Search Results (1,203)

Background/Objectives: Can three-dimensional (3D) reconstruction software that simulates postoperative lung volumes more effectively identify suitable candidates for anatomical lung resection compared to conventional methods, particularly in personalized surgical planning? Patients/Methods: This single-center pilot study included 20 patients (10 females; age 68 ± 10 years) who underwent segmental or lobar VATS resection of the right upper lobe for NSCLC. Three-dimensional simulations from preoperative HRCT scans were correlated with measured pulmonary function and compared with predictions from the “5% per segment rule” and the model proposed by Brunelli et al. Results: Patients (8/20) with increased postoperative FEV1 [2.40 (0.56) vs. 2.30 (0.55)] had a lower proportion of healthy tissue [76 (18)% vs. 89 (10)%, p = 0.045] in 3D simulations than those with decreased FEV1. Mean postoperative FEV1 was 2.3 (0.54); the Brunelli model predicted 1.8 (0.36) and the “5% rule” 2.2 (0.54). Both models underestimated postoperative function, though the “5% rule” was more accurate. Conclusions: This pilot study suggests that 3D-HRCT reconstruction has the potential to facilitate patient-tailored identification of individuals who may derive greater benefit from surgical intervention compared to conventional methods. Further research is needed to determine whether this technology can more accurately predict postoperative pulmonary function in patients with severe COPD. Utilizing 3D-segmental-HRCT-reconstruction software, the advantages of lung resection in the context of NSCLC can be assessed on an individualized patient basis. Full article

Background/Objectives: Radiology often presents communication challenges due to its technical complexity, particularly for patients, trainees, and non-specialist clinicians. This study aims to evaluate the effectiveness of RadioBot, an AI-powered chatbot developed on the Botpress platform, in enhancing radiological communication through natural language processing (NLP). Methods: RadioBot was designed to provide context-sensitive responses based on guidelines from the American College of Radiology (ACR) and the Radiological Society of North America (RSNA). It addresses queries related to imaging indications, contraindications, preparation, and post-procedural care. A structured evaluation was conducted with twelve participants—patients, residents, and radiologists—who assessed the chatbot using a standardized quality and satisfaction scale. Results: The chatbot received high satisfaction scores, particularly from patients (mean = 4.425) and residents (mean = 4.250), while radiologists provided more critical feedback (mean = 3.775). Users appreciated the system’s clarity, accessibility, and its role in reducing informational bottlenecks. The perceived usefulness of the chatbot inversely correlated with the user’s level of expertise, serving as an educational tool for novices and a time-saving reference for experts. Conclusions: RadioBot demonstrates strong potential in improving radiological communication and supporting clinical workflows, especially with patients where it plays an important role in personalized medicine by framing radiology data within each individual’s cognitive and emotional context, which improves understanding and reduces associated diagnostic anxiety. Despite limitations such as occasional contextual incoherence and limited multimodal capabilities, the system effectively disseminates radiological knowledge. Future developments should focus on enhancing personalization based on user specialization and exploring alternative platforms to optimize performance and user experience. Full article

A healthy vasculature with well-regulated perfusion and pulsatility is essential for the brain. One vascular structure that has received little attention is the carotid siphon. The proximal portion of the siphon is stiff due to the narrow location in the skull base, whilst the distal portion is highly flexible. This flexible part in combination with the specific curves lead to lower pulsatility at the cost of energy deposition in the arterial wall. This deposited energy contributes to damage and calcification. Severe siphon calcification stiffens the distal part of the siphon, leading to less damping of the pulsatility. Increased blood flow pulsatility is a possible cause of stroke and cognitive disorders. In this review, based on comprehensive multimodality imaging, we first describe the anatomy and physiology of the carotid siphon. Subsequently, we review the in vivo imaging data, which indeed suggest that the siphon attenuates pulsatility. Finally, the data as available in the literature are shown to provide convincing evidence that severe siphon calcifications and the calcification pattern are linked to incident stroke and dementia. Interventional studies are required to test whether this association is causal and how an assessment of pulsatility and the siphon calcification pattern can improve personalized medicine, working to prevent and treat brain disease. Full article

