Radiology: Confronting misinterpretation can help breast cancer misdiagnosis on MR

Cancer not recognized at the time of imaging, related to a preaxillary location, in a 65-year-old menopausal woman with a history of left breast cancer treated by means of mastectomy. Transverse T2-weighted turbo spin-echo show small mass (arrow) in contact with vessels, not described on the prospective report. Source: Radiology (doi: 10.1148/radiol.12111917)

Nearly half of breast cancers seen at MRI had a potential observer error on a prior MRI study, resulting more from misinterpretation than from mismanagement or nonrecognition, based on a study published online April 20 in Radiology. Guidelines designed to decrease the rate of misinterpretation or mismanagement must be followed, according to study authors.

“Of all currently available breast imaging techniques, MR offers the highest sensitivity for both invasive and intraductal cancers,” wrote study authors Emmanuelle Bouic Pages, MD, and colleagues from the department of medical imaging at Centre Hospitalier Universitaire (CHU) Lapeyronie in Montpellier, France. Despite the high sensitivity, some breast cancers are overlooked with MRI, and the authors’ intention was to study rates of nonrecognition, misinterpretation or mismanagement to determine the cause.

Pages and colleagues conducted a retrospective evaluation of 58 pairs of MRI studies—one diagnostic study with a subsequent finding of cancer and a prior study without a diagnosis of cancer—which featured a total of 60 cancers. Prior images were analyzed to determine the rate of false-negatives, and all false-negatives were classified by cause.

Results showed that 47 percent of the cancers were initially not diagnosed, and were retrospectively diagnosed as grade 3, 4 or 5 lesions on the Breast Imaging Reporting and Data System. Ten percent of the lesions were unidentified, compared with 25 percent that were potentially misinterpreted and 12 percent that were mismanaged, meaning they were considered suspicious, but biopsy did not identify a malignancy.

“Our study highlights missed breast cancer may result, in part, from pitfalls in MR imaging interpretation,” wrote the study authors. They described the main causes of misinterpretation as the mass having smooth margins, stability in size and location of a nonmass in a postsurgical area, whereas mismanagement was mostly caused by inadequate correlations between MRI and ultrasonographic features.

The authors looked at some of the causes of misinterpretation and provided recommendations for avoiding them. Regarding smooth margins of a mass, they noted that this is indeed the most predictive feature of benignancy, but carcinomas have still been found in 17 percent of smooth margin masses. “We thus assumed that smooth margins shown on MR images need to be correlated with smooth margins at mammography or [ultrasound] before concluding that a lesion is benign,” they wrote.

Pages et al also said lesions should not be ignored because of their stability. Stability of the lesion for at least six months of follow-up was the main reason for error in three of the misinterpreted cases included in the study.

“The stability of proved breast cancer is a known paradigm,” wrote the authors. “It is mainly encountered in older patients, whereas high-risk younger patients have higher-doubling-time breast cancer. However, even in high-risk patients known to have more aggressive tumors, the lesion may remain stable.”

Ultrasound-guided biopsy is preferable to the more expensive and time consuming MRI-guided technique, but lesions seen on MRI can be seen with ultrasound in about half of patients. Knowing this, the authors wrote that it is important to ensure that findings between ultrasound and MRI correspond.

“Guidelines must therefore be carefully followed in biopsy guided by means of targeted [ultrasound] for lesions detected initially on MR images: clip placement and follow-up imaging of benign concordant results are recommended to detect cases in which the presumed US correlate is inaccurate to diagnose unsuspected false-negative biopsies.”