Imaging and Pathology of Ductal Carcinoma in Situ of the Breast: The Forest and the Trees

HomeRadiologyVol. 303, No. 2 PreviousNext Reviews and CommentaryFree AccessEditorialImaging and Pathology of Ductal Carcinoma in Situ of the Breast: The Forest and the TreesHabib Rahbar Habib Rahbar Author AffiliationsFrom the Department of Radiology, University of Washington, 1959 NE Pacific St, Box 357115, Seattle, WA 98195-7115.Address correspondence to the author (e-mail: [email protected]).Habib Rahbar Published Online:Feb 15 2022https://doi.org/10.1148/radiol.213292MoreSectionsPDF ToolsImage ViewerAdd to favoritesCiteTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinked In See also the article by Lee and Kim et al in this issue.Dr Habib Rahbar is an associate professor and vice chair of clinical operations in the Department of Radiology at the University of Washington. His primary research focus is on the use of breast MRI in detecting and characterizing ductal carcinoma in situ. He is a National Institutes of Health–funded principal investigator, a fellow of the Society of Breast Imaging, and cochair of the ECOG-ACRIN Radiomics Working Group.Download as PowerPointOpen in Image Viewer Ductal carcinoma in situ (DCIS) of the breast is considered to be the earliest form of breast cancer and is usually identified in women who are asymptomatic and present for screening. Although early detection of breast cancer remains a vital pillar of the medical success story of decreasing breast cancer mortality over the past 5 decades, DCIS also accounts for the most instances of breast cancer overdiagnosis. Breast cancer overdiagnosis is problematic because it leads to overtreatment. Overtreatments include the use of surgery and adjuvant therapies more appropriate for full-fledged invasive cancer than a nonlethal precursor (1).Part of the challenge in addressing DCIS overtreatment is it is generally treated as a single disease rather than what it is, which is a range of intraductal proliferations reflecting a spectrum of biologic potential and aggressiveness. To this end, individual DCIS lesions demonstrate substantial intralesional heterogeneity, with half composed of multiple nuclear grades within the same lesion (2). The inherent heterogeneity of individual DCIS lesions combined with the subjective and variable outcomes in nuclear grade characterization (3) and discrimination from related atypical lesions (4) by using limited sections of tissue highlights the daunting task our colleagues in the field of pathology face when diagnosing and characterizing DCIS. To make matters worse, up to a quarter of DCIS lesions diagnosed at core-needle biopsy (CNB) upstage to invasive cancer at surgical excision (5). Even surgical pathologic analysis is prone to sampling error: It is estimated that less than 0.2% of excised breast tissue in a lumpectomy is evaluated with standard-of-care pathologic analysis by using slides that consist of ultrathin tissue slices (6).The imprecise pathologic characterization of DCIS is problematic because nuclear grade, comedonecrosis, and hormone receptor positivity are the principal markers of aggressiveness and risk of recurrence that clinicians rely on to make treatment decisions. For example, an early report from the Low Risk DCIS, or LORIS, active surveillance trial of DCIS indicated that almost half (45 of 100) of potentially eligible patients had differing assessments of comedonecrosis, nuclear grade, and the presence of invasive disease between site and central levels (7), highlighting the challenge in identifying appropriate populations for whom DCIS treatment may be de-escalated (8). Whereas the problem of invasive breast cancer understaging in the setting of CNB-diagnosed DCIS is acknowledged and studied (5,9), the issue of imprecise DCIS nuclear grade assessment remains underappreciated. Each DCIS lesion is heterogeneous. Thus, a CNB-diagnosed DCIS lesion classified as low nuclear grade and considered an appropriate candidate for active surveillance may in fact consist of higher risk areas filled with intermediate to high nuclear grade DCIS because of sampling error.In this issue of Radiology (10), Lee and Kim et al aim to develop a predictive model by using conventional (mammography and US) imaging features to help increase the confidence of DCIS nuclear grade assessments at CNB. By using a single institution data set of 470 women with 477 pure DCIS lesions (ie, no presence of invasive disease at final excision), an expert breast imaging radiologist who was blinded to outcomes retrospectively