Background: Previous studies have indicated that quantitative MRI (qMR) is beneficial for diagnosis of breast cancer. As a novel qMR technology, synthetic MRI (syMRI) may be advantageous by offering simultaneous generation of T1 and T2 mapping in one scan within a few minutes and without concern to the deposition of the gadolinium contrast agent in cell nucleus. In this study, the potential of quantitative mapping derived from Synthetic MRI (SyMRI) to diagnose breast cancer was investigated. Methods: From April 2018 to May 2019, a total of 87 patients with suspicious breast lesions underwent both conventional and SyMRI before treatment. The quantitative metrics derived from SyMRI, including T1 and T2 values, were measured in breast lesions. The diagnostic performance of SyMRI was evaluated with unpaired Student’s t-tests, receiver operating characteristic curve analysis and multivariate logistic regression analysis. The AUCs of quantitative values were compared using Delong test. Results: Among 77 patients who met the inclusion criteria, 48 were diagnosed with histopathological confirmed breast cancers, and the rest had benign lesions. The breast cancers showed significantly higher T1 (1611.61 ± 215.88 ms) values and lower T2 (80.93 ± 7.51 ms) values than benign lesions. The area under the ROC curve (AUC) values were 0.931 (95% CI: 0.874–0.989) and 0.883 (95% CI: 0.810–0.956) for T1 and T2 maps, respectively, in diagnostic discrimination between breast cancers and benign lesions. A slightly increased AUC of 0.978 (95% CI: 0.915–0.993) was achieved by combining those two relaxation-based quantitative metrics. Conclusion: In conclusion, our preliminary study showed that the quantitative T1 and T2 values obtained by SyMRI could distinguish effectively between benign and malignant breast lesions, and T1 relaxation time showed the highest diagnostic efficiency. Furthermore, combining the two quantitative relaxation metrics further improved their diagnostic performance.

Since accurate grading of gliomas has important clinical value, the aim of this study is to evaluate the diagnostic efficacy of perfusion values derived from arterial spin labeling (ASL) to grade gliomas. In addition, the correlation between perfusion and isocitrate dehydrogenase 1 (IDH1) genotypes and chromosome arms 1p and 19q (1p/19q) status of gliomas was assessed. A total of 52 cases of supratentorial gliomas in adults who received ASL imaging were enrolled in this retrospective study. The cerebral blood flow (CBF) images derived from ASL and anatomical maps were normalized to the Montreal Neurological Institute coordinate system and matched. The mean CBF (meanCBF), the maximum CBF (maxCBF), and their relative values (rmeanCBF and rmaxCBF, respectively) were assessed in each case. The tumor grades, IDH1 genotypes, and 1p/19q status were diagnosed according to the 2016 WHO criteria. Receiver operating characteristic curves were performed to assess the efficacy of perfusion parameters for grading. Qualitatively, all gliomas were divided into high- and low-perfusion groups. The crosstabs chi-square test of independence was performed to calculate contingency coefficient (C) and Cramer V coefficient to assess the correlation between perfusion and IDH1 genotypes and 1p/19q status of gliomas. The rmaxCBF showed the best diagnostic efficacy; meanwhile, rmeanCBF had the best specificity for grade discrimination. In astrocytoma, there was a mild correlation between IDH1 genotypes and tumor perfusion with the Cramer's V coefficient of 0.378. There was no significant association between 1p/19q codeletion and perfusion in grade II and III gliomas.

