Jin Joo Kim1, Jin You Kim2, Hie Bum Suh1, Lee Hwangbo1, Nam Kyung Lee1, Suk Kim1, Ji Won Lee1, Ki Seok Choo3, Kyung Jin Nam3, Taewoo Kang4, Heeseung Park4. 1. Department of Radiology, Medical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine and Medical Research Institute, 1-10, Ami-Dong, Seo-gu, Busan, 602-739, Republic of Korea. 2. Department of Radiology, Medical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine and Medical Research Institute, 1-10, Ami-Dong, Seo-gu, Busan, 602-739, Republic of Korea. youdosa@naver.com. 3. Department of Radiology, Pusan National University Yangsan Hospital, Yangsan, Republic of Korea. 4. Busan Cancer Center, Pusan National University Hospital, Busan, Republic of Korea.
Abstract
OBJECTIVE: To investigate whether intratumoral heterogeneity, assessed via dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI), reflects the molecular subtypes of invasive breast cancers. MATERIAL AND METHODS: We retrospectively evaluated data from 248 consecutive women (mean age ± standard deviation, 54.6 ± 12.2 years) with invasive breast cancer who underwent preoperative DCE-MRI and DWI between 2019 and 2020. To evaluate intratumoral heterogeneity, kinetic heterogeneity (a measure of heterogeneity in the proportions of tumor pixels with delayed washout, plateau, and persistent components within a tumor) was assessed with DCE-MRI using a commercially available computer-aided diagnosis system. Apparent diffusion coefficients (ADCs) were obtained using a region-of-interest technique, and ADC heterogeneity was calculated using the following formula: (ADCmax-ADCmin)/ADCmean. Possible associations between imaging-based heterogeneity values and breast cancer subtypes were analyzed. RESULTS: Of the 248 invasive breast cancers, 61 (24.6%) were classified as luminal A, 130 (52.4%) as luminal B, 25 (10.1%) as HER2-enriched, and 32 (12.9%) as triple-negative breast cancer (TNBC). There were significant differences in the kinetic and ADC heterogeneity values among tumor subtypes (p < 0.001 and p = 0.023, respectively). The TNBC showed higher kinetic and ADC heterogeneity values, whereas the HER2-enriched subtype showed higher kinetic heterogeneity values compared to the luminal subtypes. Multivariate linear analysis showed that the HER2-enriched (p < 0.001) and TNBC subtypes (p < 0.001) were significantly associated with higher kinetic heterogeneity values. The TNBC subtype (p = 0.042) was also significantly associated with higher ADC heterogeneity values. CONCLUSIONS: Quantitative assessments of heterogeneity in enhancement kinetics and ADC values may provide biological clues regarding the molecular subtypes of breast cancer. KEY POINTS: • Higher kinetic heterogeneity was associated with HER2-enriched and triple-negative breast cancer. • Higher ADC heterogeneity was associated with triple-negative breast cancer. • Aggressive breast cancer subtypes exhibited higher intratumoral heterogeneity based on MRI.
OBJECTIVE: To investigate whether intratumoral heterogeneity, assessed via dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI), reflects the molecular subtypes of invasive breast cancers. MATERIAL AND METHODS: We retrospectively evaluated data from 248 consecutive women (mean age ± standard deviation, 54.6 ± 12.2 years) with invasive breast cancer who underwent preoperative DCE-MRI and DWI between 2019 and 2020. To evaluate intratumoral heterogeneity, kinetic heterogeneity (a measure of heterogeneity in the proportions of tumor pixels with delayed washout, plateau, and persistent components within a tumor) was assessed with DCE-MRI using a commercially available computer-aided diagnosis system. Apparent diffusion coefficients (ADCs) were obtained using a region-of-interest technique, and ADC heterogeneity was calculated using the following formula: (ADCmax-ADCmin)/ADCmean. Possible associations between imaging-based heterogeneity values and breast cancer subtypes were analyzed. RESULTS: Of the 248 invasive breast cancers, 61 (24.6%) were classified as luminal A, 130 (52.4%) as luminal B, 25 (10.1%) as HER2-enriched, and 32 (12.9%) as triple-negative breast cancer (TNBC). There were significant differences in the kinetic and ADC heterogeneity values among tumor subtypes (p < 0.001 and p = 0.023, respectively). The TNBC showed higher kinetic and ADC heterogeneity values, whereas the HER2-enriched subtype showed higher kinetic heterogeneity values compared to the luminal subtypes. Multivariate linear analysis showed that the HER2-enriched (p < 0.001) and TNBC subtypes (p < 0.001) were significantly associated with higher kinetic heterogeneity values. The TNBC subtype (p = 0.042) was also significantly associated with higher ADC heterogeneity values. CONCLUSIONS: Quantitative assessments of heterogeneity in enhancement kinetics and ADC values may provide biological clues regarding the molecular subtypes of breast cancer. KEY POINTS: • Higher kinetic heterogeneity was associated with HER2-enriched and triple-negative breast cancer. • Higher ADC heterogeneity was associated with triple-negative breast cancer. • Aggressive breast cancer subtypes exhibited higher intratumoral heterogeneity based on MRI.
Authors: C M Perou; T Sørlie; M B Eisen; M van de Rijn; S S Jeffrey; C A Rees; J R Pollack; D T Ross; H Johnsen; L A Akslen; O Fluge; A Pergamenschikov; C Williams; S X Zhu; P E Lønning; A L Børresen-Dale; P O Brown; D Botstein Journal: Nature Date: 2000-08-17 Impact factor: 49.962
Authors: M Höckel; C Knoop; K Schlenger; B Vorndran; E Baussmann; M Mitze; P G Knapstein; P Vaupel Journal: Radiother Oncol Date: 1993-01 Impact factor: 6.280
Authors: Jin You Kim; Jin Joo Kim; Lee Hwangbo; Hie Bum Suh; Suk Kim; Ki Seok Choo; Kyung Jin Nam; Taewoo Kang Journal: Radiology Date: 2020-03-31 Impact factor: 11.105