3 patients (22.2%), although this difference did not reach statistical significance. Functionally, Grade 3 patients had significantly worse NYHA functional class (p\u0026thinsp;=\u0026thinsp;0.028) and shorter 6-minute walk test distance (298\u0026thinsp;\u0026plusmn;\u0026thinsp;110 m vs. 366\u0026thinsp;\u0026plusmn;\u0026thinsp;38 m; p\u0026thinsp;=\u0026thinsp;0.039). This was accompanied by significantly higher cardiac troponin I levels (0.099\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09 mcg/l vs. 0.025\u0026thinsp;\u0026plusmn;\u0026thinsp;0.009 mcg/l; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Differences in BNP did not reach statistical significance (139\u0026thinsp;\u0026plusmn;\u0026thinsp;82 vs 332\u0026thinsp;\u0026plusmn;\u0026thinsp;341; p\u0026thinsp;=\u0026thinsp;0.12).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of echocardiographic parameters between Grade 2 and Grade 3 groups (N\u0026thinsp;=\u0026thinsp;53). Abbreviations: LVEF\u0026thinsp;=\u0026thinsp;left ventricular ejection fraction; LV GLS\u0026thinsp;=\u0026thinsp;left ventricular global longitudinal strain; MWT\u0026thinsp;=\u0026thinsp;maximal wall thickness; LAVi\u0026thinsp;=\u0026thinsp;left atrial volume index; E/e\u0026prime; = ratio of early mitral inflow velocity to early diastolic mitral annular velocity; S\u0026prime; = systolic tricuspid annular velocity; PAT\u0026thinsp;=\u0026thinsp;pulmonary acceleration time; LVEDDi\u0026thinsp;=\u0026thinsp;left ventricular end diastolic diameter index. ^Calculated using Fisher's Exact Test (2\u0026ndash;sided)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGrade 2 (N \u0026ndash; 8)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGrade 3 (N \u0026ndash; 45)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\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\u003eLVEF (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49.1\u0026thinsp;\u0026plusmn;\u0026thinsp;8.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLV GLS (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.0\u0026thinsp;\u0026plusmn;\u0026thinsp;4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.5\u0026thinsp;\u0026plusmn;\u0026thinsp;3.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.037\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMWT (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.6\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.009\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLVEDDi (mm/m2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.460\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLAVi (ml/m2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48.2\u0026thinsp;\u0026plusmn;\u0026thinsp;15.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51.5\u0026thinsp;\u0026plusmn;\u0026thinsp;16.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE/e\u0026rsquo;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.8\u0026thinsp;\u0026plusmn;\u0026thinsp;3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.6\u0026thinsp;\u0026plusmn;\u0026thinsp;5.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.186\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS\u0026rsquo; (cm/s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.7\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAT (ms)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e106\u0026thinsp;\u0026plusmn;\u0026thinsp;12.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e94\u0026thinsp;\u0026plusmn;\u0026thinsp;15.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePericardial effusion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (22.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.325^\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eApical sparing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40/45 (88.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.021^\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of CMR parameters between Grade 2 and Grade 3 groups (N\u0026thinsp;=\u0026thinsp;38). Abbreviations: LVEDVi\u0026thinsp;=\u0026thinsp;left ventricular end diastolic volume index; LVSVi\u0026thinsp;=\u0026thinsp;left ventricular stroke volume index; LVEF\u0026thinsp;=\u0026thinsp;left ventricular ejection fraction; RVEDVi\u0026thinsp;=\u0026thinsp;right ventricular end\u0026ndash;diastolic volume index; RVSVi\u0026thinsp;=\u0026thinsp;right ventricular stroke volume index; RVEF\u0026thinsp;=\u0026thinsp;right ventricular ejection fraction; LAAi\u0026thinsp;=\u0026thinsp;left atrial area index; LVMi\u0026thinsp;=\u0026thinsp;left ventricular mass index; ECV\u0026thinsp;=\u0026thinsp;extracellular volume fraction, RVFWT\u0026thinsp;=\u0026thinsp;right ventricular free wall thickness; ^ calculated using Fisher's Exact Test (2\u0026ndash;sided)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFeature\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGrade 2 (N \u0026ndash; 8)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGrade 3 (N \u0026ndash; 30)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\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\u003eLVEDVi (ml/m2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79.4\u0026thinsp;\u0026plusmn;\u0026thinsp;17.