Assessment of the Spatial Heterogeneity of Breast Cancers: Associations Between Computed Tomography and Immunohistochemistry.

BACKGROUND: Tumour heterogeneity is considered an important mechanism of treatment failure. Imaging-based assessment of tumour heterogeneity is showing promise but the relationship between these mathematically derived measures and accepted 'gold standards' of tumour biology such as immunohistochemical measures is not established. METHODS: A total of 20 women with primary breast cancer underwent a research dynamic contrast-enhanced computed tomography prior to treatment with data being available for 15 of these. Texture analysis was performed of the primary tumours to extract 13 locoregional and global parameters. Immunohistochemical analysis associations were assessed by the Spearman rank correlation. RESULTS: Hypoxia-inducible factor-1α was correlated with first-order kurtosis (r = -0.533, P = .041) and higher order neighbourhood grey-tone difference matrix coarseness (r = 0.54, P = .038). Vascular maturity-related smooth muscle actin was correlated with higher order grey-level run-length long-run emphasis (r = -0.52, P = .047), fractal dimension (r = 0.613, P = .015), and lacunarity (r = -0.634, P = .011). Micro-vessel density, reflecting angiogenesis, was also associated with lacunarity (r = 0.547, P = .035). CONCLUSIONS: The associations suggest a biological basis for these image-based heterogeneity features and support the use of imaging, already part of standard care, for assessing intratumoural heterogeneity.

Arterial input functions in dynamic contrast-enhanced magnetic resonance imaging: which model performs best when assessing breast cancer response?

OBJECTIVE: To evaluate the performance of six models of population arterial input function (AIF) in the setting of primary breast cancer and neoadjuvant chemotherapy (NAC). The ability to fit patient dynamic contrast-enhanced MRI (DCE-MRI) data, provide physiological plausible data and detect pathological response was assessed. METHODS: Quantitative DCE-MRI parameters were calculated for 27 patients at baseline and after 2 cycles of NAC for 6 AIFs. Pathological complete response detection was compared with change in these parameters from a reproduction cohort of 12 patients using the Bland-Altman approach and receiver-operating characteristic analysis. RESULTS: There were fewer fit failures pre-NAC for all models, with the modified Fritz-Hansen having the fewest pre-NAC (3.6%) and post-NAC (18.8%), contrasting with the femoral artery AIF (19.4% and 43.3%, respectively). Median transfer constant values were greatest for the Weinmann function and also showed greatest reductions with treatment (-68%). Reproducibility (r) was the lowest for the Weinmann function (r = -49.7%), with other AIFs ranging from r = -27.8 to -39.2%. CONCLUSION: Using the best performing AIF is essential to maximize the utility of quantitative DCE-MRI parameters in predicting response to NAC treatment. Applying our criteria, the modified Fritz-Hansen and cosine bolus approximated Parker AIF models performed best. The Fritz-Hansen and biexponential approximated Parker AIFs performed less well, and the Weinmann and femoral artery AIFs are not recommended. ADVANCES IN KNOWLEDGE: We demonstrate that using the most appropriate AIF can aid successful prediction of response to NAC in breast cancer.

Magnetic Resonance Imaging, Digital Mammography, and Sonography: Tumor Characteristics and Tumor Biology in Primary Setting.

The use of imaging in the arena of primary treatment for breast cancer is gaining importance as a technique for assessing response to chemotherapy as well as assessing the underlying tumor biology. Both mammography and ultrasound have traditionally been used, in addition to clinical evaluation, to evaluate response to treatment although they have shed little light on the underlying biological processes. Functional magnetic resonance imaging techniques have the ability to assess response to treatments in addition to providing valuable information on changes in tumor perfusion, vascular permeability, oxygenation, cellularity, proliferation, and metabolism both at baseline and after treatment. This noninvasive method of evaluating cellular function is of importance both as endpoints for clinical trials and to our understanding of the biological mechanisms of cancer.

Assessing response in breast cancer with dynamic contrast-enhanced magnetic resonance imaging: are signal intensity-time curves adequate?

Quantitative DCE-MRI parameters including K(trans) (transfer constant min(-1)) can predict both response and outcome in breast cancer patients treated with neoadjuvant chemotherapy (NAC). Quantitative methods are time-consuming to calculate, requiring expensive software and interpretive expertise. For diagnostic purposes, signal intensity-time curves (SITCs) are used for tissue characterisation. In this study, we compare the ability of NAC-related changes in SITCs with K(trans) to predict response and outcomes. 73 women with primary breast cancer underwent DCE-MRI studies before and after two cycles of NAC. Patients received anthracycline and/or docetaxel-based chemotherapy. At completion of NAC, patients had local treatment with surgery & radiotherapy and further systemic treatments. SITCs for paired DCE-MRI studies were visually scored using a five-curve type classification schema encompassing wash-in and wash-out phases and correlated with K(trans) values and to the endpoints of pathological response, OS and DFS. 58 paired patients studies were evaluable. The median size by MRI measurement for 52 tumours was 38 mm (range 17-86 mm) at baseline and 26 mm (range 10-85 mm) after two cycles of NAC. Median baseline K(trans) (min(-1)) was 0.214 (range 0.085-0.469), and post-two cycles of NAC was 0.128 (range 0.013-0.603). SITC shapes were significantly related to K(trans) values both before (χ (2) = 43.3, P = 0.000) and after two cycles of NAC (χ (2) = 60.5, P = 0.000). Changes in curve shapes were significantly related to changes in K(trans) (χ (2) = 53.5, P = 0.000). Changes in curve shape were significantly correlated with clinical (P = 0.005) and pathological response (P = 0.005). Reductions in curve shape of ≥1 point were significant for overall improved survival using Kaplan-Meier analysis with a 5-year OS of 80.9 versus 68.6 % (P = 0.048). SITCs require no special software to generate and provide a useful method of assessing the effectiveness of NAC for primary breast cancer.

Biological dosimetry for breast cancer radiotherapy: a comparison of external beam and intraoperative radiotherapy.

PURPOSE: External beam radiotherapy (EBRT) is the gold standard adjuvant treatment after breast conserving surgery although a recent phase 3 trial has shown the non-inferiority of intraoperative radiotherapy (IORT). Radiation exposure of the heart and cardiac vessels causes an increase in morbidity and mortality following EBRT for breast cancer. We have used γ-H2AX foci formation in peripheral blood lymphocytes as a surrogate marker of dose delivered to the heart and great vessels and have assessed the feasibility of using this technique for biological dosimetry. METHODS: 34 patients were recruited, having either EBRT or IORT as part of a randomised controlled trial (TARGIT). Blood samples were taken prior to and after first fraction of radiotherapy, and the γ-H2AX biomarker then quantified. RESULTS: Data were available for 31 patients. Following TARGIT-IORT there was an increase of 0.203 foci per cell (range -1.436 to 1.275) compared with 0.935 foci per cell (range -0.679 to 2.216) in the EBRT group; this difference was highly significant (p = 0.009). As TARGIT-IORT treatment is completed with a single fraction, whilst EBRT requires at least 15 fractions, the actual difference is estimated to be many times more. CONCLUSIONS: These data show a significantly greater change in γ-H2AX foci number per cell following one fraction of EBRT compared to TARGIT-IORT. This is the first study to demonstrate this effect using a biomarker and demonstrates a proof of concept methodology for similar applications.