Multicontrast MRI-based radiomics for the prediction of pathological complete response to neoadjuvant chemotherapy in patients with early triple negative breast cancer.

INTRODUCTION: To assess pre-therapeutic MRI-based radiomic analysis to predict the pathological complete response to neoadjuvant chemotherapy (NAC) in women with early triple negative breast cancer (TN). MATERIALS AND METHODS: This monocentric retrospective study included 75 TN female patients with MRI (T1-weighted, T2-weighted, diffusion-weighted and dynamic contrast enhancement images) performed before NAC. For each patient, the tumor(s) and the parenchyma were independently segmented and analyzed with radiomic analysis to extract shape, size, and texture features. Several sets of features were realized based on the 4 different sequence images. Performances of 4 classifiers (random forest, multilayer perceptron, support vector machine (SVM) with linear or quadratic kernel) were compared based on pathological complete response (defined on the excised tissues), on 100 draws with 75% as training set and 25% as test. RESULTS: The combination of features extracted from different MR images improved the classifier performance (more precisely, the features from T1W, T2W and DWI). The SVM with quadratic kernel showed the best performance with a mean AUC of 0.83, a sensitivity of 0.85 and a specificity of 0.75 in the test set. CONCLUSION: MRI-based radiomics may be relevant to predict NAC response in TN cancer. Our results promote the use of multi-contrast MRI sources for radiomics, providing enrich source of information to enhance model generalization.

3D Chemical Shift-Encoded MRI for Volume and Composition Quantification of Abdominal Adipose Tissue During an Overfeeding Protocol in Healthy Volunteers.

BACKGROUND: Overweight and obesity are major worldwide health concerns characterized by an abnormal accumulation of fat in adipose tissue (AT) and liver. PURPOSE: To evaluate the volume and the fatty acid (FA) composition of the subcutaneous adipose tissue (SAT) and the visceral adipose tissue (VAT) and the fat content in the liver from 3D chemical-shift-encoded (CSE)-MRI acquisition, before and after a 31-day overfeeding protocol. STUDY TYPE: Prospective and longitudinal study. SUBJECTS: Twenty-one nonobese healthy male volunteers. FIELD STRENGTH/SEQUENCE: A 3D spoiled-gradient multiple echo sequence and STEAM sequence were performed at 3T. ASSESSMENT: AT volume was automatically segmented on CSE-MRI between L2 to L4 lumbar vertebrae and compared to the dual-energy X-ray absorptiometry (DEXA) measurement. CSE-MRI and MR spectroscopy (MRS) data were analyzed to assess the proton density fat fraction (PDFF) in the liver and the FA composition in SAT and VAT. Gas chromatography-mass spectrometry (GC-MS) analyses were performed on 13 SAT samples as a FA composition countermeasure. STATISTICAL TESTS: Paired t-test, Pearson's correlation coefficient, and Bland-Altman plots were used to compare measurements. RESULTS: SAT and VAT volumes significantly increased (P < 0.001). CSE-MRI and DEXA measurements were strongly correlated (r = 0.98, P < 0.001). PDFF significantly increased in the liver (+1.35, P = 0.002 for CSE-MRI, + 1.74, P = 0.002 for MRS). FA composition of SAT and VAT appeared to be consistent between localized-MRS and CSE-MRI (on whole segmented volume) measurements. A significant difference between SAT and VAT FA composition was found (P < 0.001 for CSE-MRI, P = 0.001 for MRS). MRS and CSE-MRI measurements of the FA composition were correlated with the GC-MS results (for ndb: rMRS/GC-MS = 0.83 P < 0.001, rCSE-MRI/GC-MS = 0.84, P = 0.001; for nmidb: rMRS/GC-MS = 0.74, P = 0.006, rCSE-MRI/GC-MS = 0.66, P = 0.020) DATA CONCLUSION: The follow-up of liver PDFF, volume, and FA composition of AT during an overfeeding diet was demonstrated through different methods. The CSE-MRI sequence associated with a dedicated postprocessing was found reliable for such quantification. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:1587-1599.

Comparison of MRI-derived vs. traditional estimations of fatty acid composition from MR spectroscopy signals.

