High-quality expert annotations enhance artificial intelligence model accuracy for osteosarcoma X-ray diagnosis.

Primary malignant bone tumors, such as osteosarcoma, significantly affect the pediatric and young adult populations, necessitating early diagnosis for effective treatment. This study developed a high-performance artificial intelligence (AI) model to detect osteosarcoma from X-ray images using highly accurate annotated data to improve diagnostic accuracy at initial consultations. Traditional models trained on unannotated data have shown limited success, with sensitivities of approximately 60%-70%. In contrast, our model used a data-centric approach with annotations from an experienced oncologist, achieving a sensitivity of 95.52%, specificity of 96.21%, and an area under the curve of 0.989. The model was trained using 468 X-ray images from 31 osteosarcoma cases and 378 normal knee images with a strategy to maximize diversity in the training and validation sets. It was evaluated using an independent dataset of 268 osteosarcoma and 554 normal knee images to ensure generalizability. By applying the U-net architecture and advanced image processing techniques such as renormalization and affine transformations, our AI model outperforms existing models, reducing missed diagnoses and enhancing patient outcomes by facilitating earlier treatment. This study highlights the importance of high-quality training data and advocates a shift towards data-centric AI development in medical imaging. These insights can be extended to other rare cancers and diseases, underscoring the potential of AI in transforming diagnostic processes in oncology. The integration of this AI model into clinical workflows could support physicians in early osteosarcoma detection, thereby improving diagnostic accuracy and patient care.

Dermatoscopic features of vulvar lichen sclerosus in children: A retrospective study.

OBJECTIVES: To explore the dermoscopic features of lichen sclerosus in different parts of the external genitalia in children. METHODS: A retrospective analysis of the dermoscopic features of 42 female children with vulvar lichen sclerosus treated in the Department of Dermatology of Shanxi Children's Hospital from January 2020 to May 2023. RESULTS: Among the 42 female children, aged 3-14 years (mean: 7.24 ± 2.43 years), the duration of vulvar lichen sclerosus ranged from 3 months to 2 years (mean: 9.83 ± 4.93 months). Clinical lesions occurred in the labia minora in 18 cases (42.9%), labia majora in 38 cases (90.5%), posterior fourchette in 36 cases (85.7%), perianal area in 13 cases (31.0%), anterior fourchette in 17 cases (40.5%), clitoris in seven cases (16.7%), and interlabial sulcus in 11 cases (26.2%). Dermoscopic findings common in the labia majora included follicular keratotic plugs, cloverleaf-like structures, comedo-like openings, and linear vessels (p < .05); however, purple-red globules and patches and white linear streaks were more common in the posterior fourchette (p < .05), whereas dotted vessels were more common in the labia minora (p < .05). CONCLUSIONS: Common dermoscopic findings in pediatric vulvar lichen sclerosus were yellow-white structureless areas, white linear streaks, follicular keratotic plugs, and cloverleaf-like structures; yellow-white structureless areas and white linear streaks showed the highest specificity. The dermoscopic findings varied among different affected areas, which provides a basis for further understanding of the characteristics of different sites of vulvar lichen sclerosus in the pediatric population.

Diagnostic Musculoskeletal Ultrasound for Medial Collateral Ligament Injuries: Applications in Rehabilitation.

Medial collateral ligament (MCL) injuries are prevalent in sports and other physical activities and constitute a significant cause of knee pain and dysfunction. Traditional diagnostic modalities such as magnetic resonance imaging (MRI) are often utilized for their detailed visualization capabilities. However, musculoskeletal ultrasound (MSK-US) has emerged as a pivotal diagnostic tool in the evaluation of MCL injuries due to its non-invasive nature, cost-effectiveness, and dynamic imaging capabilities. This article reviews the utility and advantages of MSK-US in diagnosing MCL injuries, with a specific focus on its implications for rehabilitation providers. We discuss the technical aspects of ultrasound (US) imaging, including the sonographic appearance of MCL injuries across various grades, and compare its diagnostic accuracy with other imaging modalities such as MRI. Additionally, the role of US in monitoring the healing process and guiding rehabilitation strategies is explored. This review emphasizes the practical application of MSK-US in clinical settings, offering rehabilitation providers a comprehensive understanding of how US can be integrated into patient management protocols to enhance outcomes in patients with MCL injuries.

