aBSI

The aBSI device is a cloud-based software system designed for quantitative analysis of skeletal disease from nuclear medicine bone scans, functioning as a Picture Archiving and Communications System (PACS) with specialized oncology tools. It utilizes an improved algorithm and an expanded skeletal atlas to calculate the Bone Scan Index (BSI), a measure shown in clinical studies to be associated with overall survival and disease progression in patients with metastatic castration-resistant prostate cancer.

The aBSI is a software-only medical device intended for use by trained healthcare professionals and researchers to facilitate the acceptance, transfer, storage, display, manipulation, quantification, and reporting of digital medical images acquired via nuclear medicine (NM) imaging. Its core function is to provide a fully quantitative assessment of a patient’s skeletal disease, presented as the Bone Scan Index (BSI), which represents the fraction of the total skeleton weight affected by disease. The device integrates general Picture Archiving and Communications System (PACS) tools with specific clinical applications for oncology, such as lesion marking and quantitative analysis. The methodology involves an improved algorithm for detecting high-intensity regions (hotspots) within a refined skeletal atlas that now covers the entire femur and humerus. Images are normalized to a predefined level for healthy bone tissue, and the system is delivered as a cloud-based service, an update from its predicate's CD or downloadable file installation. Clinical performance data for aBSI was established through two studies involving patients with metastatic castration-resistant prostate cancer (mCRPC). Study I, a Phase 3 validation with 721 evaluable patients, found that aBSI was significantly associated with overall survival (OS), symptomatic progression, and time to opiate use, with aBSI remaining an independent predictor of OS in multivariate models. Study II, a retrospective analysis of 169 mCRPC patients, demonstrated that an increase in aBSI had a similar association with OS as the PCWG criteria for radiographic progression, and quantified the aBSI increase in patients meeting PCWG criteria. Bench testing further confirmed the linearity, accuracy, precision, and reproducibility of the BSI calculation with different cameras and multiple images. The device differs from its predicate by removing CT image display capability and being cloud-based, among other technological enhancements aimed at improving efficiency and analytical scope.

AI Regulatory Concerns

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Jev reads the full FDA letter and returns calibrated concern probabilities per regulatory category. These are AI estimates, not regulatory advice.

• Q1. How does the refined skeletal atlas in aBSI, now covering the entire femur and humerus, impact the sensitivity and specificity of hotspot detection and BSI calculation compared to the previous version that covered only down to ¾ of these bones?; What were the specific algorithmic improvements made to the hotspot detection in aBSI, and how do these changes quantitatively affect performance metrics such as detection accuracy, false positive/negative rates, or processing time compared to the predicate EXINI device?; Given that aBSI showed an association with overall survival comparable to PCWG criteria in Study II, what is the incremental clinical utility or advantage of using aBSI over or in conjunction with established PCWG criteria in routine oncological practice for mCRPC patients?; Study I demonstrated aBSI's prognostic value in a large mCRPC cohort. Has the performance of aBSI been evaluated in other cancer types with bone metastases or in different stages of prostate cancer (e.g., non-castration resistant)?; Considering aBSI is now a cloud-based service, what specific measures are in place to ensure data security, patient privacy (e.g., HIPAA compliance), data integrity during transfer and storage, and system reliability/uptime for clinical use?