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Reactive stroma is a tissue feature commonly observed in the tumor microenvironment of prostate cancer and has previously been associated with more aggressive tumors. The aim of this study was to detect differentially expressed genes and metabolites according to reactive stroma content measured on the exact same prostate cancer tissue sample. Reactive stroma was evaluated using histopathology from 108 fresh frozen prostate cancer samples gathered from 43 patients after prostatectomy (Biobank1). A subset of the samples was analyzed both for metabolic (n = 85) and transcriptomic alterations (n = 78) using high resolution magic angle spinning magnetic resonance spectroscopy (HR-MAS MRS) and RNA microarray, respectively. Recurrence-free survival was assessed in patients with clinical follow-up of minimum five years (n = 38) using biochemical recurrence (BCR) as endpoint. Multivariate metabolomics and gene expression analysis compared low (≤15%) against high reactive stroma content (≥16%). High reactive stroma content was associated with BCR in prostate cancer patients even when accounting for the influence of Grade Group (Cox hazard proportional analysis, p = 0.013). In samples with high reactive stroma content, metabolites and genes linked to immune functions and extracellular matrix (ECM) remodeling were significantly upregulated. Future validation of these findings is important to reveal novel biomarkers and drug targets connected to immune mechanisms and ECM in prostate cancer. The fact that high reactive stroma grading is connected to BCR adds further support for the clinical integration of this histopathological evaluation. [ABSTRACT FROM AUTHOR]

Background: The relationship between cholesterol and prostate cancer has been extensively studied for decades, where high levels of cellular cholesterol are generally associated with cancer progression and less favorable outcomes. However, the role of in vivo cellular cholesterol synthesis in this process is unclear, and data on the transcriptional activity of cholesterol synthesis pathway genes in tissue from prostate cancer patients are inconsistent.Methods: A common problem with cancer tissue data from patient cohorts is the presence of heterogeneous tissue which confounds molecular analysis of the samples. In this study we present a general method to minimize systematic confounding from stroma tissue in any prostate cancer cohort comparing prostate cancer and normal samples. In particular we use samples assessed by histopathology to identify genes enriched and depleted in prostate stroma. These genes are then used to assess stroma content in tissue samples from other prostate cancer cohorts where no histopathology is available. Differential expression analysis is performed by comparing cancer and normal samples where the average stroma content has been balanced between the sample groups. In total we analyzed seven patient cohorts with prostate cancer consisting of 1713 prostate cancer and 230 normal tissue samples.Results: When stroma confounding was minimized, differential gene expression analysis over all cohorts showed robust and consistent downregulation of nearly all genes in the cholesterol synthesis pathway. Additional Gene Ontology analysis also identified cholesterol synthesis as the most significantly altered metabolic pathway in prostate cancer at the transcriptional level.Conclusion: The surprising observation that cholesterol synthesis genes are downregulated in prostate cancer is important for our understanding of how prostate cancer cells regulate cholesterol levels in vivo. Moreover, we show that tissue heterogeneity explains the lack of consistency in previous expression analysis of cholesterol synthesis genes in prostate cancer. [ABSTRACT FROM AUTHOR]

This corrects the article DOI: 10.1038/bjc.2017.346 [ABSTRACT FROM AUTHOR]

Background: The metabolic consequences of preoperative carbohydrate load in breast cancer patients are not known. The present explorative study investigated the systemic and tumor metabolic changes after preoperative per-oral carbohydrate load and their influence on tumor characteristics and survival.Methods: The study setting was on university hospital level with primary and secondary care functions in south-west Norway. Serum and tumor tissue were sampled from a population-based cohort of 60 patients with operable breast cancer who were randomized to either per-oral carbohydrate load (preOp™; n = 25) or standard pre-operative fasting (n = 35) before surgery. Magnetic resonance (MR) metabolomics was performed on serum samples from all patients and high-resolution magic angle spinning (HR-MAS) MR analysis on 13 tumor samples available from the fasting group and 16 tumor samples from the carbohydrate group.Results: Fourteen of 28 metabolites were differently expressed between fasting and carbohydrate groups. Partial least squares discriminant analysis showed a significant difference in the metabolic profile between the fasting and carbohydrate groups, compatible with the endocrine effects of insulin (i.e., increased serum-lactate and pyruvate and decreased ketone bodies and amino acids in the carbohydrate group). Among ER-positive tumors (n = 18), glutathione was significantly elevated in the carbohydrate group compared to the fasting group (p = 0.002), with a positive correlation between preoperative S-insulin levels and the glutathione content in tumors (r = 0.680; p = 0.002). In all tumors (n = 29), glutamate was increased in tumors with high proliferation (t-test; p = 0.009), independent of intervention group. Moreover, there was a positive correlation between tumor size and proliferation markers in the carbohydrate group only. Patients with ER-positive / T2 tumors and high tumor glutathione (≥1.09), high S-lactate (≥56.9), and high S-pyruvate (≥12.5) had inferior clinical outcomes regarding relapse-free survival, breast cancer-specific survival, and overall survival. Moreover, Integrated Pathway Analysis (IPA) in serum revealed activation of five major anabolic metabolic networks contributing to proliferation and growth.Conclusions: Preoperative carbohydrate load increases systemic levels of lactate and pyruvate and tumor levels of glutathione and glutamate in ER-positive patients. These biological changes may contribute to the inferior clinical outcomes observed in luminal T2 breast cancer patients.Trial Of Registration: ClinicalTrials.gov; NCT03886389. Retrospectively registered March 22, 2019. [ABSTRACT FROM AUTHOR]