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88.2\u0026thinsp;\u0026plusmn;\u0026thinsp;18.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLVSVi (ml/m2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42.8\u0026thinsp;\u0026plusmn;\u0026thinsp;8.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46.3\u0026thinsp;\u0026plusmn;\u0026thinsp;9.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLVEF (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54.7\u0026thinsp;\u0026plusmn;\u0026thinsp;9.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53.0\u0026thinsp;\u0026plusmn;\u0026thinsp;7.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.643\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRVEDVi (ml/m2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69.2\u0026thinsp;\u0026plusmn;\u0026thinsp;19.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78.0\u0026thinsp;\u0026plusmn;\u0026thinsp;24.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.386\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRVSVi (ml/m2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41.6\u0026thinsp;\u0026plusmn;\u0026thinsp;9.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43.9\u0026thinsp;\u0026plusmn;\u0026thinsp;10.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.606\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRVEF (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61.6\u0026thinsp;\u0026plusmn;\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58.2\u0026thinsp;\u0026plusmn;\u0026thinsp;11.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.462\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRVFWT (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRV-LGE (N(%))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (37.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28 (93.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.002^\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLAAi (cm2/m2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.2\u0026thinsp;\u0026plusmn;\u0026thinsp;3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLVMi (g/m2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68.1\u0026thinsp;\u0026plusmn;\u0026thinsp;16.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e106.0\u0026thinsp;\u0026plusmn;\u0026thinsp;22.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eECV (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35.1\u0026thinsp;\u0026plusmn;\u0026thinsp;4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45.2\u0026thinsp;\u0026plusmn;\u0026thinsp;7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMyocardial T1 (ms)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1348\u0026thinsp;\u0026plusmn;\u0026thinsp;45.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1386\u0026thinsp;\u0026plusmn;\u0026thinsp;53.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.069\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\u003eEchocardiographic analysis revealed that Grade 3 patients had a more severe cardiac phenotype, characterized by significantly higher MWT (16.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2 mm vs. 14.6\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3 mm; p\u0026thinsp;=\u0026thinsp;0.009), lower LVEF (49.1\u0026thinsp;\u0026plusmn;\u0026thinsp;8.2% vs. 53.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3%; p\u0026thinsp;=\u0026thinsp;0.003), and worse GLS (12.5\u0026thinsp;\u0026plusmn;\u0026thinsp;3.9% vs. 16.0\u0026thinsp;\u0026plusmn;\u0026thinsp;4.6%; p\u0026thinsp;=\u0026thinsp;0.037), as well as higher rates of apical sparing (50% vs 88.9%, p\u0026thinsp;=\u0026thinsp;0.021). Indexed left atrial volume (LAVi) was similar between the groups.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCMR data\u003c/h3\u003e\n\u003cp\u003eThe Grade 3 group demonstrated significantly higher LVMi (106.0\u0026thinsp;\u0026plusmn;\u0026thinsp;22.2 g/m\u0026sup2;) compared to the Grade 2 group (68.1\u0026thinsp;\u0026plusmn;\u0026thinsp;16.7 g/m\u0026sup2;; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Despite this significant difference in mass, all other volumetric parameters were similar between the groups. Regarding myocardial tissue characteristics, pre-contrast T1 mapping values showed a trend towards being higher in the Grade 3 group (1386\u0026thinsp;\u0026plusmn;\u0026thinsp;53.1 ms vs. 1348\u0026thinsp;\u0026plusmn;\u0026thinsp;45.9 ms for Grade 2; p\u0026thinsp;=\u0026thinsp;0.069). Furthermore, extracellular volume (ECV) was significantly higher in the Grade 3 cohort (45.2\u0026thinsp;\u0026plusmn;\u0026thinsp;7.8%) compared to the Grade 2 cohort (35.1\u0026thinsp;\u0026plusmn;\u0026thinsp;4.4%; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Among those with CMR data, Grade 3 patients (N\u0026thinsp;=\u0026thinsp;30) had higher RVFWT (6.