Background: Transcranial direct current stimulation (tDCS) has emerged as a promising neuromodulatory tool for language rehabilitation in chronic aphasia. However, the effects of bi-hemispheric, multisite stimulation remain largely unexplored, especially in people with chronic and treatment-resistant language impairments. The goal of this study is to look at the effects on behavior and brain activity of an individualized language training program that combines bi-hemispheric multisite anodal tDCS with personalized language training for Albert, a patient with long-standing, treatment-resistant non-fluent aphasia. Methods: Albert, a right-handed retired physician, had transcortical motor aphasia (TCMA) subsequent to a left-hemispheric ischemic stroke occurring more than six years before the operation. Even after years of traditional treatment, his expressive and receptive language deficits remained severe and persistent despite multiple rounds of traditional therapy. He had 15 sessions of bi-hemispheric multisite anodal tDCS aimed at bilateral dorsal language streams, administered simultaneously with language training customized to address his particular phonological and syntactic deficiencies. Psycholinguistic evaluations were performed at baseline, immediately following the intervention, and at 1, 2, 3, and 6 months post-intervention. Resting-state fMRI was conducted at baseline and following the intervention to evaluate alterations in functional connectivity (FC). Results: We noted statistically significant enhancements in auditory sentence comprehension and oral reading, particularly at the 1- and 3-month follow-ups. Neuroimaging showed decreased functional connectivity (FC) in the left inferior frontal and precentral regions (dorsal stream) and in maladaptive right superior temporal regions, alongside increased FC in left superior temporal areas (ventral stream). This pattern suggests that language networks may be reorganizing in a more efficient way. There was no significant improvement in phonological processing, which may indicate reduced connectivity in the left inferior frontal areas. Conclusions: This case underscores the potential of combining individualized, network-targeted language training with bi-hemispheric multisite tDCS to enhance recovery in chronic, treatment-resistant aphasia. The convergence of behavioral gains and neuroplasticity highlights the importance of precision neuromodulation approaches. However, findings are preliminary and warrant further validation through controlled studies to establish broader efficacy and sustainability of outcomes. Full article

Background/Objectives: To identify factors associated with the referral by a multiprofessional team to dental services for children and adolescents with rare genetic diseases. Methods: A cross-sectional study was developed with 87 children/adolescents with mucopolysaccharidosis (n = 26) and osteogenesis imperfecta (n = 61) and their caregivers. Recruitment took place at reference centers for rare genetic conditions in five Brazilian states. The caregivers answered a questionnaire on the children. They were examined for malocclusion, dental anomalies, caries experience, and gingivitis. Bivariate and multivariate analyses of the data were performed, considering a 95% confidence level. Results: The average age of children/adolescents was 10.4 years (±5.6) and 17.3% had never gone to a dentist. Among those with past dental experience, the reason for most appointments was oral prophylaxis/preventive maintenance (62.1%). With regard to referrals to a dentist by the multidisciplinary team, 29.9% had never received a referral. The likelihood of having been referred to a dentist by the multiprofessional team was 2.67 times greater for female patients (95% CI: 0.96–7.42) and 7.74 times greater for children/adolescents with a history of toothache (95% CI: 1.61–37.14). Conclusions: Female children/adolescents with mucopolysaccharidosis and osteogenesis imperfecta and those with a history of dental pain were more likely to have been advised by the multiprofessional team to seek dental treatment. Full article

