Radiology Research Articles

Medical-Focused Computer Program for Teaching Arabic as a Foreign Language for Medical Purposes

The study sets out to develop an online course for medical professionals who are not native Arabic speakers. The present study relied on a questionnaire developed by reviewing relevant theoretical literature and prior research in order to apply descriptive and analytical methods to accomplish the study's aims. The researcher sent an online questionnaire to a large number of healthcare workers, including doctors, nurses, lab techs, and radiology technicians. The objective of this survey is to learn about the linguistic communication needs of healthcare workers and to find out when Arabic is useful for communicating with patients and meeting quality standards in healthcare. The study compiled a list of 36 linguistic needs pertaining to various medical settings (e.g., emergency rooms, outpatient clinics, hypnosis rooms, labs, and radiology departments), developed an electronic program to teach Arabic to non-native speakers, and made several suggestions and recommendations.

Impact of Structured Reporting of Lower Extremity CT Angiography on Report Quality and Workflow Efficiency.

We assessed the effects of structured reporting (SR) of lower extremity CT angiography (CTA) on report quality and workflow efficiency compared with conventional reports (CR). Surveys were conducted at an academic radiology department before and after the introduction of an SR template. Participants (n = 39, 21) rated report quality and report creation effort (1: very dissatisfied/low to 10: very satisfied/high) and whether SR represents an improvement over CR (1: completely disagree to 5: completely agree). Four residents and two supervising radiologists created both CR and SR of 40 CTA examinations. Report creation time was measured and the factual accuracy of residents' reports was judged. Report completeness (median 8.0 vs. 7.0, p = 0.016) and clinical usefulness (7.0 vs. 4.0, p = 0.029) were rated higher for SR. Supervising radiologists found report clarity improved by SR (8.0 vs. 4.5, p = 0.029). Report creation effort was unchanged (7.0 vs. 6.0, p > 0.05). SR was considered an improvement over CR (median 4.0, IQR,3.0-5.0). Report supervision was shortened by SR (6.2 ± 2.0 min vs. 10.6 ± 3.5 min, p < 0.001) but total time for report creation remained unchanged (36.6 ± 12.8 min vs. 36.4 ± 11.0 min, p > 0.05). Factual accuracy of residents' SR was deemed higher (8.0/9.5 vs. 7.0/7.0, p = 0.006/ < 0.001). In conclusion, SR has the potential to improve report quality and workflow efficiency for lower extremity CTA.

Prospective Evaluation of Artificial Intelligence Triage of Intracranial Hemorrhage on Noncontrast Head CT Examinations.

Background: Retrospective studies evaluating artificial intelligence (AI) algorithms for intracranial hemorrhage (ICH) detection on noncontrast CT (NCCT) have shown promising results but lack prospective validation. Objective: To evaluate the impact on radiologists' real-world aggregate performance for ICH detection and report turnaround times for ICH-positive examinations of a radiology department's implementation of an AI triage and notification system for ICH detection on head NCCT examinations. Methods: This prospective single-center study included adult patients who underwent head NCCT examinations from May 12, 2021 to June 30, 2021 (phase 1) or September 30, 2021 to December 4, 2021 (phase 2). Before phase 1, the radiology department implemented a commercial AI triage system for ICH detection that processed head NCCT examinations and notified radiologists of positive results through a widget with a floating pop-up display. Examinations were interpreted by neuroradiologists or emergency radiologists, who evaluated examinations without and with AI assistance in phase 1 and phase 2, respectively. A panel of radiologists conducted a review process for all examinations with discordance between the radiology report and AI and a subset of remaining examinations, to establish the reference standard. Diagnostic performance and report turnaround times were compared using Pearson chi-square test and Wilcoxon rank-sum test, respectively. Bonferroni correction was used to account for five diagnostic performance metrics (adjusted significance threshold, .01 [α=.05/5]). Results: A total of 9954 examinations from 7371 patients (mean age, 54.8±19.8 years; 3773 female, 3598 male) were included. In phases 1 and 2, 19.8% (735/3716) and 21.9% (1368/6238) of examinations, respectively, were positive for ICH (P=.01). Radiologists without versus with AI showed no significant difference in accuracy (99.5% vs 99.2%), sensitivity (98.6% vs 98.9%), PPV (99.0% vs 99.7%), or NPV (99.7% vs 99.7%) (all P>.01); specificity was higher for radiologists without than with AI (99.8% vs 99.3%, respectively, P=.004). Mean report turnaround time for ICH-positive examinations was 147.1 minutes without AI versus 149.9 minutes with AI (P=.11). Conclusion: An AI triage system for ICH detection did not improve radiologists' diagnostic performance or report turnaround times. Clinical Impact: This large prospective real-world study does not support use of AI assistance for ICH detection.

