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Abstract Objective The dentato‐thalamo‐cortical tract (DTT) is the main cerebellar efferent pathway. Degeneration of the DTT is a core feature of Friedreich ataxia (FRDA). However, it remains unclear whether DTT disruption is spatially specific, with some segments being more impacted than others. This study aimed to investigate microstructural integrity along the DTT in FRDA using a profilometry diffusion MRI (dMRI) approach. Methods MRI data from 45 individuals with FRDA (mean age: 33.2 ± 13.2, Male/Female: 26/19) and 37 healthy controls (mean age: 36.5 ± 12.7, Male/Female:18/19) were included in this cross‐sectional multicenter study. A profilometry analysis was performed on dMRI data by first using tractography to define the DTT as the white matter pathway connecting the dentate nucleus to the contralateral motor cortex. The tract was then divided into 100 segments, and dMRI metrics of microstructural integrity (fractional anisotropy, mean diffusivity and radial diffusivity) at each segment were compared between groups. The process was replicated on the arcuate fasciculus for comparison. Results Across all diffusion metrics, the region of the DTT connecting the dentate nucleus and thalamus was more impacted in FRDA than downstream cerebral sections from the thalamus to the cortex. The arcuate fasciculus was minimally impacted. Interpretation Our study further expands the current knowledge about brain involvement in FRDA, showing that microstructural abnormalities within the DTT are weighted to early segments of the tract (i.e., the superior cerebellar peduncle). These findings are consistent with the hypothesis of DTT undergoing anterograde degeneration arising from the dentate nuclei and progressing to the primary motor cortex.

The chicken embryo has emerged as a valuable model for preclinical studies due to its unique combination of accessibility, affordability, and relevance to human biology. Its rapid development, external growth environment, and clear structural visibility offer distinct advantages over traditional mammalian models. These features facilitate the study of real-time biological processes, including tissue development, tumor growth, angiogenesis, and drug delivery, using various imaging modalities, such as optical imaging, magnetic resonance imaging, positron emission tomography, computed tomography, and ultrasound. The chicken embryo model also minimizes ethical concerns compared to mammalian models, as it allows for early-stage research without the complexity of a fully developed animal. Moreover, its ability to integrate human tumor cells into xenograft models provides a reliable platform for cancer research, enabling high-throughput screening of therapeutic interventions and tracking molecular dynamics in vivo. Advances in molecular imaging techniques further enhance the resolution and depth of data obtained from these studies, offering insights into cellular and molecular mechanisms underlying disease. Given its versatility, cost-effectiveness, and translational potential, the chicken embryo represents a promising tool for advancing preclinical research, particularly in drug development, cancer biology, and regenerative medicine.

Abstract Despite the key-role of the Prostate Imaging and Reporting and Data System (PI-RADS) in the diagnosis and characterization of prostate cancer (PCa), this system remains to be affected by several limitations, primarily associated with the interpretation of equivocal PI-RADS 3 lesions and with the debated role of Dynamic Contrast Enhanced-Magnetic Resonance Imaging (DCE-MRI), which is only used to upgrade peripheral PI-RADS category 3 lesions to PI-RADS category 4 if enhancement is focal. We aimed at investigating the usefulness of radiomics for detection of PCa lesions (Gleason Score ≥ 6) in PI-RADS 3 lesions and in peripheral PI-RADS 3 upgraded to PI-RADS 4 lesions (upPI-RADS 4). Multiparametric MRI (mpMRI) data of patients who underwent prostatic mpMRI between April 2013 and September 2018 were retrospectively evaluated. Biopsy results were used as gold standard. PI-RADS 3 and PI-RADS 4 lesions were re-scored according to the PI-RADS v2.1 before and after DCE-MRI evaluation. Radiomic features were extracted from T2-weighted MRI (T2), Apparent diffusion Coefficient (ADC) map and DCE-MRI subtracted images using PyRadiomics. Feature selection was performed using Wilcoxon-ranksum test and Minimum Redundancy Maximum Relevance (mRMR). Predictive models were constructed for PCa detection in PI-RADS 3 and upPI-RADS 4 lesions using at each step an imbalance-adjusted bootstrap resampling (IABR) on 1000 samples. 41 PI-RADS 3 and 32 upPI-RADS 4 lesions were analyzed. Among 293 radiomic features, the top selected features derived from T2 and ADC. For PI-RADS 3 stratification, second order model showed higher performances (Area Under the Receiver Operating Characteristic Curve—AUC— = 80%), while for upPI-RADS 4 stratification, first order model showed higher performances respect to superior order models (AUC = 89%). Our results support the significant role of T2 and ADC radiomic features for PCa detection in lesions scored as PI-RADS 3 and upPI-RADS 4. Radiomics models showed high diagnostic efficacy in classify PI-RADS 3 and upPI-RADS 4 lesions, outperforming PI-RADS v2.1 performance.