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6 vs. 4.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4 mm, p\u0026thinsp;=\u0026thinsp;0.001) and more frequent RV involvement, as determined by the presence of LGE (28/30; 93.3% vs. 3/8; 37.5% in Grade 2, p\u0026thinsp;=\u0026thinsp;0.002).\u003c/p\u003e\n\u003ch3\u003eCorrelation analysis\u003c/h3\u003e\n\u003cp\u003eCorrelation analyses were performed to assess relationships among Perugini grade, clinical variables, and imaging parameters. Correlation parameters are presented in Table \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e5\u003c/span\u003e. Perugini grade demonstrated strong, significant correlations with LVMi (r\u0026thinsp;=\u0026thinsp;0.608, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and ECV (r\u0026thinsp;=\u0026thinsp;0.530, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). It also correlated significantly with cardiac biomarkers, including Troponin I (r\u0026thinsp;=\u0026thinsp;0.549, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and BNP (r\u0026thinsp;=\u0026thinsp;0.355, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\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 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation Matrix of Key Clinical, Imaging, and Biomarker Parameters (N\u0026thinsp;=\u0026thinsp;53 for clinical characteristics and echocardiographic data, N\u0026thinsp;=\u0026thinsp;38 for CMR parameters). Data represent Pearson's correlation coefficient (r), except for correlations with Perugini Grade, which use Spearman's correlation coefficient. * p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01. Abbreviations: 6MWT\u0026thinsp;=\u0026thinsp;6\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTroponin I\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBNP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6MWT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGLS (echo)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMWT (echo)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLVMi (CMR)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eECV\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePerugini grade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.549**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.355*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-0.307*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.315*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.608**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.530**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTroponin I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-0.332*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.081\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.321\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.414*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBNP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-0.492**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.518**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.478**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.357*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6MWT\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 \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.301*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.066\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGLS (echo)\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 \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e-0.597**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e-0.547**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-\u003cb\u003e0.339*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMWT (echo)\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 \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.692**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.019\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLVMi (CMR)\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 \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.553**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eMinute Walk Test; BNP\u0026thinsp;=\u0026thinsp;B\u0026ndash;type Natriuretic Peptide; ECV\u0026thinsp;=\u0026thinsp;Extracellular Volume; GLS\u0026thinsp;=\u0026thinsp;Global Longitudinal Strain; LVMi\u0026thinsp;=\u0026thinsp;Left Ventricular Mass Index; MWT\u0026thinsp;=\u0026thinsp;Maximal Wall Thickness. Negative correlations with GLS reflect worsening myocardial function, as GLS values are reported as absolute