Predicting response to neoadjuvant chemotherapy in primary breast cancer using volumetric helical perfusion computed tomography: a preliminary study.

Autor: Li, Sonia, Makris, Andreas, Gogbashian, Andrew, Simcock, Ian, Stirling, J., Goh, Vicky
Předmět:
Zdroj: European Radiology; Sep2012, Vol. 22 Issue 9, p1871-1880, 10p, 2 Color Photographs, 1 Diagram, 5 Charts, 1 Graph
Abstrakt: Objectives: To investigate whether CT-derived vascular parameters in primary breast cancer predict complete pathological response (pCR) to neoadjuvant chemotherapy (NAC). Methods: Twenty prospective patients with primary breast cancer due for NAC underwent volumetric helical perfusion CT to derive whole tumour regional blood flow (BF), blood volume (BV) and flow extraction product (FE) by deconvolution analysis. A pCR was achieved if no residual invasive cancer was detectable on pathological examination. Relationships between baseline BF, BV, FE, tumour size and volume, and pCR were examined using the Mann-Whitney U test. Receiver operating characteristic (ROC) curve analysis was performed to assess the parameter best able to predict response. Intra- and inter-observer variability was assessed using Bland-Altman statistics. Results: Seventeen out of 20 patients completed NAC with four achieving a pCR. Baseline BF and FE were higher in patients who achieved a pCR compared with those who did not ( P = 0.032); tumour size and volume were not significantly different ( P > 0.05). ROC analysis revealed that BF and FE were able to identify responders effectively (AUC = 0.87; P = 0.03). There was good intra- and inter-observer agreement. Conclusions: Primary breast cancers which exhibited higher levels of perfusion before treatment were more likely to achieve a pCR to NAC. Key Points: • CT-derived vascular parameters may be useful in breast cancer treatment. • Perfusion CT can help predict response to neoadjuvant chemotherapy in breast cancer. • Baseline blood flow and flow extraction product are higher in complete pathological responders. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index