Background: Food addiction (FA) is an emerging construct that mirrors the behavioral and neurobiological characteristics of substance use disorders. Despite growing interest, its association with specific psychiatric disorders among bariatric patients remains understudied. Objective: Our aim was to examine the prevalence and strength of associations between FA and seven major psychiatric disorders in individuals who underwent bariatric surgery. Methods: In a sample of 100 post-bariatric patients referred for psychiatric evaluation, FA was assessed using the modified Yale Food Addiction Scale 2.0 (mYFAS 2.0), and psychiatric disorders were diagnosed using the Mini International Neuropsychiatric Interview (MINI). Logistic regression models were used to estimate adjusted odds ratios (aORs) for the association between FA and each psychiatric disorder, controlling for sex, age, body mass index (BMI), employment status, the number of children, clinical comorbidities, physical activity, family psychiatric history, and region of residence. Results: FA was present in 51% of the sample. Descriptive analyses revealed a significantly higher prevalence of major depressive disorder, panic disorder, generalized anxiety disorder, social anxiety disorder, agoraphobia, obsessive–compulsive disorder, and bulimia nervosa among individuals with FA. Multivariate models showed robust associations between FA and bulimia nervosa (aOR = 19.42, p < 0.05), generalized anxiety disorder (aOR = 2.88, p < 0.05), obsessive–compulsive disorder (aOR = 6.64, p < 0.05), agoraphobia (aOR = 3.14, p < 0.05), social anxiety disorder (aOR = 4.28, p < 0.05) and major depressive disorder (aOR = 2.79, p < 0.05). Conclusions: FA is strongly associated with a range of psychiatric comorbidities in post-bariatric patients, reinforcing the need for comprehensive mental health screening in this population. These findings underscore the potential role of FA as a clinical marker for stratified risk assessment, supporting more personalized approaches to mental health monitoring and intervention following bariatric surgery. Full article

Background/Objectives: Transcatheter aortic valve replacement (TAVR) has been introduced as an optimal treatment for patients with severe aortic stenosis, offering a minimally invasive alternative to surgical aortic valve replacement. Predicting these outcomes following TAVR is crucial. Artificial intelligence (AI) has emerged as a promising tool for improving post-TAVR outcome prediction. In this systematic review and meta-analysis, we aim to summarize the current evidence on utilizing AI in predicting post-TAVR outcomes. Methods: A comprehensive search was conducted to evaluate the studies focused on TAVR that applied AI methods for risk stratification. We assessed various ML algorithms, including random forests, neural networks, extreme gradient boosting, and support vector machines. Model performance metrics—recall, area under the curve (AUC), and accuracy—were collected with 95% confidence intervals (CIs). A random-effects meta-analysis was conducted to pool effect estimates. Results: We included 43 studies evaluating 366,269 patients (mean age 80 ± 8.25; 52.9% men) following TAVR. Meta-analyses for AI model performances demonstrated the following results: all-cause mortality (AUC = 0.78 (0.74–0.82), accuracy = 0.81 (0.69–0.89), and recall = 0.90 (0.70–0.97); permanent pacemaker implantation or new left bundle branch block (AUC = 0.75 (0.68–0.82), accuracy = 0.73 (0.59–0.84), and recall = 0.87 (0.50–0.98)); valve-related dysfunction (AUC = 0.73 (0.62–0.84), accuracy = 0.79 (0.57–0.91), and recall = 0.54 (0.26–0.80)); and major adverse cardiovascular events (AUC = 0.79 (0.67–0.92)). Subgroup analyses based on the model development approaches indicated that models incorporating baseline clinical data, imaging, and biomarker information enhanced predictive performance. Conclusions: AI-based risk prediction for TAVR complications has demonstrated promising performance. However, it is necessary to evaluate the efficiency of the aforementioned models in external validation datasets. Full article