values\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eBNP, as a marker of neurohormonal stress, showed significant correlations with structural and functional parameters, including a strong positive correlation with increased cardiac mass, as measured by both echocardiographic MWT (r\u0026thinsp;=\u0026thinsp;0.518, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and CMR-derived LVMi (r\u0026thinsp;=\u0026thinsp;0.478, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). It was also significantly correlated with myocardial infiltration, as quantified by ECV (r\u0026thinsp;=\u0026thinsp;0.357, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Functionally, higher BNP levels were strongly correlated with worse myocardial function (lower absolute GLS, r = -0.492, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). There was, however, no significant correlation between BNP and Troponin I (r\u0026thinsp;=\u0026thinsp;0.140) or functional capacity (6MWT, r = -0.242).\u003c/p\u003e \u003cp\u003eTroponin I levels were significantly correlated with a key marker of infiltration \u0026ndash; ECV (r\u0026thinsp;=\u0026thinsp;0.414, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). It was also significantly correlated with markers of cardiac function \u0026ndash; GLS (-0.332, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and RVEF (-0.425, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). However, there was no statistical association with echo-derived MWT (r\u0026thinsp;=\u0026thinsp;0.081) or CMR-derived LVMi (r\u0026thinsp;=\u0026thinsp;0.321). Furthermore, troponin did not correlate with neurohormonal stress (BNP, r\u0026thinsp;=\u0026thinsp;0.14) or functional capacity (6MWT, r = -0.084). As expected, echocardiographic and CMR parameters of mass (MWT and LVMi) were highly correlated (r\u0026thinsp;=\u0026thinsp;0.692, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this single-center study, we describe a 7-year experience with the diagnosis of ATTR-CM in a Lithuanian referral center. Our data demonstrate a substantial increase in diagnostic yield following adoption of the non-invasive diagnostic algorithm and highlight important clinical and imaging differences between patients with Perugini grade 2 and grade 3 myocardial uptake. While both grades fulfill current diagnostic criteria for ATTR-CM, we have found important differences in myocardial involvement, with higher scintigraphic uptake reflecting more advanced structural and functional disease. Taken together, these findings support the interpretation of Perugini scintigraphic grade as a marker of myocardial amyloid burden and phenotypic disease severity, rather than a purely binary diagnostic variable.\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eDiagnostic yield\u003c/h2\u003e \u003cp\u003eApproximately one third of all 99mTc-PYP scans demonstrated myocardial uptake on planar imaging; however, nearly half of these were graded as equivocal or grade 1, and none of these patients were ultimately diagnosed with ATTR-CM. SPECT-CT imaging clarified that most grade 1 cases represented blood-pool activity rather than true myocardial tracer uptake, underscoring the limitations of planar imaging alone and reinforcing current guideline recommendations for SPECT/CT confirmation [12]. This finding is in-line with previous reports that grade 1 patients have favourable outcomes[13, 14]. The overall diagnostic yield of \u0026ge;grade 2 uptake was approximately 15%, consistent with prior reports from referral populations [14, 15], supporting the effectiveness of targeted scintigraphic screening in patients with clinical or echocardiographic suspicion of amyloid cardiomyopathy.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eCirculating biomarkers\u003c/h2\u003e \u003cp\u003eCirculating biomarkers demonstrated distinct and complementary associations with imaging findings. BNP correlated strongly with markers of myocardial remodeling and functional impairment, including echocardiographic maximal wall thickness, CMR-derived LV mass index, and impaired longitudinal systolic function. In contrast, troponin I correlated with Perugini grade and extracellular volume fraction (ECV), but not with myocardial bulk parameters. Notably, BNP and troponin I did not correlate with each other, underscoring their reflection of different pathophysiological processes.\u003c/p\u003e \u003cp\u003eThis dissociation is biologically plausible. Troponin release in ATTR-CM likely reflects ongoing myocardial injury driven by amyloid infiltration, microvascular dysfunction, direct cytotoxic effects, and increased wall stress at the cellular level [16, 17]. Natriuretic peptides, by contrast, predominantly reflect hemodynamic consequences of increased myocardial stiffness and chamber pressure overload [18]. Similar findings were reported by Morioka et al., who observed higher troponin levels in patients with greater histological amyloid burden despite comparable natriuretic peptide levels and myocardial mass [19]. Collectively, these findings support a multi-marker approach to staging: Troponin I appears to reflect the extent of infiltration and active toxicity, whereas BNP reflects the hemodynamic consequence of that infiltration.