Evaluating current acute aortic syndrome pathways: Collaborative Acute Aortic Syndrome Project (CAASP)

Abstract Background Diagnosis of acute aortic syndrome is challenging and associated with high perihospital mortality rates. The study aim was to evaluate current pathways and understand the chronology of acute aortic syndrome patient care. Method Consecutive patients with acute aortic syndrome imaging diagnosis between 1 January 2018 and 1 June 2021 were identified using a predetermined search strategy and followed up for 6 months through retrospective case note review. The UK National Interventional Radiology Trainee Research and Vascular and Endovascular Research Network co-ordinated the study. Results From 15 UK sites, 620 patients were enrolled. The median age was 67 (range 25–98) years, 62.0% were male and 92.9% Caucasian. Type-A dissection (41.8%) was most common, followed by type-B (34.5%); 41.2% had complicated acute aortic syndrome. Mode of presentation included emergency ambulance (80.2%), self-presentation (16.2%), and primary care referral (3.6%). Time (median (i.q.r.)) to hospital presentation was 3.1 (1.8–8.6) h and decreased by sudden onset chest pain but increased with migratory pain or hypertension. Time from hospital presentation to imaging diagnosis was 3.2 (1.3–6.5) h and increased by family history of aortic disease and decreased by concurrent ischaemic limb. Time from diagnosis to treatment was 2 (1.0–4.3) h with interhospital transfer causing delay. Management included conservative (60.2%), open surgery (32.2%), endovascular (4.8%), hybrid (1.4%) and palliative (1.4%). Factors associated with a higher mortality rate at 30 days and 6 months were acute aortic syndrome type, complicated disease, no critical care admission and age more than 70 years (P &amp;lt; 0.05). Conclusions This study presents a longitudinal data set linking time-based delays to diagnosis and treatment with clinical outcomes. It can be used to prioritize research strategies to streamline patient care.

Quality Assessment of Periapical Radiographs Taken by Dental Assistants Using the Recent Faculty of General Dental Practice (FGDP) Guidelines.

Periapical radiographs play a pivotal role in dentistry, offering invaluable insights essential for various dental procedures. This study aims to systematically assess the quality of intraoral periapical (IOPA) radiographs evaluating adherence to the recent guidelines established by the Faculty of General Dental Practice (FGDP). A cross-sectional study was conducted at the University College of Dentistry (UCD), employing a non-probability consecutive sampling technique to acquire a calculated sample of 300 IOPA radiographs from the operative, oral surgery, and oral radiology departments. Two senior faculty members evaluated the radiographs according to the recent two-tier grading system outlined in the FGDP guidelines. The study revealed that 197 (65.67%) of the assessed radiographs were diagnostically acceptable, while 103 (34.33%) were deemed diagnostically unacceptable. Contrast problems emerged as the most prevalent issue, accounting for 85 (28.3%) of the cases. Other common problems included incorrect film positioning in 66 (22%), incorrect vertical cone angulation in 37 (12.3%), incorrect horizontal cone angulation in 11 (3.7%), and incorrect processing in 15 (5%) of the IOPA radiographs. This study revealed that approximately two-thirds of the IOPA radiographs were deemed diagnostically acceptable. However, contrast issues emerged as the predominant concern affecting image quality. These findings highlight the critical importance of continuous quality improvement initiatives in radiographic practices to enhance diagnostic precision and ensure optimal patient care.

Cost-effectiveness of diagnostic imaging modalities in symptomatic patients with lower limb peripheral arterial disease: discrete event simulation model.