Objectives: To compare the performance of currently available biopsy decision support tools incorporating magnetic resonance imaging (MRI) findings in predicting clinically significant prostate cancer (csPCa). Patients and Methods: We retrospectively included men who underwent prostate MRI and subsequent targeted and/or systematic prostate biopsies in two large European centres. Available decision support tools were identified by a PubMed search. Performance was assessed by calibration, discrimination, decision curve analysis (DCA) and numbers of biopsies avoided vs csPCa cases missed, before and after recalibration, at risk thresholds of 5%–20%. Results: A total of 940 men were included, 507 (54%) had csPCa. The median (interquartile range) age, prostate‐specific antigen (PSA) level, and PSA density (PSAD) were 68 (63–72) years, 9 (7–15) ng/mL, and 0.20 (0.13–0.32) ng/mL2, respectively. In all, 18 multivariable risk calculators (MRI‐RCs) and dichotomous biopsy decision strategies based on MRI findings and PSAD thresholds were assessed. The Van Leeuwen model and the Rotterdam Prostate Cancer Risk Calculator (RPCRC) had the best discriminative ability (area under the receiver operating characteristic curve 0.86) of the MRI‐RCs that could be assessed in the whole cohort. DCA showed the highest clinical utility for the Van Leeuwen model, followed by the RPCRC. At the 10% threshold the Van Leeuwen model would avoid 22% of biopsies, missing 1.8% of csPCa, whilst the RPCRC would avoid 20% of biopsies, missing 2.6% of csPCas. These multivariable models outperformed all dichotomous decision strategies based only on MRI‐findings and PSAD. Conclusions: Even in this high‐risk cohort, biopsy decision support tools would avoid many prostate biopsies, whilst missing very few csPCa cases. The Van Leeuwen model had the highest clinical utility, followed by the RPCRC. These multivariable MRI‐RCs outperformed and should be favoured over decision strategies based only on MRI and PSAD. [ABSTRACT FROM AUTHOR]

Metabolic reprogramming in breast cancer involves changes in steroid hormone synthesis and metabolism. Alterations in estrogen levels in both breast tissue and blood may influence carcinogenesis, breast cancer growth, and response to therapy. Our aim was to examine whether serum steroid hormone concentrations could predict the risk of recurrence and treatment-related fatigue in patients with breast cancer. This study included 66 postmenopausal patients with estrogen receptor-positive breast cancer who underwent surgery, radiotherapy, and adjuvant endocrine treatment. Serum samples were collected at six different time points [before the start of radiotherapy (as baseline), immediately after radiotherapy, and then 3, 6, 12 months, and 7–12 years after radiotherapy]. Serum concentrations of eight steroid hormones (cortisol, cortisone, 17α-hydroxyprogesterone, 17β-estradiol, estrone, androstenedione, testosterone, and progesterone) were measured using a liquid chromatography–tandem mass spectrometry-based method. Breast cancer recurrence was defined as clinically proven relapse/metastatic breast cancer or breast cancer-related death. Fatigue was assessed with the QLQ-C30 questionnaire. Serum steroid hormone concentrations measured before and immediately after radiotherapy differed between relapse and relapse-free patients [(accuracy 68.1%, p = 0.02, and 63.2%, p = 0.03, respectively, partial least squares discriminant analysis (PLS-DA)]. Baseline cortisol levels were lower in patients who relapsed than in those who did not (p < 0.05). The Kaplan–Meier analysis showed that patients with high baseline concentrations of cortisol (≥ median) had a significantly lower risk of breast cancer recurrence than patients with low cortisol levels (

Purpose: To evaluate the diagnostic relevance of T2-weighted (T2W) MRI-derived textural features relative to quantitative physiological parameters derived from diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) MRI in Gleason score (GS) 3+4 and 4+3 prostate cancers.Materials and Methods: 3T multiparametric-MRI was performed on 23 prostate cancer patients prior to prostatectomy. Textural features [angular second moment (ASM), contrast, correlation, entropy], apparent diffusion coefficient (ADC), and DCE pharmacokinetic parameters (Ktrans and Ve) were calculated from index tumours delineated on the T2W, DW, and DCE images, respectively. The association between the textural features and prostatectomy GS and the MRI-derived parameters, and the utility of the parameters in differentiating between GS 3+4 and 4+3 prostate cancers were assessed statistically.Results: ASM and entropy correlated significantly (p < 0.05) with both GS and median ADC. Contrast correlated moderately with median ADC. The textural features correlated insignificantly with Ktrans and Ve. GS 4+3 cancers had significantly lower ASM and higher entropy than 3+4 cancers, but insignificant differences in median ADC, Ktrans, and Ve. The combined texture-MRI parameters yielded higher classification accuracy (91%) than the individual parameter sets.Conclusion: T2W MRI-derived textural features could serve as potential diagnostic markers, sensitive to the pathological differences in prostate cancers.Key Points: • T2W MRI-derived textural features correlate significantly with Gleason score and ADC. • T2W MRI-derived textural features differentiate Gleason score 3+4 from 4+3 cancers. • T2W image textural features could augment tumour characterization. [ABSTRACT FROM AUTHOR]

Background: Traditional biomarkers used to measure risk of myocardial infarction (MI) only explain a modest proportion of the incidence. Lipoprotein subfractions have the potential to improve risk prediction of MI. Aim: We aimed to identify lipoprotein subfractions that were associated with imminent MI risk. Methods: We identified apparently healthy participants with a predicted low 10-year risk of MI from The Trøndelag Health Survey 3 (HUNT3) that developed MI within 5 years after inclusion (cases, n = 50) and 100 matched controls. Lipoprotein subfractions were analyzed in serum by nuclear magnetic resonance spectroscopy at time of inclusion in HUNT3. Lipoprotein subfractions were compared between cases and controls in the full population (N = 150), and in subgroups of males (n = 90) and females (n = 60). In addition, a sub analysis was performed in participants that experienced MI within two years and their matched controls (n = 56). Results: None of the lipoprotein subfractions were significantly associated with future MI when adjusting for multiple testing (p<0.002). At nominal significance level (p<0.05), the concentration of apolipoprotein A1 in the smallest high-density lipoprotein (HDL) subfractions was higher in cases compared to controls. Further, in sub analyses based on sex, male cases had lower lipid concentration within the large HDL subfractions and higher lipid concentration within the small HDL subfractions compared to male controls (p<0.05). No differences were found in lipoprotein subfractions between female cases and controls. In sub analysis of individuals suffering from MI within two years, triglycerides in low-density lipoprotein were higher among cases (p<0.05). Conclusion: None of the investigated lipoprotein subfractions were associated with future MI after adjustment for multiple testing. However, our findings suggests that HDL subfractions may be of interest in relation to risk prediction for MI, especially in males. This need to be further investigated in future studies. [ABSTRACT FROM AUTHOR]

