Multimodal imaging and electrophysiological study in the differential diagnosis of rest tremor.

Introduction: Distinguishing tremor-dominant Parkinson's disease (tPD) from essential tremor with rest tremor (rET) can be challenging and often requires dopamine imaging. This study aimed to differentiate between these two diseases through a machine learning (ML) approach based on rest tremor (RT) electrophysiological features and structural MRI data. Methods: We enrolled 72 patients including 40 tPD patients and 32 rET patients, and 45 control subjects (HC). RT electrophysiological features (frequency, amplitude, and phase) were calculated using surface electromyography (sEMG). Several MRI morphometric variables (cortical thickness, surface area, cortical/subcortical volumes, roughness, and mean curvature) were extracted using Freesurfer. ML models based on a tree-based classification algorithm termed XGBoost using MRI and/or electrophysiological data were tested in distinguishing tPD from rET patients. Results: Both structural MRI and sEMG data showed acceptable performance in distinguishing the two patient groups. Models based on electrophysiological data performed slightly better than those based on MRI data only (mean AUC: 0.92 and 0.87, respectively; p = 0.0071). The top-performing model used a combination of sEMG features (amplitude and phase) and MRI data (cortical volumes, surface area, and mean curvature), reaching AUC: 0.97 ± 0.03 and outperforming models using separately either MRI (p = 0.0001) or EMG data (p = 0.0231). In the best model, the most important feature was the RT phase. Conclusion: Machine learning models combining electrophysiological and MRI data showed great potential in distinguishing between tPD and rET patients and may serve as biomarkers to support clinicians in the differential diagnosis of rest tremor syndromes in the absence of expensive and invasive diagnostic procedures such as dopamine imaging.

Measurement invariance across countries of the Test of Memory Strategies (TMS): A contribution to the cross-national validity study.

Previous literature showed a complex interpretation of recall tasks due to the complex relationship between Executive Functions (EF) and Long Term Memory (M). The Test of Memory Strategies (TMS) could be useful for assessing this issue, because it evaluates EF and M simultaneously. This study aims to explore the validity of the TMS structure, comparing the models proposed by Vaccaro et al. (2022) and evaluating the measurement invariance according to three countries (Italy, Spain, and Portugal) through Confirmatory Factor Analysis (CFA). Four hundred thirty-one healthy subjects (Age mean = 54.84, sd = 20.43; Education mean = 8.85, sd =4.05; M = 177, F = 259) were recruited in three countries (Italy, Spain, and Portugal). Measurement invariance across three country groups was evaluated through Structural Equation modeling. Also, convergent and divergent validity were examined through the correlation between TMS and classical neuropsychological tests. CFA outcomes suggested that the best model was the three-dimensional model, in which list 1 and list2 reflect EF, list 3 reflects a mixed factor of EF and M (EFM) and list4 and list5 reflect M. This result is in line with the theory that TMS decreases EF components progressively. TMS was metric invariant to the country, but scalar invariance was not tenable. Finally, the factor scores of TMS showed convergent validity with the classical neuropsychological tests. The overall results support cross-validation of TMS in the three countries considered.

Combined cortical thickness and blink reflex recovery cycle to differentiate essential tremor with and without resting tremor.

Objective: To investigate the performance of structural MRI cortical and subcortical morphometric data combined with blink-reflex recovery cycle (BRrc) values using machine learning (ML) models in distinguishing between essential tremor (ET) with resting tremor (rET) and classic ET. Methods: We enrolled 47 ET, 43 rET patients and 45 healthy controls (HC). All participants underwent brain 3 T-MRI and BRrc examination at different interstimulus intervals (ISIs, 100-300 msec). MRI data (cortical thickness, volumes, surface area, roughness, mean curvature and subcortical volumes) were extracted using Freesurfer on T1-weighted images. We employed two decision tree-based ML classification algorithms (eXtreme Gradient Boosting [XGBoost] and Random Forest) combining MRI data and BRrc values to differentiate between rET and ET patients. Results: ML models based exclusively on MRI features reached acceptable performance (AUC: 0.85-0.86) in differentiating rET from ET patients and from HC. Similar performances were obtained by ML models based on BRrc data (AUC: 0.81-0.82 in rET vs. ET and AUC: 0.88-0.89 in rET vs. HC). ML models combining imaging data (cortical thickness, surface, roughness, and mean curvature) together with BRrc values showed the highest classification performance in distinguishing between rET and ET patients, reaching AUC of 0.94 ± 0.05. The improvement in classification performances when BRrc data were added to imaging features was confirmed by both ML algorithms. Conclusion: This study highlights the usefulness of adding a simple electrophysiological assessment such as BRrc to MRI cortical morphometric features for accurately distinguishing rET from ET patients, paving the way for a better classification of these ET syndromes.