Abstract Genomic and radiomic data integration, namely radiogenomics, can provide meaningful knowledge in cancer diagnosis, prognosis and treatment. Despite several data structures based on multi-layer architecture proposed to combine multi-omic biological information, none of these has been designed and assessed to include radiomic data as well. To meet this need, we propose to use the MultiAssayExperiment (MAE), an R package that provides data structures and methods for manipulating and integrating multi-assay experiments, as a suitable tool to manage radiogenomic experiment data. To this aim, we first examine the role of radiogenomics in cancer phenotype definition, then the current state of radiogenomics data integration in public repository and, finally, challenges and limitations of including radiomics in MAE, designing an extended framework and showing its application on a case study from the TCGA-TCIA archives. Radiomic and genomic data from 91 patients have been successfully integrated in a single MAE object, demonstrating the suitability of the MAE data structure as container of radiogenomic data.

Introduction Treatment options for non-alcoholic fatty liver disease (NAFLD) in patients with type 2 diabetes (T2D) are still a matter of debate. We compared the effects of a diet including different components versus a proven beneficial diet rich in monounsaturated fatty acids (MUFAs) on liver fat in T2D.Research design and methods According to a parallel design, 49 individuals with T2D, overweight/obese, with high waist circumference, 35–75 years-old, in satisfactory blood glucose control with diet or drugs not affecting liver fat content, were randomly assigned to an 8-week isocaloric intervention with a MUFA diet (n=26) or a multifactorial diet rich in fiber, MUFA, n-6 and n-3 polyunsaturated fatty acids, polyphenols, and vitamins D, E, and C (n=23). Before and after the intervention, liver fat content was evaluated by proton magnetic resonance spectroscopy (1H-MRS). 1H-MRS complete data were available for n=21 (MUFA diet) and n=18 (multifactorial diet) participants.Results Adherence to dietary interventions was optimal. No significant differences between groups in body weight reduction, plasma glycated hemoglobin, insulin, glucose, lipids and liver enzymes were observed. Liver fat significantly decreased after both the multifactorial diet (9.18%±7.78% vs 5.22%±4.80%, p=0.003) and the MUFA diet (9.47%±8.89% vs 8.07%±8.52%, p=0.027) with a statistically significant difference between changes either in absolute terms (−4.0%±4.5% vs −1.4%±2.7%, p=0.035) or percent (−40%±33% vs −19%±25%, p=0.030).Conclusions An isocaloric multifactorial diet including several beneficial dietary components induced a clinically relevant reduction of liver fat in patients with T2D, more pronounced than that induced by simply replacing saturated fat with MUFA. This suggests that the ‘optimal diet’ for NAFLD treatment in T2D should be based on synergic actions of different dietary components on multiple pathophysiological pathways.Trial registration number NCT03380416.