Although high body mass index (BMI) was reported to associate with a better prognosis for metastatic renal cell cancer (mRCC) patients receiving anti-vascular endothelial growth factor (anti-VEGF) therapy, it is an imperfect proxy for the body composition, especially in Asian patients with a lower BMI. The role of visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), and perirenal fat thickness (PRFT) in mRCC patients was still unknown. Therefore, a multicenter retrospective study of 358 Chinese mRCC patients receiving anti-VEGF therapy was conducted and their body composition was measured via computed tomography. We parameterized VAT, SAT and PRFT according to their median value and BMI according to Chinese criteria (overweight: BMI ≥ 24). We found VAT, SAT, and PRFT (all p < 0.05) but not BMI, significantly associated with overall survival (OS) and progression-free survival (PFS). Multivariate Cox analysis identified PRFT was the independent predictor of OS and PFS, and IMDC expanded with PRFT showed the highest C-index in predicting OS (OS:0.71) compared with VAT, SAT, and BMI. PRFT could increase the area under the curve of the traditional International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) model in OS (70.54% increase to 74.71%) and PFS (72.22% increase to 75.03%). PRFT was introduced to improve the IMDC model and PRFT-modified IMDC demonstrated higher AIC in predicting OS and PFS compared with the traditional IMDC model. Gene sequencing analysis (n = 6) revealed that patients with high PRFT had increased angiogenesis gene signatures (NES = 1.46, p = 0.04) which might explain why better drug response to anti-VEGF therapy in mRCC patients with high PRFT. The main limitation is retrospective design. This study suggests body composition, especially PRFT, is significantly associated with prognosis in Chinese mRCC patients receiving anti-VEGF therapy. PRFT-modified IMDC model proposed in this study has better clinical predictive value.

Background: Field-of-view optimized and constrained undistorted single-shot imaging (FOCUS) is a new sequence that shows enhanced anatomical details, improving the diffusion-weighted (DW) images. Purpose: To investigate the value of FOCUS diffusion-weighted imaging (DWI) in the evaluation of nasopharyngeal carcinoma (NPC) and compare it with the single-shot echo planner imaging (SS-EPI) DWI approach. Material and Methods: A total of 87 patients with NPC underwent magnetic resonance imaging, including FOCUS and SS-EPI DWI sequences. The signal-to-noise ratio (SNR), signal-intensity ratio (SIR), contrast-to-noise ratio (CNR), and apparent diffusion coefficient (ADC) values of the nasopharyngeal lesions were measured and compared. According to the clinical stages of patients, T and N were divided into early and advanced stage groups, respectively. The mean ADC values of the two techniques were computed, and the area under the curve (AUC) was estimated to calculate the diagnostic efficiency. Results: Subjective and objective image qualitative values of FOCUS were significantly higher than those of SS-EPI. The ADC values for FOCUS of early T and N stages were significantly lower than those of the advanced stages. Conclusion: FOCUS provides significantly better image quality in NPC compared to SS-EPI, with lower ADC values for early-stage disease than late-stage disease.

Objectives: To determine the values of quantitative metrics derived from synthetic MRI (SyMRI) and apparent diffusion coefficient (ADC) in evaluating the prognostic factors of cervical carcinoma (CC). Methods: In this prospective study, 74 patients with pathologically confirmed CC were enrolled. Pretreatment quantitative metrics including T1, T2 and ADC values were obtained from SyMRI and diffusion-weighted imaging (DWI) sequences. The values of all metrics were compared for different prognostic features using Student’s t-test or Mann-Whitney U-test. The receiver operating characteristic (ROC) curve and multivariate logistic regression analysis were utilized to evaluate the diagnostic performance of quantitative variables. Results: T1 and T2 values of parametrial involvement (PMI)-negative were significantly higher than those of PMI-positive (p = 0.002 and < 0.001), while ADC values did not show a significant difference. The area under curve (AUC) of T1 and T2 values for identifying PMI were 0.743 and 0.831. Only the T2 values showed a significant difference between the lymphovascular space involvement (LVSI)-negative and LVSI-positive (p < 0.001), and the AUC of T2 values for discriminating LVSI was 0.814. The differences of T1, T2, and ADC values between the well/moderately and the poorly differentiated CC were significant (all p < 0.001). The AUCs of T1, T2 and ADC values for predicting differentiation grades were 0.762, 0.830, and 0.808. The combined model of all metrics proved to achieve good diagnostic performance with the AUC of 0.866. Conclusion: SyMRI may be a potential noninvasive tool for assessing the prognostic factors such as PMI, LVSI, and differentiation grades in CC. Moreover, the overall diagnostic performances of synthetic quantitative metrics were superior to the ADC values, especially in identifying PMI and LVSI. Advances in knowledge: This is the first study to assess the utility of SyMRI-derived parameters and ADC value in evaluating the prognostic factors in CC.