Decoding the Versatile Landscape of Autophagic Protein VMP1 in Cancer: A Comprehensive Review across Tissue Types and Regulatory Mechanisms.

Autophagy, a catabolic process orchestrating the degradation of proteins and organelles within lysosomes, is pivotal for maintaining cellular homeostasis. However, its dual role in cancer involves preventing malignant transformation while fostering progression and therapy resistance. Vacuole Membrane Protein 1 (VMP1) is an essential autophagic protein whose expression, per se, triggers autophagy, being present in the whole autophagic flux. In pancreatic cancer, VMP1-whose expression is linked to the Kirsten Rat Sarcoma Virus (KRAS) oncogene-significantly contributes to disease promotion, progression, and chemotherapy resistance. This investigation extends to breast cancer, colon cancer, hepatocellular carcinoma, and more, highlighting VMP1's nuanced nature, contingent on specific tissue contexts. The examination of VMP1's interactions with micro-ribonucleic acids (miRNAs), including miR-21, miR-210, and miR-124, enhances our understanding of its regulatory network in cancer. Additionally, this article discusses VMP1 gene fusions, especially with ribosomal protein S6 kinase B1 (RPS6KB1), shedding light on potential implications for tumor malignancy. By deciphering the molecular mechanisms linking VMP1 to cancer progression, this exploration paves the way for innovative therapeutic strategies to disrupt these pathways and potentially improve treatment outcomes.

Acute effects of a chewable beetroot-based supplement on cognitive performance: a double-blind randomized placebo-controlled crossover clinical trial.

BACKGROUND: Dietary nitrate (NO3-) has been shown to be useful as an ergogenic aid with potential applications in health and disease (e.g., blood pressure control). However, there is no consensus about the effects of dietary NO3- or beetroot (BR) juice supplementation on cognitive function. OBJECTIVE: The aim of this study was to evaluate the effects of a single dose of a chewable BR-based supplement on cognitive performance. METHODS: A double-blind randomized placebo-controlled two-period crossover clinical trial was carried out based on the extension of the CONSORT guidelines for randomized crossover trials. A total of 44 participants (24 F; 20 M; 32.7 [12.5] years; 66.3 [9.0] kg; 170 [9.2] cm; 22.8 [1.4] kg/m2) were randomly allocated to receive first either four BR-based chewable tablets (BR-CT) containing 3 g of a Beta vulgaris extract (RedNite®) or four tablets of a placebo (maltodextrin). A 4-day washout period was used before crossover. Ninety minutes after ingestion of the treatments, a neuropsychological testing battery was administered in each period. The trial was registered at clinicaltrials.gov NCT05509075. RESULTS: Significant improvements with moderate effect size were found on memory consolidation at the short and long term only after BR-CT supplementation via the Rey Auditory Verbal Learning Test immediate (+ 20.69%) and delayed (+ 12.34%) recalls. Likewise, enhancement on both frontal lobe functions (+ 2.57%) and cognitive flexibility (+ 11.16%) were detected after BR-CT. There was no significant change (p < 0.05) on verbal memory of short-term digits, working memory and information processing speed. Mixed results were found on mood and anxiety through the Beck Depression Inventory-II (BDI-II) and the State-Trait Anxiety Inventory (STAI-Y1 and STAI-Y2); however, sequence and period effects were seen on STAI-Y2. CONCLUSIONS: The acute administration of a chewable BR-based supplement improves certain aspects of cognitive function in healthy females and males, particularly memory capacity and frontal skills.

Neuroimaging correlates of postural instability in Parkinson's disease.