Lower limb peripheral arterial disease in the symptomatic stage has a significant effect on patients´ functional disability. Before an intervention, an imaging diagnostic examination is necessary to determine the extent of the disability. This study evaluates cost-effectiveness of duplex ultrasonography (DUS), digital subtraction angiography (DSA), computed tomography angiography (CTA) and magnetic resonance angiography (MRA) in the diagnostics of symptomatic patients with lower limb peripheral arterial disease indicated for endovascular or surgical intervention. Discrete event simulation was used to capture lifetime costs and effects. Costs were calculated from the perspective of the health care payer, and the effects were calculated as quality-adjusted life year's (QALY's). The cost-effectiveness analysis was performed to pairwise compare CTA, MRA and DSA with DUS as the baseline diagnostic modality. A scenario analysis and probabilistic sensitivity analysis were carried out to evaluate the robustness of the results. In the basic case, the DUS diagnostic was the least expensive modality, at a cost of EUR 10,778, compared with EUR 10,804 for CTA, EUR 11,184 for MRA, and EUR 11,460 for DSA. The effects of DUS were estimated at 5.542 QALYs compared with 5.554 QALYs for both CTA and MRA, and 5.562 QALYs for DSA. The final incremental cost-effectiveness ratio (ICER) value of all evaluated modalities was below the cost-effectiveness threshold whereas CTA has the lowest ICER of EUR 2,167 per QALY. However, the results were associated with a large degree of uncertainty, because iterations were spread across all cost-effectiveness quadrants in the probabilistic sensitivity analysis. For imaging diagnosis of symptomatic patients with lower limb peripheral arterial disease, CTA examination appears to be the most cost-effective strategy with the best ICER value. Baseline diagnostics of the DUS modality has the lowest costs, but also the lowest effects. DSA achieves the highest QALYs, but it is associated with the highest costs.

Frequency of bile duct variant anatomy on MRCP on 3.0t in liver donors.

Objective: To determine the frequency of bile duct variant using magnetic resonance cholangiopancreatography (MRCP) on a magnetic field strength of 3.0 Tesla in liver donors. Study Design: Descriptive Cross-sectional study. Setting: Department of Radiology, Armed Forces Institute of Radiology and Imaging, Military Hospital Rawalpindi. Period: May 2019 to November 2019. Methods: The research comprised people who went to the hospital for magnetic resonance cholangiopancreatography. 85 liver transplant recipients between the ages of 20 and 70 were chosen for the research. According to Yoshida categorization, bile duct variation was noted. The MRCP methodology includes multiplanar imaging, maximum intensity projection pictures, thin slab axial HASTE, thick slab coronal HASTE, and T2 3D sequence. The Siemens Avanto 3 Tesla machine was used for the study. Results: The study's participants ranged in age from 20 to 70, with a mean age of 41.73 ± 10.03 years. The majority of the 54 patients (63.53 percent) were aged 20 to 45. The male to female ratio was 1:1 among the 85 patients, with 43 (50.59 percent) men and 42 (49.41 percent) women. In my research of liver donors, 57 (67.05 percent) showed normal biliary tree structure and 28 (32.95 percent) exhibited abnormalities. Conclusion: This study concluded that normal biliary tree anatomy was seen in 67.05% and 32.95% had variations in biliary anatomy on MRCP on 3.0T in liver donors.

Haemorrhagic cholecystitis: a case report—focus on the optimal diagnosis and management algorithm

Haemorrhagic cholecystitis refers to an inflammatory process of the gallbladder, complicated by bleeding into the gallbladder or biliary system (haemobilia). Approximately 10–15% of adults have cholelithiasis, but most patients do not develop symptoms. Acute cholecystitis occurs in about 10% of symptomatic patients. Among the recognized complications of acute cholecystitis, the haemorrhagic form occurs uncommonly. Underlying risk factors include a bleeding diathesis or treatment with anticoagulants, aneurysm rupture of colecystic artery and trauma. It is often associated with cholelithiasis. The presenting feature is right upper quadrant pain, which is a dominant feature and may mimic non-haemorrhagic acute cholecystitis. Haemorrhagic cholecystitis is diagnosed by radiographic imaging. The first-choice exam is ultrasonography. However, ultrasound does not appear to be ideal for differentiating between acute and haemorrhagic cholecystitis. Computed tomography (CT) scan is the gold standard in the diagnosis of haemorrhagic cholecystitis. MRI may show breakdown products of blood and can be used to estimate the age of the haemorrhage. Surgical resection or embolization of a cystic artery pseudoaneurysm should be considered the treatment of choice, due to the high risk of fatality associated with this condition. We describe a case of haemorrhagic cholecystitis in an 80-year-old male with secondary haemophilia and cholelithiasis who presented to our department of radiology with right upper quadrant pain.

