Spatial Matching of 2D Mammography Images and Specimen Radiographs: Towards Improved Characterization of Suspicious Microcalcifications

TL;DR

This paper presents a template matching approach to align mammography images with histopathology specimens, aiming to improve the characterization of suspicious microcalcifications for better diagnostic accuracy.

Contribution

It introduces a novel template matching method using microcalcifications as landmarks to align radiographs with biopsy specimens, enhancing microcalcification analysis.

Findings

High negative predictive value of 0.98 in identifying biopsy regions

Modest precision of 0.66 and recall of 0.58 in localization accuracy

Demonstrates potential for improved microcalcification characterization

Abstract

Accurate characterization of suspicious microcalcifications is critical to determine whether these calcifications are associated with invasive disease. Our overarching objective is to enable the joint characterization of microcalcifications and surrounding breast tissue using mammography images and digital histopathology images. Towards this goal, we investigate a template matching-based approach that utilizes microcalcifications as landmarks to match radiographs taken of biopsy core specimens to groups of calcifications that are visible on mammography. Our approach achieved a high negative predictive value (0.98) but modest precision (0.66) and recall (0.58) in identifying the mammographic region where microcalcifications were taken during a core needle biopsy.