BACKGROUND: Postural instability (PI) is a common disabling symptom in Parkinson's disease (PD), but little is known on its pathophysiological basis. OBJECTIVE: In this study, we aimed to identify the brain structures associated with PI in PD patients, using different MRI approaches. METHODS: We consecutively enrolled 142 PD patients and 45 control subjects. PI was assessed using the MDS-UPDRS-III pull-test item (PT). A whole-brain regression analysis identified brain areas where grey matter (GM) volume correlated with the PT score in PD patients. Voxel-based morphometry (VBM) and Tract-Based Spatial Statistics (TBSS) were also used to compare unsteady (PT ≥ 1) and steady (PT = 0) PD patients. Associations between GM volume in regions of interest (ROI) and several clinical features were then investigated using LASSO regression analysis. RESULTS: PI was present in 44.4% of PD patients. The whole-brain approach identified the bilateral inferior frontal gyrus (IFG) and superior temporal gyrus (STG) as the only regions associated with the presence of postural instability. VBM analysis showed reduced GM volume in fronto-temporal areas (superior, middle, medial and inferior frontal gyrus, and STG) in unsteady compared with steady PD patients, and the GM volume of these regions was selectively associated with the PT score and not with any other motor or non-motor symptom. CONCLUSIONS: This study demonstrates a significant atrophy of fronto-temporal regions in unsteady PD patients, suggesting that these brain areas may play a role in the pathophysiological mechanisms underlying postural instability in PD. This result paves the way for further studies on postural instability in Parkinsonism.

Ubiquitination Is a Novel Post-Translational Modification of VMP1 in Autophagy of Human Tumor Cells.

Autophagy is a tightly regulated catabolic process involved in the degradation and recycling of proteins and organelles. Ubiquitination plays an important role in the regulation of autophagy. Vacuole Membrane Protein 1 (VMP1) is an essential autophagy protein. The expression of VMP1 in pancreatic cancer stem cells carrying the activated Kirsten rat sarcoma viral oncogene homolog (KRAS) triggers autophagy and enables therapy resistance. Using biochemical and cellular approaches, we identified ubiquitination as a post-translational modification of VMP1 from the initial steps in autophagosome biogenesis. VMP1 remains ubiquitinated as part of the autophagosome membrane throughout autophagic flux until autolysosome formation. However, VMP1 is not degraded by autophagy, nor by the ubiquitin-proteasomal system. Mass spectrometry and immunoprecipitation showed that the cell division cycle protein cdt2 (Cdt2), the substrate recognition subunit of the E3 ligase complex associated with cancer, cullin-RING ubiquitin ligase complex 4 (CRL4), is a novel interactor of VMP1 and is involved in VMP1 ubiquitination. VMP1 ubiquitination decreases under the CRL inhibitor MLN4924 and increases with Cdt2 overexpression. Moreover, VMP1 recruitment and autophagosome formation is significantly affected by CRL inhibition. Our results indicate that ubiquitination is a novel post-translational modification of VMP1 during autophagy in human tumor cells. VMP1 ubiquitination may be of clinical relevance in tumor-cell-therapy resistance.

Neuroimaging correlates of postural instability in Progressive Supranuclear Palsy.

OBJECTIVE: We aimed to identify the brain structures associated with postural instability (PI) in Progressive Supranuclear Palsy (PSP). METHODS: Forty-seven PSP patients and 45 control subjects were enrolled in this study. PI was assessed using the items 27 and 28 of the PSP rating scale (postural instability score, PIS). PSP patients were compared with controls using voxel-based morphometry (VBM). In PSP patients, LASSO regression model was used to investigate associations between VBM-based Region-Of-Interest grey matter (GM) volumes and different categories of the PSP rating scale. A whole-brain multi-regression analysis was also used to identify brain areas where GM volumes correlated with the PIS in PSP patients. RESULTS: VBM analysis showed widespread GM atrophy (fronto-temporal-parietal-occipital regions, limbic lobes, insula, cerebellum, and basal ganglia) in PSP patients compared with control subjects. In PSP patients, LASSO regression analysis showed associations of the right cerebellar lobules IV-V with ocular motor category score, and the left Rolandic area with bulbar category score, while the right inferior frontal gyrus (IFG) was negatively correlated with the PIS. The whole-brain multi-regression analysis identified the right IFG as the only area significantly associated with the PIS. CONCLUSIONS: In our study, two different approaches demonstrated that the IFG volume was associated with PIS in PSP patients, suggesting that this area may play a role in the pathophysiological mechanisms underlying PI. Our findings may have important implications for developing optimal Transcranial Magnetic Stimulation protocols targeting IFG in parkinsonism with postural disorders.

Differentiating between common PSP phenotypes using structural MRI: a machine learning study.