Evaluation of guided reporting: quality and reading time of automatically generated radiology report in breast magnetic resonance imaging using a dedicated software solution.

Unstructured, free-text dictation (FT), the current standard in breast magnetic resonance imaging (MRI) reporting, is considered time-consuming and prone to error. The purpose of this study is to assess the usability and performance of a novel, software-based guided reporting (GR) strategy in breast MRI. Eighty examinations previously evaluated for a clinical indication (e.g., mass and focus/non-mass enhancement) with FT were reevaluated by three specialized radiologists using GR. Each radiologist had a different number of cases (R1, n = 24; R2, n = 20; R3, n = 36). Usability was assessed by subjective feedback, and quality was assessed by comparing the completeness of automatically generated GR reports with that of their FT counterparts. Errors in GR were categorized and analyzed for debugging with a final software version. Combined reading and reporting times and learning curves were analyzed. Usability was rated high by all readers. No non-sense, omission/commission, or translational errors were detected with the GR method. Spelling and grammar errors were observed in 3/80 patient reports (3.8%) with GR (exclusively in the discussion section) and in 36/80 patient reports (45%) with FT. Between FT and GR, 41 patient reports revealed no content differences, 33 revealed minor differences, and 6 revealed major differences that resulted in changes in treatment. The errors in all patient reports with major content differences were categorized as content omission errors caused by improper software operation (n = 2) or by missing content in software v. 0.8 displayable with v. 1.7 (n = 4). The mean combined reading and reporting time was 576 s (standard deviation: 327 s; min: 155 s; max: 1,517 s). The mean times for each reader were 485, 557, and 754 s, and the respective learning curves evaluated by regression models revealed statistically significant slopes (P = 0.002; P = 0.0002; P < 0.0001). Overall times were shorter compared with external references that used FT. The mean combined reading and reporting time of MRI examinations using FT was 1,043 s and decreased by 44.8% with GR. GR allows for complete reporting with minimized error rates and reduced combined reading and reporting times. The streamlining of the process (evidenced by lower reading times) for the readers in this study proves that GR can be learned quickly. Reducing reporting errors leads to fewer therapeutic faults and lawsuits against radiologists. It is known that delays in radiology reporting hinder early treatment and lead to poorer patient outcomes. While the number of scans and images per examination is continuously rising, staff shortages create a bottleneck in radiology departments. The IT-based GR method can be a major boon, improving radiologist efficiency, report quality, and the quality of simultaneously generated data.

Machine learning analysis for detecting late recurrence and loss to follow‐up after renal cell carcinoma surgery

AbstractObjectivesRenal cell carcinoma (RCC) is shown to have a tendency for late recurrence, occurring 5 or more years after curative surgery. Imaging diagnosis is required for follow‐up, and there is no definitive answer as to how long this should continue. Some patients discontinue follow‐up visits at their own discretion. How best to predict late recurrence and loss to follow‐up (LF) remains unclear.Patients and methodsThis study targeted patients diagnosed with non‐metastatic RCC who underwent either radical or partial nephrectomy at Chiba University Hospital between 1988 and 2021. Follow‐up for patients with RCC is typically lifelong. We used random survival forests (RSFs), a machine learning‐based survival analysis method, to predict late recurrence and LF. For verification of prediction accuracy, we applied the time‐dependent area under the receiver operating characteristic curve (t‐AUC). To analyse the risks of late recurrence and LF, SurvSHAP(t) and partial dependence plots were used.ResultsWe analysed 1051 cases in this study. Median follow‐up was 58.5 (range: 0–376) months. The predictive accuracy of recurrence using RSF was t‐AUC 0.806, 0.761, 0.674 and 0.566 at 60, 120, 180 and 240 months postoperatively, respectively. The recurrence risk impact showed a time‐dependent increase up to approximately 50 months postoperatively. Beyond 50 months, there were no distinct risk factors characteristic of late recurrence. The predictive accuracy of LF using RSF was t‐AUC 0.542, 0.699, 0.685, 0.628 and 0.674 at 60, 120, 180, 240 and 300 months postoperatively, respectively. The risk of LF increased with advancing age beyond 70 years.ConclusionIt is difficult to identify factors that predict late recurrence. For long‐term follow‐up observation, it is essential to pay particular attention to patients with RCC aged 70 years and above. Establishing frameworks to facilitate collaboration with local hospitals near patients' residences and providing care within the community is necessary.