Lipoprotein subfractions currently represent a new source of cardiovascular disease (CVD) risk markers that may provide more information than conventional lipid measures. We aimed to investigate whether lipoprotein subfractions are associated with coronary atherosclerosis in patients without prior known CVD. Fasting serum samples from 60 patients with suspected coronary artery disease (CAD) were collected before coronary angiography and analyzed by nuclear magnetic resonance (NMR) spectroscopy. The severity of coronary atherosclerosis was quantified by the Gensini score (≤20.5 = nonsignificant coronary atherosclerosis, 20.6–30.0 = intermediate coronary atherosclerosis, ≥30.1 = significant CAD). Differences in lipoprotein subfractions between the three Gensini groups were assessed by two-way ANOVA, adjusted for statin use. Despite no differences in conventional lipid measures between the three Gensini groups, patients with significant CAD had higher apolipoprotein-B/apolipoprotein-A1 ratio, 30% more small and dense low-density lipoprotein 5 (LDL-5) particles, and increased levels of cholesterol, triglycerides, and phospholipids within LDL-5 compared with patients with nonsignificant coronary atherosclerosis and intermediate coronary atherosclerosis (P ≤ 0.001). In addition, the low-density lipoprotein (LDL) cholesterol/high-density lipoprotein cholesterol ratio, and triglyceride levels of LDL 4 were significantly increased in patients with significant CAD compared with patients with nonsignificant coronary atherosclerosis. In conclusion, small and dense lipoprotein subfractions were associated with coronary atherosclerosis in patients without prior CVD. Additional studies are needed to explore whether lipoprotein subfractions may represent biomarkers offering a clinically meaningful improvement in the risk prediction of CAD. [ABSTRACT FROM AUTHOR]

Background: Our understanding of the mechanisms through which physical activity might benefit lipoprotein metabolism is inadequate. Here we characterise the continuous associations between physical activity of different intensities, sedentary time, and a comprehensive lipoprotein particle profile. Methods: Our cohort included 762 fifth grade (mean [SD] age = 10.0 [0.3] y) Norwegian schoolchildren (49.6% girls) measured on two separate occasions across one school year. We used targeted proton nuclear magnetic resonance (1H NMR) spectroscopy to produce 57 lipoprotein measures from fasted blood serum samples. The children wore accelerometers for seven consecutive days to record time spent in light-, moderate-, and vigorous-intensity physical activity, and sedentary time. We used separate multivariable linear regression models to analyse associations between the device-measured activity variables—modelled both prospectively (baseline value) and as change scores (follow-up minus baseline value)—and each lipoprotein measure at follow-up. Results: Higher baseline levels of moderate-intensity and vigorous-intensity physical activity were associated with a favourable lipoprotein particle profile at follow-up. The strongest associations were with the larger subclasses of triglyceride-rich lipoproteins. Sedentary time was associated with an unfavourable lipoprotein particle profile, the pattern of associations being the inverse of those in the moderate-intensity and vigorous-intensity physical activity analyses. The associations with light-intensity physical activity were more modest; those of the change models were weak. Conclusion: We provide evidence of a prospective association between time spent active or sedentary and lipoprotein metabolism in schoolchildren. Change in activity levels across the school year is of limited influence in our young, healthy cohort. Trial registration: ClinicalTrials.gov, #NCT02132494. Registered 7th April 2014 [ABSTRACT FROM AUTHOR]

Background: The aim of this study was to gain an increased understanding of the aetiology of breast cancer, by investigating possible associations between serum lipoprotein subfractions and metabolites and the long-term risk of developing the disease.Methods: From a cohort of 65,200 participants within the Trøndelag Health Study (HUNT study), we identified all women who developed breast cancer within a 22-year follow-up period. Using nuclear magnetic resonance (NMR) spectroscopy, 28 metabolites and 89 lipoprotein subfractions were quantified from prediagnostic serum samples of future breast cancer patients and matching controls (n = 1199 case-control pairs).Results: Among premenopausal women (554 cases) 14 lipoprotein subfractions were associated with long-term breast cancer risk. In specific, different subfractions of VLDL particles (in particular VLDL-2, VLDL-3 and VLDL-4) were inversely associated with breast cancer. In addition, inverse associations were detected for total serum triglyceride levels and HDL-4 triglycerides. No significant association was found in postmenopausal women.Conclusions: We identified several associations between lipoprotein subfractions and long-term risk of breast cancer in premenopausal women. Inverse associations between several VLDL subfractions and breast cancer risk were found, revealing an altered metabolism in the endogenous lipid pathway many years prior to a breast cancer diagnosis. [ABSTRACT FROM AUTHOR]

High intensity interval training (HIIT) has been shown to benefit patients with psoriatic arthritis (PsA). However, magnetic resonance (MR) imaging has uncovered bone marrow edema (BME) in healthy volunteers after vigorous exercise. The purpose of this study was to investigate MR images of the spine of PsA patients for changes in BME after HIIT. PsA patients went through 11 weeks of HIIT (N = 19, 4 men, median age 52 years) or no change in physical exercise habits (N = 20, 8 men, median age 45 years). We acquired scores for joint affection and pain and short tau inversion recovery (STIR) and T1-weighted MR images of the spine at baseline and after 11 weeks. MR images were evaluated for BME by a trained radiologist, by SpondyloArthritis Research Consortium of Canada (SPARCC) scoring, and by extraction of textural features. No significant changes of BME were detected in MR images of the spine after HIIT. This was consistent for MR image evaluation by a radiologist, by SPARCC, and by texture analysis. Values of textural features were significantly different in BME compared to healthy bone marrow. In conclusion, BME in spine was not changed after HIIT, supporting that HIIT is safe for PsA patients. [ABSTRACT FROM AUTHOR]

