Histogram analysis and visual heterogeneity of diffusion-weighted imaging with apparent diffusion coefficient mapping in the prediction of molecular subtypes of invasive breast cancers Journal Article


Authors: Horvat, J. V.; Iyer, A.; Morris, E. A.; Apte, A.; Bernard-Davila, B.; Martinez, D. F.; Leithner, D.; Sutton, O. M.; Ochoa-Albiztegui, R. E.; Giri, D.; Pinker, K.; Thakur, S. B.
Article Title: Histogram analysis and visual heterogeneity of diffusion-weighted imaging with apparent diffusion coefficient mapping in the prediction of molecular subtypes of invasive breast cancers
Abstract: Objective. To investigate if histogram analysis and visually assessed heterogeneity of diffusion-weighted imaging (DWI) with apparent diffusion coefficient (ADC) mapping can predict molecular subtypes of invasive breast cancers. Materials and Methods. In this retrospective study, 91 patients with invasive breast carcinoma who underwent preoperative magnetic resonance imaging (MRI) with DWI at our institution were included. Two radiologists delineated a 2-D region of interest (ROI) on ADC maps in consensus. Tumors were also independently classified into low and high heterogeneity based on visual assessment of DWI. First-order statistics extracted through histogram analysis within the ROI of the ADC maps (mean, 10th percentile, 50th percentile, 90th percentile, standard deviation, kurtosis, and skewness) and visually assessed heterogeneity were evaluated for associations with tumor receptor status (ER, PR, and HER2 status) as well as molecular subtype. Results. HER2-positive lesions demonstrated significantly higher mean (p=0.034), Perc50 (p=0.046), and Perc90 (p=0.040), with AUCs of 0.605, 0.592, and 0.652, respectively, than HER2-negative lesions. No significant differences were found in the histogram values for ER and PR statuses. Neither quantitative histogram analysis based on ADC maps nor qualitative visual heterogeneity assessment of DWI images was able to significantly differentiate between molecular subtypes, i.e., luminal A versus all other subtypes (luminal B, HER2-enriched, and triple negative) combined, luminal A and B combined versus HER2-enriched and triple negative combined, and triple negative versus all other types combined. Conclusion. Histogram analysis and visual heterogeneity assessment cannot be used to differentiate molecular subtypes of invasive breast cancer. © 2019 Joao V. Horvat et al.
Keywords: adult; human tissue; aged; major clinical study; clinical feature; breast cancer; image analysis; epidermal growth factor receptor 2; retrospective study; prediction; radiologist; quantitative analysis; estrogen receptor; progesterone receptor; diffusion weighted imaging; tumor classification; histogram; tumor invasion; apparent diffusion coefficient; human; priority journal; article
Journal Title: Contrast Media and Molecular Imaging
Volume: 2019
ISSN: 1555-4309
Publisher: John Wiley & Sons  
Date Published: 2019-01-01
Start Page: 2972189
Language: English
DOI: 10.1155/2019/2972189
PUBMED: 31819738
PROVIDER: scopus
PMCID: PMC6893252
DOI/URL:
Notes: Article -- Export Date: 2 January 2020 -- Source: Scopus
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