Background: Peritoneal metastases from gastric cancer (GCPM) represent a significant clinical challenge in terms of therapeutic options and prognosis. Cytoreductive surgery (CRS) combined with hyperthermic intraperitoneal chemotherapy (HIPEC) has demonstrated promising survival benefits within a multimodal approach, particularly in carefully selected patients. Methods: This retrospective single-center study evaluated outcomes in patients with synchronous GCPM treated with CRS + HIPEC following neoadjuvant chemotherapy. The primary endpoints included overall survival (OS), disease-free survival (DFS), and identification of prognostic factors associated with poor outcomes. Additionally, we sought to characterize patients achieving long-term survival (OS ≥ 24 months). Results: The median OS and DFS were 18 and 13 months, respectively. A peritoneal cancer index (PCI) ≥ 7 and major postoperative complications were independently associated with reduced survival. Recurrence was significantly linked to PCI ≥ 7 and signet ring cell histology. Stratification by survival outcome identified PCI ≥ 7 as the only statistically significant variable differentiating average- and long-survival groups. Moreover, elevated PCI was independently associated with a higher incidence of major postoperative complications. Conclusions: CRS + HIPEC may offer a survival advantage over the use of systemic therapy exclusively in appropriately selected patients, particularly those with limited peritoneal disease burden. These results underscore the importance of accurate patient selection to balance surgical risks and maximize oncological benefits in the treatment of GCPM. Full article

Background/Objectives: Degenerative joint diseases (DJDs) involve intricate molecular disruptions within bone, cartilage, and synovial tissues, often preceding overt radiographic changes. These tissues exhibit complex biomolecular architectures and their degeneration leads to microstructural disorganization and inflammation that are challenging to detect with conventional imaging techniques. This review aims to synthesize recent advances in imaging, computational modeling, and sequencing technologies that enable high-resolution, non-invasive characterization of joint tissue health. Methods: We examined advanced modalities including high-resolution MRI (e.g., T1ρ, sodium MRI), quantitative and dual-energy CT (qCT, DECT), and ultrasound elastography, integrating them with radiomics, deep learning, and multi-scale modeling approaches. We also evaluated RNA-seq, spatial transcriptomics, and mass spectrometry-based proteomics for omics-guided imaging biomarker discovery. Results: Emerging technologies now permit detailed visualization of proteoglycan content, collagen integrity, mineralization patterns, and inflammatory microenvironments. Computational frameworks ranging from convolutional neural networks to finite element and agent-based models enhance diagnostic granularity. Multi-omics integration links imaging phenotypes to gene and protein expression, enabling predictive modeling of tissue remodeling, risk stratification, and personalized therapy planning. Conclusions: The convergence of imaging, AI, and molecular profiling is transforming musculoskeletal diagnostics. These synergistic platforms enable early detection, multi-parametric tissue assessment, and targeted intervention. Widespread clinical integration requires robust data infrastructure, regulatory compliance, and physician education, but offers a pathway toward precision musculoskeletal care. Full article

Background/Objectives: There is a growing need for efficient prostate MRI protocols due to their increasing use in managing prostate cancer (PCa) and potential inclusion in screening. Deep learning reconstruction (DLR) may enhance MR acquisitions and improve image quality compared to conventional acceleration techniques. This systematic review examines DLR approaches to prostate MRI. Methods: A search of PubMed, Web of Science, and Google Scholar identified eligible studies comparing DLR to conventional reconstruction for prostate imaging. A narrative synthesis was performed to summarize the impact of DLR on acquisition time, image quality, and diagnostic performance. Results: Thirty-three studies showed that DLR can reduce acquisition times for T₂w and DWI imaging while maintaining or improving image quality. It did not significantly affect clinical tasks, such as biopsy decisions, and performed comparably to human readers in PI-RADS scoring and the detection of extraprostatic extension. However, AI models trained on conventional data might be less accurate with DLR images. The heterogeneity in image quality metrics among the studies prevented quantitative synthesis. Discussion: DLR has the potential to achieve substantial time savings in prostate MRI while maintaining image quality, which is especially relevant because of increased MRI demands. Future research should address the effect of DLR on clinically relevant downstream tasks, including AI algorithms’ performances and biopsy decisions, and explore task-specific accelerated protocols for screening, image-guided biopsy, and treatment. Full article