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003ePerugini grade and disease severity\u003c/h2\u003e \u003cp\u003eIn our cohort, patients with Perugini grade 3 uptake presented with a significantly more advanced clinical profile than those with grade 2. These patients had worse NYHA functional class, lower exercise tolerance, worse troponin I levels and a higher prevalence of conduction system disease \u0026ndash; specifically wider QRS intervals and a greater need for pacemaker implantation. Structural imaging mirrored this clinical decline: echocardiography showed increased MWT and lower LVEF, while CMR confirmed a higher amyloid burden through increased LVMi, RVFWT, and expanded ECV. Additionally, both CMR and echocardiography confirmed near-universal RV involvement in Grade 3 patients with CMR data.\u003c/p\u003e \u003cp\u003eRV involvement in ATTRM-CM was studied in a large SPECT-based study by Porcari et al. [20]. They showed that some degree of RV involvement is a universal finding in ATTR-CM patients on SPECT. However, patients with diffuse RV involvement had a more severe clinical profile, as evidenced by multiple imaging and biomarker parameters. They also found that diffuse RV involvement was correlated with higher Perugini grades. Our cohort showed a strong correlation between RVEF and troponin I values, further supporting the idea that RV involvement tracks with increased amyloid load and likely reflects a transition from predominantly LV-focused disease to a diffuse cardiomyopathy.\u003c/p\u003e \u003cp\u003eImportantly, the phenotypic differences that we have observed do not translate to prognostic difference of Perugini grade 2 and 3 patients in past large-scale studies [20, 21]. It has been argued that quantification of Perugini grades can be confounded by competitive radiotracer uptake from surrounding soft-tissue, thus higher visual grades may not reflect higher cardiac uptake but rather a decrease in bone uptake [22]. However, recent studies on semi-quantitative scintigraphic parameters have shown associations with more severe disease profile and worse outcomes [23, 24].\u003c/p\u003e \u003cp\u003eIn this context, our findings suggest that higher scintigraphic grade reflects a more advanced structural involvement without translating into measurable difference in prognosis. Survival in ATTR-CM is influenced by multiple competing factors, including age, comorbidities, referral patterns, and treatment, which may obscure biological gradients detectable by detailed imaging and biomarker assessment. It is also possible that past a certain point myocardial infiltration primarily drives functional and biventricular involvement, rather than incremental mortality risk.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eThis study has several limitations. Its retrospective, single-center design and relatively small number of Grade 2 patients limit statistical power and generalizability. However, this likely reflects real-world referral patterns. CMR data were not available for all patients, potentially introducing selection bias related to availability, contraindications, or image quality. BNP values were available, but NT-proBNP was not, precluding application of established staging systems. Finally, outcome data were not analyzed, preventing direct assessment of the prognostic implications of Perugini grade differences. These findings should not be interpreted as demonstrating prognostic differences between Perugini grades.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, while Perugini grade 2 and grade 3 myocardial uptake on PYP scan, both satisfy non-invasive diagnostic criteria for ATTR-CM, they are associated with distinct clinical and imaging phenotypes. Our cohort shows that higher PYP uptake reflects greater myocardial amyloid burden, more advanced functional impairment, and increased biomarkers of cardiac injury.