Cardiovascular magnetic resonance insights into anomalies of the mitral valve apparatus in Fabry cardiomyopathy and hypertrophic cardiomyopathy.

Background and aims: Despite different etiopathogenesis, Fabry Disease cardiomyopathy (FDc) and sarcomeric hypertrophic cardiomyopathy (HCM) share a similar hypertrophic phenotype, including anomalies of the mitral valve apparatus (AMVA). Some of these anomalies have also been described in the pre-hypertrophic stage of both diseases. This cardiovascular magnetic resonance (CMR) study aimed to: (i) compare AMVA between FDc and HCM with a similar degree of left ventricular hypertrophy (LVH), to add new insights into differential diagnosis; (ii) assess whether AMVA represent an early and progressive alteration in FDc; (iii) propose simple and potentially reproducible measurements of AMVA. Methods: This observational, retrospective study enrolled: (i) 80 Fabry patients, divided into three groups with increasing severity of cardiac phenotype (20 patients LVH-/normal T1, 20 patients LVH-/low T1 and 40 patients LVH+), and (ii) 40 patients with HCM. All patients underwent CMR. The LVH + FDc and the HCM groups were matched for age, sex, body surface area and left ventricular (LV) mass. The following AMVA were measured on cine images: papillary muscles (PMs) hypertrophy (maximal diameter (Dmax) of anterolateral (Al) and posteromedial (Pm) PM), apical displacement, anteriorization of Al PM and anterior mitral valve leaflet (AMVL) elongation. Reference values for defining AMVA were derived from a matched healthy control group (n = 40). Results: Both HCM and FDc LVH + patients showed PMs hypertrophy, with a greater degree in the FDc LVH + group [Dmax Al PM 16 ± 3.4 vs. 15 ± 3.1 mm, p 0.017; Dmax Pm PM 14 ± 4.0 vs.12 mm (10.0-14.0), p 0.039] As compared to controls, both HCM and FDc LVH + patients showed PMs apical displacement (HCM 83% vs. healthy volunteers 8%, p < 0.001; FDc LVH + 65% vs. healthy volunteers 8%, p < 0.001), with a greater prevalence in HCM. Anteriorization of Al PM was only evident in HCM (15 ± 6.2 vs. healthy controls 21 ± 5.3 mm, p < 0.001). Elongation of AMVL was detected both in HCM and FDc with LVH + (HCM 29 ± 4.0 vs. healthy volunteers 24 ± 2.9 mm, p < 0.001; FDc LVH + 27 ± 4.0 vs. healthy volunteers 24 ± 2.9 mm, p < 0.001) without significant differences between the two phenocopies. The prevalence of myocardial crypts was higher among HCM patients than in FDc LVH + patients (75% vs. 48%, p 0.012). Conclusions: we report greater PMs hypertrophy in FDc and a higher prevalence of PMs positional alterations (anterior and apical displacement) and myocardial crypts in HCM. All these AMVA became more pronounced with the progression of the FDc phenotype. We suggest the systematic inclusion of the analysis of AMVA by simple linear measurements on cine images in the CMR assessment of hypertrophic cardiomyopathies, to help in the differential diagnosis between HCM and FDc and to facilitate early detection of cardiac involvement in FDc.

Clinical impact of AI in radiology department management: a systematic review.

PURPOSE: Artificial intelligence (AI) has revolutionized medical diagnosis and treatment. Breakthroughs in diagnostic applications make headlines, but AI in department administration (admin AI) likely deserves more attention. With the present study we conducted a systematic review of the literature on clinical impacts of admin AI in radiology. METHODS: Three electronic databases were searched for studies published in the last 5 years. Three independent reviewers evaluated the records using a tailored version of the Critical Appraisal Skills Program. RESULTS: Of the 1486 records retrieved, only six met the inclusion criteria for further analysis, signaling the scarcity of evidence for research into admin AI. CONCLUSIONS: Despite the scarcity of studies, current evidence supports our hypothesis that admin AI holds promise for administrative application in radiology departments. Admin AI can directly benefit patient care and treatment outcomes by improving healthcare access and optimizing clinical processes. Furthermore, admin AI can be applied in error-prone administrative processes, allowing medical professionals to spend more time on direct clinical care. The scientific community should broaden its attention to include admin AI, as more real-world data are needed to quantify its benefits. LIMITATIONS: This exploratory study lacks extensive quantitative data backing administrative AI. Further studies are warranted to quantify the impacts.