Low cardiorespiratory fitness is a strong and independent risk factor for cardiovascular disease (CVD). Serum profiling of healthy individuals with large differences in cardiorespiratory fitness may therefore reveal early biomarkers of CVD development. Thus, we aimed to identify circulating lipoprotein subfractions differentially expressed between groups of individuals with large differences in cardiorespiratory fitness, measured as maximal oxygen uptake (VO 2max). Healthy subjects (40–59 years) were selected from the third wave of the Trøndelag health study (HUNT3) based on having an age-dependent high VO 2max (47.1 ± 7.7 mL kg−1·min−1, n = 103) or low VO 2max (31.4 ± 4.9 mL kg−1·min−1, n = 108). The individuals were matched on gender, age, physical activity level and fasting status. 99 lipoprotein subfractions were quantified in serum samples using nuclear magnetic resonance (NMR) lipidomics. Standard clinical analyses showed similar levels of total cholesterol, low-density lipoprotein (LDL)-cholesterol and high-density lipoprotein (HDL)-cholesterol between the groups, and slightly higher levels of triglycerides in participants with low VO 2max. Thirteen lipoprotein subfractions were increased in the low VO 2max group compared to the high VO 2max group (p < 0.005), including mainly large very low-density lipoprotein (VLDL) subfractions. In addition, triglyceride levels in small-sized HDL and LDL particles were increased in participants with low VO 2max. Correlation analyses between VO 2max and lipoproteins subfractions displayed a negative correlation between VO 2max and the levels of cholesterol and phospholipids in the small HDL particles. The lipoprotein profile of individuals with low VO 2max is similar to the profile of insulin resistant individuals. Low VO 2max was associated with enrichment of large VLDL particles, as well as an increased triglycerides content in the small and dense HDL and LDL particles. This unfavorable lipid profile is likely to be involved in the strong associations between VO 2max and CVD. [Display omitted] • The circulating levels of very low-density lipoprotein (VLDL) subfractions were significantly higher in participants with low cardiorespiratory fitness (VO 2max) compared to participants with high VO 2max. • Triglyceride levels in small-sized high-density lipoprotein (HDL) and low-density lipoprotein (LDL) particles were higher in participants with low VO 2max. • When comparing healthy individuals with high and low VO 2max , the lipoprotein subfraction profile of individuals with low VO 2max showed similarities to the profile of insulin resistant individuals. • The identified lipoprotein subfractions associated with VO 2max may represent early risk markers of CVD development. [ABSTRACT FROM AUTHOR]

The associations between aerobic fitness and traditional measures of lipid metabolism in children are uncertain. We investigated whether higher levels of aerobic fitness benefit lipoprotein metabolism by exploring associations with a comprehensive lipoprotein particle profile. In our prospective cohort study, we used targeted proton nuclear magnetic resonance (1H NMR) spectroscopy to profile 57 measures of lipoprotein metabolism from fasting serum samples of 858 fifth-grade Norwegian schoolchildren (49.0% girls; mean age 10.0 years). Aerobic fitness was measured using an intermittent shuttle run aerobic fitness test. We used multiple linear regression adjusted for potential confounders to examine cross-sectional and prospective associations between aerobic fitness and lipoprotein particle profile. Higher levels of aerobic fitness were associated with a favourable lipoprotein particle profile in the cross-sectional analysis, which included inverse associations with all measures of very low-density lipoprotein (VLDL) particles (e.g., −0.06 mmol·L−1 or –0.23 SD units; 95% CI = −0.31, −0.16 for VLDL cholesterol concentration). In the prospective analysis, the favourable pattern of associations persisted, though the individual associations tended to be more consistent with those of the cross-sectional analysis for the VLDL subclass measures compared to the low-density lipoproteins and high-density lipoproteins. Adjustment for adiposity attenuated the associations in both cross-sectional and prospective models. Nevertheless, an independent effect of aerobic fitness remained for some measures. Improving children's aerobic fitness levels should benefit lipoprotein metabolism, though a concomitant reduction in adiposity would likely potentiate this effect. [Display omitted] • Associations between aerobic fitness and lipoprotein particle profile were examined in a cohort of Norwegian schoolchildren. • Aerobic fitness was favourably associated cross-sectionally and prospectively with a number of lipoprotein measures. • The associations tended to be stronger with measures of very low-density lipoprotein (VLDL) particles and triglycerides concentrations. [ABSTRACT FROM AUTHOR]

Metabolomics analysis of biofluids is a feasible tool for disease characterization and monitoring due to its minimally invasive nature. To reduce unwanted variation in biobanks and clinical studies, it is important to determine the effect of external factors on metabolic profiles of biofluids. In this study we examined the effect of sample collection and sample processing procedures on NMR measured serum lipoproteins and small-molecule metabolites in serum and urine, using a cohort of men diagnosed with either prostate cancer or benign prostatic hyperplasia. We determined day-to-day reliability of metabolites by systematic sample collection at two different days, in both fasting and non-fasting conditions. Study participants received prostate massage the first day to assess the differences between urine with and without prostate secretions. Further, metabolic differences between first-void and mid-stream urine samples, and the effect of centrifugation of urine samples before storage were assessed. Our results show that day-to-day reliability is highly variable between metabolites in both serum and urine, while lipoprotein subfractions possess high reliability. Further, fasting status clearly influenced the metabolite concentrations, demonstrating the importance of keeping this condition constant within a study cohort. Day-to-day reliabilities were however comparable in fasting and non-fasting samples. Urine sampling procedures such as sampling of first-void or mid-stream urine, and centrifugation or not before sample storage, were shown to only have minimal effect on the overall metabolic profile, and is thus unlikely to constitute a confounder in clinical studies utilizing NMR derived metabolomics. Image 1 • Serum lipoprotein subfractions possess high day-to-day reliability. • Day-to-day reliability of serum and urine metabolites ranges from low to high. • Prostate massage leads to release of prostate-specific metabolites into urine. • Metabolic differences between first-void and mid-stream urine are small. • Urine metabolite concentrations are minimally affected by pre-freezing centrifugation. [ABSTRACT FROM AUTHOR]

