The ISMRM Open Science Initiative for Perfusion Imaging (OSIPI): Results from the OSIPI-Dynamic Contrast-Enhanced challenge.

PURPOSE: K trans $$ {K}^{\mathrm{trans}} $$ has often been proposed as a quantitative imaging biomarker for diagnosis, prognosis, and treatment response assessment for various tumors. None of the many software tools for K trans $$ {K}^{\mathrm{trans}} $$ quantification are standardized. The ISMRM Open Science Initiative for Perfusion Imaging-Dynamic Contrast-Enhanced (OSIPI-DCE) challenge was designed to benchmark methods to better help the efforts to standardize K trans $$ {K}^{\mathrm{trans}} $$ measurement. METHODS: A framework was created to evaluate K trans $$ {K}^{\mathrm{trans}} $$ values produced by DCE-MRI analysis pipelines to enable benchmarking. The perfusion MRI community was invited to apply their pipelines for K trans $$ {K}^{\mathrm{trans}} $$ quantification in glioblastoma from clinical and synthetic patients. Submissions were required to include the entrants' K trans $$ {K}^{\mathrm{trans}} $$ values, the applied software, and a standard operating procedure. These were evaluated using the proposed OSIP I gold $$ \mathrm{OSIP}{\mathrm{I}}_{\mathrm{gold}} $$ score defined with accuracy, repeatability, and reproducibility components. RESULTS: Across the 10 received submissions, the OSIP I gold $$ \mathrm{OSIP}{\mathrm{I}}_{\mathrm{gold}} $$ score ranged from 28% to 78% with a 59% median. The accuracy, repeatability, and reproducibility scores ranged from 0.54 to 0.92, 0.64 to 0.86, and 0.65 to 1.00, respectively (0-1 = lowest-highest). Manual arterial input function selection markedly affected the reproducibility and showed greater variability in K trans $$ {K}^{\mathrm{trans}} $$ analysis than automated methods. Furthermore, provision of a detailed standard operating procedure was critical for higher reproducibility. CONCLUSIONS: This study reports results from the OSIPI-DCE challenge and highlights the high inter-software variability within K trans $$ {K}^{\mathrm{trans}} $$ estimation, providing a framework for ongoing benchmarking against the scores presented. Through this challenge, the participating teams were ranked based on the performance of their software tools in the particular setting of this challenge. In a real-world clinical setting, many of these tools may perform differently with different benchmarking methodology.

Bench to Bedside Development of [18F]Fluoromethyl-(1,2-2H4)choline ([18F]D4-FCH).

Malignant transformation is characterised by aberrant phospholipid metabolism of cancers, associated with the upregulation of choline kinase alpha (CHKα). Due to the metabolic instability of choline radiotracers and the increasing use of late-imaging protocols, we developed a more stable choline radiotracer, [18F]fluoromethyl-[1,2-2H4]choline ([18F]D4-FCH). [18F]D4-FCH has improved protection against choline oxidase, the key choline catabolic enzyme, via a 1H/2D isotope effect, together with fluorine substitution. Due to the promising mechanistic and safety profiles of [18F]D4-FCH in vitro and preclinically, the radiotracer has transitioned to clinical development. [18F]D4-FCH is a safe positron emission tomography (PET) tracer, with a favourable radiation dosimetry profile for clinical imaging. [18F]D4-FCH PET/CT in lung and prostate cancers has shown highly heterogeneous intratumoral distribution and large lesion variability. Treatment with abiraterone or enzalutamide in metastatic castrate-resistant prostate cancer patients elicited mixed responses on PET at 12-16 weeks despite predominantly stable radiological appearances. The sum of the weighted tumour-to-background ratios (TBRs-wsum) was associated with the duration of survival.

Radiomics-based decision support tool assists radiologists in small lung nodule classification and improves lung cancer early diagnosis.