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eATTR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCM\u0026ndash;Transthyretin amyloid cardiomyopathy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBNP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eB\u0026ndash;type natriuretic peptide\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCMR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCardiac magnetic resonance\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eComputed tomography\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eECG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eElectrocardiogram\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eECV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eExtracellular volume\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGLS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGlobal longitudinal strain\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLeft ventricular\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLVEF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLeft ventricular ejection fraction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLVMi\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLeft ventricular mass index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMWT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMaximal wall thickness\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNYHA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNew York Heart Association\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRVFWT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRight ventricular free wall thickness\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStandard deviation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSPECT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSingle\u0026ndash;photon emission computed tomography\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSPECT/CT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSingle\u0026ndash;photon emission computed tomography/computed tomography\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTTR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTransthyretin\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e The authors declare no competing interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e The authors declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e The study was approved by the Kaunas regional bioethics committee (Reference Nr. BE-2-50).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u0026nbsp;\u003c/strong\u003eInformed consent was obtained from all individual participants included in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDataset availability\u003c/strong\u003e The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions \u003c/strong\u003eConceptualization, E.E., D.V., data collection, E.Z., M.S, P.B., G.S., writing of original draft, P.B., review and editing, E.E., A.K., T.L, A.J., J.P. All authors have read and agreed to the published version of the manuscript. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eGarcia-Pavia P, Rapezzi C, Adler Y, Arad M, Basso C, Brucato A, et al. Diagnosis and treatment of cardiac amyloidosis: a position statement of the ESC Working Group on Myocardial and Pericardial Diseases. Eur Heart J. 2021 Apr 21;42(16):1554\u0026ndash;68. \u003c/li\u003e\n\u003cli\u003eGillmore JD, Maurer MS, Falk RH, Merlini G, Damy T, Dispenzieri A, et al. Nonbiopsy Diagnosis of Cardiac Transthyretin Amyloidosis. Circulation. 2016 Jun 14;133(24):2404\u0026ndash;12. \u003c/li\u003e\n\u003cli\u003eGillmore JD, Judge DP, Cappelli F, Fontana M, Garcia-Pavia P, Gibbs S, et al. Efficacy and Safety of Acoramidis in Transthyretin Amyloid Cardiomyopathy. New England Journal of Medicine. 2024 Jan 11;390(2):132\u0026ndash;42. \u003c/li\u003e\n\u003cli\u003eFontana M, Berk JL, Gillmore JD, Witteles RM, Grogan M, Drachman B, et al. Vutrisiran in Patients with Transthyretin Amyloidosis with Cardiomyopathy. New England Journal of Medicine. 2025 Jan 2;392(1):33\u0026ndash;44. \u003c/li\u003e\n\u003cli\u003eMaurer MS, Schwartz JH, Gundapaneni B, Elliott PM, Merlini G, Waddington-Cruz M, et al. Tafamidis Treatment for Patients with Transthyretin Amyloid Cardiomyopathy. New England Journal of Medicine. 2018 Sep 13;379(11):1007\u0026ndash;16. \u003c/li\u003e\n\u003cli\u003eMoya A, Oeste CL, Beles M, Verstreken S, Dierckx R, Heggermont W, et al. Detection of transthyretin amyloid cardiomyopathy by automated data extraction from electronic health records. ESC Heart Fail. 2023 Dec 19;10(6):3483\u0026ndash;92. \u003c/li\u003e\n\u003cli\u003eSuomalainen O, Pilv J, Loimaala A, M\u0026auml;tzke S, Heli\u0026ouml; T, Uusitalo V. Prognostic significance of incidental suspected transthyretin amyloidosis on routine bone scintigraphy. Journal of Nuclear Cardiology. 2022 Jun 1;29(3):1021\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eRettl R, Duca F, Kronberger C, Binder C, Willixhofer R, Ermolaev N, et al. Prognostic implication of DPD quantification in transthyretin cardiac amyloidosis. Eur Heart J Cardiovasc Imaging. 2025 Feb 1;26(2):251\u0026ndash;60. \u003c/li\u003e\n\u003cli\u003ePerugini E, Guidalotti PL, Salvi F, Cooke RMT, Pettinato C, Riva L, et al. Noninvasive Etiologic Diagnosis of Cardiac Amyloidosis Using 99m Tc-3,3-Diphosphono-1,2-Propanodicarboxylic Acid Scintigraphy. J Am Coll Cardiol. 