Background/Objectives: Recently, shear wave elastography (SWE) and dispersion (SWD) targeting the pancreas have been attempted as noninvasive procedures to evaluate personalized conditions. This study aimed to analyze the feasibility of utilizing them for evaluating the individual need of introducing insulin therapy, combined with the C-peptide index (CPI), in patients with type 2 diabetes mellitus (T2DM). Methods: This study involved 51 patients with T2DM aged ≥20 years old and 20 control subjects without impaired glucose tolerance (CTRL). T2DM were divided into non-insulin-treated (non-INS) and insulin-treated (INS) groups. Their background data, shear wave speed (SWS), and dispersion slope (DS) of the pancreas were obtained on the same day. Results: Pancreatic SWS was higher in T2DM than in CTRL (p < 0.0001), with an AUC of 0.840, sensitivity of 89.1%, and specificity of 70.6%, using a Youden index cutoff of 1.31 m/s. INS and non-INS were discriminated with the cutoff value of 1.70 m/s (p = 0.031, AUC 0.736, sensitivity 55.6% and specificity 89.2%). Pancreatic DS of INS and non-INS was 13.52 and 12.16 (m/s)/kHz, respectively (p = 0.046). Using 12.38 (m/s)/kHz as the cutoff, AUC was 0.718, with sensitivity of 88.9%, specificity of 56.8% and negative predictive value of 95.5%. CPI had AUC of 0.724, sensitivity of 66.7% and specificity of 83.3% with the cutoff of 0.63. With combination of SWS and CPI, all patients with SWS < 1.70 m/s and CPI > 0.476 belonged to non-INS. Conclusions: Simultaneous non-invasive SWE and CPI evaluation showed the feasibility for estimating personalized insulin initiation needs in T2DM, integrating biophysical and hormonal perspectives. Further investigation with a larger, multi-center study population is warranted to enhance the level of evidence. Full article

Primary hyperparathyroidism is commonly caused by parathyroid adenomas, hyperplasia, or, rarely, carcinoma. In up to 20% of cases, parathyroid tissue may be ectopic, often located in the mediastinum due to aberrant embryologic migration. Ectopic parathyroid glands pose a diagnostic and therapeutic challenge, and an accurate preoperative localization is essential for an effective and safe resection. Imaging modalities such as CT scan, TC-sestamibi scintigraphy, PET/CT, ultrasonography and MRI are routinely employed, whereas combined techniques offer improved diagnostic accuracy. Emerging approaches, however, including PET/CT with choline tracers, have shown promise in enhancing sensitivity in complex or recurrent cases. When ectopic glands are in the mediastinum, thoracic surgical intervention is required. Traditional open approaches, such as sternotomy or thoracotomy, are associated with significant morbidity. The development and evolution of minimally invasive surgery (MIS) has become the preferred approach in selected cases. When MIS is performed, intraoperative assessment and parathyroid identification are crucial to ensure complete gland removal. Intraoperative parathyroid hormone (ioPTH) monitoring provides real-time confirmation of surgical success. The integration of advanced imaging, intraoperative monitoring, and minimally invasive techniques significantly improves surgical outcomes while minimizing complications and accelerating patient recovery. Ultimately, the effective treatment of ectopic parathyroid glands relies on a personalized approach, adapting both diagnostic and surgical strategies to the unique anatomical and clinical context of each patient. Integration of advanced imaging, intraoperative monitoring, and minimally invasive techniques, combined with a multidisciplinary team involving endocrinologists, radiologists, and thoracic surgeons, is key to optimizing outcomes and reducing patient morbidity. Full article

