Magnetic resonance imaging tumor regression shrinkage patterns after neoadjuvant chemotherapy in patients with locally advanced breast cancer: correlation with tumor biological subtypes and pathological response after therapy

The objective of this study is to analyze magnetic resonance imaging shrinkage pattern of tumor regression after neoadjuvant chemotherapy and to evaluate its relationship with biological subtypes and pathological response. We reviewed the magnetic resonance imaging studies of 51 patients with single mass-enhancing lesions (performed at time 0 and at the II and last cycles of neoadjuvant chemotherapy). Tumors were classified as Luminal A, Luminal B, HER2+, and Triple Negative based on biological and immunohistochemical analysis after core needle biopsy. We classified shrinkage pattern, based on tumor regression morphology on magnetic resonance imaging at the II cycle, as concentric, nodular, and mixed. We assigned a numeric score (0: none; 1: low; 2: medium; 3: high) to the enhancement intensity decrease. Pathological response on the surgical specimen was classified as complete (grade 5), partial (grades 4-3), and non-response (grades 1-2) according to Miller and Payne system. Fisher test was used to relate shrinkage pattern with biological subtypes and final pathological response. Seventeen patients achieved complete response, 25 partial response, and 9 non-response. A total of 13 lesions showed nodular pattern, 20 concentric, and 18 mixed. We found an association between concentric pattern and HER2+ (p < 0.001) and mixed pattern and Luminal A lesions (p < 0.001). We observed a statistical significant correlation between concentric pattern and complete response (p < 0.001) and between mixed pattern and non-response (p = 0.005). Enhancement intensity decrease 3 was associated with complete response (p < 0.001). Shrinkage pattern and enhancement intensity decrease may serve as early response indicators after neoadjuvant chemotherapy. Shrinkage pattern correlates with tumor biological subtypes

Role of galectin-3 combined with multi-detector contrast enhanced computed tomography in predicting disease recurrence in patients with ovarian cancer

Galectin-3 (Gal-3) is an endogenous β-galactoside-binding lectin, playing an important role in the pathogenesis of multiple malignancies. Aim of the study was to evaluate in a group of patients treated for ovarian cancer (EOC), the role of Gal-3 combined with multi-detector contrast-enhanced computed tomography (MDCT), as predictor of recurrence disease. Seventeen follow-up patients with recurrent ovarian cancer and 13 follow-up patients with stable ovarian disease, who performed MDCT at one-year follow-up after cytoreductive treatment, were enrolled. Serum Gal-3 concentrations were determined by using ELISA method. Twenty healthy controls were included in the analysis. Two radiologist blinded to patients status, reviewed MDCT exams, recording the following signs of disease recurrence: local tumor spread, enlarged lymph-nodes, carcinomatosis implants and metastases. We calculated the respective threshold values of Gal- 3 identified by ROC curve analysis for each imaging findings related to disease recurrence : lymphoadenopathies 92.45 ng/ml (AUC: 0.81, Se=91% Spe=73%), carcinomatosis 85.95 ng/ml (AUC:0.93 Se= 93.7%, Spe=92.8%), local tumor spread 99.05 (AUC:0.90, Se=100%, Spe=73% ) and metastasis 99.05ng/ml (AUC :0,78, Se=100% , Spe=70%). A significant correlation between high Gal-3 serum levels and presence of local tumor spread (n=11/17, p:0.001), carcinomatosis (n=16/17, p:0.00), lymphoadenopathies (n=15/17, p:0.00) and metastasis (n=11/17, p:0.003) related with recurrence disease was observed. Patients with recurrence of ovarian cancer presents higher Gal-3 values compared to women with stable diseases. Gal-3 combined to CECT should be used to improve the monitoring of EOC patients

Endometriosis: 10 keys points for MRI

Endometriosis is a chronic disease and a clinical problem in women of fertile age, with a high impact on quality of life, work productivity and health care management. Two imaging modalities are employed in the diagnosis and evaluation of extent of disease: ultrasound examination with endovaginal approach and magnetic resonance imaging (MRI). MRI, thanks to its high contrast and resolution characteristics, offers a high level of accuracy in the study of endometriosis and adenomyosis. We illustrate here 10 key MRI points for the detection and diagnosis of endometriosis

[A statistical evaluation of the variability in the measurements of the resistive index in kidney transplantation].

Doppler ultrasound (US) is a valuable tool to measure blood flow in the transplanted kidney, but its operator-dependence can greatly affect repeatability and reproducibility of measurements. Aim of this work was to evaluate intraobserver and interobserver variability in measuring the resistive index (RI) in renal transplants. Ten renal transplant recipients were randomly selected among those undergoing follow-up and examined by two operators (FG and LB) with 3.5 MHz and 10 MHz scanheads to assess the variability of RI measurements. Each observer obtained two measurements of the RI with each scanhead within a 10-15 minutes' period. In all, 80 measurements were made, 4 per patient per observer. The statistical analysis included two-tailed Student's t-test for paired data and calculation of repeatability/reproducibility coefficients. Student's t-test analysis demonstrated a statistically significant difference (p = 0.037) between the means of the first and second measurements by FG with the 3.5 MHz scanhead and the first and the second measurements by LB with the same scanhead. Differences between the other means were not statistically significant. Intraobserver variability ranged 0.03 units (or 2.07%) and 0.07 units (or 4.24%), while interobserver variability was 0.04 units with both 3.5 and 10 MHz scanheads, or 3.61 and 3.73%, respectively. Doppler US of renal transplants has statistically quantifiable operator-dependent variability: the possible evidence of statistically significant differences can be minimized by having the same operator make the measurements. However, RI variations ranging 0.02 to 0.04 units should not be considered significant