Head-to-head comparison of contrast-enhanced CT, dual-layer spectral-detector CT, and Gd-EOB-DTPA-enhanced MR in detecting neuroendocrine tumor liver metastases.

PURPOSE: To explore the optimal of kiloelectron voltage (keV) of virtual monoenergetic imaging (VMI) of dual-layer spectral-detector CT (DLCT) in detecting neuroendocrine tumor liver metastases (NETLM) and to investigate diagnostic performance of polyenergetic images (PEI), DLCT, and Gd-EOB-DTPA-enhanced MR. METHODS: Seventy-two patients with suspected NETLM who underwent DLCT and Gd-EOB-DTPA-enhanced MR were retrospectively enrolled. Tumor signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were compared between PEI and VMI at 40-140 keV. Two radiologists read the CT examinations with and without VMI separately in consensus. Two other radiologists read the Gd-EOB-DTPA-enhanced MR in consensus. The diagnostic performance was evaluated. Reference standard was histopathology, follow-up, and interpretation of all available imaging. RESULTS: The highest SNR and CNR were observed at VMI40keV, significantly higher than PEI in the arterial and venous phases (all P<0.01). A total of 477 lesions were identified (396 metastases, 81 benign lesions). Per-lesion AUC was 0.86, 0.91, and 0.97 (PEI, DLCT, and Gd-EOB-DTPA-enhanced MR, respectively). Sensitivity of PEI, DLCT, and Gd-EOB-DTPA-enhanced MRI were 0.76, 0.86, and 0.95, respectively. DLCT significantly improved sensitivity compared to PEI. MR had significantly higher sensitivity than DLCT and PEI. Subgroup analysis demonstrated that the difference in diagnostic performance was concentrated on lesions < 10 mm. CONCLUSION: The image quality of VMI40keV is higher than that of PEI. DLCT with VMI40keV provides better diagnostic sensitivity for NETLM detection than PEI. Gd-EOB-DTPA-enhanced MR yielded the best diagnostic performance for NETLM detection.

ESR Essentials: imaging in fibrotic lung diseases-practice recommendations by the European Society of Thoracic Imaging.

Fibrotic lung diseases (FLDs) represent a subgroup of interstitial lung diseases (ILDs), which can progress over time and carry a poor prognosis. Imaging has increased diagnostic discrimination in the evaluation of FLDs. International guidelines have stated the role of radiologists in the diagnosis and management of FLDs, in the context of the interdisciplinary discussion. Chest computed tomography (CT) with high-resolution technique is recommended to correctly recognise signs, patterns, and distribution of individual FLDs. Radiologists may be the first to recognise the presence of previously unknown interstitial lung abnormalities (ILAs) in various settings. A systematic approach to CT images may lead to a non-invasive diagnosis of FLDs. Careful comparison of serial CT exams is crucial in determining either disease progression or supervening complications. This 'Essentials' aims to provide radiologists a concise and practical approach to FLDs, focusing on CT technical requirements, pattern recognition, and assessment of disease progression and complications. Hot topics such as ILAs and progressive pulmonary fibrosis (PPF) are also discussed. KEY POINTS: Chest CT with high-resolution technique is the recommended imaging modality to diagnose pulmonary fibrosis. CT pattern recognition is central for an accurate diagnosis of fibrotic lung diseases (FLDs) by interdisciplinary discussion. Radiologists are to evaluate disease behaviour by accurately comparing serial CT scans.

Automated Association for Osteosynthesis Foundation and Orthopedic Trauma Association classification of pelvic fractures on pelvic radiographs using deep learning.