Physical activity is favourably associated with certain markers of lipid metabolism. The relationship of physical activity with lipoprotein particle profiles in children is not known. Here we examine cross-sectional associations between objectively measured physical activity and sedentary time with serum markers of lipoprotein metabolism. Our cohort included 880 children (49.0% girls, mean age 10.2 years). Physical activity intensity and time spent sedentary were measured objectively using accelerometers. 30 measures of lipoprotein metabolism were quantified using nuclear magnetic resonance spectroscopy. Multiple linear regression models adjusted for age, sex, sexual maturity and socioeconomic status were used to determine associations of physical activity and sedentary time with lipoprotein measures. Additional models were adjusted for adiposity. Isotemporal substitution models quantified theoretical associations of replacing 30 min of sedentary time with 30 min of moderate- to vigorous-intensity physical activity (MVPA). Time spent in MVPA was associated with a favourable lipoprotein profile independent of sedentary time. There were inverse associations with a number of lipoprotein measures, including most apolipoprotein B-containing lipoprotein subclasses and triglyceride measures, the ratio of total to high-density lipoprotein (HDL) cholesterol, and non-HDL cholesterol concentration. There were positive associations with larger HDL subclasses, HDL cholesterol concentration and particle size. Reallocating 30 min of sedentary time to MVPA had broadly similar associations. Sedentary time was only partly and weakly associated with an unfavourable lipoprotein profile. Physical activity of at least moderate-intensity is associated with a favourable lipoprotein profile in schoolchildren, independent of time spent sedentary, adiposity and other confounders. Image 1 • Moderate- to vigorous-intensity physical activity is associated with a favourable lipoprotein profile in schoolchildren. • These beneficial associations are independent of sedentary time. • Replacing sedentary time with moderate- to vigorous-intensity physical activity is similarly beneficial. • Sedentary time is only partly and weakly associated with an unfavourable profile. [ABSTRACT FROM AUTHOR]

Hyperpolarized 13C isotope resolved spectroscopy boosts NMR signal intensity, which improves signal detection and allows metabolic fluxes to be analyzed. Such hyperpolarized flux data may offer new approaches to tissue classification and biomarker identification that could be translated in vivo. Here we used hyperpolarized stable isotope resolved analysis (SIRA) to measure metabolite specific 13C isotopic enrichments in the central carbon metabolism of mouse prostate. Prostate and tumor tissue samples were acquired from transgenic adenocarcinomas of the mouse prostate (TRAMP) mice. Before euthanasia, mice were injected with [U–13C]glucose intraperitoneally (i.p.). Polar metabolite extracts were prepared, and hyperpolarized 1D-13C NMR spectra were obtained from normal prostate (n = 19) and cancer tissue (n = 19) samples. Binary classification and feature analysis was performed to make a separation model and to investigate differences between samples originating from normal and cancerous prostate tissue, respectively. Hyperpolarized experiments were carried out according to a standardized protocol, which showed a high repeatability (CV = 15%) and an average linewidth in the 1D-13C NMR spectra of 2 ± 0.5 Hz. The resolution of the hyperpolarized 1D-13C spectra was high with little signal overlap in the carbonyl region and metabolite identification was easily accomplished. A discrimination with 95% success rate could be made between samples originating from TRAMP mice prostate and tumor tissue based on isotopomers from uniquely identified metabolites. Hyperpolarized 13C-SIRA allowed detailed metabolic information to be obtained from tissue specimens. The positional information of 13C isotopic enrichments lead to easily interpreted features responsible for high predictive classification of tissue types. This analytical approach has matured, and the robust experimental protocols currently available allow systematic tracking of metabolite flux ex vivo. [Display omitted] • Hyperpolarized 13C NMR on tissue extracts provides high SNR metabolic activity data. • High discernment is obtained between normal and cancer prostate tissue from mice. • Ex vivo biomarker discovery may aid design of in vivo metabolic contrast agents. [ABSTRACT FROM AUTHOR]

In this work, we introduce spatial and chemical saturation options for artefact reduction in magnetic resonance fingerprinting (MRF) and assess their impact on T 1 and T 2 mapping accuracy. An existing radial MRF pulse sequence was modified to enable spatial and chemical saturation. Phantom experiments were performed to demonstrate flow artefact reduction and evaluate the accuracy of the T 1 and T 2 maps. As an in vivo demonstration, MRF of the prostate was performed on an asymptomatic volunteer using saturation modules to reduce flow-related artefacts. T 1 , T 2 and B 1 + maps obtained with and without saturation modules were compared. Application of spatial saturation in prostate MRF reduced streaking artefacts from the femoral vessels. When saturation is enabled T 1 accuracy is preserved, and T 2 accuracy remains acceptable up to approximately 100 ms. Chemical and spatial saturation can be incorporated into MRF sequences with limited impact on T 1 accuracy. Further sequence optimisation may be needed to accurately estimate long T 2 components. Spatial saturation modules have potential in prostate MRF applications as a means to reduce flow-related artefacts., (© 2025 The Author(s). NMR in Biomedicine published by John Wiley & Sons Ltd.)