BACKGROUND: Differentiating Progressive supranuclear palsy-Richardson's syndrome (PSP-RS) from PSP-Parkinsonism (PSP-P) may be extremely challenging. In this study, we aimed to distinguish these two PSP phenotypes using MRI structural data. METHODS: Sixty-two PSP-RS, 40 PSP-P patients and 33 control subjects were enrolled. All patients underwent brain 3 T-MRI; cortical thickness and cortical/subcortical volumes were extracted using Freesurfer on T1-weighted images. We calculated the automated MR Parkinsonism Index (MRPI) and its second version including also the third ventricle width (MRPI 2.0) and tested their classification performance. We also employed a Machine learning (ML) classification approach using two decision tree-based algorithms (eXtreme Gradient Boosting [XGBoost] and Random Forest) with different combinations of structural MRI data in differentiating between PSP phenotypes. RESULTS: MRPI and MRPI 2.0 had AUC of 0.88 and 0.81, respectively, in differentiating PSP-RS from PSP-P. ML models demonstrated that the combination of MRPI and volumetric/thickness data was more powerful than each feature alone. The two ML algorithms showed comparable results, and the best ML model in differentiating between PSP phenotypes used XGBoost with a combination of MRPI, cortical thickness and subcortical volumes (AUC 0.93 ± 0.04). Similar performance (AUC 0.93 ± 0.06) was also obtained in a sub-cohort of 59 early PSP patients. CONCLUSION: The combined use of MRPI and volumetric/thickness data was more accurate than each MRI feature alone in differentiating between PSP-RS and PSP-P. Our study supports the use of structural MRI to improve the early differential diagnosis between common PSP phenotypes, which may be relevant for prognostic implications and patient inclusion in clinical trials.

Assessing of the Italian version of the Memory Strategy Test (TMS) in people with Parkinson disease: a preliminary descriptive psychometric study.

BACKGROUND: Previous literature has shown that executive functions (EF) are related to performance in memory (M) tasks. The Test of Memory strategies (TMS) is a psychometric test that examines EF and M simultaneously and it was recently validated on an Italian healthy cohort. The first aim of the study was to apply TMS, for the first time, on a sample of patients with Parkinson's disease (PD), who are characterized by mild cognitive impairment. The second aim is to investigate whether TMS scores can discriminate PD patients from healthy controls. METHOD: Ninety-eight subjects were enrolled, including 68 patients with PD, and 30 Italian healthy controls (HC), who also underwent a memory evaluation through well-known tests. RESULTS: Confirmatory factor analysis (CFA) demonstrated that TMS of PD patients had a bi-dimensional structure as previously found in healthy cohort. In detail, The TMS-1 and TMS-2 lists require greater involvement of the EF factor, while TMS-3, TMS-4 and TMS-5 the M factor. Receiver operating characteristic (ROC) curves and precision-recall (PR) curves showed that the M subscale can distinguish between HC and PD, while EF had poor discrimination power. CONCLUSION: The hypothesized prediction model of TMS test seems to have adequate ability to discriminate PD from HC especially for the M function.

Cortical involvement in essential tremor with and without rest tremor: a machine learning study.

INTRODUCTION: There is some debate on the relationship between essential tremor with rest tremor (rET) and the classic ET syndrome, and only few MRI studies compared ET and rET patients. This study aimed to explore structural cortical differences between ET and rET, to improve the knowledge of these tremor syndromes. METHODS: Thirty-three ET patients, 30 rET patients and 45 control subjects (HC) were enrolled. Several MR morphometric variables (thickness, surface area, volume, roughness, mean curvature) of brain cortical regions were extracted using Freesurfer on T1-weighted images and compared among groups. The performance of a machine learning approach (XGBoost) using the extracted morphometric features was tested in discriminating between ET and rET patients. RESULTS: rET patients showed increased roughness and mean curvature in some fronto-temporal areas compared with HC and ET, and these metrics significantly correlated with cognitive scores. Cortical volume in the left pars opercularis was also lower in rET than in ET patients. No differences were found between ET and HC. XGBoost discriminated between rET and ET with mean AUC of 0.86 ± 0.11 in cross-validation analysis, using a model based on cortical volume. Cortical volume in the left pars opercularis was the most informative feature for classification between the two ET groups. CONCLUSION: Our study demonstrated higher cortical involvement in fronto-temporal areas in rET than in ET patients, which may be linked to the cognitive status. A machine learning approach based on MR volumetric data demonstrated that these two ET subtypes can be distinguished using structural cortical features.

Evaluating Autophagy Levels in Two Different Pancreatic Cell Models Using LC3 Immunofluorescence.

