Micro-computed tomography (micro-CT) for intraoperative surgical margin assessment of breast cancer: A feasibility study in breast conserving surgery.

PURPOSE: Around 15%-30% of patients receiving breast-conserving surgery (BCS) for invasive breast carcinoma or ductal carcinoma in situ (DCIS) need a reoperation due to tumor-positive margins at final histopathology. Currently available intraoperative surgical margin assessment modalities all have specific limitations. Therefore, we aimed to assess the feasibility and accuracy of micro-computed tomography (micro-CT) as a novel method for intraoperative margin assessment in BCS. METHODS: Lumpectomy specimens from 30 consecutive patients diagnosed with invasive breast cancer or DCIS were imaged using a micro-CT. Margin status was assessed on micro-CT images by two investigators who were blinded to the final histopathological margin status. The micro-CT margin status was compared with the histopathological margin status. RESULTS: The margin status could be assessed by micro-CT in 29 out of 30 patients. Of these, nine patients had a positive tumor margin and 20 a negative tumor margin at final histopathology. Margin status evaluation by micro-CT took always less than 15 min. The margin status in 25 patients was correctly predicted by micro-CT. There were four false-negative predictions. The accuracy, sensitivity, specificity, positive predictive value and negative predictive value of micro-CT in margin status prediction were 86%, 56%, 100%, 100% and 83%, respectively. With micro-CT, the positive margin rate could potentially have been reduced from 31% to 14%. CONCLUSIONS: Whole lumpectomy specimen micro-CT scanning is a promising technique for intraoperative margin assessment in BCS. Intraoperative quick feedback on the margin status could potentially lead to a reduction in the number of reoperations.

[Targeted therapy: the benefit of new oncological tests]. / Therapie op maat: nut van nieuwe oncologische testen.

An increasing number of targeted drug treatments are becoming available for many types of cancer. There is a great need for adequate biomarkers that can predict the effect of targeted therapy in individual cancer patients, in order to determine the correct oncological treatment per patient. This way, non-effective treatments can be spared, side-effects avoided, and costs reduced. Oestrogen receptor (ER) and the human epidermal growth factor receptor 2 (HER2) are examples of standardized tests for breast cancer that have been validated in randomised studies. Data from randomised studies is also expected for gene expression profiles that correlate with tumour growth. Quantifying the predictive value of tests for anticipated treatment effects is costly and time-consuming. Given the increasing availability of targeted agents and diagnostic and prognostic techniques, alternative clinical study designs that can lead to quicker and more efficient verification are being sought in many different domains.