Background: Prostate-specific membrane antigen (PSMA) positron emission tomography (PET) can change management in a large fraction of patients with biochemically recurrent prostate cancer (BCR)., Purpose: To investigate the added value of PET to MRI and CT for this patient group, and to explore whether the choice of the PET paired modality (PET/MRI vs. PET/CT) impacts detection rates and clinical management., Study Type: Retrospective., Subjects: 41 patients with BCR (median age [range]: 68 [55-78])., Field Strength/sequence: 3T, including T1-weighted gradient echo (GRE), T2-weighted turbo spin echo (TSE) and dynamic contrast-enhanced GRE sequences, diffusion-weighted echo-planar imaging, and a T1-weighted TSE spine sequence. In addition to MRI, [ 18 F]PSMA-1007 PET and low-dose CT were acquired on the same day., Assessment: Images were reported using a five-point Likert scale by two teams each consisting of a radiologist and a nuclear medicine physician. The radiologist performed a reading using CT and MRI data and a joint reading between radiologist and nuclear medicine physician was performed using MRI, CT, and PET from either PET/MRI or PET/CT. Findings were presented to an oncologist to create intended treatment plans. Intrareader and interreader agreement analysis was performed., Statistical Tests: McNemar test, Cohen's κ, and intraclass correlation coefficients. A P-value <0.05 was considered significant., Results: 7 patients had positive findings on MRI and CT, 22 patients on joint reading with PET/CT, and 18 patients joint reading with PET/MRI. For overall positivity, interreader agreement was poor for MR and CT (κ = 0.36) and almost perfect with addition of PET (PET/CT κ = 0.85, PET/MRI κ = 0.85). The addition of PET from PET/CT and PET/MRI changed intended treatment in 20 and 18 patients, respectively. Between joint readings, intended treatment was different for eight patients., Data Conclusion: The addition of [ 18 F]PSMA-1007 PET/MRI or PET/CT to MRI and CT may increase detection rates, could reduce interreader variability, and may change intended treatment in half of patients with BCR., Level of Evidence: 3 TECHNICAL EFFICACY: Stage 3., (© 2024 The Authors. Journal of Magnetic Resonance Imaging published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

High acceleration factors in radial magnetic resonance fingerprinting (MRF) of the prostate lead to strong streak-like artefacts from flow in the femoral blood vessels, possibly concealing important anatomical information. Region-optimised virtual (ROVir) coils is a beamforming-based framework to create virtual coils that maximise signal in a region of interest while minimising signal in a region of interference. In this study, the potential of removing femoral flow streak artefacts in prostate MRF using ROVir coils is demonstrated in silico and in vivo. The ROVir framework was applied to radial MRF k-space data in an automated pipeline designed to maximise prostate signal while minimising signal from the femoral vessels. The method was tested in 15 asymptomatic volunteers at 3 T. The presence of streaks was visually assessed and measurements of whole prostate T 1 , T 2 and signal-to-noise ratio (SNR) with and without streak correction were examined. In addition, a purpose-built simulation framework in which blood flow through the femoral vessels can be turned on and off was used to quantitatively evaluate ROVir's ability to suppress streaks in radial prostate MRF. In vivo it was shown that removing selected ROVir coils visibly reduces streak-like artefacts from the femoral blood flow, without increasing the reconstruction time. On average, 80% of the prostate SNR was retained. A similar reduction of streaks was also observed in silico, while the quantitative accuracy of T 1 and T 2 mapping was retained. In conclusion, ROVir coils efficiently suppress streaking artefacts from blood flow in radial MRF of the prostate, thereby improving the visual clarity of the images, without significant sacrifices to acquisition time, reconstruction time and accuracy of quantitative values. This is expected to help enable T 1 and T 2 mapping of prostate cancer in clinically viable times, aiding differentiation between prostate cancer from noncancer and healthy prostate tissue., (© 2024 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd.)

Background and Objective: The aim of our study was to investigate whether repeat prostate-specific antigen (PSA) testing as currently recommended improves risk stratification for men undergoing magnetic resonance imaging (MRI) and targeted biopsy for suspected prostate cancer (PCa)., Methods: Consecutive men undergoing MRI and prostate biopsy who had at least two PSA tests before prostate biopsy were retrospectively registered and assigned to a development cohort ( n  = 427) or a validation ( n  = 174) cohort. Change in PSA level was assessed as a predictor of clinically significant PCa (csPCa; Gleason score ≥3 + 4, grade group ≥2) by multivariable logistic regression analysis. We developed a multivariable prediction model (MRI-RC) and a dichotomous biopsy decision strategy incorporating the PSA change. The performance of the MRI-RC model and dichotomous decision strategy was assessed in the validation cohort and compared to prediction models and decision strategies not including PSA change in terms of discriminative ability and decision curve analysis., Results: Men who had a decrease on repeat PSA testing had significantly lower risk of csPCa than men without a decrease (odds ratio [OR] 0.3, 95% confidence interval [CI] 0.16-0.54; p  < 0.001). Men with an increased repeat PSA had a significantly higher risk of csPCa than men without an increase (OR 2.97, 95% CI 1.62-5.45; p  < 0.001). Risk stratification using both the MRI-RC model and the dichotomous decision strategy was improved by incorporating change in PSA as a parameter., Conclusions and Clinical Implications: Repeat PSA testing gives predictive information regarding men undergoing MRI and targeted prostate biopsy. Inclusion of PSA change as a parameter in an MRI-RC model and a dichotomous biopsy decision strategy improves their predictive performance and clinical utility without requiring additional investigations., Patient Summary: For men with a suspicion of prostate cancer, repeat PSA (prostate-specific antigen) testing after an MRI (magnetic resonance imaging) scan can help in identifying patients who can safely avoid prostate biopsy., (© 2024 The Author(s).)