Radiation therapy (RT) of thoracic cancers may cause severe radiation dermatitis (RD), which impacts on the quality of a patient's life. Aim of this study was to analyze the incidence of acute RD and develop normal tissue complication probability (NTCP) models for severe RD in thoracic cancer patients treated with Intensity-Modulated RT (IMRT) or Passive Scattering Proton Therapy (PSPT). We analyzed 166 Non-Small-Cell Lung Cancer (NSCLC) patients prospectively treated at a single institution with IMRT (103 patients) or PSPT (63 patients). All patients were treated to a prescribed dose of 60 to 74 Gy in conventional daily fractionation with concurrent chemotherapy. RD was scored according to CTCAE v3 scoring system. For each patient, the epidermis structure (skin) was automatically defined by an in house developed segmentation algorithm. The absolute dose-surface histogram (DSH) of the skin were extracted and normalized using the Body Surface Area (BSA) index as scaling factor. Patient and treatment-related characteristics were analyzed. The Lyman-Kutcher-Burman (LKB) NTCP model recast for DSH and the multivariable logistic model were adopted. Models were internally validated by Leave-One-Out method. Model performance was evaluated by the area under the receiver operator characteristic curve, and calibration plot parameters. Fifteen of 166 (9%) patients developed severe dermatitis (grade 3). RT technique did not impact RD incidence. Total gross tumor volume (GTV) size was the only non dosimetric variable significantly correlated with severe RD (p = 0.027). Multivariable logistic modeling resulted in a single variable model including S20Gy, the relative skin surface receiving more than 20 Gy (OR = 31.4). The cut off for S20Gy was 1.1% of the BSA. LKB model parameters were TD50 = 9.5 Gy, m = 0.24, n = 0.62. Both NTCP models showed comparably high prediction and calibration performances. Despite skin toxicity has long been considered a potential limiting factor in the clinical use of PSPT, no significant differences in RD incidence was found between RT modalities. Once externally validated, the availability of NTCP models for prediction of severe RD may advance treatment planning optimization.

Dixon-based methods for the detection of fatty liver have the advantage of being non-invasive, easy to perform and analyze, and to provide a whole-liver coverage during the acquisition. The aim of the study was to assess the feasibility of a whole-liver Dixon-based approach for liver fat quantification in type 2 diabetes (T2D) patients who underwent two different isocaloric dietary treatments: a diet rich in monosaturated fatty acids (MUFA) and a multifactorial diet. Thirty-nine T2D patients were randomly assigned to MUFA diet (n = 21) and multifactorial diet (n = 18). The mean values of the proton density fat fraction (PDFF) over the whole liver and over the ROI corresponding to that chosen for MRS were compared to MRS-PDFF using Spearman’s correlation (ρ). Before–after changes in percentage of liver volume corresponding to MRI-PDFF above thresholds associated with hepatic steatosis (LV%TH, with TH = 5.56%, 7.97% and 8.8%) were considered to assess the proposed approach and compared between diets using Wilcoxon rank-sum test. Statistical significance set at p < 0.05. A strong linear relationship was found between MRS-PDFF and MRI-PDFFs (ρ = 0.85, p < 0.0001). Changes in LV%TH% were significantly higher (p < 0.05) in the multifactorial diet than in MUFA diet (25% vs. 9%, 35% vs. 12%, and 38% vs. 13% decrease, respectively, for TH = 5.56%, 7.97%, and 8.8%) and this was reproducible compared to results obtained using the standard liver fat analysis. A volumetric approach based on Dixon method could be an effective, non-invasive technique that could be used for the quantitative analysis of hepatic steatosis in T2D patients.

Abstract Background Cancer patients often have a history of chemotherapy, putting them at increased risk of liver toxicity and pancytopenia, leading to elevated liver fat and elevated liver iron respectively. T1-in-and-out-of-phase, the conventional MR technique for liver fat assessment, fails to detect elevated liver fat in the presence of concomitantly elevated liver iron. IDEAL-IQ is a more recently introduced MR fat quantification method that corrects for multiple confounding factors, including elevated liver iron. Methods This retrospective study was approved by the institutional review board with a waiver for informed consent. We reviewed the MRI studies of 50 cancer patients (30 males, 20 females, 50–78 years old) whose exams included (1) T1-in-and-out-of-phase, (2) IDEAL-IQ, and (3) T2* mapping. Two readers independently assessed fat and iron content from conventional and IDEAL-IQ MR methods. Intraclass correlation coefficient (ICC) was estimated to evaluate agreement between conventional MRI and IDEAL-IQ in measuring R2* level (a surrogate for iron level), and in measuring fat level. Agreement between the two readers was also assessed. Wilcoxon signed rank test was employed to compare iron level and fat fraction between conventional MRI and IDEAL-IQ. Results Twenty percent of patients had both elevated liver iron and moderate/severe hepatic steatosis. Across all patients, there was high agreement between readers for IDEAL-IQ fat fraction (ICC = 0.957) and IDEAL R2* (ICC = 0.971) measurements, but lower agreement for conventional fat fraction measurements (ICC = 0.626). The fat fractions calculated with IOP were statistically significantly different from those calculated with IDEAL-IQ (reader 1: p