High-energy impacts, like vehicle crashes or falls, can lead to pelvic ring injuries. Rapid diagnosis and treatment are crucial due to the risks of severe bleeding and organ damage. Pelvic radiography promptly assesses fracture extent and location, but struggles to diagnose bleeding. The AO/OTA classification system grades pelvic instability, but its complexity limits its use in emergency settings. This study develops and evaluates a deep learning algorithm to classify pelvic fractures on radiographs per the AO/OTA system. Pelvic radiographs of 773 patients with pelvic fractures and 167 patients without pelvic fractures were retrospectively analyzed at a single center. Pelvic fractures were classified into types A, B, and C using medical records categorized by an orthopedic surgeon according to the AO/OTA classification system. Accuracy, Dice Similarity Coefficient (DSC), and F1 score were measured to evaluate the diagnostic performance of the deep learning algorithms. The segmentation model showed high performance with 0.98 accuracy and 0.96-0.97 DSC. The AO/OTA classification model demonstrated effective performance with a 0.47-0.80 F1 score and 0.69-0.88 accuracy. Additionally, the classification model had a macro average of 0.77-0.94. Performance evaluation of the models showed relatively favorable results, which can aid in early classification of pelvic fractures.

Role of Magnetic Resonance Spectroscopy in Evaluating Choline Levels in Gallbladder Carcinoma: A Comprehensive Review.

Gallbladder carcinoma (GBC) presents a significant clinical challenge due to its aggressive nature and often asymptomatic progression, resulting in late-stage diagnoses and a poor prognosis. Early detection and accurate staging are pivotal for improving patient outcomes, highlighting the critical role of advanced imaging techniques in oncological practice. Magnetic resonance spectroscopy (MRS) has emerged as a valuable non-invasive tool capable of assessing biochemical changes within tissues, including alterations in choline metabolism-a biomarker indicative of cell membrane turnover and proliferation. This review explores the application of MRS in evaluating choline levels in gallbladder carcinoma, synthesizing current literature to elucidate its potential in clinical settings. By analyzing studies investigating the correlation between choline levels detected via MRS and tumor characteristics, this review underscores MRS's role in enhancing diagnostic precision and guiding therapeutic decision-making. Moreover, it discusses the challenges and limitations associated with MRS in clinical practice alongside future research and technological advancement directions. Ultimately, integrating MRS into the diagnostic armamentarium for gallbladder carcinoma promises to improve early detection and treatment outcomes. This review provides insights into the evolving landscape of MRS in oncology, emphasizing its contribution to personalized medicine approaches aimed at optimizing patient care and management strategies for GBC.

A cross-national investigation of CT, MRI, PET, mammography, and radiation therapy resources and utilization.

PURPOSE: This study aimed to analyze the domestic and international landscape of imaging diagnostics and treatments, focusing on Japan, to provide current insights for policymaking, clinical practice enhancement, and international collaboration. METHODS: Data from 1996 to 2021 were collected from Japan's Ministry of Health, Labor and Welfare database for medical device counts of CT, MRI, PET, mammography, and radiotherapy. The National Database of Health Insurance Claims and Specific Health Checkups of Japan was utilized for examination numbers. An international comparison was made with data from 41 countries using the Organization for Economic Cooperation and Development (OECD) database. RESULTS: The data included a total of 108,596 CT devices, 47,233 MRI devices, 2998 PET devices, 20,641 MMG devices, and 8023 RT devices during the survey period. Upon international comparison, Japan ranked first in CT and MRI devices per million people and second in examination numbers per 1000 people. The number of PET devices per million people exceeded OECD averages; however, the number of examinations per 1000 people was below the OECD average in 2020 (Japan: 4.0, OECD: 4.9). Although Japan exceeded OECD averages in mammography device counts (Japan: 33.8, OECD: 24.5 in 2020), radiotherapy device counts were similar to OECD averages (Japan: 8.3, OECD: 7.9 in 2020). CONCLUSION: We have analyzed the utilization of equipment in the context of diagnostic imaging and radiotherapy in Japan. Since the initial survey year, all devices have shown an upward trend. However, it is essential not only to increase the number of devices and examinations but also to address the chronic shortage of radiologists and allied health professionals. Based on the insights gained from this study, understanding the actual status of diagnostic imaging and radiation therapy equipment is critical for grasping the domestic situation and may contribute to improving the quality of healthcare in Japan.