When Paying Attention Pays Back: Missense Mutation c.1006G>A p. (Val336Ile) in PRKAG2 Gene Causing Left Ventricular Hypertrophy and Conduction Abnormalities in a Caucasian Patient: Case Report and Literature Review.

PRKAG2 cardiomyopathy is a rare genetic disorder that manifests early in life with an autosomal dominant inheritance pattern. It harbors left ventricular hypertrophy (LVH), ventricular pre-excitation and progressively worsening conduction system defects. Its estimated prevalence among patients with LVH ranges from 0.23 to about 1%, but it is likely an underdiagnosed condition. We report the association of the PRKAG2 missense variant c.1006G>A p. (Val336Ile) with LVH, conduction abnormalities (short PR interval and incomplete right bundle branch bock) and early-onset arterial hypertension (AH) in a 44-year-old Caucasian patient. While cardiac magnetic resonance (CMR) showed a mild hypertrophic phenotype with maximal wall thickness of 17 mm in absence of tissue alterations, the electric phenotype was relevant including brady-tachy syndrome and recurrent syncope. The same variant has been detected in the patient's sister and daughter, with LVH + early-onset AH and electrocardiographic (ECG) alterations + lipothymic episodes, respectively. Paying close attention to the coexistence of LVH and ECG alterations in the proband has been helpful in directing genetic tests to exclude primary cardiomyopathy. Hence, identifying the genetic basis in the patient allowed for familial screening as well as a proper follow-up and therapeutic management of the affected members. A review of the PRKAG2 cardiomyopathy literature is provided alongside the case report.

Errors in Radiology: A Standard Review.

Radiological interpretations, while essential, are not infallible and are best understood as expert opinions formed through the evaluation of available evidence. Acknowledging the inherent possibility of error is crucial, as it frames the discussion on improving diagnostic accuracy and patient care. A comprehensive review of error classifications highlights the complexity of diagnostic errors, drawing on recent frameworks to categorize them into perceptual and cognitive errors, among others. This classification underpins an analysis of specific error types, their prevalence, and implications for clinical practice. Additionally, we address the psychological impact of radiological practice, including the effects of mental health and burnout on diagnostic accuracy. The potential of artificial intelligence (AI) in mitigating errors is discussed, alongside ethical and regulatory considerations in its application. This research contributes to the body of knowledge on radiological errors, offering insights into preventive strategies and the integration of AI to enhance diagnostic practices. It underscores the importance of a nuanced understanding of errors in radiology, aiming to foster improvements in patient care and radiological accuracy.

ESR Essentials: image guided drainage of fluid collections-practice recommendations by the Cardiovascular and Interventional Radiological Society of Europe.

This ESR Essentials article intends to provide detailed, step-by-step, information on the role of imaging in the diagnosis, procedural management, and follow-up of patients with fluid collections. Evidence-based medicine recommendations for the positioning of percutaneous drainages and/or for diagnostic/therapeutic aspiration of fluid collections are provided. Although medical history, clinical symptoms, physical examination, and laboratory tests can raise suspicions regarding a collection, an imaging assessment is usually necessary for the diagnosis. Radiologists can easily identify fluid collections that are clinically suspected by using a wide range of imaging modalities, such as ultrasound, CT, MRI, and cone-beam CT. Consequently, these imaging methods (either alone or combined), can be used to aspirate the collection or for the placement of a drainage catheter. The choice of imaging technique to be used is influenced by the location of the collection, operator preference, size, and content of the collection. In addition, it is of utmost importance to underline the role of the interventional radiologist in the management and follow-up of patients with percutaneous drains, in collaboration with surgeons, clinicians, and diagnostic radiologists. KEY POINTS: Indications for percutaneous imaging-guided drainage are supported by clinical findings, laboratory tests, and pre-procedural imaging. Deciding between aspiration or drain insertion should follow patient assessment and fluid collection characterization. The interventional radiologist should be part of the entire patient care process including follow-up.

Dual-Energy Computed Tomography in Urological Diseases: A Narrative Review.

Dual-Energy computed tomography (DECT) with its various advanced techniques, including Virtual Non-Contrast (VNC), effective atomic number (Z-eff) calculation, Z-maps, Iodine Density Index (IDI), and so on, holds great promise in the diagnosis and management of urogenital tumours. In this narrative review, we analyze the current status of knowledge of this technology to provide better lesion characterization, improve the staging accuracy, and give more precise treatment response assessments in relation to urological tumours.