BACKGROUND: Methods to improve stratification of small (≤15 mm) lung nodules are needed. We aimed to develop a radiomics model to assist lung cancer diagnosis. METHODS: Patients were retrospectively identified using health records from January 2007 to December 2018. The external test set was obtained from the national LIBRA study and a prospective Lung Cancer Screening programme. Radiomics features were extracted from multi-region CT segmentations using TexLab2.0. LASSO regression generated the 5-feature small nodule radiomics-predictive-vector (SN-RPV). K-means clustering was used to split patients into risk groups according to SN-RPV. Model performance was compared to 6 thoracic radiologists. SN-RPV and radiologist risk groups were combined to generate "Safety-Net" and "Early Diagnosis" decision-support tools. RESULTS: In total, 810 patients with 990 nodules were included. The AUC for malignancy prediction was 0.85 (95% CI: 0.82-0.87), 0.78 (95% CI: 0.70-0.85) and 0.78 (95% CI: 0.59-0.92) for the training, test and external test datasets, respectively. The test set accuracy was 73% (95% CI: 65-81%) and resulted in 66.67% improvements in potentially missed [8/12] or delayed [6/9] cancers, compared to the radiologist with performance closest to the mean of six readers. CONCLUSIONS: SN-RPV may provide net-benefit in terms of earlier cancer diagnosis.

Feasibility of [18F]fluoropivalate hybrid PET/MRI for imaging lower and higher grade glioma: a prospective first-in-patient pilot study.

PURPOSE: MRI and PET are used in neuro-oncology for the detection and characterisation of lesions for malignancy to target surgical biopsy and to plan surgical resections or stereotactic radiosurgery. The critical role of short-chain fatty acids (SCFAs) in brain tumour biology has come to the forefront. The non-metabolised SCFA radiotracer, [18F]fluoropivalate (FPIA), shows low background signal in most tissues except eliminating organs and has appropriate human dosimetry. Tumour uptake of the radiotracer is, however, unknown. We investigated the uptake characteristics of FPIA in this pilot PET/MRI study. METHODS: Ten adult glioma subjects were identified based on radiological features using standard-of-care MRI prior to any surgical intervention, with subsequent histopathological confirmation of glioma subtype and grade (lower-grade - LGG - and higher-grade - HGG - patients). FPIA was injected as an intravenous bolus injection (range 342-368 MBq), and dynamic PET and MRI data were acquired simultaneously over 66 min. RESULTS: All patients tolerated the PET/MRI protocol. Three patients were reclassified following resection and histology. Tumour maximum standardised uptake value (SUVmax,60) increased in the order LGG (WHO grade 2) < HGG (WHO grade 3) < HGG (WHO grade 4). The net irreversible solute transfer, Ki, and influx rate constant, K1, were significantly higher in HGG (p < 0.05). Of the MRI variables studied, DCE-MRI-derived extravascular-and-extracellular volume fraction (ve) was high in tumours of WHO grade 4 compared with other grades (p < 0.05). SLC25A20 protein expression was higher in HGG compared with LGG. CONCLUSION: Tumoural FPIA PET uptake is higher in HGG compared to LGG. This study supports further investigation of FPIA PET/MRI for brain tumour imaging in a larger patient population. CLINICAL TRIAL REGISTRATION: Clinicaltrials.gov, NCT04097535.

Dynomics: A Novel and Promising Approach for Improved Breast Cancer Prognosis Prediction.

Traditional imaging techniques for breast cancer (BC) diagnosis and prediction, such as X-rays and magnetic resonance imaging (MRI), demonstrate varying sensitivity and specificity due to clinical and technological factors. Consequently, positron emission tomography (PET), capable of detecting abnormal metabolic activity, has emerged as a more effective tool, providing critical quantitative and qualitative tumor-related metabolic information. This study leverages a public clinical dataset of dynamic 18F-Fluorothymidine (FLT) PET scans from BC patients, extending conventional static radiomics methods to the time domain-termed as 'Dynomics'. Radiomic features were extracted from both static and dynamic PET images on lesion and reference tissue masks. The extracted features were used to train an XGBoost model for classifying tumor versus reference tissue and complete versus partial responders to neoadjuvant chemotherapy. The results underscored the superiority of dynamic and static radiomics over standard PET imaging, achieving accuracy of 94% in tumor tissue classification. Notably, in predicting BC prognosis, dynomics delivered the highest performance, achieving accuracy of 86%, thereby outperforming both static radiomics and standard PET data. This study illustrates the enhanced clinical utility of dynomics in yielding more precise and reliable information for BC diagnosis and prognosis, paving the way for improved treatment strategies.

