Abstract IA024: DCIS and MRI: Challenges translating MRI depiction of DCIS to improved clinical performance and future opportunities to optimize treatment
Authors: Rahbar Habib 
Published: December 2022

The value of breast MRI for DCIS detection and characterization remains highly debated. Though initially thought to be poor for DCIS detection, MRI is now well-established as the most superior imaging tool for DCIS detection and characterization. This is particularly true of high nuclear grade subtypes, possibly due MRI’s ability to not only reflect neovascularity but also basement membrane permeability. NMEs account for the majority of DCIS lesions identified on MRI and generally reflect a pathology growth pattern that extends along the milk ducts. Rarer presentations of DCIS as masses or foci may indicate a more indolent DCIS growth pattern that primarily expands rather than spreads along the milk ducts. DCIS exhibits variable semi-quantitative kinetic features, generally peaking later than invasive cancers and often resulting in medium initial phase and/or delayed phase persistent or plateau. The appearance of DCIS on diffusion weighted imaging and novel ultrafast sequences remains areas of active investigation. MRI is also more accurate than mammography at determining DCIS extent. Of nine studies published to date, eight concluded that MRI span is more accurate than mammographic span. However, the practical surgical benefit of this improved depiction of DCIS is less clear, with a meta-analysis and a recent systematic review showing no reduction in re-operation rate with preoperative MRI. Two more recent prospective multicenter trials (E4112 and IRCIS) and two newer retrospective studies have suggested that MRI may be associated with better surgical outcomes without increasing mastectomy rates. Still, there remains uncertainty in how MRI affects surgical management of DCIS. It is possible that MRI’s improved depiction of DCIS will only be of substantial clinical benefit when guiding future treatment de-escalation approaches to mitigate overtreatment, such as guiding multiple lumpectomies in lieu of mastectomies and/or omitting radiation therapy. Advances in artificial intelligence applied to radiological image features to develop and validate imaging biomarkers have created a major opportunity for MRI to assist with DCIS management by further illuminating lesion biology and heterogeneity. Prior studies have suggested that simple MRI features can correlate with basic pathologic features, such as nuclear grade, comedonecrosis, or ER positivity. MRI-based radiomic features have recently been shown to predict clinical outcomes such as ipsilateral breast recurrent for invasive cancers. Two pilots studies of DCIS and MRI radiomics demonstrated that quantitative parameters could predict nuclear grade and HER2 amplification and IBR. Preliminary data from the E4112 trial also has suggested that MRI radiomic features results in two distinct phenotypes that may have independent prognostic value. Future trials of DCIS should carefully standardize imaging approaches so that imaging markers can be developed and validated to improve DCIS management.

Citation Format: Habib Rahbar. DCIS and MRI: Challenges translating MRI depiction of DCIS to improved clinical performance and future opportunities to optimize treatment [abstract]. In: Proceedings of the AACR Special Conference on Rethinking DCIS: An Opportunity for Prevention?; 2022 Sep 8-11; Philadelphia, PA. Philadelphia (PA): AACR; Can Prev Res 2022;15(12 Suppl_1): Abstract nr IA024.