Autophagy is a specialized catabolic process that selectively degrades cytoplasmic components, including proteins and damaged organelles. Autophagy allows cells to physiologically respond to stress stimuli and, thus, maintain cellular homeostasis. Cancer cells might modulate their autophagy levels to adapt to adverse conditions such as hypoxia, nutrient deficiency, or damage caused by chemotherapy. Ductal pancreatic adenocarcinoma is one of the deadliest types of cancer. Pancreatic cancer cells have high autophagy activity due to the transcriptional upregulation and post-translational activation of autophagy proteins. Here, the PANC-1 cell line was used as a model of pancreatic human cancer cells, and the AR42J pancreatic acinar cell line was used as a physiological model of highly differentiated mammalian cells. This study used the immunofluorescence of microtubule-associated protein light chain 3 (LC3) as an indicator of the status of autophagy activation. LC3 is an autophagy protein that, in basal conditions, shows a diffuse pattern of distribution in the cytoplasm (known as LC3-I in this condition). Autophagy induction triggers the conjugation of LC3 to phosphatidylethanolamine on the surface of newly formed autophagosomes to form LC3-II, a membrane-bound protein that aids in the formation and expansion of autophagosomes. To quantify the number of labeled autophagic structures, the open-source software FIJI was utilized with the aid of the "3D Objects Counter" tool. The measure of the autophagic levels both in physiological conditions and in cancer cells allows us to study the modulation of autophagy under diverse conditions such as hypoxia, chemotherapy treatment, or the knockdown of certain proteins.

Autophagy in Inflammatory Response against SARS-CoV-2.

The coronavirus disease pandemic, which profoundly reshaped the world in 2019 (COVID-19), and is currently ongoing, has affected over 200 countries, caused over 500 million cumulative cases, and claimed the lives of over 6.4 million people worldwide as of August 2022. The causative agent is severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Depicting this virus' life cycle and pathogenic mechanisms, as well as the cellular host factors and pathways involved during infection, has great relevance for the development of therapeutic strategies. Autophagy is a catabolic process that sequesters damaged cell organelles, proteins, and external invading microbes, and delivers them to the lysosomes for degradation. Autophagy would be involved in the entry, endo, and release, as well as the transcription and translation, of the viral particles in the host cell. Secretory autophagy would also be involved in developing the thrombotic immune-inflammatory syndrome seen in a significant number of COVID-19 patients that can lead to severe illness and even death. This review aims to review the main aspects that characterize the complex and not yet fully elucidated relationship between SARS-CoV-2 infection and autophagy. It briefly describes the key concepts regarding autophagy and mentions its pro- and antiviral roles, while also noting the reciprocal effect of viral infection in autophagic pathways and their clinical aspects.

Cluster Analysis Method Reveals Gender Attitudes in Sociosexual Orientation of a Southern Italy Population During the COVID-19 Lockdown.

Introduction: The COVID-19 epidemic and its lockdown dramatically impacted the general well-being of the population and affected sociosexual experiences, thus modifying sexual behavior, desire, and well-being. Clustering analysis has not yet been applied to research and data investigating sociosexuality. The cluster analysis method could be a valid support for clinicians in investigating the condition of a population with respect to problems related to sociosexuality. The aim of the present study was to analyze the different perceptions of the sociosexual experiences in southern population during the COVID-19 pandemic. Methods: We enrolled 734 (450 female) participants with a carried out anonymous web-based survey from the 16th of April 2020 to the 3rd June of 2020. The revised Sociosexual Orientation Inventory (SOI-R) is a self-report test assessing three theoretically meaningful facets of sociosexual orientation (behavior, attitude, and desire). Results: We found eleven clusters, and the findings showed, for the first time, an intra- and inter-diagnostic heterogeneity in the sexual profile of participants. Theoretically, we identified subtype clusters whose sexual attitude was to avoid sexual promiscuity with significant gender differences. Women show a greater propensity for attitude and desire facet than men. Conclusions: Our new method of unsupervised learning could represent a reliable tool to support socio-cultural analysis studies on issues influenced by cultural mechanisms in a quick and explanatory way, as in the case of sexual orientation and attitude differences between men and women. Social and Policy Implications: Understanding these gaps is fundamental for policy makers, managers of social networks, those who deal with engaged couples and families, and sexuality starting from the very youngest adolescents. We claim to devise a strategy to measure how much a sexist culture implicitly and explicitly limits the freedom of sexual expression and how this can affect psycho-sexual well-being in a society. Supplementary Information: The online version contains supplementary material available at 10.1007/s13178-022-00771-2.

The validity and reliability of the Test of Memory Strategies among Italian healthy adults.

