Artificial intelligence in endocrinology: a comprehensive review.

BACKGROUND AND AIM: Artificial intelligence (AI) has emerged as a promising technology in the field of endocrinology, offering significant potential to revolutionize the diagnosis, treatment, and management of endocrine disorders. This comprehensive review aims to provide a concise overview of the current landscape of AI applications in endocrinology and metabolism, focusing on the fundamental concepts of AI, including machine learning algorithms and deep learning models. METHODS: The review explores various areas of endocrinology where AI has demonstrated its value, encompassing screening and diagnosis, risk prediction, translational research, and "pre-emptive medicine". Within each domain, relevant studies are discussed, offering insights into the methodology and main findings of AI in the treatment of different pathologies, such as diabetes mellitus and related disorders, thyroid disorders, adrenal tumors, and bone and mineral disorders. RESULTS: Collectively, these studies show the valuable contributions of AI in optimizing healthcare outcomes and unveiling new understandings of the intricate mechanisms underlying endocrine disorders. Furthermore, AI-driven approaches facilitate the development of precision medicine strategies, enabling tailored interventions for patients based on their individual characteristics and needs. CONCLUSIONS: By embracing AI in endocrinology, a future can be envisioned where medical professionals and AI systems synergistically collaborate, ultimately enhancing the lives of individuals affected by endocrine disorders.

Resting-state brain correlates of cardiovascular complexity.

While estimates of complex heartbeat dynamics have provided effective prognostic and diagnostic markers for a wide range of pathologies, brain correlates of complex cardiac measures in general and of complex sympatho-vagal dynamics in particular are still unknown. In this study we combine resting state functional Magnetic Resonance Imaging (fMRI) and physiological signal acquisition from 34 healthy subjects selected from the Human Connectome Project (HCP) repository with inhomogeneous point-process approximate and sample heartbeat entropy measures (ipApEn and ipSampEn) to investigate brain areas involved in complex cardiovascular control. Our results show that activity in the Temporal Gyrus, Frontal Orbital Cortex, Temporal Fusiform and Opercular cortices, Planum Temporale, and Paracingulate cortex are negatively correlated with ipApEn dynamics. Activity in the same cortical areas as well as in the Temporal Fusiform cortex are negatively correlated with ipSampEn dynamics. No significant positive correlations were found. These pioneering results suggest that cardiovascular complexity at rest is linked to a few specific cortical brain structures, including crucial areas connected with parasympathetic outflow. This corroborates the hypothesis of a multidimensional central network which controls nonlinear cardiac dynamics under a predominantly vagally-driven tone.

Resting-state brain correlates of instantaneous autonomic outflow.

A prominent pathway of brain-heart interaction is represented by autonomic nervous system (ANS) heartbeat modulation. While within-brain resting state networks have been the object of intense functional Magnetic Resonance Imaging (fMRI) research, technological and methodological limitations have hampered research on the central correlates of cardiovascular control dynamics. Here we combine the high temporal and spatial resolution as well as data volume afforded by the Human Connectome Project with a probabilistic model of heartbeat dynamics to characterize central correlates of sympathetic and parasympathetic ANS activity at rest. We demonstrate an involvement of a number of brain regions such as the Insular cortex, Frontal Gyrus, Lateral Occipital Cortex, Paracingulate and Cingulate Gyrus and Precuneous Cortex, as well as subcortical structures (Thalamus, Putamen, Pallidum, Brain-Stem, Hippocampus, Amygdala, and Right Caudate) in the modulation of ANS-mediated cardiovascular control, possibly indicating a broader definition of the central autonomic network (CAN). Our findings provide a basis for an informed neurobiological interpretation of the numerous studies which employ HRV-related measures as standalone biomarkers in health and disease.

Effectiveness of 3D T2-Weighted FLAIR FSE Sequences with Fat Suppression for Detection of Brain MR Imaging Signal Changes in Children.