Role of ultrasound and magnetic resonance neurography in the detection of median nerve abnormalities in carpal tunnel syndrome

BackgroundThe most prevalent cause of peripheral nerve entrapment is carpal tunnel syndrome, which is characterized by compression of the median nerve at the wrist as a result of nearby or localized microvascular interference as well as structural alterations to the median nerve or adjacent tissues. However, no special information regarding the median nerve or its surroundings is provided by clinical examination or electrophysiological testing. The purpose of this study is to evaluate the effectiveness of magnetic resonance neurography (MRN) and ultrasound in identifying changes and abnormalities of the median nerve in carpal tunnel syndrome.MethodsThe twenty-five patients in this study ranged in age from 27 to 63 years old, with a mean age of 47. There were 18 female patients and seven male patients. All patients were sent to the radiology department from the orthopedics, neurology, outpatient clinic, and neurology department, at Ain Shams Hospital, Faculty of Medicine, Ain Shams University. All of the patients had clinically manifested pain along the median nerve distribution, each of the sixteen patients had hand paresthesia, and four had thenar muscle atrophy.ResultsIn the current study, Ultrasound exhibits low negative predictive value of 67% and specificity of 67%, but high positive predictive value of 95%, sensitivity of 95%, and overall accuracy of 92%. On the other hand, (MRN) exhibits a low negative predictive value of 60% and a high specificity of 75% in the diagnosis of nerve entrapment, but it also displays a high positive predictive value of 95%, sensitivity of 90%, and overall accuracy of 88%. Regarding the assessment of the recurrence cause and post-surgical evaluation is more reliable by Magnetic Resonance Neurography examination.ConclusionsMagnetic resonance neurography and high-resolution ultrasonography can be utilized to diagnose patients with median nerve entrapment and patients who cannot be diagnosed electrophysiologically.MRN is a more accurate method for detecting the exact location of nerve entrapment and evaluating nerve recovery after surgical intervention than nerve conduction studies and electromyography. Additionally, MRN can be used to identify causes that were not previously recognized based on physical examination and electrophysiological tests.

Diagnostic Value of Pericholedochal Hypointense Ring Sign in MRI T2W Images in Cases of Pancreatic Ductal Adenocarcinoma.

To determine the value of hypointense pericholedocal ring sign in magnetic resonance imaging (MRI) T2W sequence images in the diagnosis of pancreatic ductal adenocarcinoma (PDA). Retrospective observational study. Place and Duration of the Study: Department of Radiology, Bakirkoy Dr Sadi Konuk Training and Research Hospital, Istanbul, Turkiye, from January 2016 and March 2022. Retrospective analysis of MRI scans was performed on 70 patients with postoperative histopathological confirmation of a diagnosis of periampullary cancer. The patients' demographic information, the results of their histopathological examinations, and the findings of their MRIs were recorded. The results of the MRI were statistically analysed and compared between the PDA and the non-PDA groups. The study included 43 (61.4%) male and 27 (38.5%) female patients, with a mean age of 62.2 ± 8.4 years. The means of Wirsung diameter and tumour diameter were significantly higher in PDA group (p = 0.034, p = 0.010, respectively). A progressive contrast enhancement pattern of 95.3% was observed in PDA group, while 40.7% rapid contrast enhancement pattern was observed in the non-PDA group. Hypointense pericholedochal ring sign, observed in T2W sequences, was detected in 74.2% (n = 32) of the PDA group and 11.1% (n = 3) of the non-PDA group, and the findings were statistically significant (p <0.001). Hypointense pericholedochal ring sign in axial T2W sequences in periampullary tumours is a complementary MRI finding in the distinction between the PDA and the non-PDA groups. Magnetic resonance imaging, Pancreatic ductal adenocarcinoma, Periampullary tumours, Pericholedochal ring sign.

