Abstract

Abstract Introduction: We used micro-computed tomography (microCT), a high-resolution imaging option, to detect and characterize microcalcifications (MCs) in three dimensions within pathology blocks of benign and malignant breast tissues. Methods: A set of 44 formalin-fixed, paraffin-embedded breast tissue blocks were assessed from n=22 women at two time points: benign breast biopsy and subsequent DCIS or DCIS with invasive disease breast cancer. Blocks were scanned using the Bruker Skyscan 1276 microCT at a resolution of 10 µm. SkyScan analysis CTAn software was utilized to prepare and analyze morphological parameters and multiple MCs contained within each block were averaged. Paired morphological parameters were compared between the benign and subsequent cancer samples within women using Wilcoxon signed-rank tests. Results: Median age of patients was 53 years (range 37-77 years) at initial benign biopsy and developed breast cancer at median of 5.6 years (range: 2.3-12.8 years) later. The initial benign biopsies were for proliferative disease without atypia in the majority (59%), while 23% had non-proliferative lesions and 18% atypical hyperplasia. The average structural model index was consistent with a near rod-like shape (median 2.99, range: 2.71-3.29). Paired comparisons between benign and cancer blocks showed that the average surface area of MCs was significantly higher in the cancer samples (p=0.0467), as was the average volume of MCs (p=0.0298) (Table 1). Conclusions: Preliminarily, we demonstrate that microCT of routinely prepared pathology blocks of breast tissues may be useful in characterizing the 3-D morphometry of MCs with suggestive differences in benign and cancer tissues. Given that MCs are a sentinel radiologic marker of DCIS but are common in benign breast disease, developing improved approaches for classifying MCs may have value in breast cancer screening and management. Table 1. Comparison of MC parameters in biopsy tissues (IQR = Interquartile Range). Benign sample from women who later developed breast cancer Breast cancer after prior benign sample Paired Differences (Cancer - Benign) Wilcoxon signed-rank p value (N=22) (N=22) (N=22) Number of Objects (Median (IQR)) 43.5 (14, 789) 69.5 (33, 289) -6 (-139, 67) 0.6830 Average Surface Area (mm2)(Median (IQR)) 0.0225 (0.0134, 0.0393) 0.0342 (0.0185, 0.0656) 0.0113 (-0.0027, 0.0322) 0.0467 Average Volume (mm3) (Median (IQR)) 0.0003 (0.0001, 0.0007) 0.0007 (0.0003, 0.0022) 0.0003 (0.000002, 0.0020) 0.0298 Average Surface Area/Volume (mm−1)(Median (IQR)) 214.92 (162.25, 328.39) 199.55 (151.89, 230.52) -20.85 (-86.05, 27.04) 0.1433 Average Structural Thickness (mm)(Median (IQR)) 0.0341(0.0196, 0.0446) 0.0395 (0.0336, 0.0505) 0.0074 (-0.0062, 0.0153) 0.1173 Average Structural Model Index (Median (IQR)) 2.9758 (2.8465, 3.1175) 3.0026 (2.9281, 3.0927) 0.0075 (-0.1073, 0.1381) 0.7656 Citation Format: Sarah E. Schrup, Thomas de Bel, Tanya Hoskin, Teresa Allers, Stacey Winham, Derek Radisky, Laura Pacheco-Spann, Lisa Seymour, Amy Degnim, Mark Sherman. High resolution microCT to analyze the 3D morphology of microcalcifications in benign breast disease and breast cancer biopsy tissues. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3587.

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