BACKGROUND AND PURPOSE: T2-weighted FLAIR can be combined with 3D-FSE sequences with isotropic voxels, yielding higher signal-to-noise ratio than 2D-FLAIR. Our aim was to explore whether a T2-weighted FLAIR-volume isotropic turbo spin-echo acquisition sequence (FLAIR-VISTA) with fat suppression shows areas of abnormal brain T2 hyperintensities with better conspicuity in children than a single 2D-FLAIR sequence. MATERIALS AND METHODS: One week after a joint training session with 20 3T MR imaging examinations (8 under sedation), 3 radiologists independently evaluated the presence and conspicuity of abnormal areas of T2 hyperintensities of the brain in FLAIR-VISTA with fat suppression (sagittal source and axial and coronal reformatted images) and in axial 2D-FLAIR without fat suppression in a test set of 100 3T MR imaging examinations (34 under sedation) of patients 2-18 years of age performed for several clinical indications. Their agreement was measured with weighted κ statistics. RESULTS: Agreement was "substantial" (mean, 0.61 for 3 observers; range, 0.49-0.69 for observer pairs) for the presence of abnormal T2 hyperintensities and "fair" (mean, 0.29; range, 0.23-0.38) for the comparative evaluation of lesion conspicuity. In 21 of 23 examinations in which the 3 radiologists agreed on the presence of abnormal T2 hyperintensities, FLAIR-VISTA with fat suppression images were judged to show hyperintensities with better conspicuity than 2D-FLAIR. In 2 cases, conspicuity was equal, and in no case was conspicuity better in 2D-FLAIR. CONCLUSIONS: FLAIR-VISTA with fat suppression can replace the 2D-FLAIR sequence in brain MR imaging protocols for children.

Forecasting nanoparticle toxicity using nonlinear predictive regressor learning systems.

Nanoparticle (NP) toxicity is determined by a vast number of topological, sterical, physico-chemical as well as biological properties, rendering a priori evaluation of the effect of NP on biological tissue as arduous as it is necessary and urgent. We aimed at mining the HORIZON 2020 MODENA COST NP cytotoxicity database through nonlinear predictive regressor learning systems in order to assess the power of available NP descriptors and assay characteristics in predicting NP toxicity. Specifically, we assessed the results of cytotoxicity assays performed on 57 NP and trained two different nonlinear regressors (Support Vector Regressors [SVR] with polynomical kernels and Radial Basis Function [RBF] regressors) within a nested-cross validation scheme for parameter optimization to predict toxicity as quantified by EC25, EC50 and slope while using the regressional ReliefF algorithm (RReliefF) for feature selection. Available NP attributes were material, coating, cell type, dispersion protocol, shape, 1st and 2nd dimension, aspect ratio, surface area, zeta potential and size in situ. In most regressor learning systems, after feature selection with the RReliefF algorithm, the correlation between real and estimated toxicity endpoint values increased monotonically with the number of included features, reaching values above 0.90. The best performance was obtained with RBF regressors, and the most informative features in predicting toxicity endpoints were related to nanoparticle structure. These trends did not change significantly between toxicity endpoints. In conclusion, EC25, EC50 and slope can be predicted with high correlation using purely data-driven, machine learning methods in Adenosine triphosphate (ATP)-based NP cytotoxicity assays.

Cortical thickness in de novo patients with Parkinson disease and mild cognitive impairment with consideration of clinical phenotype and motor laterality.

BACKGROUND AND PURPOSE: Parkinson's disease (PD) is a progressive neurodegenerative disorder with motor and non-motor symptoms, including cognitive deficits. Several magnetic resonance imaging approaches have been applied to investigate brain atrophy in PD. The aim of this study was to detect early structural cortical and subcortical changes in de novo PD whilst distinguishing cognitive status, clinical phenotype and motor laterality. METHODS: Eighteen de novo PD with mild cognitive impairment (PD-MCI), 18 de novo PD without MCI (PD-NC) and 18 healthy control subjects were evaluated. In the PD-MCI group, nine were tremor dominant and nine were postural instability gait disorder (PIGD) phenotype; 11 had right-sided symptom dominance and seven had left-sided symptom dominance. FreeSurfer was used to measure cortical thickness/folding, subcortical structures and to study group differences as well as the association with clinical and neuropsychological data. RESULTS: Parkinson's disease with MCI showed regional thinning in the right frontal, right middle temporal areas and left insula compared to PD-NC. A reduction of the volume of the left and right thalamus and left hippocampus was found in PD-MCI compared to PD-NC. PD-MCI PIGD showed regional thinning in the right inferior parietal area compared to healthy controls. A decreased volume of the left thalamus was reported in PD-MCI with right-sided symptom dominance compared to PD-NC and PD-MCI with left-sided symptom dominance. CONCLUSIONS: When MCI was present, PD patients showed a fronto-temporo-parietal pattern of cortical thinning. This cortical pattern does not appear to be influenced by motor laterality, although one-sided symptom dominance may contribute to volumetric reduction of specific subcortical structures.