2005 Sep;46(6):1076\u0026ndash;84. \u003c/li\u003e\n\u003cli\u003eLang RM, Badano LP, Mor-Avi V, Afilalo J, Armstrong A, Ernande L, et al. Recommendations for Cardiac Chamber Quantification by Echocardiography in Adults: An Update from the American Society of Echocardiography and the European Association of Cardiovascular Imaging. Eur Heart J Cardiovasc Imaging. 2015 Mar;16(3):233\u0026ndash;71. \u003c/li\u003e\n\u003cli\u003eSchulz-Menger J, Bluemke DA, Bremerich J, Flamm SD, Fogel MA, Friedrich MG, et al. Standardized image interpretation and post-processing in cardiovascular magnetic resonance - 2020 update. Journal of Cardiovascular Magnetic Resonance. 2020 Jan;22(1):19. \u003c/li\u003e\n\u003cli\u003eCaobelli F, Dweck MR, Albano D, Gheysens O, Georgoulias P, Nekolla S, et al. Hybrid cardiovascular imaging. A clinical consensus statement of the european association of nuclear medicine (EANM) and the european association of cardiovascular imaging (EACVI) of the ESC. Eur J Nucl Med Mol Imaging. 2025 Feb 22;52(3):1095\u0026ndash;118. \u003c/li\u003e\n\u003cli\u003eItzhaki Ben Zadok O, Ruhrman‐Sahar N, Mats I, Vaxman I, Shiyovich A, Aviv Y, et al. The short and long‐term characteristics and outcomes of patients with grade 1 myocardial uptake on cardiac scintigraphy. ESC Heart Fail. 2023 Jun 17;10(3):1666\u0026ndash;76. \u003c/li\u003e\n\u003cli\u003eChai J, Cheung M, Yim J, Chen LK, Didi A, Balthazaar SJT, et al. Equivocal vs Positive Technetium-99m-Pyrophosphate Scintigraphy for Transthyretin Amyloid Cardiomyopathy: Comparing Outcomes, Demographics, and Imaging. CJC Open. 2025 Oct;7(10):1282\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eThe use of PYP scan for evaluation of ATTR cardiac amyloidosis at a tertiary medical centre. British Journal of Cardiology. 2022; \u003c/li\u003e\n\u003cli\u003eDe Michieli L, Cipriani A, Iliceto S, Dispenzieri A, Jaffe AS. Cardiac Troponin in Patients With Light Chain and Transthyretin Cardiac Amyloidosis. JACC CardioOncol. 2024 Feb;6(1):1\u0026ndash;15. \u003c/li\u003e\n\u003cli\u003eKociol RD, Pang PS, Gheorghiade M, Fonarow GC, O\u0026rsquo;Connor CM, Felker GM. Troponin Elevation in Heart Failure. J Am Coll Cardiol. 2010 Sep;56(14):1071\u0026ndash;8. \u003c/li\u003e\n\u003cli\u003eMueller C, McDonald K, de Boer RA, Maisel A, Cleland JGF, Kozhuharov N, et al. Heart Failure Association of the European Society of Cardiology Practical Guidance on the Use of Natriuretic Peptide Concentrations. Eur J Heart Fail. 2019 Jun 1;21(6):715\u0026ndash;31. \u003c/li\u003e\n\u003cli\u003eMorioka M, Takashio S, Nakashima N, Nishi M, Fujiyama A, Hirakawa K, et al. Correlation Between Cardiac Images, Biomarkers, and Amyloid Load in Wild‐Type Transthyretin Amyloid Cardiomyopathy. J Am Heart Assoc. 2022 Jun 21;11(12). \u003c/li\u003e\n\u003cli\u003ePorcari A, Fontana M, Canepa M, Biagini E, Cappelli F, Gagliardi C, et al. Clinical and Prognostic Implications of Right Ventricular Uptake on Bone Scintigraphy in Transthyretin Amyloid Cardiomyopathy. Circulation. 2024 Apr 9;149(15):1157\u0026ndash;68. \u003c/li\u003e\n\u003cli\u003eSheikh A, Achten A, Aimo A, Razvi Y, Mansell J, Rauf MU, et al. Myocardial Amyloid Burden in Transthyretin Amyloidosis. JACC. 2025 Nov; \u003c/li\u003e\n\u003cli\u003eKoeckerling D, Reddy RK, Eichhorn C, Braun V, Ahmad Y, Howard JP, et al. Echocardiographic risk stratification in light chain and transthyretin amyloidosis: a meta-analysis. European Heart Journal Open. 2025 Jul 4;5(4). \u003c/li\u003e\n\u003cli\u003eHutt DF, Fontana M, Burniston M, Quigley A-M, Petrie A, Ross JC, et al. Prognostic utility of the Perugini grading of 99mTc-DPD scintigraphy in transthyretin (ATTR) amyloidosis and its relationship with skeletal muscle and soft tissue amyloid. Eur Heart J Cardiovasc Imaging. 2017 Dec 1;18(12):1344\u0026ndash;50. \u003c/li\u003e\n\u003cli\u003eScully PR, Morris E, Patel KP, Treibel TA, Burniston M, Klotz E, et al. DPD Quantification in Cardiac Amyloidosis. JACC Cardiovasc Imaging. 2020 Jun;13(6):1353\u0026ndash;63. \u003c/li\u003e\n\u003cli\u003eRettl R, Duca F, Kronberger C, Binder C, Willixhofer R, Ermolaev N, et al. Prognostic implication of DPD quantification in transthyretin cardiac amyloidosis. Eur Heart J Cardiovasc Imaging. 2025 Jan 31;26(2):251\u0026ndash;60. \u003c/li\u003e\n\u003cli\u003eHarapoz M, Evans S, Geenty P, Kwok F, Stewart G, Taylor MS, et al. Correlation Between Quantitative Uptake of 99mTC-DPD and Echocardiographic Parameters in Cardiac ATTR: A Novel Follow-Up Strategy. Front Cardiovasc Med. 2021 Oct 15;8. \u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table 2","content":"\u003cp\u003eTable 2 is not available with this version.