Breast cancer (BC) is a leading cause of cancer-related death worldwide. The diverse nature and heterogeneous biology of BC pose challenges for survival prediction, as patients with similar diagnoses often respond differently to treatment. Clinically relevant BC intrinsic subtypes have been established through gene expression profiling and are implemented in the clinic. While these intrinsic subtypes show a significant association with clinical outcomes, their long-term survival prediction beyond 5 years often deviates from expected clinical outcomes. This study aimed to identify naturally occurring long-term prognostic subgroups of BC based on an integrated multi-omics analysis. This study incorporates a clinical cohort of 335 untreated BC patients from the Oslo2 study with long-term follow-up (>12 years). Multi-Omics Factor Analysis (MOFA+) was employed to integrate transcriptomic, proteomic, and metabolomic data obtained from the tumor tissues. Our analysis revealed three prominent multi-omics clusters of BC patients with significantly different long-term prognoses (p = 0.005). The multi-omics clusters were validated in two independent large cohorts, METABRIC and TCGA. Importantly, a lack of prognostic association to long-term follow-up above 12 years in the previously established intrinsic subtypes was shown for these cohorts. Through a systems-biology approach, we identified varying enrichment levels of cell-cycle and immune-related pathways among the prognostic clusters. Integrated multi-omics analysis of BC revealed three distinct clusters with unique clinical and biological characteristics. Notably, these multi-omics clusters displayed robust associations with long-term survival, outperforming the established intrinsic subtypes., (© 2024. The Author(s).)

Introduction: Systemic and local steroid hormone levels may function as novel prognostic and predictive biomarkers in breast cancer patients. We aimed at developing a novel liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for the simultaneous measurement of multiple, biologically pivotal steroid hormones in human serum and breast cancer tissue., Methods: The quantitative method consisted of liquid-liquid extraction, Sephadex LH-20 chromatography for tissue extracts, and analysis of steroid hormones by liquid-chromatography-tandem mass spectrometry. We analyzed serum and tissue steroid hormone levels in 16 and 40 breast cancer patients, respectively, and assessed their correlations with clinical parameters., Results: The method included quantification of nine steroid hormones in serum [including cortisol, cortisone, corticosterone, estrone (E1), 17β-estradiol (E2), 17α-hydroxyprogesterone, androstenedione (A4), testosterone and progesterone) and six (including cortisone, corticosterone, E1, E2, A4, and testosterone) in cancer tissue. The lower limits of quantification were between 0.003-10 ng/ml for serum (250 µl) and 0.038-125 pg/mg for tissue (20 mg), respectively. Accuracy was between 98%-126%, intra-assay coefficient of variations (CV) was below 15%, and inter-assay CV were below 11%. The analytical recoveries for tissue were between 76%-110%. Tissue levels of E1 were positively correlated with tissue E2 levels (p<0.001), and with serum levels of E1, E2 and A4 (p<0.01). Tissue E2 levels were positively associated with serum E1 levels (p=0.02), but not with serum E2 levels (p=0.12). The levels of tissue E2 and ratios of E1 to A4 levels (an index for aromatase activity) were significantly higher in patients with larger tumors (p=0.03 and p=0.02, respectively)., Conclusions: The method was convenient and suitable for a specific and accurate profiling of clinically important steroid hormones in serum. However, the sensitivity of the profile method in steroid analysis in tissue samples is limited, but it can be used for the analysis of steroids in breast cancer tissues if the size of the sample or its steroid content is sufficient., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Wang, Eikeland, Reidunsdatter, Hagen, Engstrøm, Geisler, Haanpää, Hämäläinen, Giskeødegård and Bathen.)

Introduction: The progression of solid cancers is manifested at the systemic level as molecular changes in the metabolome of body fluids, an emerging source of cancer biomarkers., Methods: We analyzed quantitatively the serum metabolite profile using high-resolution mass spectrometry. Metabolic profiles were compared between breast cancer patients (n=112) and two groups of healthy women (from Poland and Norway; n=95 and n=112, respectively) with similar age distributions., Results: Despite differences between both cohorts of controls, a set of 43 metabolites and lipids uniformly discriminated against breast cancer patients and healthy women. Moreover, smaller groups of female patients with other types of solid cancers (colorectal, head and neck, and lung cancers) were analyzed, which revealed a set of 42 metabolites and lipids that uniformly differentiated all three cancer types from both cohorts of healthy women. A common part of both sets, which could be called a multi-cancer signature, contained 23 compounds, which included reduced levels of a few amino acids (alanine, aspartate, glutamine, histidine, phenylalanine, and leucine/isoleucine), lysophosphatidylcholines (exemplified by LPC(18:0)), and diglycerides. Interestingly, a reduced concentration of the most abundant cholesteryl ester (CE(18:2)) typical for other cancers was the least significant in the serum of breast cancer patients. Components present in a multi-cancer signature enabled the establishment of a well-performing breast cancer classifier, which predicted cancer with a very high precision in independent groups of women (AUC>0.95)., Discussion: In conclusion, metabolites critical for discriminating breast cancer patients from controls included components of hypothetical multi-cancer signature, which indicated wider potential applicability of a general serum metabolome cancer biomarker., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Mrowiec, Debik, Jelonek, Kurczyk, Ponge, Wilk, Krzempek, Giskeødegård, Bathen and Widłak.)

In this study, we investigated the potential of the multivariate curve resolution alternating least squares (MCR-ALS) algorithm for analyzing three-dimensional (3D) 1 H-MRSI data of the prostate in prostate cancer (PCa) patients. MCR-ALS generates relative intensities of components representing spectral profiles derived from a large training set of patients, providing an interpretable model. Our objectives were to classify magnetic resonance (MR) spectra, differentiating tumor lesions from benign tissue, and to assess PCa aggressiveness. We included multicenter 3D 1 H-MRSI data from 106 PCa patients across eight centers. The patient cohort was divided into a training set (N = 63) and an independent test set (N = 43). Singular value decomposition determined that MR spectra were optimally represented by five components. The profiles of these components were extracted from the training set by MCR-ALS and assigned to specific tissue types. Using these components, MCR-ALS was applied to the test set for a quantitative analysis to discriminate tumor lesions from benign tissue and to assess tumor aggressiveness. Relative intensity maps of the components were reconstructed and compared with histopathology reports. The quantitative analysis demonstrated a significant separation between tumor and benign voxels (t-test, p < 0.001). This result was achieved including voxels with low-quality MR spectra. A receiver operating characteristic analysis of the relative intensity of the tumor component revealed that low- and high-risk tumor lesions could be distinguished with an area under the curve of 0.88. Maps of this component properly identified the extent of tumor lesions. Our study demonstrated that MCR-ALS analysis of 1 H-MRSI of the prostate can reliably identify tumor lesions and assess their aggressiveness. It handled multicenter data with minimal preprocessing and without using prior knowledge or quality control. These findings indicate that MCR-ALS can serve as an automated tool to assess the presence, extent, and aggressiveness of tumor lesions in the prostate, enhancing diagnostic capabilities and treatment planning of PCa patients., (© 2023 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd.)

