Caracterización de cánceres de mama sintomáticos invisibles en mamografía digital y tomosíntesis: correlación radiopatológica / Characterization of invisible breast cancers in digital mammography and tomosynthesis: radio-pathological correlation

Objetivo. Revisar las características radiopatológicas de carcinomas mamarios sintomáticos ocultos en mamografía digital (MD) y tomosíntesis (TS). Material y métodos. Análisis retrospectivo de 169 lesiones provenientes de pacientes sintomáticas con diagnóstico histológico de cáncer de mama y que fueron estudiadas con MD, TS, ecografía y resonancia magnética (RM). Se identificaron las lesiones ocultas (falsos negativos verdaderos) en MD y TS. Se analizaron datos clínicos, de densidad, los hallazgos con ecografía y RM, y la histopatología de las lesiones. Resultados. Se detectaron siete lesiones neoplásicas ocultas en MD y TS. El 57% (4/7) se presentó en mamas densas (tipo c y d), y las restantes en mamas de densidad b. Se identificaron seis de los carcinomas por ecografía y RM (masas BI-RADS 4); la lesión restante solo se visualizó en RM. En el 57% de las neoplasias, el tamaño medido con RM fue mayor de 3cm. Todas fueron carcinomas ductales infiltrantes, seis de ellos con alta proporción estromal. En cuanto a los subtipos moleculares, solo una fue triple negativo y las demás fueron de tipo luminal. Se analizaron los márgenes tumorales de dos carcinomas intervenidos sin quimioterapia previa, y ambos presentaban márgenes que desplazaban sin infiltrar el parénquima adyacente. Conclusión. Los carcinomas ocultos en MD y TS representaron el 4% de las lesiones detectadas en pacientes sintomáticas, fueron mayoritariamente masas, todas tuvieron diagnóstico de carcinoma ductal infiltrante (con predominio del inmunofenotipo luminal) y se detectaron en mamas de densidad tipo b, c y d (AU)

Objective. To review the radio-pathologic features of symptomatic breast cancers not detected at digital mammography (DM) and digital breast tomosynthesis (DBT). Material and methods. Retrospective analysis of 169 lesions from symptomatic patients with breast cancer that were studied with DM, DBT, ultrasound (US) and magnetic resonance (MR). We identified occult lesions (true false negatives) in DM and DBT. Clinical data, density, US and MR findings were analyzed as well as histopathological results. Results. We identified seven occult lesions in DM and DBT. 57% (4/7) of the lesions were identified in high-density breasts (type c and d), and the rest of them in breasts of density type b. Six carcinomas were identified at US and MR (BI-RADS 4 masses); the remaining lesion was only identified at MR. The tumor size was larger than 3cm at MRI in 57% of the lesions. All tumors were ductal infiltrating carcinomas, six of them with high stromal proportion. According to molecular classification, we found only one triple-negative breast cancer, the other lesions were luminal-type. We analyzed the tumor margins of two resected carcinomas that were not treated with neoadjuvant chemotherapy, both lesions presented margins that displaced the adjacent parenchyma without infiltrating it. Conclusion. Occult breast carcinomas in DM and DBT accounted for 4% of lesions detected in patients with symptoms. They were mostly masses, all of them presented the diagnosis of infiltrating ductal carcinoma (with predominance of the luminal immunophenotype) and were detected in breasts of density type b, c and d (AU)

Characterization of invisible breast cancers in digital mammography and tomosynthesis: radio-pathological correlation. / Caracterización de cánceres de mama sintomáticos invisibles en mamografía digital y tomosíntesis: correlación radiopatológica.