Spatiotemporal learning of dynamic positron emission tomography data improves diagnostic accuracy in breast cancer.

Positron emission tomography (PET) can reveal metabolic activity in a voxelwise manner. PET analysis is commonly performed in a static manner by analyzing the standardized uptake value (SUV) obtained from the plateau region of PET acquisitions. A dynamic PET acquisition can provide a map of the spatiotemporal concentration of the tracer in vivo, hence conveying information about radiotracer delivery to tissue, its interaction with the target and washout. Therefore, tissue-specific biochemical properties are embedded in the shape of time activity curves (TACs), which are generally used for kinetic analysis. Conventionally, TACs are employed along with information about blood plasma activity concentration, i.e., the arterial input function (AIF), and specific compartmental models to obtain a full quantitative analysis of PET data. The main drawback of this approach is the need for invasive procedures requiring arterial blood sample collection during the whole PET scan. In this paper, we address the challenge of improving PET diagnostic accuracy through an alternative approach based on the analysis of time signal intensity patterns. Specifically, we demonstrate the diagnostic potential of tissue TACs provided by dynamic PET acquisition using various deep learning models. Our framework is shown to outperform the discriminative potential of classical SUV analysis, hence paving the way for more accurate PET-based lesion discrimination without additional acquisition time or invasive procedures. Clinical Relevance- The diagnostic accuracy of dynamic PET data exploited by deep-learning based time signal intensity pattern analysis is superior to that of static SUV imaging.

A predictive model using the mesoscopic architecture of the living brain to detect Alzheimer's disease.

Background: Alzheimer's disease, the most common cause of dementia, causes a progressive and irreversible deterioration of cognition that can sometimes be difficult to diagnose, leading to suboptimal patient care. Methods: We developed a predictive model that computes multi-regional statistical morpho-functional mesoscopic traits from T1-weighted MRI scans, with or without cognitive scores. For each patient, a biomarker called "Alzheimer's Predictive Vector" (ApV) was derived using a two-stage least absolute shrinkage and selection operator (LASSO). Results: The ApV reliably discriminates between people with (ADrp) and without (nADrp) Alzheimer's related pathologies (98% and 81% accuracy between ADrp - including the early form, mild cognitive impairment - and nADrp in internal and external hold-out test sets, respectively), without any a priori assumptions or need for neuroradiology reads. The new test is superior to standard hippocampal atrophy (26% accuracy) and cerebrospinal fluid beta amyloid measure (62% accuracy). A multiparametric analysis compared DTI-MRI derived fractional anisotropy, whose readout of neuronal loss agrees with ADrp phenotype, and SNPrs2075650 is significantly altered in patients with ADrp-like phenotype. Conclusions: This new data analytic method demonstrates potential for increasing accuracy of Alzheimer diagnosis.

Alzheimer's disease is the most common cause of dementia, impacting memory, thinking and behaviour. It can be challenging to diagnose Alzheimer's disease which can lead to suboptimal patient care. During the development of Alzheimer's disease the brain shrinks and the cells within it die. One method that can be used to assess brain function is magnetic resonance imaging, which uses magnetic fields and radio waves to produce images of the brain. In this study, we develop a method that uses magnetic resonance imaging data to identify differences in the brain between people with and without Alzheimer's disease, including before obvious shrinkage of the brain occurs. This method could be used to help diagnose patients with Alzheimer's Disease.

Consideration of Metabolite Efflux in Radiolabelled Choline Kinetics.