AI in Radiology: Navigating Medical Responsibility.

The application of Artificial Intelligence (AI) facilitates medical activities by automating routine tasks for healthcare professionals. AI augments but does not replace human decision-making, thus complicating the process of addressing legal responsibility. This study investigates the legal challenges associated with the medical use of AI in radiology, analyzing relevant case law and literature, with a specific focus on professional liability attribution. In the case of an error, the primary responsibility remains with the physician, with possible shared liability with developers according to the framework of medical device liability. If there is disagreement with the AI's findings, the physician must not only pursue but also justify their choices according to prevailing professional standards. Regulations must balance the autonomy of AI systems with the need for responsible clinical practice. Effective use of AI-generated evaluations requires knowledge of data dynamics and metrics like sensitivity and specificity, even without a clear understanding of the underlying algorithms: the opacity (referred to as the "black box phenomenon") of certain systems raises concerns about the interpretation and actual usability of results for both physicians and patients. AI is redefining healthcare, underscoring the imperative for robust liability frameworks, meticulous updates of systems, and transparent patient communication regarding AI involvement.

Radiologists' perceptions on AI integration: An in-depth survey study.

PURPOSE: To assess the perceptions and attitudes of radiologists toward the adoption of artificial intelligence (AI) in clinical practice. METHODS: A survey was conducted among members of the SIRM Lombardy. Radiologists' attitudes were assessed comprehensively, covering satisfaction with AI-based tools, propensity for innovation, and optimism for the future. The questionnaire consisted of two sections: the first gathered demographic and professional information using categorical responses, while the second evaluated radiologists' attitudes toward AI through Likert-type responses ranging from 1 to 5 (with 1 representing extremely negative attitudes, 3 indicating a neutral stance, and 5 reflecting extremely positive attitudes). Questionnaire refinement involved an iterative process with expert panels and a pilot phase to enhance consistency and eliminate redundancy. Exploratory data analysis employed descriptive statistics and visual assessment of Likert plots, supported by non-parametric tests for subgroup comparisons for a thorough analysis of specific emerging patterns. RESULTS: The survey yielded 232 valid responses. The findings reveal a generally optimistic outlook on AI adoption, especially among young radiologist (<30) and seasoned professionals (>60, p<0.01). However, while 36.2 % (84 out 232) of subjects reported daily use of AI-based tools, only a third considered their contribution decisive (30 %, 25 out of 84). AI literacy varied, with a notable proportion feeling inadequately informed (36 %, 84 out of 232), particularly among younger radiologists (46 %, p < 0.01). Positive attitudes towards the potential of AI to improve detection, characterization of anomalies and reduce workload (positive answers > 80 %) and were consistent across subgroups. Radiologists' opinions were more skeptical about the role of AI in enhancing decision-making processes, including the choice of further investigation, and in personalized medicine in general. Overall, respondents recognized AI's significant impact on the radiology profession, viewing it as an opportunity (61 %, 141 out of 232) rather than a threat (18 %, 42 out of 232), with a majority expressing belief in AI's relevance to future radiologists' career choices (60 %, 139 out of 232). However, there were some concerns, particularly among breast radiologists (20 of 232 responders), regarding the potential impact of AI on the profession. Eighty-four percent of the respondents consider the final assessment by the radiologist still to be essential. CONCLUSION: Our results indicate an overall positive attitude towards the adoption of AI in radiology, though this is moderated by concerns regarding training and practical efficacy. Addressing AI literacy gaps, especially among younger radiologists, is essential. Furthermore, proactively adapting to technological advancements is crucial to fully leverage AI's potential benefits. Despite the generally positive outlook among radiologists, there remains significant work to be done to enhance the integration and widespread use of AI tools in clinical practice.

Prostate Artery Embolization (PAE) with Small Beads for the Treatment of Benign Prostatic Hyperplasia (BPH).

