Hruska, Carrie B.

BACKGROUND: Technetium-based cardiac amyloid radionuclide imaging enables noninvasive diagnosis of transthyretin amyloid cardiomyopathy (ATTR-CM), but conventional planar and visual semiquantitative approaches have important limitations. We developed the quantitative 3-dimensional Mayo 3D Score, defined as the ratio of mean left ventricular myocardial radiotracer uptake to right atrial blood-pool uptake using computed tomography (CT)-fused single-photon emission CT (SPECT) volumes of interest, and sought to validate its diagnostic performance against myocardial pathology. METHODS: Consecutive patients who underwent 99m Tc-pyrophosphate SPECT/CT at Mayo Clinic for suspected ATTR-CM between June 2017 and January 2025 with archived myocardial tissue were included. Baseline characteristics, including demographics, echocardiogram, biomarkers, visual semiquantitative, and Mayo 3D Score metrics, were collected. Myocardial specimens underwent histopathologic confirmation of amyloid, with amyloid subtype determination and further semiquantitative grading of amyloid burden and deposition patterns. RESULTS: Among 230 patients (median age, 72 years; 78% male), 107 (47%) had ATTR-CM, of whom 9 had hereditary ATTR-CM. The Mayo 3D Score showed excellent discrimination against pathology (area under the receiver operating characteristic curve, 0.92 [0.88–0.96]), exceeding planar Perugini (0.87 [0.83–0.92]; P =0.006), and heart-to-contralateral lung ratio (0.86 [0.81–0.91]; P =0.004) and comparable to SPECT Perugini (0.90 [0.86–0.94]; P =0.12). A cutoff ≥1.0 yielded 86.0% sensitivity, 92.7% specificity, 91.1% positive predictive value, and 88.4% negative predictive value. Among ATTR-positive cases, the Mayo 3D Score correlated strongly with semiquantitative amyloid burden (Spearman ρ=0.69), was higher in pericellular than nodular deposition patterns ( P <0.001), and was not associated with vascular involvement ( P =0.42). CONCLUSIONS: In patients with suspected ATTR-CM undergoing 99m Tc-pyrophosphate SPECT/CT, the Mayo 3D Score demonstrated superior diagnostic performance compared with planar metrics and comparable to SPECT Perugini, while correlating with myocardial ATTR burden and deposition patterns on pathology. These findings support its integration as a quantitative adjunct within clinical diagnostic ATTR-CM workflows.

BACKGROUND: Guidelines recommend 3-hour cardiac amyloid radionuclide imaging (CARI) for transthyretin amyloid cardiomyopathy. Citing rapid blood clearance of 99m Tc-hydroxymethylene-diphosphonate (HMDP) and efficient laboratory throughput, 1-hour imaging is increasingly practiced despite limited supporting evidence. We sought to compare diagnostic performance and interpreter experience of 1-hour versus 3-hour HMDP-CARI. METHODS: Consecutive patients with suspected transthyretin amyloid cardiomyopathy (n=114) underwent both 1-hour and 3-hour HMDP single photon emission computed tomography (CT)/CT. Two cardiologist-radiologist reader teams, blinded to imaging timepoint (1 versus 3 hours), assessed overall interpretation, single photon emission CT–based Perugini grade, interpretation difficulty, interpreter confidence, and need for CT-fused images for anatomic localization. Discordant, equivocal, and difficult cases were arbitrated by a third tie-breaking team. The myocardial-to-blood-pool radiotracer uptake ratio (3-dimensional Score) was measured as a surrogate of contrast resolution. RESULTS: Interinterpreter agreement was high at both time points (κ≥0.81), with more cases requiring arbitration at 3 hours versus 1 hour (22% versus 13%; P =0.049). Overall interpretation and Perugini grades were concordant between time points in 111/114 (97%) and 106/114 (93%) patients, respectively. Three patients (3%) were negative at 1 hour but equivocal at 3 hours, all of which were clinically ruled out for transthyretin amyloid cardiomyopathy. Interpreter confidence was comparable at both timepoints (97% versus 95%; P =0.317). Compared with 3-hour imaging, contrast resolution was inferior (lower 3-dimensional score, P <0.001) and CT fusion was more frequently needed (57% versus 31%, P <0.001) at 1-hour imaging. CONCLUSIONS: In a prospective, blinded comparison of 1-hour versus 3-hour HMDP-CARI, diagnostic performance and interpreter experience were similar, with readers requesting CT fusion more frequently at 1 hour to optimize myocardial-to-blood pool discrimination.