Hypoxia is a complex microenvironmental condition known to regulate choline kinase α (CHKA) activity and choline transport through transcription factor hypoxia-inducible factor-1α (HIF-1α) and, therefore, may confound the uptake of choline radiotracer [18F]fluoromethyl-[1,2-2H4]-choline ([18F]-D4-FCH). The aim of this study was to investigate how hypoxia affects the choline radiotracer dynamics. Three underlying mechanisms by which hypoxia could potentially alter the uptake of the choline radiotracer, [18F]-D4-FCH, were investigated: 18F-D4-FCH import, CHKA phosphorylation activity, and the efflux of [18F]-D4-FCH and its phosphorylated product [18F]-D4-FCHP. The effects of hypoxia on [18F]-D4-FCH uptake were studied in CHKA-overexpressing cell lines of prostate cancer, PC-3, and breast cancer MDA-MB-231 cells. The mechanisms of radiotracer efflux were assessed by the cell uptake and immunofluorescence in vitro and examined in vivo (n = 24). The mathematical modelling methodology was further developed to verify the efflux hypothesis using [18F]-D4-FCH dynamic PET scans from non-small cell lung cancer (NSCLC) patients (n = 17). We report a novel finding involving the export of phosphorylated [18F]-D4-FCH and [18F]-D4-FCHP via HIF-1α-responsive efflux transporters, including ABCB4, when the HIF-1α level is augmented. This is supported by a graphical analysis of human data with a compartmental model (M2T6k + k5) that accounts for the efflux. Hypoxia/HIF-1α increases the efflux of phosphorylated radiolabelled choline species, thus supporting the consideration of efflux in the modelling of radiotracer dynamics.

Spatial heterogeneity of radiolabeled choline positron emission tomography in tumors of patients with non-small cell lung cancer: first-in-patient evaluation of [18F]fluoromethyl-(1,2-2H4)-choline.

Purpose: The spatio-molecular distribution of choline and its metabolites in tumors is highly heterogeneous. Due to regulation of choline metabolism by hypoxic transcriptional signaling and other survival factors, we envisage that detection of such heterogeneity in patient tumors could provide the basis for advanced localized therapy. However, non-invasive methods to assess this phenomenon in patients are limited. We investigated such heterogeneity in Non-Small Cell Lung Cancer (NSCLC) with [18F]fluoromethyl-(1,2-2H4) choline ([18F]D4-FCH) and positron emission tomography/computed tomography (PET/CT). Experimental design: [18F]D4-FCH (300.5±72.9MBq [147.60-363.6MBq]) was administered intravenously to 17 newly diagnosed NSCLC patients. PET/CT scans were acquired concurrently with radioactive blood sampling to permit mathematical modelling of blood-tissue transcellular rate constants. Comparisons were made with biopsy-derived choline kinase-α (CHKα) expression and diagnostic [18F]fluorodeoxyglucose ([18F]FDG) scans. Results: Oxidation of [18F]D4-FCH to [18F]D4-fluorobetaine was suppressed (48.58±0.31% parent at 60 min) likely due to the deuterium isotope effect embodied within the design of the radiotracer. Early (5 min) and late (60 min) images showed specific uptake of tracer in all 51 lesions (tumors, lymph nodes and metastases) from 17 patients analyzed. [18F]D4-FCH-derived uptake (SUV60max) in index primary lesions (n=17) ranged between 2.87-10.13; lower than that of [18F]FDG PET [6.89-22.64]. Mathematical modelling demonstrated net irreversible uptake of [18F]D4-FCH at steady-state, and parametric mapping of the entire tumor showed large intratumorally heterogeneity in radiotracer retention, which is likely to have influenced correlations with biopsy-derived CHKα expression. Conclusions: [18F]D4-FCH is detectable in NSCLC with large intratumorally heterogeneity, which could be exploited in the future for targeting localized therapy.

Monitoring Response to Transarterial Chemoembolization in Hepatocellular Carcinoma Using 18F-Fluorothymidine PET.