Benign Prostatic Hyperplasia (BPH) is the most frequent cause of Lower Urinary Tract Symptoms (LUTSs) in elderly populations. Minimally invasive treatments of BPH are safe and effective and are gaining popularity among both professionals and patients. Prostate Artery Embolization (PAE) has proven to be effective in Trans-Urethral Resection of the Prostate (TURP) in terms of prostate volume reduction and LUTS relief. PAE entails the selective catheterization of the prostatic artery and later embolization of distal vessels with beads of various calibers. Universal consensus regarding the ideal particle size is yet to be defined. We retrospectively evaluated 24 consecutive patients (median age: 75 years; range: 59-86 years) treated with PAE at our institution from October 2015 to November 2022. Particles of different sizes were employed; 12 patients were treated with 40-120 µm particles, 5 with 100 µm, 5 with 100-300 µm and 2 with 250 µm. Technical success, defined as selective prostate artery catheterization and controlled release of embolizing beads, was achieved in all patients. Removal vs. retention of the urinary catheter at the first post-procedural urological visit was the main clinical objective. No major peri-procedural complications were recorded, with 56% of patients successfully removing the urinary catheter.

Computed-Tomography-Guided Lung Biopsy: A Practice-Oriented Document on Techniques and Principles and a Review of the Literature.

Computed tomography (CT)-guided lung biopsy is one of the oldest and most widely known minimally invasive percutaneous procedures. Despite being conceptually simple, this procedure needs to be performed rapidly and can be subject to meaningful complications that need to be managed properly. Therefore, knowledge of principles and techniques is required by every general or interventional radiologist who performs the procedure. This review aims to contain all the information that the operator needs to know before performing the procedure. The paper starts with the description of indications, devices, and types of percutaneous CT-guided lung biopsies, along with their reported results in the literature. Then, pre-procedural evaluation and the practical aspects to be considered during procedure (i.e., patient positioning and breathing) are discussed. The subsequent section is dedicated to complications, with their incidence, risk factors, and the evidence-based measures necessary to both prevent or manage them; special attention is given to pneumothorax and hemorrhage. After conventional CT, this review describes other available CT modalities, including CT fluoroscopy and cone-beam CT. At the end, more advanced techniques, which are already used in clinical practice, like fusion imaging, are included.

Transperineal Laser Ablation of the Prostate for Symptomatic Benign Prostatic Hyperplasia: Long-Term Follow-Up in 40 Patients.

PURPOSE: To evaluate the durability, effectiveness, and safety of transperineal laser ablation (TPLA) of the prostate. MATERIALS AND METHODS: Patients with symptomatic benign prostatic hyperplasia (BPH) underwent TPLA with a 1,064-nm continuous-wave diode laser. International Prostate Symptom Score (IPSS), quality of life (QoL), postvoid residual (PVR), and prostate volume were evaluated at baseline and successive timepoints. RESULTS: Forty prospectively enrolled patients had follow-up of ≥36 months; median duration of follow-up was 57 months (range, 36-76 months). Compared with baseline, the median reduction in IPSS at 12-month follow-up was 74% (interquartile range [IQR], 60%-81%) (P < .001). Median QoL score at 12 months was improved from 5 (IQR, 4-5) at baseline to 1 (IQR, 0-1) (P < .001). Median PVR at 12 months decreased from 108 mL (IQR, 38-178 mL) to 13.5 mL (IQR, 0-40.5 mL) (P < .001), a median reduction of 88% (IQR, 61%-100%). At 12 months, median prostate volume was significantly reduced from 66 mL (IQR, 48.5-86.5 mL) to 46 mL (IQR, 36-65 mL) (P < .001), a median reduction of 32% (IQR, 21%-45%). For all of these parameters, the benefit of TPLA persisted at last follow-up, and all changes were statistically significant compared with baseline. There were no intraprocedural adverse events; periprocedural adverse events consisted of 1 case of prostatitis and 1 case of urinary tract infection (both Society of Interventional Radiology [SIR] Grade I). CONCLUSIONS: TPLA for symptomatic BPH produced durable benefits across a range of clinical outcomes and was well tolerated in follow-up at median duration of 57 months.

Patients' Perceptions and Attitudes to the Use of Artificial Intelligence in Breast Cancer Diagnosis: A Narrative Review.