Progression of microstructural damage in spinocerebellar ataxia type 2: a longitudinal DTI study.

BACKGROUND AND PURPOSE: The ability of DTI to track the progression of microstructural damage in patients with inherited ataxias has not been explored so far. We performed a longitudinal DTI study in patients with spinocerebellar ataxia type 2. MATERIALS AND METHODS: Ten patients with spinocerebellar ataxia type 2 and 16 healthy age-matched controls were examined twice with DTI (mean time between scans, 3.6 years [patients] and 3.3 years [controls]) on the same 1.5T MR scanner. Using tract-based spatial statistics, we analyzed changes in DTI-derived indices: mean diffusivity, axial diffusivity, radial diffusivity, fractional anisotropy, and mode of anisotropy. RESULTS: At baseline, the patients with spinocerebellar ataxia type 2, as compared with controls, showed numerous WM tracts with significantly increased mean diffusivity, axial diffusivity, and radial diffusivity and decreased fractional anisotropy and mode of anisotropy in the brain stem, cerebellar peduncles, cerebellum, cerebral hemisphere WM, corpus callosum, and thalami. Longitudinal analysis revealed changes in axial diffusivity and mode of anisotropy in patients with spinocerebellar ataxia type 2 that were significantly different than those in the controls. In patients with spinocerebellar ataxia type 2, axial diffusivity was increased in WM tracts of the right cerebral hemisphere and the corpus callosum, and the mode of anisotropy was extensively decreased in hemispheric cerebral WM, corpus callosum, internal capsules, cerebral peduncles, pons and left cerebellar peduncles, and WM of the left paramedian vermis. There was no correlation between the progression of changes in DTI-derived indices and clinical deterioration. CONCLUSIONS: DTI can reveal the progression of microstructural damage of WM fibers in the brains of patients with spinocerebellar ataxia type 2, and mode of anisotropy seems particularly sensitive to such changes. These results support the potential of DTI-derived indices as biomarkers of disease progression.

Whole-lung volume and density in spirometrically-gated inspiratory and expiratory CT in systemic sclerosis: correlation with static volumes at pulmonary function tests.

BACKGROUND: Spiral low-dose computed tomography (LDCT) permits to measure whole-lung volume and density in a single breath-hold. OBJECTIVE: To evaluate the agreement between static lung volumes measured with LDCT and pulmonary function test (PFT) and the correlation between the LDCT volumes and lung density in restrictive lung disease. DESIGN: Patients with Systemic Sclerosis (SSc) with (n = 24) and without (n = 16) pulmonary involvement on sequential thin-section CT and patients with chronic obstructive pulmonary disease (COPD)(n = 29) underwent spirometrically-gated LDCT at 90% and 10% of vital capacity to measure inspiratory and expiratory lung volumes and mean lung attenuation (MLA). Total lung capacity and residual volume were measured the same day of CT. RESULTS: Inspiratory [95% limits of agreement (95% LoA)--43.8% and 39.2%] and expiratory (95% LoA -45.8% and 37.1%) lung volumes measured on LDCT and PFT showed poor agreement in SSc patients with pulmonary involvement, whereas they were in substantial agreement (inspiratory 95% LoA -14.1% and 16.1%; expiratory 95% LoA -13.5% and 23%) in SSc patients without pulmonary involvement and in inspiratory scans only (95% LoA -23.1% and 20.9%) of COPD patients. Inspiratory and expiratory LDCT volumes, MLA and their deltas differentiated both SSc patients with or without pulmonary involvement from COPD patients. LDCT lung volumes and density were not correlated in SSc patients with pulmonary involvement, whereas they did correlate in SSc without pulmonary involvement and in COPD patients. CONCLUSIONS: In restrictive lung disease due to SSc there is poor agreement between static lung volumes measured using LDCT and PFT and the relationship between volume and density values on CT is altered.

Regional analysis of the magnetization transfer ratio of the brain in mild Alzheimer disease and amnestic mild cognitive impairment.