INTRODUCTION: The composition of fatty acids in the body is gaining increasing interest, and can be followed up noninvasively by quantitative magnetic resonance spectroscopy (MRS). However, current MRS quantification methods have been shown to provide different quantitative results in terms of lipid signals, with possible varying outcomes for a given biological examination. Quantitative magnetic resonance imaging using multigradient echo sequence (MGE-MRI) has recently been added to MRS approaches. In contrast, these methods fit the undersampled magnetic resonance temporal signal with a simplified model function (expressing the triglyceride [TG] spectrum with only three TG parameters), specific implementations and prior knowledge. In this study, an adaptation of an MGE-MRI method to MRS lipid quantification is proposed. METHODS: Several versions of the method - with time data fully or undersampled, including or excluding the spectral peak T2 knowledge in the fitting - were compared theoretically and on Monte Carlo studies with a time-domain, peak-fitting approach. Robustness, repeatability and accuracy were also inspected on in vitro oil acquisitions and test-retest in vivo subcutaneous adipose tissue acquisitions, adding results from the reference LCModel method. RESULTS: On simulations, the proposed method provided TG parameter estimates with the smallest variability, but with a possible bias, which was mitigated by fitting on undersampled data and considering peak T2 values. For in vitro measurements, estimates for all approaches were correlated with theoretical values and the best concordance was found for the usual MRS method (LCModel and peak fitting). Limited in vivo test-retest variability was found (4.1% for PUFAindx, 0.6% for MUFAindx and 3.6% for SFAindx), as for LCModel (7.6% for PUFAindx, 7.8% for MUFAindx and 3.0% for SFAindx). CONCLUSION: This study shows that fitting the three TG parameters directly on MRS data is one valuable solution to circumvent the poor conditioning of the MRS quantification problem.

Reproducibility of in vivo magnetic resonance imaging T1 rho and T2 relaxation time measurements of hip cartilage at 3.0T in healthy volunteers.

PURPOSE: To assess the T1 ρ and T2 values in the hip cartilage of healthy volunteers and to evaluate the reproducibility of these measurements. MATERIALS AND METHODS: The right hip joint of 30 asymptomatic volunteers was explored with 3T magnetic resonance imaging (MRI). Quantitative 3D T1 ρ- and T2 -maps sequences were repeated twice with a 30-minute delay (immediate reproducibility). The same protocol was repeated 14 days later (short-term reproducibility). Immediate and short-term reproducibility were estimated using coefficients of variation and correlation concordance coefficients (CCC). The precisions of the measurements were estimated by the ratio of the standard deviations. A mixed linear model was used to analyze the effect of patient's characteristics on T1 ρ and T2 values. RESULTS: Immediate reproducibility was significantly better than short-term reproducibility for T1 ρ (CCC of 0.75 versus 0.55; P = 0.007) and T2 (CCC 0.65 versus 0.32; P < 0.001). The precisions of the measurements were estimated between 5.5% and 9.1%. Median T1 ρ values were 6.0 msec higher in women than in men (P = 0.006), with no significant influence of age, body mass index (BMI), or sports activity. Median T2 values were not significantly different between men and women (0.4 msec lower in women; P = 0.76). There was no significant influence of age, BMI, or sports activity. T1 ρ and T2 values were lower in lateral regions than in medial regions (4.9 msec and 2.5 msec lower respectively; P < 0.0001). CONCLUSION: Immediate reproducibility of T1 ρ and T2 values is better than short-term, with limited effect of 30 minutes decubitus. T1 ρ values are significantly higher in women. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1022-1033.

Adipose tissue angiogenesis genes are down-regulated by grape polyphenols supplementation during a human overfeeding trial.