Breast cancer remains the most prevalent cancer among women worldwide, necessitating advancements in diagnostic methods. The integration of artificial intelligence (AI) into mammography has shown promise in enhancing diagnostic accuracy. However, understanding patient perspectives, particularly considering the psychological impact of breast cancer diagnoses, is crucial. This narrative review synthesizes literature from 2000 to 2023 to examine breast cancer patients' attitudes towards AI in breast imaging, focusing on trust, acceptance, and demographic influences on these views. Methodologically, we employed a systematic literature search across databases such as PubMed, Embase, Medline, and Scopus, selecting studies that provided insights into patients' perceptions of AI in diagnostics. Our review included a sample of seven key studies after rigorous screening, reflecting varied patient trust and acceptance levels towards AI. Overall, we found a clear preference among patients for AI to augment rather than replace the diagnostic process, emphasizing the necessity of radiologists' expertise in conjunction with AI to enhance decision-making accuracy. This paper highlights the importance of aligning AI implementation in clinical settings with patient needs and expectations, emphasizing the need for human interaction in healthcare. Our findings advocate for a model where AI augments the diagnostic process, underlining the necessity for educational efforts to mitigate concerns and enhance patient trust in AI-enhanced diagnostics.

Role of Flex-Dose Delivery Program in Patients Affected by HCC: Advantages in Management of Tare in Our Experience.

Background: Introduced in the latest BCLC 2022, endovascular trans-arterial radioembolization (TARE) has an important role in the treatment of unresectable hepatocellular carcinoma (HCC) as a "bridge" or "downstaging" of disease. The evolution of TARE technology allows a more flexible and personalized target treatment, based on the anatomy and vascular characteristics of each HCC. The flex-dose delivery program is part of this perspective, which allows us to adjust the dose and its radio-embolizing power in relation to the size and type of cancer and to split the therapeutic dose of Y90 in different injections (split-bolus). Methods: From January 2020 to January 2022, we enrolled 19 patients affected by unresectable HCC and candidates for TARE treatment. Thirteen patients completed the treatment following the flex-dose delivery program. Response to treatment was assessed using the mRECIST criteria with CT performed 6 and 9 months after treatment. Two patients did not complete the radiological follow-up and were not included in this retrospective study. The final cohort of this study counts eleven patients. Results: According to mRECIST criteria, six months of follow-up were reported: five cases of complete response (CR, 45.4% of cases), four cases of partial response (PR, 36.4%), and two cases of progression disease (PD, 18.2%). Nine months follow-up reported five cases of complete response (CR, 45.4%), two cases of partial response (PR, 18.2%), and four cases of progression disease (PD, 36.4%). No intra and post-operative complications were described. The average absorbed doses to the hepatic lesion and to the healthy liver tissue were 319 Gy (range 133-447 Gy) and 9.5 Gy (range 2-19 Gy), respectively. Conclusions: The flex-dose delivery program represents a therapeutic protocol capable of "saving" portions of healthy liver parenchyma by designing a "custom-made" treatment for the patient.

The Role of Artificial Intelligence and Texture Analysis in Interventional Radiological Treatments of Liver Masses: A Narrative Review.

Liver lesions, including both benign and malignant tumors, pose significant challenges in interventional radiological treatment planning and prognostication. The emerging field of artificial intelligence (AI) and its integration with texture analysis techniques have shown promising potential in predicting treatment outcomes, enhancing precision, and aiding clinical decision-making. This comprehensive review aims to summarize the current state-of-the-art research on the application of AI and texture analysis in determining treatment response, recurrence rates, and overall survival outcomes for patients undergoing interventional radiological treatment for liver lesions. Furthermore, the review addresses the challenges associated with the implementation of AI and texture analysis in clinical practice, including data acquisition, standardization of imaging protocols, and model validation. Future directions and potential advancements in this field are discussed. Integration of multi-modal imaging data, incorporation of genomics and clinical data, and the development of predictive models with enhanced interpretability are proposed as potential avenues for further research. In conclusion, the application of AI and texture analysis in predicting outcomes of interventional radiological treatment for liver lesions shows great promise in augmenting clinical decision-making and improving patient care. By leveraging these technologies, clinicians can potentially enhance treatment planning, optimize intervention strategies, and ultimately improve patient outcomes in the management of liver lesions.

Radiomics and Artificial Intelligence in Renal Lesion Assessment.

Radiomics, the extraction and analysis of quantitative features from medical images, has emerged as a promising field in radiology with the potential to revolutionize the diagnosis and management of renal lesions. This comprehensive review explores the radiomics workflow, including image acquisition, feature extraction, selection, and classification, and highlights its application in differentiating between benign and malignant renal lesions. The integration of radiomics with artificial intelligence (AI) techniques, such as machine learning and deep learning, can help patients' management and allow the planning of the appropriate treatments. AI models have shown remarkable accuracy in predicting tumor aggressiveness, treatment response, and patient outcomes. This review provides insights into the current state of radiomics and AI in renal lesion assessment and outlines future directions for research in this rapidly evolving field.