characterized all lesions into one of five categories on the basis of the qualitative US and mammographic features. The authors then divided the patients into training and validation sets and evaluated whether these imaging categories, alone or in combination with clinical and pathologic features, could be used to confirm the presence of purely low nuclear grade DCIS and to exclude upgrade to higher nuclear grade assessment at surgical excision.Remarkably, the authors found that almost four in 10 low nuclear grade DCIS lesions diagnosed at CNB were upgraded to a higher nuclear grade lesion at surgical excision, underscoring the challenge of relying on CNB pathologic features alone to stratify DCIS risk. They also found that lesions manifesting as a mass at US without mammographic calcifications and no comedonecrosis at CNB were much more likely to represent low nuclear grade DCIS, and the validation set demonstrated high diagnostic performance (area under receiver operating characteristic curve [AUC], 0.97). This is exciting because it could provide patients who are considering active surveillance approaches more reassurance that their DCIS lesions are low risk and may be monitored rather than excised. These features could also be integrated into active surveillance trials to increase certainty about appropriate patient selection.Toward the ultimate goal of reducing overdiagnosis of low-risk DCIS, the authors also assessed the value of imaging features alone without CNB information to identify low nuclear grade DCIS lesions that might avoid biopsy altogether, which resulted in a lower but still impressive performance (AUC, 0.87). Finally, they explored the ability of imaging and pathologic features to help predict which DCIS lesions diagnosed at CNB will upgrade to higher nuclear grade lesions at surgery. They found that lesion size, presence of comedonecrosis, and Ki-67 positivity were associated with nuclear grade upstaging at surgery.There are some important limitations worth emphasizing. The study is from a single institution that includes both mammographic and US information. As the authors acknowledge, many sites do not routinely use US in evaluation of DCIS lesions, which limits clinical translation. In addition, the study does not leverage the value of DCIS characterization at breast MRI. Breast MRI has the potential to further refine DCIS risk assessments and help identify a distinct subset of biologically active DCIS independent from nuclear grade and other pathologic analysis–based assessments because of its ability to reflect angiogenesis (1). Qualitative imaging feature categorization was performed by a single expert radiologist familiar with appearance of DCIS at US and mammography; it thus remains unclear if these categorizations are reproducible. Finally, the study relies on an imperfect reference standard of surgical excision assessment of nuclear grade.This study also underscores a truth about the pathologic evaluation of DCIS and the supportive role imaging can play that remains underrecognized. Current standard-of-care pathologic evaluation of breast lesions is limited because it reflects small samples of otherwise heterogeneous lesions. This point is illustrated by the fact that so many low nuclear grade DCIS lesions diagnosed at CNB were upgraded to a higher nuclear grade at excision. The study also suggests that imaging features can provide large-scale information of the entirety of a DCIS lesion complementary to the microscopic pathologic assessment to allow for improved radiology-pathology concordance. To adapt a common expression, imaging can provide the perspective of the whole forest whereas pathologic analysis provides the details of a few trees. Both perspectives will likely prove essential for optimal DCIS risk stratification, yet the imaging perspective remains underappreciated by clinicians and radiologists alike. To this end, reduction of DCIS overdiagnosis and overtreatment will indeed hinge on the ability of imaging to provide greater certainty that the pathologic features of a few DCIS "trees" provide an accurate representation of the whole "forest."As breast imaging radiologists look to help our oncology specialists optimize DCIS management (8), it will become ever more important to recognize that within a given radiologic image, there is information beyond a Breast Imaging Reporting and Data System assessment and recommendation indicating whether or not a biopsy should be performed. Indeed, there is also prognostic information embedded across various breast