Background: Previous literature has shown that executive functions (EF) are related to performance in memory (M) tasks. Nevertheless, there is a shortage of psychometric tests that examine these two constructs simultaneously. The Test of Memory Strategies (TMS; previously validated in Spain and Portugal) could be a useful verbal learning task that evaluates these two constructs at once. In this study, we aimed to evaluate the psychometric properties of the TMS in an Italian adult sample. Method: One hundred twenty-one healthy volunteers (74 F, Mean age = 45.9 years old, SD = 20.4) who underwent a neuropsychological examination participated in this study. We conducted a Confirmatory factor analysis (CFA) to evaluate the structural validity of the TMS. We conducted a latent variable analysis to examine convergent and discriminant validity of the TMS sub-scale scores reflecting executive functions and memory. We also examined the TMS reliability in terms of internal consistency through the McDonald's omega. Results: The CFA confirmed the expectation that the TMS-1 and TMS-2 subtests reflect a factor and that the TMS-3, TMS-4, and TMS-5 subtests reflect a different factor. This result is in line with the prediction that TMS-1 and TMS-2 require the use of executive functions and memory simultaneously, and therefore we called this factor executive functions (EF); whereas the TMS-3, TMS-4, and TMS-5 subtests require less involvement of executive functions, thus reflecting a construct that we named memory (M). The TMS subtests for EF and M showed convergent validity with the test scores using a traditional neuropsychological battery, assessing memory and executive functions separately. Finally, the reliability of the subtests was good. Conclusions: These preliminary findings suggest that TMS is a valid and reliable scale to simultaneously assess M and EF while among Italian healthy adults.

Protein expression in exocrine pancreatic diseases. Focus on VMP1 mediated autophagy.

The exocrine pancreas produces enzymes involved in the digestive process whereas endocrine pancreas mainly regulates glucose metabolism. Diseases of the exocrine pancreas are characterized by high morbidity and mortality. Acute pancreatitis is a painful disease in which pancreatic secretory proteins are prematurely activated causing the digestion of the gland. Pancreatic adenocarcinoma is one of the most malignant cancers due to its resistance to treatment, its late diagnosis and high capacity for metastasis. Autophagy is a catabolic process that aims at degrading cytoplasmic contents and damaged organelles, to preserve cell viability and homeostasis. VMP1 is a transmembrane protein that plays a key role in triggering autophagy and being part of the autophagosome membrane. A specific type of selective autophagy pathway called zymophagy protects the pancreas against self-digestion in the setting of acute pancreatitis by sequestering intracellularly activated zymogen granules. Mitophagy is also responsible for maintaining pancreatitis as a mild disease by preserving mitochondrial function. Dysregulation of these selective autophagic processes by pancreatitis itself constitutes a risk factor for development of severe disease. In pancreatic adenocarcinoma, VMP1 mediated autophagy promotes cancer cell survival and resistance to chemotherapy. Therefore, it is relevant to highlight a role for controlling VMP1 expression and targeting VMP1 molecular pathways to improve exocrine pancreatic diseases prognosis.

Cortical atrophy distinguishes idiopathic normal-pressure hydrocephalus from progressive supranuclear palsy: A machine learning approach.

INTRODUCTION: Progressive supranuclear palsy (PSP) and idiopathic normal pressure hydrocephalus (iNPH) share several clinical and radiological features, making the differential diagnosis challenging. In this study, we aimed to differentiate between these two diseases using a machine learning approach based on cortical thickness and volumetric data. METHODS: Twenty-three iNPH patients, 50 PSP patients and 55 control subjects were enrolled. All participants underwent a brain 3T-MRI, and cortical thickness and volumes were extracted using Freesurfer 6 on T1-weighted images and compared among groups. Finally, the performance of a machine learning approach with random forest using the extracted cortical features was investigated to differentiate between iNPH and PSP patients. RESULTS: iNPH patients showed cortical thinning and volume loss in the frontal lobe, temporal lobe and cingulate cortex, and thickening in the superior parietal gyrus in comparison with controls and PSP patients. PSP patients only showed mild thickness and volume reduction in the frontal lobe, compared to control subjects. Random Forest algorithm distinguished iNPH patients from controls with AUC of 0.96 and from PSP patients with AUC of 0.95, while a lower performance (AUC 0.76) was reached in distinguishing PSP from controls. CONCLUSION: This study demonstrated a more severe and widespread cortical involvement in iNPH than in PSP, possibly due to the marked lateral ventricular enlargement which characterizes iNPH. A machine learning model using thickness and volumetric data led to accurate differentiation between iNPH and PSP patients, which may help clinicians in the differential diagnosis and in the selection of patients for shunt procedures.