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"journal-of-cardiovascular-imaging","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Journal of Cardiovascular Imaging](https://jcvi.biomedcentral.com/)","snPcode":"44348","submissionUrl":"https://submission.springernature.com/new-submission/44348/3","title":"Journal of Cardiovascular Imaging","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8838252/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8838252/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eTransthyretin amyloid cardiomyopathy (ATTR-CM) has undergone a shift towards non-invasive diagnostics using bone tracer scintigraphy with Perugini grading. While both grades 2 and 3 are considered diagnostic, potential phenotypic differences between these groups remain uncertain. We aimed to evaluate the diagnostic yield of technetium-99m pyrophosphate (99mTc-PYP) scintigraphy and to compare clinical and multimodality imaging characteristics across scintigraphic grades in a single-center cohort.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003e We retrospectively reviewed all patients who underwent 99mTc-PYP scintigraphy for suspected cardiac amyloidosis between 2018 and 2025. Patients with confirmed ATTR-CM were stratified by Perugini grade (grade 2 vs. grade 3). Clinical features, biomarkers, electrocardiography, echocardiography, and cardiac magnetic resonance (CMR) parameters were compared. Correlations between scintigraphic grade, imaging markers, and biomarkers were assessed.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAmong 302 scans, 101 (33.4%) demonstrated myocardial uptake. Fifty-three patients were diagnosed with ATTR-CM, including 8 (15.1%) with grade 2 and 45 (84.9%) with grade 3 uptake. Grade 3 patients exhibited worse functional status, shorter 6-minute walk distance, and higher troponin I levels. Echocardiography showed greater maximal wall thickness, lower left ventricular ejection fraction, and worse global longitudinal strain. In the subset with CMR (N\u0026thinsp;=\u0026thinsp;38), grade 3 patients (N\u0026thinsp;=\u0026thinsp;30) had significantly higher left ventricular mass index, extracellular volume fraction, right ventricular free wall thickness, and more frequent right ventricular involvement. Perugini grade correlated strongly with left ventricular mass index (r\u0026thinsp;=\u0026thinsp;0.61, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and extracellular volume (r\u0026thinsp;=\u0026thinsp;0.53, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and moderately with troponin I (r\u0026thinsp;=\u0026thinsp;0.55) and B-type natriuretic peptide (r\u0026thinsp;=\u0026thinsp;0.36, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Grade 1 uptake was not associated with subsequent ATTR-CM diagnosis.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eNon-invasive scintigraphy provides effective detection of ATTR-CM in a referral population. Although grades 2 and 3 both meet diagnostic criteria, grade 3 uptake is associated with greater myocardial amyloid burden, more advanced structural remodeling, and worse functional impairment. In our cohort, Perugini grade appears to reflect disease severity rather than serving solely as a binary diagnostic marker.\u003c/p\u003e","manuscriptTitle":"Multimodality Imaging Characterization of Perugini Scintigraphic Grades in Transthyretin Amyloid Cardiomyopathy: a single center experience","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-18 05:28:13","doi":"10.21203/rs.3.rs-8838252/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-23T09:32:16+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-19T14:56:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"6344513095821789161454818981578559633","date":"2026-03-28T13:10:45+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-06T04:17:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"297869728168592536802428595212186646855","date":"2026-02-25T23:53:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"152322817606867790235031972325419265291","date":"2026-02-12T08:23:39+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-12T08:08:22+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-11T06:12:45+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-11T06:10:20+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Cardiovascular Imaging","date":"2026-02-10T07:50:26+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-cardiovascular-imaging","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Journal of Cardiovascular Imaging](https://jcvi.biomedcentral.com/)","snPcode":"44348","submissionUrl":"https://submission.springernature.com/new-submission/44348/3","title":"Journal of Cardiovascular Imaging","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4c069e9a-8b23-49e7-acb8-1df74786e002","owner":[],"postedDate":"February 18th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-04-23T09:40:13+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-18 05:28:13","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8838252","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8838252","identity":"rs-8838252","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}