Abstract Background Molecular breast imaging (MBI) has shown utility as a supplement to mammography in women with dense breasts. Background parenchymal uptake (BPU), which describes the level of Tc-99m sestamibi in fibroglandular tissue on MBI, varies among women with similar density. Higher BPU is associated with greater breast cancer risk. The goal of this work is to investigate the histological correlations of BPU that may explain this association with risk. Methods We compared histologic features of prospectively collected benign breast tissue biopsies from healthy women who had a region of dense tissue on mammography exhibiting one of the extreme categories of BPU on MBI: either photopenic or marked. Tissue composition of specimens was assessed by measuring area of epithelium, stroma, and fat and counting lobules. Lobular involution status was assessed by an expert pathologist as either none, partial, or complete. Ki-67 index and estrogen receptor-alpha expression were also assessed. Results Biopsies were performed in 48 women (mean age 54.9 years [SD 11.1 years]), including 20 with marked BPU and 28 with photopenic BPU. Women with marked BPU were younger (mean age 49.9 vs. 58.4 years, p = 0.004), had higher body mass index ( p = 0.01), and were more likely premenopausal ( p = 0.005). Marked BPU specimens had a higher proportion of epithelium (14.5% vs. 2.2%, p < 0.001), lower stromal content (44.8% vs. 84.2%, p = 0.005), similar fat (18.9% vs. 12.9%, p = 0.41), and greater lobule counts (15.5 vs. 6.3, p < 0.001) compared to photopenic specimens. Complete lobular involution was less frequent in marked tissue than in photopenic tissue (10.5% vs. 76%, p < 0.001). Ki-67 index was higher in marked BPU tissues (5.4% vs. 1.6%, p = 0.006), though the difference was attenuated after adjustment for epithelial area (p = 0.26). Estrogen receptor-alpha expression did not differ between marked and photopenic groups (25.6% vs. 28.4%, p = 0.12). Conclusions Marked BPU on MBI is associated with greater epithelial content, less lobular involution, and higher proliferative activity—features characteristic of tissue at elevated risk for malignant transformation. These findings suggest that BPU provides functional information beyond mammographic density, supporting its role as an imaging biomarker for breast cancer risk in women with dense breasts. Trial Registration: NCT01240278 and NCT01588834

In women with dense breasts, adding molecular breast imaging to digital breast tomosynthesis (DBT) increased both overall and invasive cancer detection rates, while modestly raising the recall rate compared with DBT alone.

PURPOSE Artificial intelligence (AI) algorithms improve breast cancer detection on mammography, but their contribution to long-term risk prediction for advanced and interval cancers is unknown. METHODS We identified 2,412 women with invasive breast cancer and 4,995 controls matched on age, race, and date of mammogram, from two US mammography cohorts, who had two-dimensional full-field digital mammograms performed 2-5.5 years before cancer diagnosis. We assessed Breast Imaging Reporting and Data System density, an AI malignancy score (1-10), and volumetric density measures. We used conditional logistic regression to estimate odds ratios (ORs), 95% CIs, adjusted for age and BMI, and C-statistics (AUC) to describe the association of AI score with invasive cancer and its contribution to models with breast density measures. Likelihood ratio tests (LRTs) and bootstrapping methods were used to compare model performance. RESULTS On mammograms between 2-5.5 years prior to cancer, a one unit increase in AI score was associated with 20% greater odds of invasive breast cancer (OR, 1.20; 95% CI, 1.17 to 1.22; AUC, 0.63; 95% CI, 0.62 to 0.64) and was similarly predictive of interval (OR, 1.20; 95% CI, 1.13 to 1.27; AUC, 0.63) and advanced cancers (OR, 1.23; 95% CI, 1.16 to 1.31; AUC, 0.64) and in dense (OR, 1.18; 95% CI, 1.15 to 1.22; AUC, 0.66) breasts. AI score improved prediction of all cancer types in models with density measures ( P LRT values < .001); discrimination improved for advanced cancer (ie, AUC for dense volume increased from 0.624 to 0.679, Δ AUC 0.065, P = .01) but did not reach statistical significance for interval cancer. CONCLUSION AI imaging algorithms coupled with breast density independently contribute to long-term risk prediction of invasive breast cancers, in particular, advanced cancer.