Abstract The risk of radiation-induced toxicity in patients treated for head and neck (HN) cancer with radiation therapy (RT) is traditionally estimated by condensing the 3D dose distribution into a monodimensional cumulative dose-volume histogram which disregards information on dose localization. We hypothesized that a voxel-based approach would identify correlations between radiation-induced morbidity and local dose release, thus providing a new insight into spatial signature of radiation sensitivity in composite regions like the HN district. This methodology was applied to a cohort of HN cancer patients treated with RT at risk of radiation-induced acute dysphagia (RIAD). We implemented an inter-patient elastic image registration framework that proved robust enough to match even the most elusive HN structures and to provide accurate dose warping. A voxel-based statistical analysis was then performed to test regional dosimetric differences between patients with and without RIAD. We identified a significantly higher dose delivered to RIAD patients in two voxel clusters in correspondence of the cricopharyngeus muscle and cervical esophagus. Our study goes beyond the well-established organ-based philosophy exploring the relationship between radiation-induced morbidity and local dose differences in the HN region. This approach is generally applicable to different HN toxicity endpoints and is not specific to RIAD.

Abstract Background Cholangitis is an inflammatory process of the biliary tract with a wide range of clinical manifestations and it is not always considered in the differential diagnosis in asymptomatic patients. To the best of our knowledge there is no previous report in the English literature of focal cholangitis manifesting exclusively as liver parenchymal changes mimicking liver metastasis in asymptomatic patients with pancreatic ductal adenocarcinoma (PDAC) and history of manipulation of the biliary tree. The purpose of this article is to present six cases of subclinical focal cholangitis mimicking liver metastasis in asymptomatic patients with history of PDAC and biliary tree intervention. Case presentation There are six cases with new hepatic lesions detected on follow-up scans in asymptomatic patients with history of PDAC and manipulation of biliary tree. Overall seven lesions were detected, all of them were on the liver periphery, five were hypovascular and two were hypervascular. None of those patients had elevation of CA 19.9 compared with the previous exams. The three patients that had magnetic resonance imaging presented restriction on diffusion weighted imaging and high signal intensity on T2-weighted image. Two patients underwent liver biopsy, which showed only inflammatory changes. All patients were treated with antibiotics and underwent imaging follow-up, which demonstrated resolution of the lesions. None of the patients showed imaging or clinical signs of disease progression during this interval. Conclusion Radiologists and oncologists need to be aware of the possibility of focal cholangitis causing hepatic lesions mimicking neoplasia in patients with history of biliary tree intervention, even in the absence of clinical symptoms.

In radiation oncology, the need for a modern Normal Tissue Complication Probability (NTCP) philosophy to include voxel-based evidence on organ radio-sensitivity (RS) has been acknowledged. Here a new formalism (Probabilistic Atlas for Complication Estimation, PACE) to predict radiation-induced morbidity (RIM) is presented. The adopted strategy basically consists in keeping the structure of a classical, phenomenological NTCP model, such as the Lyman-Kutcher-Burman (LKB), and replacing the dose distribution with a collection of RIM odds, including also significant non-dosimetric covariates, as input of the model framework. The theory was first demonstrated in silico on synthetic dose maps, classified according to synthetic outcomes. PACE was then applied to a clinical dataset of thoracic cancer patients classified for lung fibrosis. LKB models were trained for comparison. Overall, the obtained learning curves showed that the PACE model outperformed the LKB and predicted synthetic outcomes with an accuracy >0.8. On the real patients, PACE performance, evaluated by both discrimination and calibration, was significantly higher than LKB. This trend was confirmed by cross-validation. Furthermore, the capability to infer the spatial pattern of underlying RS map for the analyzed RIM was successfully demonstrated, thus paving the way to new perspectives of NTCP models as learning tools.

