Abstract PS3-16: Identifying the most relevant descriptors when evaluating ultrasound images in breast cancer diagnostics: A secondary analysis of an international multicenter trial

Abstract

Abstract Background and objectives: The Breast Imaging Reporting and Data System (BI-RADS) provides a standardized way to describe ultrasound images in breast cancer diagnostics. However, there is little information which descriptors are most strongly associated with malignancy and to which extend the single descriptors (tissue composition, shape, orientation, margin of lesion, echo pattern, posterior features, and calcifications) should be considered for the final evaluation of risk of malignancy. Thus, we aimed to identify which BI-RADS descriptors are most strongly associated with malignancy when evaluating ultrasound images in breast cancer diagnostics. Methods: This multicenter, prospective trial took place at 11 trial sites in Austria, France, Germany, Japan, Netherlands, Portugal, and the US from February 2016 to March 2019. The trial enrolled 1288 women presenting with a lesion ≥0.5 and ≤5 cm in 2D B-mode ultrasound. The examiner conducted a routine 2D B-mode ultrasound examination and had additional standard information about the patients’ disease history and family history. The examiner described the ultrasound images according to BI-RADS. All patients underwent histopathological confirmation which was the gold standard against which the clinical examiner was compared. We performed univariate and multivariate analyses using descriptive statistics, Chi-Square test, and logistic regression to identify which image descriptors are associated with malignancy. Results: Histopathologic evaluation showed malignancy in 368 of 1288 lesions (28.6%). The descriptors most strongly associated with malignancy were spiculated margins (rate of malignancy 84.9%; 79 of 93), calcification (69.9%; 51 of 73), un-parallel orientation (65.9%; 187 of 284), angular margins (64.6%; 64 of 99), posterior shadowing (62.4%; 88 of 142), irregular shape (55.2%; 208 of 377), and indistinct margins (52.0%; 185 of 356). Different tissue compositions and echo patterns were least useful to distinguish between malign and benign lesions. Upon multivariate analysis, calcifications (OR 5.52; 95% CI 1.94-15.87) and posterior shadowing (OR 16.13; 95% CI 2.75-90.91) remained significantly (p<0.05) associated with malignancy. Conclusion: We identified which BI-RADS descriptors are most strongly associated with malignancy when evaluating ultrasound images in breast cancer diagnostics. Future research may look into providing not only a standardized image description but also a standardized final evaluation for the rate of malignancy with respect to the different predictive usefulness of the single descriptors. This may further standardize and objectify the risk evaluation in breast cancer diagnostics. Trial registration: NCT02638935 Table 1: Association of BI-RADS descriptors with final histopathologic resultsbenign pathologymalignant pathologyp-valuetissue compositionp<0.0001homogeneous background texture; fat —no. (%)185 (60.3)122 (39.74)homogeneous background texture; fibroglandular —no. (%)378 (77.3)111 (22.7)heterogeneous background texture —no. (%)356 (72.7)134 (27.4)shape of lesionp<0.0001oval —no. (%)659 (86.1)106 (13.8)round —no. (%)89 (62.7)53 (37.3)irregular —no. (%)169 (44.8)208 (55.2)orientation of lesionp<0.0001parallel —no. (%)806 (82.6)170 (17.42)not parallel —no. (%)97 (34.15)187 (65.9)margin of lesionp<0.0001circumcised —no. (%)644 (89.0)80 (11.0)indistinct margin —no. (%)171 (48.0)185 (52.0)angular margin —no. (%)35 (35.4)64 (64.6)microlobulated margin —no. (%)117 (60.0)78 (40.0)spiculated margin —no. (%)14 (15.1)79 (84.9)echo patternp=0.02anechoic —no. (%)7 (100)0 (0.0)hyperechoic —no. (%)30 (79.0)8 (21.0)complex cystic and solid —no. (%)52 (82.5)11 (17.5)hypoechoic —no. (%)645 (71.0)264 (29.0)isoechoic —no. (%)40 (78.4)11 (21.6)heterogeneous —no. (%)136 (64.8)74 (35.2)posterior featuresp<0.0001none —no. (%)590 (73.2)216 (26.8)enhancement —no. (%)249 (83.3)50 (16.7)shadowing —no. (%)53 (37.6)88 (62.4)combined pattern —no. (%)20 (58.8)14 (41.2)calcificationp<0.0001no calcification —no. (%)894 (73.8)317 (26.2)calcification —no. (%)22 (30.1)51 (69.9) Citation Format: André Pfob, Richard G. Barr, Volker Duda, Christopher Buesch, Joerg Heil, Michael Golatta. Identifying the most relevant descriptors when evaluating ultrasound images in breast cancer diagnostics: A secondary analysis of an international multicenter trial [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS3-16.