Abstract Purpose: Melanocortin 1 receptor (MC1R) has been shown in animal models to be a target for effective radionuclide therapy. This first-in-human clinical trial studied the safety and biodistribution of two novel MC1R-targeted imaging tracers designed to support the development of MC1R-targeted alpha particle therapy through image-based identification of MC1R and radiation dosimetry. Imaging was compared to MC1R expression by immunohistochemistry (IHC) of subjects’ melanoma tumors. Methods: Subjects with stage IV melanoma were randomized to receive either [203Pb]VMT01 SPECT/CT imaging followed by [68Ga]VMT02 PET/CT imaging approximately 1 month later, or vice versa in a cross-over design during their normal melanoma treatment course. Patient selection included a positive [18F]FDG PET/CT within 30 days of imaging tracer injection. 555 - 925 mBq of [203Pb]VMT01 was injected IV with imaging performed at 1, 4, and 24 hours. 74 - 277 mBq [68Ga]VMT02 was injected IV and imaging performed dynamically up to 1 hour, and at 2 and 3 hours. Due to an interruption in drug supply, only 3 subjects received [203Pb]VMT01 imaging. Key FDG-avid melanoma lesions were marked and presented to three experienced Radiologists serving as blinded reviewers. The blinded reviewers compared [18F]FDG PET/CT to experimental imaging and scored scans and key lesions on multiple metrics. Imaging positivity was defined as tumor uptake and retention of tracer in ≥ 1 melanoma tumors above background liver activity. Melanoma biopsy tissue was obtained and MC1R IHC performed as available. Results: 7 subjects were enrolled; 6 were imaged and 5 had available pathology. 3 of 6 imaged subjects had MC1R positive tumors via experimental imaging tracers. [68Ga]VMT02 PET/CT at 3 hours led to the best tumor to background ratio, and [203Pb]VMT01 SPECT/CT showed tumor retention at 24 hours. 4 of 5 subjects had positive MC1R staining by IHC. Of the 3 subjects with negative imaging, 2 had positive staining by IHC. Of the 3 subjects with positive imaging, 2 had available biopsies and all stained positive for MC1R by IHC. Conclusion: A subgroup of advanced melanoma patients were identified to express MC1R using new MC1R-targeted imaging agents. Full concordance between imaging and IHC of positive scans, but not with negative scans, suggests that IHC is a more sensitive biomarker detection method. Additional testing is needed to establish frequency of positive MC1R imaging in stage IV melanoma and its correlation to histological findings and treatment outcomes. Preferential tumor retention provides proof-of-concept that the MC1R-targeting therapy trial for [212Pb]VMT01 alpha-emitting therapy will deliver localized radiation to high MC1R expressing tumors as screened by [203Pb]VMT01 or [68Ga]VMT02. Imaging quality is sufficient for subject selection and dosimetry but may exclude subjects with MC1R receptor expression only detectable by IHC. Citation Format: Brenna M. Marks, Matthew Block, Geoffrey B. Johnson, Carrie B. Hruska, Mukesh K. Pandey, Andrew Paulsen, Michael K. Schultz, Michael A. McDonald, Edwin A. Sagastume, Frances L. Johnson. MC1R imaging and histology in the targeted imaging of melanoma for alpha-particle radiotherapy (TIMAR1) trial [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 2 (Clinical Trials and Late-Breaking Research); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(8_Suppl):Abstract nr CT104.