Value-Based Radiology in Canada: Reducing Low-Value Care and Improving System Efficiency.

Radiology departments are increasingly tasked with managing growing demands on services including long waitlists for scanning and interventional procedures, human health resource shortages, equipment needs, and challenges incorporating advanced imaging solutions. The burden of system inefficiencies and the overuse of "low-value" imaging causes downstream impact on patients at the individual level, the economy and healthcare system at the societal level, and planetary health at an overarching level. Low value imaging includes those performed for an inappropriate clinical indication, with little to no value to the management of the patient, and resulting in healthcare resource waste; it is estimated that up to a quarter of advanced imaging studies in Canada meet this criterion. Strategies to reduce low-value imaging include the development and use of referral guidelines, use of appropriateness criteria, optimization of existing protocols, and integration of clinical decision support tools into the ordering provider's workflow. Additional means of optimizing system efficiency such as centralized intake models, improved access to electronic medical records and outside imaging, enhanced communication with patients and referrers, and the utilization of artificial intelligence will further increase the value of radiology provided to patients and care providers.

Essentials of Infection Prevention and Control in Radiology Department, Review

Essentials of Infection Prevention and Control in Radiology Department, Review

Fostering Organizational Excellence through Inclusive Leadership: Practical Guide for Radiology Leaders.

Inclusive leadership styles value team members, invite diverse perspectives, and recognize and support the contributions of employees. The authors provide guidance to radiology leaders interested in developing inclusive leadership skills and competencies to improve workforce recruitment and retention and unlock the potential of a rapidly diversifying health care workforce. As health care organizations look to attract the best and brightest talent, they will be increasingly recruiting millennial and Generation Z employees, who belong to the most diverse generations in American history. Additionally, radiology departments currently face critical workforce shortages in radiologists, radiology technicians, staff, and advanced practice providers. In the context of these shortages, the costs of employee turnover have emphasized the need for radiology leaders to develop leadership behaviors that promote recruitment and retention. Radiology department leaders who perceive and treat valued employees as replaceable commodities will be forced to deal with the extremely high costs associated with recruitment and training, decreased morale, and increased burnout. The authors review inclusive versus exclusive leadership styles, describe key attributes and skills of inclusive leaders, provide radiology leaders with concrete methods to make their organizations more inclusive, and outline key steps in change management. By adopting and implementing inclusive leadership strategies, radiology groups can position themselves to succeed in rapidly diversifying health care environments. ©RSNA, 2024 See the invited commentary by Siewert in this issue.

MRCNN: Multi-input residual convolution neural network for three-dimensional reconstruction of bubble flows from light field images

Accurate measurement of bubbles in air-water two-phase flows holds immense significance in the realm of thermal hydraulics assessments within nuclear reactors. Nevertheless, conventional bubble measurement techniques grapple with challenges encompassing system intricacy, limited real-time capabilities, and inaccuracies stemming from their inherent two-dimensional (2-D) nature. In response, we pioneered an innovative three-dimensional (3-D) analysis approach that leverages light field (LF) imaging diagnosis and deep learning algorithms. Unlike traditional 2-D reconstruction methods, our approach enables direct computation of bubble depth from LF images using digital refocusing technology. Following calibration, a seamless transformation is established between the camera coordinate system and the real-world coordinate system using a sharpness evaluation algorithm. This calibration process ensures precise alignment of refocused images with real-world positions. Subsequently, fully automated and highly accurate computations of bubble depth are realized from input images via the incorporation of a multi-input residual convolution neural network (MRCNN). The limitations of traditional two-dimensional imaging techniques are effectively addressed by this methodology, resulting in a reduction in measurement errors. The study confirms the feasibility of employing LF imaging diagnosis and deep learning algorithms for bubble measurements in an air-water two-phase flow, offering a significant improvement over traditional methods.

