M Luke Marinovich1, Daniela Bernardi2, Petra Macaskill3, Anna Ventriglia2, Vincenzo Sabatino2, Nehmat Houssami3. 1. Sydney School of Public Health, Sydney Medical School, Edward Ford Building (A27), The University of Sydney, NSW 2006, Australia. Electronic address: luke.marinovich@sydney.edu.au. 2. U.O. Senologia Clinica e Screening Mammografico, Dipartimento di Radiodiagnostica, APSS Trento, Italy. 3. Sydney School of Public Health, Sydney Medical School, Edward Ford Building (A27), The University of Sydney, NSW 2006, Australia.
Abstract
PURPOSE: Tomosynthesis is proposed to improve breast cancer assessment and staging. We compared tomosynthesis and mammography in estimating the size of newly-diagnosed breast cancers. METHODS: All pathologically-confirmed cancers detected in the STORM-2 trial (90 cancers, 85 women) were retrospectively measured on tomosynthesis by two independent readers. One reader also measured cancers on mammography. Relative mean differences (MDs) and 95% limits of agreement (LOA) with pathology were estimated for tomosynthesis and mammography within a single reader (Analysis 1) and between two readers (Analysis 2). RESULTS: Where cancers were detected and hence measured by both tests, tomosynthesis overestimated pathologic size relative to mammography (Analysis 1: MD 5% versus 1%, Analysis 2: 7% versus 3%; P = 0.10 both analyses). There was similar, large measurement variability for both tests (LOA range: -60% to +166%). Overestimation by tomosynthesis was attributable to the subgroup with dense breasts (MDs = 12-13% versus 4% for mammography). There was low average bias for both tests in the low-density subgroup (MDs = 0-4%). LOA were larger in dense breasts for both tomosynthesis and mammography (P ≤ 0.02 all comparisons). Cancers detected only by tomosynthesis were more frequently in dense breasts (60-68%): for those tumours size was estimated with increased measurement variability (LOA ranging from -75% to +293%). CONCLUSIONS: On average, tomosynthesis overestimates pathologic tumour size in women with dense breasts; that difference is more likely to impact management in women with larger tumours. The main advantage of tomosynthesis appears to be detecting mammographically-occult cancers; however tomosynthesis less accurately measured those cancers in dense breasts (large measurement variability).
PURPOSE: Tomosynthesis is proposed to improve breast cancer assessment and staging. We compared tomosynthesis and mammography in estimating the size of newly-diagnosed breast cancers. METHODS: All pathologically-confirmed cancers detected in the STORM-2 trial (90 cancers, 85 women) were retrospectively measured on tomosynthesis by two independent readers. One reader also measured cancers on mammography. Relative mean differences (MDs) and 95% limits of agreement (LOA) with pathology were estimated for tomosynthesis and mammography within a single reader (Analysis 1) and between two readers (Analysis 2). RESULTS: Where cancers were detected and hence measured by both tests, tomosynthesis overestimated pathologic size relative to mammography (Analysis 1: MD 5% versus 1%, Analysis 2: 7% versus 3%; P = 0.10 both analyses). There was similar, large measurement variability for both tests (LOA range: -60% to +166%). Overestimation by tomosynthesis was attributable to the subgroup with dense breasts (MDs = 12-13% versus 4% for mammography). There was low average bias for both tests in the low-density subgroup (MDs = 0-4%). LOA were larger in dense breasts for both tomosynthesis and mammography (P ≤ 0.02 all comparisons). Cancers detected only by tomosynthesis were more frequently in dense breasts (60-68%): for those tumours size was estimated with increased measurement variability (LOA ranging from -75% to +293%). CONCLUSIONS: On average, tomosynthesis overestimates pathologic tumour size in women with dense breasts; that difference is more likely to impact management in women with larger tumours. The main advantage of tomosynthesis appears to be detecting mammographically-occult cancers; however tomosynthesis less accurately measured those cancers in dense breasts (large measurement variability).
Authors: Saedeh Zamani; Mehdi Shafeie-Ardestani; Ahmad Bitarafan-Rajabi; Ali Khalaj; Omid Sabzevari Journal: IET Nanobiotechnol Date: 2020-09 Impact factor: 1.847