OBJECTIVE: To review the radio-pathologic features of symptomatic breast cancers not detected at digital mammography (DM) and digital breast tomosynthesis (DBT). MATERIAL AND METHODS: Retrospective analysis of 169 lesions from symptomatic patients with breast cancer that were studied with DM, DBT, ultrasound (US) and magnetic resonance (MR). We identified occult lesions (true false negatives) in DM and DBT. Clinical data, density, US and MR findings were analyzed as well as histopathological results. RESULTS: We identified seven occult lesions in DM and DBT. 57% (4/7) of the lesions were identified in high-density breasts (type c and d), and the rest of them in breasts of density type b. Six carcinomas were identified at US and MR (BI-RADS 4 masses); the remaining lesion was only identified at MR. The tumor size was larger than 3cm at MRI in 57% of the lesions. All tumors were ductal infiltrating carcinomas, six of them with high stromal proportion. According to molecular classification, we found only one triple-negative breast cancer, the other lesions were luminal-type. We analyzed the tumor margins of two resected carcinomas that were not treated with neoadjuvant chemotherapy, both lesions presented margins that displaced the adjacent parenchyma without infiltrating it. CONCLUSION: Occult breast carcinomas in DM and DBT accounted for 4% of lesions detected in patients with symptoms. They were mostly masses, all of them presented the diagnosis of infiltrating ductal carcinoma (with predominance of the luminal immunophenotype) and were detected in breasts of density type b, c and d.

Impacto de la densidad mamaria mamográfica en el funcionamiento de un sistema de detección asistido por ordenador en una unidad de patología mamaria / Impact of mammographic breast density on computer-assisted detection (CAD) in a breast imaging department

Objetivo. Evaluar si la densidad mamaria influye en la sensibilidad (global y por marcas) para la detección del cáncer de mama de un sistema de detección asistido por ordenador (CAD). Materiales y métodos. Estudio prospectivo de 8.750 mamografías digitales con un sistema CAD asociado. Se clasificaron las densidades mamarias según los criterios BI-RADS. Calculamos la sensibilidad global del radiólogo y del CAD, la sensibilidad por proyección, por hallazgo, en relación con la densidad mamográfica y analizamos los carcinomas de intervalo. Para el análisis estadístico utilizamos el programa SPSS vs 11. Resultados. Sensibilidad global del CAD 88,5% IC del 95% (IC95% 83,2-92,7%), sensibilidad del radiólogo 93,5% IC95% (84,4-95,5%), sensibilidad de la proyección craneocaudal 81,6% IC95% (76,5-90,7%) vs 76,5% IC95% (69,3-89,3%) para oblicuomediolateral, sensibilidad para microcalcificaciones 98,6% IC95% (96,5-99,7%), sensibilidad de marca masa 83,4% IC95% (81,2-91,7%). Detectamos discrepancias menores del 20% tanto para las microcalcificaciones presentes en los 4 tipos de densidades como para las masas con densidades 1 y 2; mientras en las masas con densidad 3 la discrepancia fue 20,8% y en la 4 fue 55%. El CAD solo dejó de marcar el 9,1% (9/94) de los cánceres diagnosticados como masas propiamente dichas. El 50% de los carcinomas de intervalo se produjo en densidad tipo 4 y el 75% se manifestaron como masas, asimetrías y distorsiones. El 35,7% de los carcinomas de intervalo fueron marcados previamente por el CAD. Conclusiones. La sensibilidad fue mayor en la proyección craneocaudal pero no significativamente. La sensibilidad del CAD fue alta para microcalcificaciones presentes en los 4 tipos de densidades, sin embargo, para la marca masa fue baja en densidades 3 y 4. El CAD sólo dejó de marcar el 9,1% de los cánceres diagnosticados como masas propiamente dichas pero fue muy poco sensible para los otros 2 hallazgos radiológicos incluidos en esta marca. El 50% de los carcinomas de intervalo se produjeron en densidades tipo 4 y el 35,7% fueron marcados previamente por el sistema de detección asistido por ordenador (AU)