Artificial Intelligence in Bone Metastasis Imaging: Recent Progresses from Diagnosis to Treatment - A Narrative Review.

The introduction of artificial intelligence (AI) represents an actual revolution in the radiological field, including bone lesion imaging. Bone lesions are often detected both in healthy and oncological patients and the differential diagnosis can be challenging but decisive, because it affects the diagnostic and therapeutic process, especially in case of metastases. Several studies have already demonstrated how the integration of AI-based tools in the current clinical workflow could bring benefits to patients and to healthcare workers. AI technologies could help radiologists in early bone metastases detection, increasing the diagnostic accuracy and reducing the overdiagnosis and the number of unnecessary deeper investigations. In addition, radiomics and radiogenomics approaches could go beyond the qualitative features, visible to the human eyes, extrapolating cancer genomic and behavior information from imaging, in order to plan a targeted and personalized treatment. In this article, we want to provide a comprehensive summary of the most promising AI applications in bone metastasis imaging and their role from diagnosis to treatment and prognosis, including the analysis of future challenges and new perspectives.

Quantitative and Qualitative Radiological Assessment of Sarcopenia and Cachexia in Cancer Patients: A Systematic Review.

Sarcopenia, an extremely common condition in cancer patients, is described as a progressive and generalized musculoskeletal disorder that is associated with an increased likelihood of adverse outcomes, including falls, fractures, physical disability, and mortality. By contrast, cachexia is defined as a syndrome characterized by weight loss with the concomitant loss of muscle and/or fat mass. Cancer cachexia leads to functional impairment, reduced physical performance, and decreased survival, and is often accompanied by cancer progression and reduced response to therapy. The literature states that cancer patients with cachexia or sarcopenia have many more complications than patients without these conditions. The interplay between physiologic sarcopenia and cancer cachexia is, in part, responsible for the complexity of studying wasting disorders in the cancer population, particularly in the geriatric population. For these reasons, a comprehensive assessment of the body composition and physical function of these patients is necessary. There are several modalities adapted to measure skeletal muscle mass, such as dual-energy X-ray absorptiometry (DEXA), bioelectrical impedance analysis (BIA), computed tomography (CT), magnetic resonance imaging (MRI), and ultrasound (US). The gold standard for the measurement of quantitative and qualitative changes in body composition in patients with cancer is the analysis of tissue density using a CT scan. However, this technique remains poorly implemented in clinical practice because of the use of ionizing radiation. Similarly, DEXA, MRI, and US have been proposed, but their use is limited. In this review, we present and compare the imaging techniques that have been developed so far for the nutritional assessment of cancer patients.

MR sialographic assessment of the masseter muscle and the ductal kinking in patients with recurrent parotitis.

Dysfunction of the masseter muscle may cause pathological kinking of the parotid duct leading to parotitis; MR sialography is a non-invasive radiological examination that allows to evaluate dynamically the ductal system of the parotid glands. In the present study we aimed to assess the relationships between Stensen's duct and masseter muscle and their implications in the aetiopathogenesis of recurrent parotitis secondary to masseter muscle dysfunction. Forty-one patients with recurrent unilateral parotitis and nine with bilateral recurrent parotitis, all with a clinical suspicious of masseter muscle hypertrophy due to bruxism were enrolled. They underwent ultrasonography as a first line examination and then MR sialography and sialendoscopy. Different anatomical features were studied. Involved parotid glands had a wider duct compared to contralateral unaffected parotid glands of patients with recurrent parotitis (p = 0.00134); male subjects with parotitis had a longer duct compared to the salivary glands of healthy patients (p = 0.00943 for affected glands and p = 0.00629 for the contralateral). A concordance between the evidence of an acute duct angle during sialendoscopy and a wider duct in patients with parotitis was observed although not statistically significant. These initial findings suggest that the masticatory muscle dysfunction related to bruxism seems to condition alteration of parotid duct course and anatomy thus favouring the occurrence of recurrent parotitis. A specific diagnostic iter based on clinical evaluation, dynamic ultrasonography and MR sialography, is therefore, mandatory to confirm the relationship between masseter muscle anatomy and parotid duct anomalies; this is the premise for an adequate therapeutic approach to underlying masticatory muscle disorder.