imaging modalities that will likely only be fully realized when automated quantitative approaches leveraging advanced radiomics and artificial intelligence are used. The breast oncology community would be well served to consider this untapped potential as clinical trials are designed to address this controversial disease. In particular, the development of well-annotated multimodality imaging repositories linked to pathologic and clinical outcomes should be a priority.Disclosures of Conflicts of Interest: H.R. No relevant relationships.H.R. supported by grants From the National Institutes of Health/National Cancer Institute (R01CA203883) and GE Healthcare.References1. Kuhl CK. Let us move out of plato’s cave: the greater reality of DCIS. Radiology 2021;301(1):78–80. Google Scholar2. Miller NA, Chapman JA, Fish EB, et al. In situ duct carcinoma of the breast: clinical and histopathologic factors and association with recurrent carcinoma. Breast J 2001;7(5):292–302. Crossref, Medline, Google Scholar3. van Seijen M, Jóźwiak K, Pinder SE, et al. Variability in grading of ductal carcinoma in situ among an international group of pathologists. J Pathol Clin Res 2021;7(3):233–242. Crossref, Medline, Google Scholar4. Van Bockstal MR, Berlière M, Duhoux FP, Galant C. interobserver variability in ductal carcinoma in situ of the breast. Am J Clin Pathol 2020;154(5):596–609. Crossref, Medline, Google Scholar5. Grimm LJ, Rahbar H, Abdelmalak M, Hall AH, Ryser MD. Ductal carcinoma in situ: state-of-the-art review. Radiology 2021.10.1148/radiol.211839. Published online December 21, 2021. Google Scholar6. Clarke GM, Peressotti C, Constantinou P, Hosseinzadeh D, Martel A, Yaffe MJ. Increasing specimen coverage using digital whole-mount breast pathology: implementation, clinical feasibility and application in research. Comput Med Imaging Graph 2011;35(7-8):531–541. Crossref, Medline, Google Scholar7. Thomas J, Hanby A, Pinder S, et al. Abstract P3-17-06: LORIS trial of active monitoring for DCIS: how does the online pathology eligibility review process work? Cancer Res 2017;77(4 Supplement):P3-17–06. Google Scholar8. Wright JL, Rahbar H, Obeng-Gyasi S, Carlos R, Tjoe J, Wolff AC. Overcoming barriers in ductal carcinoma in situ management: from overtreatment to optimal treatment. J Clin Oncol 2022;40(3):225–230. Crossref, Medline, Google Scholar9. Meurs CJC, van Rosmalen J, Menke-Pluijmers MBE, et al. A prediction model for underestimation of invasive breast cancer after a biopsy diagnosis of ductal carcinoma in situ: based on 2892 biopsies and 589 invasive cancers. Br J Cancer 2018;119(9):1155–1162. Crossref, Medline, Google Scholar10. Lee SE, Kim GR, Han K, et al. US, mammography, and histopathologic evaluation to identify low nuclear grade ductal carcinoma in situ. Radiology 2022;303(2):276–284. Abstract, Google ScholarArticle HistoryReceived: Dec 28 2021Revision requested: Jan 12 2022Revision received: Jan 12 2022Accepted: Jan 18 2022Published online: Feb 15 2022Published in print: May 2022 FiguresReferencesRelatedDetailsAccompanying This ArticleUS, Mammography, and Histopathologic Evaluation to Identify Low Nuclear Grade Ductal Carcinoma in SituFeb 15 2022RadiologyRecommended Articles Long-term Surveillance of Ductal Carcinoma in Situ Detected with Screening Mammography versus US: Factors Associated with Second Breast CancerRadiology2019Volume: 292Issue: 1pp. 37-48Ductal Carcinoma in Situ: State-of-the-Art ReviewRadiology2021Volume: 302Issue: 2pp. 246-255Impact of Preoperative Breast MR Imaging and MR-guided Surgery on Diagnosis and Surgical Outcome of Women with Invasive Breast Cancer with and without DCIS ComponentRadiology2017Volume: 284Issue: 3pp. 645-655US, Mammography, and Histopathologic Evaluation to Identify Low Nuclear Grade Ductal Carcinoma in SituRadiology2022Volume: 303Issue: 2pp. 276-284Breast Cancers Detected at Screening MR Imaging and Mammography in Patients at High Risk: Method of Detection Reflects Tumor Histopathologic ResultsRadiology2016Volume: 280Issue: 3pp. 716-722See More RSNA Education Exhibits The Imaging of Ductal Carcinoma in SITU - Where It Is and Where It's GoingDigital Posters2022How to Recognize Ductal Carcinoma in SITU: Tips for New ResidentsDigital Posters2020Multimodality Imaging Findings of Low-Grade DCIS: Should Biopsy Be Performed in Low-Grade DCIS?Digital Posters2020 RSNA Case Collection Ductal Carcinoma In SituRSNA Case Collection2022Breast nodular FasciitisRSNA Case Collection2022Invasive Papillary CarcinomaRSNA Case Collection2020 Vol. 303, No. 2 Metrics Altmetric Score PDF download