Imaging finding of renal masses associated with pathogenic variation in succinate dehydrogenase subunit B gene.

PURPOSE: Succinate dehydrogenase (SDH)-deficient renal cell carcinoma (RCC) is a newly defined, rare subtype of renal cancer, associated with pathogenic variations in the Succinate Dehydrogenase Subunit B (SDHB) gene. Our aim is to investigate the imaging findings of SDHB-associated renal tumors, utilizing cross-sectional and FDG-PET imaging in patients with pathogenic variations in SDHB gene, to facilitate accurate tumor characterization. METHODS: Twenty SDH-deficient tumors from 16 patients with pathogenic variations in SDHB gene were retrospectively evaluated using cross-sectional and FDG-PET imaging. Clinical findings such as demographics, family history, extra-renal findings and metastases were recorded. Tumor imaging characteristics on CT/MRI included were laterality, size, homogeneity, morphology, margins, internal content, T1/T2 signal intensity, enhancement features, and restricted diffusion. RESULTS: Sixteen patients (median age 31 years, IQR 19-41, 8 males) were identified with 68.8 % of patients having a known family history of SDHB variation. 81.3 % of lesions were solitary and majority were solid (86.7 % on CT, 87.5 % on MRI) with well-defined margins in >62.5 % of lesions, without evidence of internal fat, calcifications, or vascular invasion. 100 % of lesions demonstrated restricted diffusion and avid enhancement, with degree >75 % for most lesions on CT and MRI. On FDG-PET, all renal masses showed increased radiotracer uptake. 43.8 % of patients demonstrated extra-renal manifestations and 43.8 % had distant metastasis. CONCLUSION: SDHB-associated RCC is predominantly noted in young patients with no gender predilection. On imaging, SDH-deficient RCC are frequently unilateral, solitary, and solid with well-defined margins demonstrating avid enhancement with variability in enhancement pattern and showing restricted diffusion.

Validation of the ankle-specific pediatric arthritis ultrasound scoring system in children with juvenile idiopathic arthritis.

OBJECTIVE: To validate the ankle-specific Pediatric Arthritis Ultrasound Scoring System (PAUSS-ankle) in children with juvenile idiopathic arthritis (JIA). METHODS: Patients with a diagnosis of JIA prospectively underwent a standard clinical assessment and musculoskeletal ultrasound (MSUS) of one or both ankles. B-mode and Power-Doppler mode MSUS images were acquired and scored according to the PAUSS-ankle protocol. A subset of patients received a contrast-enhanced MRI (ceMRI) of the affected ankle. ceMRI scoring for synovitis was performed according to the Rheumatoid Arthritis MRI System (RAMRIS). Test characteristics of the PAUSS-ankle scores were evaluated with ceMRI as reference. Associations between the findings on physical examination, PAUSS-ankle, and RAMRIS were investigated. RESULTS: Thirty-two patients with JIA contributed 63 MSUS and 15 ceMRIs of the ankles. The PAUSS-ankle total B-mode score had a moderate correlation with physical examination findings (correlation (r)=0.43, p < 0.001). The PAUSS-ankle B-mode score ≥1 exhibited a sensitivity of 79 % and specificity of 100 %, demonstrating excellent diagnostic accuracy with an area under the curve (AUC)= 0.89 (confidence intervals, CI, 0.78-1.00) while clinical assessment had a sensitivity of 57 % and AUC= 0.71 (CI: 0.58-0.85). The PAUSS-ankle B-mode score had significant strong correlations (r = 0.68-0.90, p < 0.005) with the RAMRIS for the assessment of disease severity for each joint area and the ankle joint as a whole. CONCLUSION: Our findings demonstrate excellent diagnostic accuracy of the PAUSS-ankle in detecting the presence and severity of ankle synovitis when compared to ceMRI. The PAUSS-ankle holds significant promise as an accurate measurement that may complement current clinical standards.