Purpose: To compare image quality and radiation dose among different protocols in patients who underwent a 128-slice dual source computed tomography coronary angiography (DSCT-CTCA). Methods: Ninety patients were retrospectively grouped according to heart rate (HR): 26 patients (group A) with stable HR ≤60 bpm were acquired using high pitch spiral mode (FLASH); 48 patients (group B) with irregular HR ≤60 bpm or stable HR between 60 and 70 bpm using step and shoot mode; and 16 patients (group C) with irregular HR >60 bpm or stable HR ≥70 bpm by retrospective electrocardiogram pulsing acquisition. Signal to noise ratio (SNR) and contrast to noise ratio (CNR) were measured for the main vascular structures. Moreover, the dose-length product and the effective dose were assessed. Results: Both SNR and CNR were higher in group A compared to group C (18.27 ± 0.32 vs 11.22 ± 0.50 and 16.75 ± 0.32 vs 10.17 ± 0.50; P = .001). The effective dose was lower in groups A and B (2.09 ± 1.27 mSv and 4.60 ± 2.78 mSv, respectively) compared to group C (9.61 ± 5.95 mSv) P < .0001. Conclusion: The correct selection of a low-dose, HR-matched CTCA scan protocol with a DSCT scanner provides substantial reduction of radiation exposure and better SNR and CNR.

The presence of significant fibrosis is an indicator for liver disease staging and prognosis. The aim of the study was to determine reproducibility of real-time shear wave elastography using a hepatic biopsy as the reference standard to identify patients with chronic liver disease. Forty patients with chronic liver disease and 12 normal subjects received shear wave elastography performed by skilled operators. Interoperator reproducibility was studied in 29 patients. Fibrosis was evaluated using the Metavir score. The median and range shear wave elastography values in chronic liver disease subjects were 6.15 kPa and 3.14-16.7 kPa and were 4.49 kPa and 2.92-7.32 kPa in normal subjects, respectively. With respect to fibrosis detected by liver biopsy, shear wave elastography did not change significantly between F0 and F1 (p = 0.334), F1 and F2 (p = 0.611), or F3 and F4 (0.327); a significant difference was observed between the F0-F2 and F3-F4 groups (p = 0.002). SWE also correlated with inflammatory activity (Rs = 0.443, p = 0.0023) and ALT levels (Rs = 0.287, p = 0.0804). Age, sex and body mass index did not affect shear wave elastography measurements. Using receiver operator characteristic curves, two threshold values for shear wave elastography were identified: 5.62 kPa for patients with fibrosis (≥F2; sensitivity 80%, specificity 69.4%, and accuracy 77%) and 7.04 kPa for patients with severe fibrosis (≥F3; sensitivity 88.9%, specificity 81%, and accuracy 89%). Overall interobserver agreement was excellent and was analysed using an interclass correlation coefficient (0.94; CI 0.87-0.97).This study shows that shear wave elastography executed by skilled operators can be performed on almost all chronic liver disease patients with high reproducibility. It is not influenced by age, sex or body mass index, identifies severely fibrotic patients and is also related to inflammatory activity.

Susceptibility Weighted Imaging (SWI) is a common MRI technique that exploits the magnetic susceptibility differences between the tissues to provide valuable image contrasts, both in research and clinical contexts. However, despite its increased clinical use, SWI is not intrinsically suitable for quantitation purposes. Conversely, quantitative Magnetic Resonance Imaging (qMRI) provides a way to disentangle the sources of common MR image contrasts (e.g. proton density, T1, etc.) and to measure physical parameters intrinsically related to tissue microstructure. Unfortunately, the poor signal-to-noise ratio and resolution, coupled with the long imaging time of most qMRI strategies, have hindered the integration of quantitative imaging into clinical protocols. Here we present the RElaxometry and SUsceptibility Mapping Expedient (RESUME) to show that the standard acquisition leading to a clinical SWI dataset can be easily turned into a thorough qMRI protocol at the cost of a further 50% of the SWI scan time. The R1, [Formula: see text], proton density and magnetic susceptibility maps provided by the RESUME scheme alongside the SWI reconstruction exhibit high reproducibility and accuracy, and a submillimeter resolution is proven to be compatible with a total scan time of 7 minutes.

