Integration of clinical parameters and deep learning based ROI enhancement in Tc-99m PYP scintigraphy for predicting SPECT/CT-adjudicated Perugini categories in suspected transthyretin cardiac amyloidosis
Technetium-99 m pyrophosphate (Tc-99 m PYP) planar scintigraphy is widely used for evaluating transthyretin cardiac amyloidosis (ATTR-CM). However, interpreting equivocal Perugini Grade 1 cardiac uptake remains a significant clinical challenge due to overlapping blood-pool activity and low signal-to-noise ratio. We aimed to develop and validate a multimodal deep learning framework to predict expert SPECT/CT adjudicated Perugini categories from planar imaging and pre-procedural clinical variables, with particular attention to Grade 1 examinations. In this multicenter study utilizing data from the Taiwan Multicenter TTCA-PYP Registry ( N = 438), we developed a multimodal neural network. The framework processes physician-verified cardiac planar ROIs (32 × 128 pixels) with a truncated Wide-ResNet50-2 encoder and 23 routine clinical variables with a frozen TabPFN embedding, aligned by a CLIP-style contrastive loss and fused by cross-attention, to predict SPECT/CT-adjudicated Perugini categories (Grade 0, Grade 1, Grades 2–3). Genetic testing status and study design were not inputs. Evaluation used 10 repetitions of a hospital- and grade-stratified assessment set with 10-fold cross-validation, decision curve analysis, and leave-one-center-out testing of the two centers with all grades (FEMH, NTUH). Overall accuracy was higher with the multimodal model than with imaging only (0.826 vs. 0.751; paired difference + 0.075, 95% CI 0.034 to 0.117), whereas macro-AUC was similar (0.925 vs. 0.917). In Grade 1, precision increased from 0.536 to 0.694 (difference + 0.159, 95% CI 0.056 to 0.261) and recall decreased from 0.704 to 0.683 (difference − 0.022, 95% CI − 0.120 to 0.077); F1-score and PR-AUC differences were less certain. Intervals used a Nadeau-Bengio correction for repeated resampling. With FEMH or NTUH held out, accuracy was 0.704 and 0.889, but Grade 1 recall was 0.312 in FEMH and Grade 0 recall 0.071 in NTUH. The multimodal framework may serve as an adjunct for standardizing expert imaging-based Perugini classification from planar Tc-99 m PYP examinations. It does not establish an etiologic diagnosis of ATTR-CM, and Grade 1 predictions remain indeterminate findings requiring monoclonal protein assessment and, where appropriate, tomographic or further clinical evaluation. Performance did not transfer uniformly to held-out centers, and independent validation is required.
Authors
- Yu-An Yen (ORCID: https://orcid.org/0000-0001-7163-2222)
- Wen-Hwa Wang
- Szu-Ying Tsai (ORCID: https://orcid.org/0000-0002-5349-5022)
- Kao Chia-Hung
- Chi‐Lun Ko (ORCID: https://orcid.org/0000-0002-4139-5892)
- De-Xiang Ou (ORCID: https://orcid.org/0009-0002-3668-6609)
- Wen-Chung Yu
- Chih-Hung Lai
- Jhih-Yuan Shih
- Chung-Lieh Hung
- Mei-Fang Cheng
- Chung-Ming Chen
- Cheng-Hau Huang
- Shan-Ying Wang
- on behalf of the TTCA-PYP investigators
- Yen-Hung Lin
- Lien-Hsin Hu
- Yen-Wen Wu
- Kuan-Cheng Chang
- Wei-Ting Chang
Institutions
- National Sun Yat-sen University (TW)
- National Yang Ming Chiao Tung University (TW)
- National Taiwan University (TW)
- China Medical University (TW)
- Mackay Memorial Hospital (TW)
- Taipei Veterans General Hospital (TW)
- Mackay Medical University (TW)
- National Yang Ming University Hospital (TW)
- Taichung Veterans General Hospital (TW)
- Far Eastern Memorial Hospital (TW)
- China Medical University Hospital (TW)
- National Taiwan University Hospital (TW)
- Chi Mei Medical Center (TW)
- Kaohsiung Veterans General Hospital (TW)
- Yuan Ze University (TW)
Publication Details
- Journal
- BMC Medical Imaging
- Published
- 2026-11-06
- DOI
- https://doi.org/10.1186/s12880-026-03036-1
- Primary Topic
- Amyloidosis: Diagnosis, Treatment, Outcomes
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Ministry of Science and Technology, Taiwan