The adaptive response to overfeeding is associated with profound modifications of gene expression in adipose tissue to support lipid storage and weight gain. The objective of this study was to assess in healthy lean men whether a supplementation with polyphenols could interact with these molecular adaptations. Abdominal subcutaneous adipose tissue biopsies were sampled from 42 subjects participating to an overfeeding protocol providing an excess of 50% of their total energy expenditure for 31 days, and who were supplemented with 2 g/day of grape polyphenols or a placebo. Gene expression profiling was performed by RNA sequencing. Overfeeding led to a modification of the expression of 163 and 352 genes in the placebo and polyphenol groups, respectively. The GO functions of these genes were mostly involved in lipid metabolism, followed by genes involved in adipose tissue remodeling and expansion. In response to overfeeding, 812 genes were differentially regulated between groups. Among them, a set of 41 genes were related to angiogenesis and were down-regulated in the polyphenol group. Immunohistochemistry targeting PECAM1, as endothelial cell marker, confirmed reduced angiogenesis in this group. Finally, quercetin and isorhamnetin, two polyphenol species enriched in the plasma of the volunteers submitted to the polyphenols, were found to inhibit human umbilical vein endothelial cells migration in vitro. Polyphenol supplementation do not prevent the regulation of genes related to lipid metabolism in human adipose tissue during overfeeding, but impact the angiogenesis pathways. This may potentially contribute to a protection against adipose tissue expansion during dynamic phase of weight gain.

Prediction of Histologic Neoadjuvant Chemotherapy Response in Osteosarcoma Using Pretherapeutic MRI Radiomics.

Histologic response to chemotherapy for osteosarcoma is one of the most important prognostic factors for survival, but assessment occurs after surgery. Although tumor imaging is used for surgical planning and follow-up, it lacks predictive value. Therefore, a radiomics model was developed to predict the response to neoadjuvant chemotherapy based on pretreatment T1-weighted contrast-enhanced MRI. A total of 176 patients (median age, 20 years [range, 5-71 years]; 107 male patients) with osteosarcoma treated with neoadjuvant chemotherapy and surgery between January 2007 and December 2018 in three different centers in France (Centre Léon Bérard in Lyon, Centre Hospitalier Universitaire de Nantes in Nantes, and Hôpital Cochin in Paris) were retrospectively analyzed. Various models were trained from different configurations of the data sets. Two different methods of feature selection were tested with and without ComBat harmonization (ReliefF and t test) to select the most relevant features, and two different classifiers were used to build the models (an artificial neural network and a support vector machine). Sixteen radiomics models were built using the different combinations of feature selection and classifier applied on the various data sets. The most predictive model had an area under the receiver operating characteristic curve of 0.95, a sensitivity of 91%, and a specificity 92% in the training set; respective values in the validation set were 0.97, 91%, and 92%. In conclusion, MRI-based radiomics may be useful to stratify patients receiving neoadjuvant chemotherapy for osteosarcomas. Keywords: MRI, Skeletal-Axial, Oncology, Radiomics, Osteosarcoma, Pediatrics Supplemental material is available for this article. © RSNA, 2022.

Polyphenol Supplementation Did Not Affect Insulin Sensitivity and Fat Deposition During One-Month Overfeeding in Randomized Placebo-Controlled Trials in Men and in Women.

Two randomized placebo-controlled double-blind paralleled trials (42 men in Lyon, 19 women in Lausanne) were designed to test 2 g/day of a grape polyphenol extract during 31 days of high calorie-high fructose overfeeding. Hyperinsulinemic-euglycemic clamps and test meals with [1,1,1-13C3]-triolein were performed before and at the end of the intervention. Changes in body composition were assessed by dual-energy X-ray absorptiometry (DEXA). Fat volumes of the abdominal region and liver fat content were determined in men only, using 3D-magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) at 3T. Adipocyte's size was measured in subcutaneous fat biopsies. Bodyweight and fat mass increased during overfeeding, in men and in women. While whole body insulin sensitivity did not change, homeostasis model assessment of insulin resistance (HOMA-IR) and the hepatic insulin resistance index (HIR) increased during overfeeding. Liver fat increased in men. However, grape polyphenol supplementation did not modify the metabolic and anthropometric parameters or counteract the changes during overfeeding, neither in men nor in women. Polyphenol intake was associated with a reduction in adipocyte size in women femoral fat. Grape polyphenol supplementation did not counteract the moderated metabolic alterations induced by one month of high calorie-high fructose overfeeding in men and women. The clinical trials are registered under the numbers NCT02145780 and NCT02225457 at ClinicalTrials.gov and available at https://clinicaltrials.gov/ct2/show/NCT02145780 and https://clinicaltrials.gov/ct2/show/NCT02225457.