Accurate disease monitoring is essential after transarterial chemoembolization (TACE) in hepatocellular carcinoma (HCC) because of the potential for profound adverse events and large variations in survival outcome. Posttreatment changes on conventional imaging can confound determination of residual or recurrent disease, magnifying the clinical challenge. On the basis of increased expression of thymidylate synthase (TYMS), thymidine kinase 1 (TK-1), and equilibrative nucleoside transporter 1 (SLC29A1) in HCC compared with liver tissue, we conducted a proof-of-concept study evaluating the efficacy of 3'-deoxy-3'-18F-fluorothymidine (18F-FLT) PET to assess response to TACE. Because previous PET studies in HCC have been hampered by high background liver signal, we investigated whether a temporal-intensity voxel clustering (kinetic spatial filtering, or KSF) improved lesion detection. Methods: A tissue microarray was built from 36 HCC samples and from matching surrounding cirrhotic tissue and was stained for TK-1 A prospective study was conducted; 18 patients with a diagnosis of HCC by the criteria of the American Association for the Study of Liver Diseases who were eligible for treatment with TACE were enrolled. The patients underwent baseline conventional imaging and dynamic 18F-FLT PET with KSF followed by TACE. Imaging was repeated 6-8 wk after TACE. The PET parameters were compared with modified enhancement-based RECIST. Results: Cancer Genome Atlas analysis revealed increased RNA expression of TYMS, TK-1, and SLC29A1 in HCC. TK-1 protein expression was significantly higher in HCC (P < 0.05). The sensitivity of 18F-FLT PET for baseline HCC detection was 73% (SUVmax, 9.7 ± 3.0; tumor to liver ratio, 1.2 ± 0.3). Application of KSF did not improve lesion detection. Lesion response after TACE by modified RECIST was 58% (14 patients with 24 lesions). A 30% reduction in mean 18F-FLT PET uptake was observed after TACE, correlating with an observed PET response of 60% (15/25). A significant and profound reduction in the radiotracer delivery parameter K1 after TACE was observed. Conclusion:18F-FLT PET can differentiate HCC from surrounding cirrhotic tissue, with PET parameters correlating with TACE response. KSF did not improve visualization of tumor lesions. These findings warrant further investigation.

[18F]Fluciclatide PET as a biomarker of response to combination therapy of pazopanib and paclitaxel in platinum-resistant/refractory ovarian cancer.

BACKGROUND: Angiogenesis is a driver of platinum resistance in ovarian cancer. We assessed the effect of combination pazopanib and paclitaxel followed by maintenance pazopanib in patients with platinum-resistant/refractory ovarian cancer. Integrins αvß3 and αvß5 are both upregulated in tumor-associated vasculature. [18F]Fluciclatide is a novel PET tracer that has high affinity for integrins αvß3/5, and was used to assess the anti-angiogenic effect of pazopanib. PATIENTS AND METHODS: We conducted an open-label, phase Ib study in patients with platinum-resistant/refractory ovarian cancer. Patients received 1 week of single-agent pazopanib (800 mg daily) followed by combination therapy with weekly paclitaxel (80 mg/m2). Following completion of 18 weeks of combination therapy, patients continued with single-agent pazopanib until disease progression. Dynamic [18F]fluciclatide-PET imaging was conducted at baseline and after 1 week of pazopanib. Response (RECIST 1.1), toxicities, and survival outcomes were recorded. Circulating markers of angiogenesis were assessed with therapy. RESULTS: Fourteen patients were included in the intention-to-treat analysis. Complete and partial responses were seen in seven patients (54%). Median progression-free survival (PFS) was 10.63 months, and overall survival (OS) was 18.5 months. Baseline [18F]fluciclatide uptake was predictive of long PFS. Elevated baseline circulating angiopoietin and fibroblast growth factor (FGF) were predictive of greater reduction in SUV60,mean following pazopanib. Kinetic modeling of PET data indicated a reduction in K1 and Ki following pazopanib indicating reduced radioligand delivery and retention. CONCLUSIONS: Combination therapy followed by maintenance pazopanib is effective and tolerable in platinum-resistant/refractory ovarian cancer. [18F]Fluciclatide-PET uptake parameters predict clinical outcome with pazopanib therapy indicating an anti-angiogenic response.

Reliability of dynamic contrast-enhanced magnetic resonance imaging data in primary brain tumours: a comparison of Tofts and shutter speed models.