Background: Charcot–Marie–Tooth disease (CMT) is a genetically and clinically heterogeneous group of progressive peripheral neuropathies. Preimplantation genetic testing for monogenic disorders (PGT-M), a well-established assisted reproductive technology used to detect specific genetic mutations in embryos before implantation, has been used in common CMT subtypes (e.g., CMT1A); however, data on its application across rarer subtypes and in de novo cases remain limited. In this study, we aimed to evaluate the effectiveness of PGT-M using karyomapping in achieving clinical pregnancies and healthy births in families affected by various CMT types, including the previously unreported subtypes CMT1B and CMT2. Methods: We analyzed 31 PGT-M cycles from 13 families with genetically confirmed CMT, including cases of previously unreported subtypes CMT1B and CMT2. A total of 150 embryos were biopsied. Through 19 embryo transfer cycles, 21 embryos were transferred. In one de novo case, karyomapping was performed using amniotic fluid from an affected fetus as a reference. Results: Of the 19 embryo transfers, 15 resulted in clinical pregnancies. Prenatal diagnosis confirmed that all fetuses were unaffected, and all pregnancies resulted in healthy live births. Successful phasing using amniotic fluid from an affected fetus enabled accurate embryo selection and led to the birth of healthy twins. Conclusions: PGT-M using karyomapping is a rapid and reliable method for achieving successful pregnancies in families affected by diverse CMT subtypes, including de novo cases, and supports broader applicability to other monogenic disorders. Full article

Introduction: Interventional radiotherapy (brachytherapy, IRT, BT) has evolved with technological advancements, improving dose precision while minimizing exposure to healthy tissues. The integration of 3D-printing technology in IRT has enabled the development of patient-specific devices, optimizing treatment personalization and dosimetric accuracy. Methods: A systematic literature search was conducted in PubMed, Scopus, and Google Scholar to identify studies published between 2020 and 2024 on 3D-printing applications in IRT. The selection process resulted in 74 peer-reviewed articles categorized by radioactive source, brachytherapy technique, endpoint of the 3D-printed product, and study type. Results: The analysis highlights the growing implementation of 3D-printed devices in brachytherapy, particularly in gynecological, prostate, and skin cancers. Most studies focus on technique, including intracavitary, interstitial, and contact applications, with custom applicators and templates emerging as predominant endpoints. The majority of studies involved in vivo clinical applications, followed by in silico computational modeling and in vitro experiments. Conclusions: The upward trend in scientific publications underscores the growing attention on 3D printing for enhancing personalized brachytherapy. The increasing use of 3D-printed templates and applicators highlights their role in optimizing dose delivery and expanding personalized treatment strategies. The current research trend is shifting toward real-world data and in vivo studies to assess clinical applications, ensuring these innovations translate effectively into routine practice. The integration of 3D printing represents a major advancement in radiation oncology, with the potential to enhance treatment efficacy and patient outcomes. Future research should focus on standardizing manufacturing processes and expanding clinical validation to facilitate broader adoption. Full article

Neurophysiological techniques, particularly somatosensory evoked potentials (SEPs) and electroencephalography (EEG), are essential tools for the functional and prognostic evaluation of patients with prolonged disorders of consciousness (DoC) in intensive neurorehabilitation settings. This narrative review critically analyzes the most relevant evidence regarding the use of SEPs and EEG in the management of post-comatose patients, highlighting the strategic role of physiatrists in integrating these assessments into individualized rehabilitation plans. A systematic search was conducted across major international databases (PubMed, Embase, Scopus, Cinahl, and DiTA) until December 2024, selecting consensus documents, official guidelines (including the 2021 ERC/ESICM guidelines), systematic reviews, observational studies, and significant Italian neurophysiological contributions. The literature supports the strong prognostic value of the bilateral presence of the N20 component in SEPs, while its early bilateral absence, particularly in post-anoxic cases, is a robust predictor of poor neurological outcomes. EEG provides complementary information, with continuous, reactive, and symmetrical patterns associated with favorable outcomes, while pathological patterns, such as burst suppression or isoelectric activity, predict a worse prognosis. Combining SEP and EEG assessments significantly improves prognostic sensitivity and specificity, especially in sedated or metabolically compromised patients. Additionally, the use of direct muscle stimulation (DMS) and nerve conduction studies enables accurate differentiation between central and peripheral impairments, which is crucial for effective rehabilitation planning. Overall, SEPs and EEG should be systematically incorporated into the evaluation and follow-up of DoC patients, and the acquisition of neurophysiological competencies by physiatrists represents a strategic priority for modern, effective, and personalized neurorehabilitation. Full article