Kasbi, Ali Abbaszadeh

Introduction Contiguous non-mass enhancement (NME) often coexists with a solid tumor component on MRI, but it can be challenging to predict whether NME represents invasive breast cancer, ductal carcinoma in situ (DCIS), benign disease, or biopsy site reaction. The purpose of this study was to determine the association between the size/extent of NME and the presence of invasive cancer and/or DCIS on final pathology. Methods This was a single institution retrospective analysis of a prospectively maintained breast cancer registry (2010-2020). Female patients who underwent surgical resection were included if they had a diagnosis of invasive breast cancer (with or without DCIS) and had an MRI showing both a solid mass and contiguous NME. The size of NME on MRI was compared with the size of invasive cancer and/or DCIS on the final pathology. Results From a total of 3443 patients, 225 patients were included. 86.2% had invasive ductal carcinoma (IDC), and 12.0% had invasive lobular carcinoma 76.9% were ER+, 16.4% were HER2+, and 13.3% were triple negative breast cancer (TNBC). 18.7% received neoadjuvant chemotherapy (NCT) of whom 31% achieved a complete radiographic/pathologic response. Pearson correlation coefficients (r) between the size of NME and invasive cancer/DCIS showed a strong and positive correlation of MRI NME with DCIS on pathology in patients without NCT. Subgroup analysis showed the strongest correlations for NME and DCIS among non-white (r = .70) and HER2 + patients (r = .74) who did not receive NCT. Conclusions Strong correlations between NME and DCIS were found for HER2 + disease and non-white patients, but only modest correlations were found for other patient/disease characteristics. These correlations may impact decisions in surgical approach.

The management of cancer has always relied heavily on the imaging modalities used to detect and monitor it. While many of these modalities have been around for decades, the technology surrounding them is always improving, and much has been discovered in recent years about the nature of tumors because of this. There have been several areas that have aided those discoveries. The use of artificial intelligence has already helped immensely in the quality of images taken but has not yet been widely implemented in clinical settings. Molecular imaging has proven to be useful in diagnosing different types of cancers based on the specificity of the probes/contrast agents used. Intravital imaging has already uncovered new information regarding the heterogeneity of the tumor vasculature. These three areas have provided a lot of useful information for the diagnosis and treatment of cancer, but further research and development in human trials is necessary to allow these techniques to fully utilize the information obtained thus far.