Morphometric evaluation of middle ear anatomical structures using full volume (12 × 9) CBCT scans: A retrospective study in Navi Mumbai

Introduction: The tympanic cavity contains three tiny bones, the malleus, incus, and stapes, which have a fundamental role in the transmission of sound. Recent research emphasizes the use of CBCT for the anatomic study of the temporal bone. The information about middle ear anatomy on CBCT scans is meager; hence, this retrospective study was conducted to identify and determine the various morphometrical parameters of the malleus using CBCT which can be helpful during reconstructive procedures for the otologic surgeon. Materials and Methods: The retrospective study was performed on 200 subjects (101 M and 99 F) in the Department of Oral and Maxillofacial Radiology. CBCT images of 200 subjects were studied in all planes to identify ossicular chain and the malleus to investigate the morphometric parameters in Indian Subjects. Result: The average of morphometric parameters shows that the mean length of the malleus is 7.2 mm, the mean width of the head of the malleus is 3.02 mm, length of superior semicircular canal is 4.90 mm, and length of external auditory canal is 19.15 mm in Navi Mumbai population. Conclusion: The obtained morphometric data of the malleus through our study will help the prosthesis maker in the formation of various implants and grafts required to treat various ear diseases.

Deep Deblurring in Teledermatology: Deep Learning Models Restore the Accuracy of Blurry Images' Classification.

Background: Blurry images in teledermatology and consultation increased the diagnostic difficulty for both deep learning models and physicians. We aim to determine the extent of restoration in diagnostic accuracy after blurry images are deblurred by deep learning models. Methods: We used 19,191 skin images from a public skin image dataset that includes 23 skin disease categories, 54 skin images from a public dataset of blurry skin images, and 53 blurry dermatology consultation photos in a medical center to compare the diagnosis accuracy of trained diagnostic deep learning models and subjective sharpness between blurry and deblurred images. We evaluated five different deblurring models, including models for motion blur, Gaussian blur, Bokeh blur, mixed slight blur, and mixed strong blur. Main Outcomes and Measures: Diagnostic accuracy was measured as sensitivity and precision of correct model prediction of the skin disease category. Sharpness rating was performed by board-certified dermatologists on a 4-point scale, with 4 being the highest image clarity. Results: The sensitivity of diagnostic models dropped 0.15 and 0.22 on slightly and strongly blurred images, respectively, and deblurring models restored 0.14 and 0.17 for each group. The sharpness ratings perceived by dermatologists improved from 1.87 to 2.51 after deblurring. Activation maps showed the focus of diagnostic models was compromised by the blurriness but was restored after deblurring. Conclusions: Deep learning models can restore the diagnostic accuracy of diagnostic models for blurry images and increase image sharpness perceived by dermatologists. The model can be incorporated into teledermatology to help the diagnosis of blurry images.

Human immunodeficiency virus‐associated Lymphomas: EHA–ESMO Clinical Practice Guideline for diagnosis, treatment and follow‐up

Highlights This EHA–ESMO Clinical Practice Guideline provides key recommendations for managing HIV‐associated lymphomas. The guideline covers clinical, imaging and pathological diagnosis; staging and risk assessment; treatment and follow‐up. The author group encompasses a multidisciplinary group of experts from different institutions and countries in Europe. Recommendations are based on available scientific data and the authors’ collective expert opinion.

Melanoma imaging and diagnosis: What does the future hold?

In Australia, artificial intelligence (AI) is increasingly being used in the field of melanoma diagnosis. Early diagnosis is arguably the most important prognostic factor for melanoma survival. The use of digital monitoring of naevi, especially dysplastic naevi, might reduce the number of biopsies needed in managing patients at risk of melanoma, especially in patients with high naevi counts. This article discusses advances in imaging and early diagnosis including the use of AI in this process. The benefits of performing biopsies must be balanced with the potential to cause harm. Whole-body imaging can assist with more accurate detection of changing lesions and enable clinicians to focus on lesions where change is detected.