Objective. To evaluate whether breast density influences the sensitivity of a computer-assisted detection (CAD) system for the detection of breast cancer. Material and methods. We prospectively studied 8750 digital mammograms with an associated CAD system. We used BI-RADS criteria to classify breast density. We calculated the overall sensitivity of the radiologist and of the CAD system, as well as the sensitivity for each projection and type of finding in relation to the mammographic density of the breast. Finally, we analyzed the interval carcinomas. We used SPSS 11 for all statistical analyses. Results. The overall sensitivity of the CAD system was 88.5% (95% CI: 83.2-92.7%), and the overall sensitivity of the radiologist was 93.5% (95% CI: 84.4%-95.5%). The sensitivity of the craniocaudal view was 81.6% (95% CI: 76.5-90.7%) vs 76.5% (95% CI: 69.3-89.3%) for the mediolateral oblique view. The sensitivity for microcalcifications was 98.6% (95% CI: 96.5-99.7%), and the sensitivity for masses 83.4% (95% CI: 81.2-91.7%). We detected discrepancies smaller than 20% both for microcalcifications present in the four types of densities and for masses with densities 1 and 2. In masses with density 3 the discrepancy was 20.8% and in those with density 4 it was 55%. The CAD system failed to mark only 9.1% (9/94) of the cancers presenting as masses. Half of the interval carcinomas were found in type 4 density and 75% manifested as masses, asymmetries, and distortions. The CAD system had marked 35.7% of the carcinomas. Conclusions. The craniocaudal view was more sensitive, although this difference was not statistically significant. The sensitivity of CAD was high for microcalcifications in all four density types; however, CAD's sensitivity for masses was low in density types 3 and 4. The CAD system only failed to mark 9.1% of the cancers presenting as masses but was not sensitive for the other two radiological findings included in this marking. Half of the interval carcinomas occurred in type 4 densities and 35.7% had been marked by the CAD sysem (AU)

[Impact of mammographic breast density on computer-assisted detection (CAD) in a breast imaging department]. / Impacto de la densidad mamaria mamográfica en el funcionamiento de un sistema de detección asistido por ordenador en una unidad de patología mamaria.

OBJECTIVE: To evaluate whether breast density influences the sensitivity of a computer-assisted detection (CAD) system for the detection of breast cancer. MATERIAL AND METHODS: We prospectively studied 8750 digital mammograms with an associated CAD system. We used BI-RADS criteria to classify breast density. We calculated the overall sensitivity of the radiologist and of the CAD system, as well as the sensitivity for each projection and type of finding in relation to the mammographic density of the breast. Finally, we analyzed the interval carcinomas. We used SPSS 11 for all statistical analyses. RESULTS: The overall sensitivity of the CAD system was 88.5% (95% CI: 83.2-92.7%), and the overall sensitivity of the radiologist was 93.5% (95% CI: 84.4%-95.5%). The sensitivity of the craniocaudal view was 81.6% (95% CI: 76.5-90.7%) vs 76.5% (95% CI: 69.3-89.3%) for the mediolateral oblique view. The sensitivity for microcalcifications was 98.6% (95% CI: 96.5-99.7%), and the sensitivity for masses 83.4% (95% CI: 81.2-91.7%). We detected discrepancies smaller than 20% both for microcalcifications present in the four types of densities and for masses with densities 1 and 2. In masses with density 3 the discrepancy was 20.8% and in those with density 4 it was 55%. The CAD system failed to mark only 9.1% (9/94) of the cancers presenting as masses. Half of the interval carcinomas were found in type 4 density and 75% manifested as masses, asymmetries, and distortions. The CAD system had marked 35.7% of the carcinomas. CONCLUSIONS: The craniocaudal view was more sensitive, although this difference was not statistically significant. The sensitivity of CAD was high for microcalcifications in all four density types; however, CAD's sensitivity for masses was low in density types 3 and 4. The CAD system only failed to mark 9.1% of the cancers presenting as masses but was not sensitive for the other two radiological findings included in this marking. Half of the interval carcinomas occurred in type 4 densities and 35.7% had been marked by the CAD system.