BACKGROUND AND PURPOSE: Manually drawn VOI-based analysis shows a decrease in magnetization transfer ratio in the hippocampus of patients with Alzheimer disease. We investigated with whole-brain voxelwise analysis the regional changes of the magnetization transfer ratio in patients with mild Alzheimer disease and patients with amnestic mild cognitive impairment. MATERIALS AND METHODS: Twenty patients with mild Alzheimer disease, 27 patients with amnestic mild cognitive impairment, and 30 healthy elderly control subjects were examined with high-resolution T1WI and 3-mm-thick magnetization transfer images. Whole-brain voxelwise analysis of magnetization transfer ratio maps was performed by use of Statistical Parametric Mapping 8 software and was supplemented by the analysis of the magnetization transfer ratio in FreeSurfer parcellation-derived VOIs. RESULTS: Voxelwise analysis showed 2 clusters of significantly decreased magnetization transfer ratio in the left hippocampus and amygdala and in the left posterior mesial temporal cortex (fusiform gyrus) of patients with Alzheimer disease as compared with control subjects but no difference between patients with amnestic mild cognitive impairment and either patients with Alzheimer disease or control subjects. VOI analysis showed that the magnetization transfer ratio in the hippocampus and amygdala was significantly lower (bilaterally) in patients with Alzheimer disease when compared with control subjects (ANOVA with Bonferroni correction, at P < .05). Mean magnetization transfer ratio values in the hippocampus and amygdala in patients with amnestic mild cognitive impairment were between those of healthy control subjects and those of patients with mild Alzheimer disease. Support vector machine-based classification demonstrated improved classification performance after inclusion of magnetization transfer ratio-related features, especially between patients with Alzheimer disease versus healthy subjects. CONCLUSIONS: Bilateral but asymmetric decrease of magnetization transfer ratio reflecting microstructural changes of the residual GM is present not only in the hippocampus but also in the amygdala in patients with mild Alzheimer disease.

Dose exposure in the ITALUNG trial of lung cancer screening with low-dose CT.

Few data are available on the effective dose received by participants in lung cancer screening programmes with low-dose CT (LDCT). We report the collective effective dose delivered to 1406 current or former smokers enrolled in the ITALUNG trial who completed 4 annual LDCT examinations and related further investigations including follow-up LDCT, 2-[(18)F]flu-2-deoxy-d-glucose positron emission tomography (FDG-PET) or CT-guided fine needle aspiration biopsy (FNAB). Using the air CT dose index and Monte Carlo simulations on an anthropomorphic phantom, the whole-body effective dose associated with LDCT was determined for the eight CT scanners used in the trial. A value of 7 mSv was assigned to FDG-PET while the measured mean effective dose of CT-guided FNAB was 1.5 mSv. The mean collective effective dose in the 1406 subjects ranged between 8.75 and 9.36 Sv and the mean effective dose to the single subject over 4 years was between 6.2 and 6.8 mSv (range 1.7-21.5 mSv) according to the cranial-caudal length of the LDCT volume. 77.4% of the dose was owing to annual LDCT and 22.6% to further investigations. Considering the nominal risk coefficients for stochastic effects after exposure to low-dose radiation according to the National Radiological Protection Board, International Commission on Radiological Protection (ICRP) 60, ICRP103 and Biological Effects of Ionizing Radiation VII, the mean number of radiation-induced cancers ranged between 0.12 and 0.33 per 1000 subjects. The individual effective dose to participants in a 4-year lung cancer screening programme with annual LDCT is very low and about one-third of the effective dose that is associated with natural background radiation and diagnostic radiology in the same time period.

Magnetization transfer imaging demonstrates a distributed pattern of microstructural changes of the cerebral cortex in amyotrophic lateral sclerosis.

BACKGROUND AND PURPOSE: To date, damage of the cerebral cortex neurons in ALS was investigated by using conventional MR imaging and proton MR spectroscopy. We explored the capability of MTI to map the microstructural changes in cerebral motor and extramotor cortices of patients with ALS. MATERIALS AND METHODS: Twenty patients with ALS and 17 age-matched healthy controls were enrolled. A high-resolution 3D SPGR sequence with and without MT saturation pulses was obtained on a 1.5T scanner to compute MTR values. Using the FMRIB Software Library tools, we automatically computed the MTR of the cerebral cortex GM in 48 regions of the entire cerebral cortex derived from the standard Harvard-Oxford cortical atlas. RESULTS: The MTR values were significantly lower in patients with ALS than in healthy controls in the primary motor cortex (precentral gyrus), nonprimary motor areas (superior and middle frontal gyri and superior parietal lobe), and some extramotor areas (frontal pole, planum temporale, and planum polare). No correlation was found between regional MTR values and the severity of clinical deficits or disease duration. CONCLUSIONS: MTI analysis can detect the distributed pattern of microstructural changes of the GM in the cerebral cortex of patients with ALS with involvement of both the motor and extramotor areas.