PURPOSE: The purpose of this study is to investigate the robustness of pharmacokinetic modelling of DCE-MRI brain tumour data and to ascertain reliable perfusion parameters through a model selection process and a stability test. METHODS: DCE-MRI data of 14 patients with primary brain tumours were analysed using the Tofts model (TM), the extended Tofts model (ETM), the shutter speed model (SSM) and the extended shutter speed model (ESSM). A no-effect model (NEM) was implemented to assess overfitting of data by the other models. For each lesion, the Akaike Information Criteria (AIC) was used to build a 3D model selection map. The variability of each pharmacokinetic parameter extracted from this map was assessed with a noise propagation procedure, resulting in voxel-wise distributions of the coefficient of variation (CV). RESULTS: The model selection map over all patients showed NEM had the best fit in 35.5% of voxels, followed by ETM (32%), TM (28.2%), SSM (4.3%) and ESSM (< 0.1%). In analysing the reliability of Ktrans, when considering regions with a CV < 20%, ≈ 25% of voxels were found to be stable across all patients. The remaining 75% of voxels were considered unreliable. CONCLUSIONS: The majority of studies quantifying DCE-MRI data in brain tumours only consider a single model and whole tumour statistics for the output parameters. Appropriate model selection, considering tissue biology and its effects on blood brain barrier permeability and exchange conditions, together with an analysis on the reliability and stability of the calculated parameters, is critical in processing robust brain tumour DCE-MRI data.

A multi-parametric PET/MRI study of breast cancer: Evaluation of DCE-MRI pharmacokinetic models and correlation with diffusion and functional parameters.

46 patients with histologically confirmed breast cancer were enrolled and imaged with a 3T hybrid PET/MRI system, at staging. Diffusion, functional and perfusion parameters (measured by Tofts and shutter speed models) were compared. Results showed a good correlation between pharmacokinetic parameters and the SUV.

Relationship between functional imaging and immunohistochemical markers and prediction of breast cancer subtype: a PET/MRI study.

PURPOSE: The aim of this study was to determine if functional parameters extracted from the hybrid positron emission tomography/magnetic resonance imaging (PET/MRI) correlate with the immunohistochemical markers of breast cancer (BC) lesions, to assess their ability to predict BC subtype. METHODS: This prospective study was approved by the institution's Ethics Committee, and all patients provided written informed consent. A total of 50 BC patients at diagnosis underwent PET/MRI before pharmacological and surgical treatment. For each primary lesion, the following data were extracted: morphological data including tumour-node-metastasis stage and lesion size; apparent diffusion coefficient (ADC); perfusion data including forward volume transfer constant (Ktrans), reverse efflux volume transfer constant (Kep) and extravascular extracellular space volume (Ve); and metabolic data including standardized uptake value (SUV), lean body mass (SUL), metabolic tumour volume and total lesion glycolysis. Immunohistochemical reports were used to determine receptor status (oestrogen, progesterone, and human epidermal growth factor receptor 2), cellular differentiation status (grade), and proliferation index (Ki67) of the tumour lesions. Correlation studies (Mann-Whitney U test and Spearman's test), receiver operating characteristic (ROC) curve analysis, and multivariate analysis were performed. RESULTS: Association studies were performed to assess the correlations between imaging and histological prognostic markers of BC. Imaging biomarkers, which significantly correlated with biological markers, were selected to perform ROC curve analysis to determine their ability to discriminate among BC subtypes. SUVmax, SUVmean and SUL were able to discriminate between luminal A and luminal B subtypes (AUCSUVmean = 0.799; AUCSUVmax = 0.833; AUCSUL = 0.813) and between luminal A and nonluminal subtypes (AUCSUVmean = 0.926; AUCSUVmax = 0.917; AUCSUL = 0.945), and the lowest SUV and SUL values were associated with the luminal A subtype. Kepmax was able to discriminate between luminal A and luminal B subtypes (AUC = 0.779), and its highest values were associated with the luminal B subtype. Ktransmax (AUC = 0.881) was able to discriminate between luminal A and nonluminal subtypes, and the highest perfusion values were associated with the nonluminal subtype. In addition, ADC (AUC = 0.877) was able to discriminate between luminal B and nonluminal subtypes, and the lowest ADCmean values were associated with the luminal B subtype. Multivariate analysis was performed to develop a prognostic model, and the best predictive model included Ktransmax and SUVmax parameters. CONCLUSION: Using multivariate analysis of both PET and MRI parameters, a prognostic model including Ktransmax and SUVmax was able to predict the tumour subtype in 38 of 49 patients (77.6%, p < 0.001), with higher accuracy for the luminal B subtype (86.2%).