Purpose: To evaluate the reproducibility of radiomics features derived via different pre-processing settings from paired T2-weighted imaging (T2WI) prostate lesions acquired within a short interval, to select the setting that yields the highest number of reproducible features, and to evaluate the impact of disease characteristics (i.e., clinical variables) on features reproducibility., Materials and Methods: A dataset of 50 patients imaged using T2WI at 2 consecutive examinations was used. The dataset was pre-processed using 48 different settings. A total of 107 radiomics features were extracted from manual delineations of 74 lesions. The inter-scan reproducibility of each feature was measured using the intra-class correlation coefficient (ICC), with ICC values > 0.75 considered good. Statistical differences were assessed using Mann-Whitney U and Kruskal-Wallis tests., Results: The pre-processing parameters strongly influenced the reproducibility of radiomics features of T2WI prostate lesions. The setting that yielded the highest number of features (25 features) with high reproducibility was the relative discretization with a fixed bin number of 64, no signal intensity normalization, and outlier filtering by excluding outliers. Disease characteristics did not significantly impact the reproducibility of radiomics features., Conclusion: The reproducibility of T2WI radiomics features was significantly influenced by pre-processing parameters, but not by disease characteristics. The selected pre-processing setting yielded 25 reproducible features., (© 2023. The Author(s).)

Purpose: Dynamic contrast-enhanced MRI (DCE) and apparent diffusion coefficient (ADC) are currently used to evaluate treatment response of breast cancer. The purpose of the current study was to evaluate the three-component Restriction Spectrum Imaging model (RSI 3C ), a recent diffusion-weighted MRI (DWI)-based tumor classification method, combined with elastic image registration, to automatically monitor breast tumor size throughout neoadjuvant therapy., Experimental Design: Breast cancer patients ( n= 27) underwent multi-parametric 3T MRI at four time points during treatment. Elastically-registered DWI images were used to generate an automatic RSI 3C response classifier, assessed against manual DCE tumor size measurements and mean ADC values. Predictions of therapy response during treatment and residual tumor post-treatment were assessed using non-pathological complete response (non-pCR) as an endpoint., Results: Ten patients experienced pCR. Prediction of non-pCR using ROC AUC (95% CI) for change in measured tumor size from pre-treatment time point to early-treatment time point was 0.65 (0.38-0.92) for the RSI 3C classifier, 0.64 (0.36-0.91) for DCE, and 0.45 (0.16-0.75) for change in mean ADC. Sensitivity for detection of residual disease post-treatment was 0.71 (0.44-0.90) for the RSI 3C classifier, compared to 0.88 (0.64-0.99) for DCE and 0.76 (0.50-0.93) for ADC. Specificity was 0.90 (0.56-1.00) for the RSI 3C classifier, 0.70 (0.35-0.93) for DCE, and 0.50 (0.19-0.81) for ADC., Conclusion: The automatic RSI 3C classifier with elastic image registration suggested prediction of response to treatment after only three weeks, and showed performance comparable to DCE for assessment of residual tumor post-therapy. RSI 3C may guide clinical decision-making and enable tailored treatment regimens and cost-efficient evaluation of neoadjuvant therapy of breast cancer., Competing Interests: Author AMD is employed and holds equity in CorTechs Labs, Inc., and serves on its Scientific Advisory Board. He is a member of the Scientific Advisory Board of Human Longevity, Inc. Author RRP is a consultant of Human Longevity, Inc. She has equity interest in CorTechs Labs, Inc. and is on their Scientific Advisory Board, Inc. She has equity interest in Curemetrix and is on the Scientific Advisory Board of Imagine Scientific. Author TMS reports honoraria from Varian Medical Systems and WebMD; he has an equity interest in CorTechs Labs, Inc. and serves on its Scientific Advisory Board. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Andreassen, Loubrie, Tong, Fang, Seibert, Wallace, Zare, Ojeda-Fournier, Kuperman, Hahn, Jerome, Bathen, Rodríguez-Soto, Dale and Rakow-Penner.)

Introduction: The five-class Dixon-based PET/MR attenuation correction (AC) model, which adds bone information to the four-class model by registering major bones from a bone atlas, has been shown to be error-prone. In this study, we introduce a novel method of accounting for bone in pelvic PET/MR AC by directly predicting the errors in the PET image space caused by the lack of bone in four-class Dixon-based attenuation correction., Methods: A convolutional neural network was trained to predict the four-class AC error map relative to CT-based attenuation correction. Dixon MR images and the four-class attenuation correction µ -map were used as input to the models. CT and PET/MR examinations for 22 patients ([ 18 F]FDG) were used for training and validation, and 17 patients were used for testing (6 [ 18 F]PSMA-1007 and 11 [ 68 Ga]Ga-PSMA-11). A quantitative analysis of PSMA uptake using voxel- and lesion-based error metrics was used to assess performance., Results: In the voxel-based analysis, the proposed model reduced the median root mean squared percentage error from 12.1% and 8.6% for the four- and five-class Dixon-based AC methods, respectively, to 6.2%. The median absolute percentage error in the maximum standardized uptake value (SUV max ) in bone lesions improved from 20.0% and 7.0% for four- and five-class Dixon-based AC methods to 3.8%., Conclusion: The proposed method reduces the voxel-based error and SUV max errors in bone lesions when compared to the four- and five-class Dixon-based AC models., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Abrahamsen, Knudtsen, Eikenes, Bathen and Elschot.)