Magnetization transfer MR imaging demonstrates degeneration of the subcortical and cortical gray matter in Huntington disease.

BACKGROUND AND PURPOSE: GM is typically affected in HD since the presymptomatic stage. Our aim was to investigate with MT MR imaging the microstructural changes of the residual brain subcortical and cortical GM in carriers of the HD gene and to preliminarily assess their correlation with the clinical features. MATERIALS AND METHODS: Fifteen HD gene carriers with a range of clinical severity and 15 age- and sex-matched healthy controls underwent MT MR imaging on a 1.5T scanner. The MT ratio was measured automatically in several subcortical and cortical GM regions (striatal nuclei; thalami; and the neocortex of the frontal, temporal, parietal, and occipital lobes) by using FLS tools. RESULTS: The MT ratio was significantly (P < .05 with Bonferroni correction for multiple comparison) decreased in all subcortical structures except the putamen and decreased diffusely in the cerebral cortex of HD carriers compared with controls. Close correlation was observed between the subcortical and cortical regional MT ratios and several clinical variables, including disease duration, motor disability, and scores in timed neuropsychological tests. CONCLUSIONS: MT imaging demonstrates degeneration of the subcortical and cortical GM in HD carriers and might serve, along with volumetric assessment, as a surrogate marker in future clinical trials of HD.

Computation of brain metabolite ratios in single-voxel proton MR spectroscopy: comparison between semiautomatic and automatic software.

PURPOSE: Metabolite ratios are the measurements most commonly utilised for clinical applications of brain proton magnetic resonance spectroscopy ((1)H-MRS) [1]. We evaluated the agreement between the metabolite ratios calculated with semiautomatic and automatic software. MATERIALS AND METHODS: Two single-voxel spectra (3.375 ml) localised in the frontal grey matter (GM) and peritrigonal white matter (WM) were obtained in 20 healthy subjects by using a point-resolved proton spectroscopy sequence (PRESS, TE=144 ms). The spectra were processed using the semiautomatic software J-Magnetic Resonance User Interface (JMRUI) and the automatic software SpectroView. Agreement of the N-acetyl-aspartate (NAA)/creatine (Cr), NAA/choline (Cho) and Cho/Cr ratios calculated with the two methods was assessed by estimating the 95% limits of agreement (LAs) of the differences of the values obtained with the two software packages. RESULTS: Mean values and standard deviations of NAA/Cr, Cho/Cr and NAA/Cho (semiautomatic//automatic software) were 1.99+/-0.53//1.73+/-0.36, 1.13+/-0.40//1.04+/-0.33, 1.85+/-0.62//1.89+/-0.69 for the GM and 2.24+/-0.41//2.37+/-0.27, 0.96+/-0.17//1.13+/-0.15, 2.37+/-0.43//2.11+/-0.23 for the WM. The 95% LAs were wider for GM spectra and ranged between -0.51, 0.17 for Cho/Cr in the WM and -1.54, 1.47 for NAA/Cho in the GM. CONCLUSIONS: The difference between brain metabolite ratios calculated with the two software packages is not negligible and reflects spectral quality.

3-D segmentation algorithm of small lung nodules in spiral CT images.

Computed tomography (CT) is the most sensitive imaging technique for detecting lung nodules, and is now being evaluated as a screening tool for lung cancer in several large samples studies all over the world. In this report, we describe a semiautomatic method for 3-D segmentation of lung nodules in CT images for subsequent volume assessment. The distinguishing features of our algorithm are the following. 1) The user interaction process. It allows the introduction of the knowledge of the expert in a simple and reproducible manner. 2) The adoption of the geodesic distance in a multithreshold image representation. It allows the definition of a fusion--segregation process based on both gray-level similarity and objects shape. The algorithm was validated on low-dose CT scans of small nodule phantoms (mean diameter 5.3--11 mm) and in vivo lung nodules (mean diameter 5--9.8 mm) detected in the Italung-CT screening program for lung cancer. A further test on small lung nodules of Lung Image Database Consortium (LIDC) first data set was also performed. We observed a RMS error less than 6.6% in phantoms, and the correct outlining of the nodule contour was obtained in 82/95 lung nodules of Italung-CT and in 10/12 lung nodules of LIDC first data set. The achieved results support the use of the proposed algorithm for volume measurements of lung nodules examined with low-dose CT scanning technique.

A comparison between internal and surface temperature measurement techniques during phacoemulsification cataract surgery: thermocamera versus thermocouple.