Postprandial Gastrointestinal Function Differs after Acute Administration of Sourdough Compared with Brewer's Yeast Bakery Products in Healthy Adults.

Background: Europeans consume large quantities of bakery products, although these are known as one of the food categories that potentially leads to postprandial symptoms (such as fullness and bloating). Objective: The aim of this study was to evaluate the effects of sourdough baked goods on gastric emptying and gastrointestinal fermentation and symptoms in healthy people. Methods: In a double-blind, randomized crossover study, 2 sourdough croissants (SCs) or 2 brewer's yeast croissants (BCs) were served as single meals to 17 healthy adults [9 women; age range: 18-40 y; body mass index range (in kg/m2): 18-24]. Gastric volume (GV) was evaluated by magnetic resonance to calculate gastric-emptying rate in the 3-h interval after croissant ingestion. A hydrogen breath test was performed to measure hydrogen production after SC and BC ingestion. Palatability and postprandial gastrointestinal symptoms (discomfort, nausea, fullness, and bloating) over a 4-h period after the meal were evaluated. The area under the curve (AUC) was used to evaluate the overall effects on all variables tested. Results: The total GV AUC was reduced by 11% during the 3 h after the consumption of SCs compared with BCs (P = 0.02). Hydrogen production during the 4-h interval after ingestion of SCs was 30% lower than after BCs (P = 0.03). SCs were rated as being >2 times as palatable as BCs (P < 0.001). The overall severity of postprandial symptoms was 36% lower during the 4 h after intake of SCs compared with BCs (P = 0.05). Conclusion: Sourdough bakery products could promote better postprandial gastrointestinal function in healthy adults and be more acceptable than those prepared with brewer's yeast. This trial was registered at www.clinicaltrials.gov as NCT03207516.

Coronary artery aneurysms detected by computed tomography coronary angiography.

AIMS: Coronary artery aneurysms (CAAs) are incidentally revealed by coronary angiography and consist in a localized dilation of a coronary artery. Although invasive coronary angiography (ICA) is the gold standard imaging technique, it can lead to the underestimation of CAAs diameter in presence of parietal thrombi. Computed tomography coronary angiography (CTCA) is a very sensitive tool in CAAs detection and provides a clear visualization of coronary lumen highlighting intraluminal thrombi. METHODS AND RESULTS: We retrospectively reviewed 390 CTCA performed at our institution, 9 patients (6 men, 3 women) resulted affected by CAAs and represented the aneurysmal group (A group). Matched controls were identified among the non-aneurysmal patients with healthy coronaries to CTCA (NAH group). Clinical variables and imaging findings were compared and correlated. CAAs prevalence in our population was 2.31%. 15 CAAs were detected, mainly on the right coronary artery (RCA) (9 aneurysms) followed by the left anterior descending coronary artery (LAD) (three aneurysms) and the left circumflex coronary artery (CX) (three aneurysms). In six patients (66.7%) CTCA displayed an aneurysmal thrombosis and in 5 patients (55.5%) CAAs were associated to coronary artery stenoses. A statistically significant difference was found between the diameters of coronary vessels measured in healthy segments in A and NAH group. CONCLUSIONS: CTCA has led to a non-invasive estimation of CAAs prevalence and characterization of aneurysmal features and coronary anatomy. Overcoming ICA limitations, CTCA has provided a fine analysis of the aneurysms, also in presence of intraluminal thrombi.

Anomalous left main coronary artery detected by CT angiography.

The growing improvements of computed tomography have made this technique more and more available for cardiac evaluation. Coronary artery anomalies (CAAs) are often incidental findings in subjects with suspected coronary artery disease (CAD) undergoing coronary angiography or computed tomography coronary angiography (CTCA). In some cases, CAAs can be clinically relevant so their identification could change radically patient management and treatment. We report the case of a 68-year-old male patient with known CAD and associated anomalous origination of the left coronary artery from the opposite sinus.