The aim of the study was to investigate the Internal Jugular Veins dynamics using contrast enhanced ultrasonography in Multiple Sclerosis patients, clinically isolated syndrome patients and healthy controls. Contrast enhanced ultrasonography imaging of the Internal Jugular Vein was performed in fifty-eight patients with Multiple Sclerosis, seven clinically isolated syndrome patients and in thirteen healthy controls. Time-intensity curves were quantified using a semi-automated method and compared with clinical disease outcomes. Wash-out parameters were calculated and six Time-intensity curves shapes were created. Significantly reduction of wash-out rate in Internal Jugular Veins was detected in Multiple Sclerosis patients compared to healthy controls [22.2% (2.7%-65.9%) vs. 33.4% (16.2%-76.8%); P

The heartbeat has been proposed as an intrinsic source of motion that can be used in combination with tagged Magnetic Resonance Imaging (MRI) to measure displacements induced in the liver as an index of liver stiffness. Optimizing a tagged MRI acquisition protocol in terms of sensitivity to these displacements, which are in the order of pixel size, is necessary to develop the method as a quantification tool for staging fibrosis. We reproduced a study of cardiac-induced strain in the liver at 3T and simulated tagged MR images with different grid tag patterns to evaluate the performance of the Harmonic Phase (HARP) image analysis method and its dependence on the parameters of tag spacing and grid angle. The Partial Volume Effect (PVE), T1 relaxation, and different levels of noise were taken into account. Four displacement fields of increasing intensity were created and applied to the tagged MR images of the liver. These fields simulated the deformation at different liver stiffnesses. An Error Index (EI) was calculated to evaluate the estimation accuracy for various parameter values. In the absence of noise, the estimation accuracy of the displacement fields increased as tag spacings decreased. EIs for each of the four displacement fields were lower at 0° and the local minima of the EI were found to correspond to multiples of pixel size. The accuracy of the estimation decreased for increasing levels of added noise; as the level increased, the improved estimation caused by decreasing the tag spacing tended to zero. The optimal tag spacing turned out to be a compromise between the smallest tag period that is a multiple of the pixel size and is achievable in a real acquisition and the tag spacing that guarantees an accurate liver displacement measure in the presence of realistic levels of noise.

Abstract Harvesting sunlight to drive carbon dioxide (CO2) valorisation represents an ideal concept to support a sustainable and carbon-neutral economy. While the photochemical reduction of CO2 to carbon monoxide (CO) has emerged as a hot research topic, the full CO2-to-CO conversion remains an often-overlooked criterion that prevents a productive and direct valorisation of CO into high-value-added chemicals. Herein, we report a photocatalytic process that unlocks full and fast CO2-to-CO conversion (

Thoracic radiation therapy (RT) is often associated with lung side effects, whose etiology is still controversial. Our aim was to explore correlations between local dose in the thoracic anatomy and the radiation-induced lung damage (RILD). To this end, we designed a robust scheme for voxel-based analysis (VBA) to explore dose patterns associated with RILD in non-small-cell lung cancer (NSCLC) patients receiving stereotactic body RT (SBRT). We analyzed 106 NSCLC SBRT patients (median prescription dose: 50 Gy; range: [40–54] Gy) in 4 fractions (range: [3–5]) with clinical and dosimetric records suitable for the analysis. The incidence of acute G1 RILD (RTOG grade  ⩾  1) was 68%. Each planning CT and dose map was spatially normalized to a common anatomical reference using a B-spline inter-patient registration algorithm after masking the gross tumor volume. The tumor-subtracted dose maps were converted into biologically effective dose maps (α/β  =  3 Gy). VBA was performed according to a non-parametric permutation test accounting for multiple comparison, based on a cluster analysis method. The underlying general linear model of RILD was designed to include dose maps and each non-dosimetric variable significantly correlated with RILD. The clusters of voxels with dose differences significantly correlated with RILD at a given p -level (Sp ) were generated. The only non-dosimetric variable significantly correlated with RILD was the chronic obstructive pulmonary disease (p   =  0.034). Patients with G1 RILD received significantly (p   ⩽  0.05) higher doses in two voxel clusters S0.05 in the lower-left lung (14 cm3) and in an area (64 cm3) largely included within the ventricles. The applied VBA represents a powerful tool to probe the dose susceptibility of inhomogeneous organs in clinical radiobiology studies. The identified subregions with dose differences associated with G1 RILD in both the heart and lower lungs endorse a trend of previously reported hypotheses on lung toxicity radiobiology. [ABSTRACT FROM AUTHOR]