PURPOSE: Corneal and scleral burns, one of the main complications that can occur during a cataract operation, are produced by overheating due to the use of the phacoemulsifier. The temperature of the anterior chamber of the eye can be measured both invasively using thermocouples and non-invasively, but only superficially, using a thermocamera. METHODS: To compare the measures obtained from both techniques an in vitro experimental analysis was conducted on pigs' eyes. During a simulated phacoemulsification cataract operation both the surface temperature with a thermocamera and the temperature inside the anterior chamber with a thermocouple were recorded. For each procedure, the maximum temperature values measured by each technique were compared. RESULTS: The results of this research show that the difference between the maximum values measured with the two techniques is on average 0.5 degrees C. CONCLUSIONS: It is possible to employ a thermocamera technique instead of a thermocouple technique to provide an indication of the temperature inside the anterior chamber.

Whole-brain histogram and voxel-based analyses of diffusion tensor imaging in patients with leukoaraiosis: correlation with motor and cognitive impairment.

BACKGROUND AND PURPOSE: Cerebral white matter changes, termed leukoaraiosis (LA), appearing as areas of increased signal intensity in T2-weighted MR images, are common in elderly subjects, but the possible correlation of LA with cognitive or motor deficit has not been established. We hypothesized that histogram and voxel-based analyses of whole-brain mean diffusivity (MD) and fractional anisotropy (FA) maps calculated from diffusion tensor imaging (DTI) could be more sensitive tools than visual scales to investigate the clinical correlates of LA. MATERIALS AND METHODS: Thirty-six patients of the Leukoaraiosis and Disability Study were evaluated with fluid-attenuated inversion recovery for LA extension, T1-weighted images for volume, and DTI for MD and FA. The extent of LA was rated visually. The normalized total, gray, and white matter brain volumes were computed, as well as the 25th percentile, 50th percentile, kurtosis, and skewness of the MD and FA maps of the whole brain. Finally, voxel-based analysis on the maps of gray and white matter volume, MD, and FA was performed with SPM2 software. Correlation analyses between visual or computerized data and motor or neuropsychologic scale scores were performed using the Spearman rank test and the SPM2 software. RESULTS: The visual score correlated with some MD and FA histogram metrics (P<.01). However, only the 25th and 50th percentiles, kurtosis, and skewness of the MD and FA histograms correlated with motor or neuropsychologic deficits. Voxel-based analysis revealed a correlation (P<.05 corrected for multiple comparisons) between a large cluster of increased MD in the corpus callosum and pericallosal white matter and motor deficit. CONCLUSIONS: These results are consistent with the hypothesis that histogram and voxel-based analyses of the whole-brain MD and FA maps are more sensitive tools than the visual evaluation for clinical correlation in patients with LA.

Whole-brain histogram and voxel-based analyses of apparent diffusion coefficient and magnetization transfer ratio in celiac disease, epilepsy, and cerebral calcifications syndrome.

BACKGROUND AND PURPOSE: Diffusion and magnetization transfer (MT) techniques have been applied to the investigation with MR of epilepsy and have revealed changes in patients with or without abnormalities on MR imaging. We hypothesized that also in the coeliac disease (CD), epilepsy and cerebral calcifications (CEC) syndrome diffusion and MT techniques could reveal brain abnormalities undetected by MR imaging and tentatively correlated to epilepsy. MATERIALS AND METHODS: Diffusion and MT weighted images were obtained in 10 patients with CEC, 8 patients with CD without epilepsy and 17 healthy volunteers. The whole brain apparent diffusion coefficient (ADC) and MT ratio (MTR) maps were analyzed with histograms and the Statistical Parametric Mapping 2 (SPM2) software. We employed the non-parametric Mann-Whitney U test to assess differences for ADC and MTR histogram metrics. Voxel by voxel comparison of the ADC and MTR maps was performed with 2 tails t-test corrected for multiple comparison. RESULTS: A significantly higher whole brain ADC value as compared to healthy controls was observed in CEC (P = 0.006) and CD (P = 0.01) patients. SPM2 showed bilateral areas of significantly decreased MTR in the parietal and temporal subcortical white matter (WM) in the CEC patients. CONCLUSION: Our study indicates that diffusion and MT techniques are also capable of revealing abnormalities undetected by MR imaging. In particular patients with CEC syndrome show an increase of the whole brain ADC histogram which is more pronounced than in patients with gluten intolerance. IN CEC patients, voxel-based analysis demonstrates a localized decrease of the MTR in the parieto-temporal subcortical WM.