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To assess early changes in synthetic relaxometry after neoadjuvant chemotherapy (NAC) for breast cancer and establish a model with contrast-free quantitative parameters for early prediction of pathological response.From March 2019 to January 2021, breast MRI were performed for a primary cohort of women with breast cancer before (n = 102) and after the first (n = 93) and second (n = 90) cycle of NAC. Tumor size, synthetic relaxometry (T1/T2 relaxation time [T1/T2], proton density), and ADC were obtained, and the changes after treatment were calculated. Prediction models were established by multivariate logistic regression; evaluated with discrimination, calibration, and clinical application; and compared with Delong tests, net reclassification (NRI), and integrated discrimination index (IDI). External validation was performed from February to June 2021 with an independent cohort of 35 patients.In the primary cohort, all parameters changed after early treatment. Synthetic relaxometry decreased to a greater degree in major histologic responders (MHR, Miller-Payne G4-5) compared with non-MHR (Miller-Payne G1-3). A model combining ADC after treatment, changes in T1 and tumor size, and cancer subtype achieved the highest AUC after the first (primary/validation cohort, 0.83/0.82) and second cycles (primary/validation cohort, 0.85/0.84). No difference of AUC (p ≥ 0.27), NRI (p ≥ 0.31), and IDI (p ≥ 0.32) was found between models with different cycles and size-measured sequences. Model calibration and decision curves demonstrated a good fitness and clinical benefit, respectively.Early reduction in synthetic relaxometry indicated pathological response to NAC. Contrast-free T1 and ADC combined with size and cancer subtype predicted effectively pathological response after one NAC cycle.• Synthetic MRI relaxometry changed after early neoadjuvant chemotherapy, which demonstrated pathological response for mass-like breast cancers. • Contrast-free quantitative parameters including T1 relaxation time and apparent diffusion coefficient, combined with tumor size and cancer subtype, stratified major histologic responders. • A contrast-free model predicted an early pathological response after the first treatment cycle of neoadjuvant chemotherapy.

Objective: To examine the effects of the methylenetetrahydrofolate reductase ( MTHFR) and methionine synthase reductase ( MTRR) gene polymorphisms and their interactions with environmental factors on serum lipid levels. Methods: We investigated totally 340 patients with essential hypertension, from Dongzhi community, Anhui, China. High-throughput TaqMan allelic discrimination assay was used for the genotyping of MTHFR C677T ( Ala222Val), MTHFR A1298C ( Glu429Ala), MTRR A66G ( Ile22Met), and MTRR His595Tyr. Results: Compared with the MTRR 66AA genotype carriers, the GG genotype carriers had lower serum total cholesterol (TC) levels (adjusted β ± standard error [SE]: −0.5 ± 0.2 mmol/L; P = .003) and low-density lipoprotein cholesterol (LDL-C) levels (adjusted β ± SE: −0.4 ± 0.2 mmol/L; P = .005). Their false discovery rate (FDR)-adjusted P values were 0.056 and 0.056, respectively. We further found that there was a statistically significant interaction between 677TT genotype and sex in their associations with LDL levels ( P interaction = .020), and significant interaction between 677TT genotype and smoking on LDL levels ( P interaction = .036). A similar pattern of interaction was found between 66GG and drinking on levels of TC ( P interaction = .034) and LDL ( P interaction = .020). However, there were no significant interactions observed after FDR adjustment. Conclusion: Both MTHFR and MTRR gene polymorphisms could be important genetic determinants of serum lipid levels in Chinese patients with hypertension. These findings need to be replicated in a larger sample.