Improved air kerma determination in the radiation field of the X-ray tube used in medical imaging systems, considering the type and thickness of the filter.

In diagnostic radiology, the air kerma is an essential parameter. Radiologists consider the air kerma, when calculating organ doses and dangers to patients. The intensity of the radiation beam is represented by the air kerma, which is the value of energy wasted by a photon as it travels through air. Because of the heel effect in X-ray sources, air kerma varies throughout the field of medical imaging systems. One possible contributor to this discrepancy is the X-ray tube's voltage. In this study, an approach has been proposed for predicting the air kerma anywhere inside the field of X-ray beams utilized in medical diagnostic imaging systems. As a first step, a diagnostic imaging system was modelled using the Monte Carlo N-Particle platform. We used a tungsten target and aluminum and beryllium filters of varying thicknesses to recreate the X-ray tube. The air kerma has been measured in different parts of the conical X-ray beam that is working at 30, 50, 70, 90, 110, 130, and 150 kV. This gives enough data for training neural networks. The voltage of the X-ray tube, filter type, filter thickness, and the coordinates of each point used to calculate the air kerma were all inputs to the MLP neural network. The MLP architecture, known for its significant advancements in research and expanding applications, was trained to predict the quantity of air kerma as its output. Specifically, by considering X-ray tube filters of varying thicknesses, the trained MLP model demonstrated its capability to accurately predict the air kerma at every point within the X-ray field for a range of X-ray tube voltages typically used in medical diagnostic radiography (30-150 kV).

The Use of 3D Printing in Fetal Surgery for Surgical Planning: A Scoping Review.

Objectives: We sought to identify in which clinical scenarios 3D printed models are used to plan for fetal surgeries as well as the main purpose and the imaging method utilized for the models. In addition, we describe benefits and shortcomings of the models, as well as potential future improvements. Methods: In this scoping review, data were collected retrospectively from scientific databases (PubMed, Embase, Cochrane CENTRAL, CINAHL, Scopus, and the Web of Science platform) and screened by title, abstract, and full text against strict criteria. The inclusion criteria required the study be performed on a live fetus and involve 3D models used for fetal surgery. The models must have been designed from diagnostic imaging modalities such as CT, MRI, or ultrasound. The articles considered include clinical trials, review articles, cohort studies, case series, case reports, and conference abstracts. Results: Of the initial 742 articles collected, six met the inclusion criteria. Spina bifida and EXIT procedures were the most frequent use cases that inspired surgeons to print models for surgical planning. The ability to view patient-specific anatomy in a 3D handheld model was often touted as providing a great benefit to the surgical team's ability to anticipate intraoperative challenges. Conclusions: Three-dimensional printing models have been applied to plan for fetal surgeries, more specifically, for EXIT procedures and fetoscopic surgical repair of spina bifida. The potential benefits of 3D printing in fetal surgery are enormous.

Symptom Persistence Relates to Volume and Asymmetry of the Limbic System after Mild Traumatic Brain Injury.

Background: Persistent symptoms have been reported in up to 50% of the 27 million people with mild traumatic brain injuries (mTBI) every year. MRI findings are currently limited by low diagnostic and prognostic sensitivities, constraining the value of imaging in the stratification of patients following mTBI. Limbic system structures are promising brain regions in offering prognostic factors for symptom persistence following mTBI. The objective of this study was to associate volume and symmetry of limbic system structures with the presence and persistence of common symptoms in patients with mTBI. Methods: This study focused on 524 adults (aged 18-82), 58% female, with 82% injured in motor vehicle accidents and 28% reporting loss of consciousness (LOC). Magnetic resonance imaging (MRI) data included a sagittal 3D T1-weighted sequence with 1.2 mm slice thickness, with voxel sizes of 0.93 mm × 0.93 mm × 1.2 mm, obtained a median of 156 days after injury. Symptom diagnosis and persistence were collected retrospectively from patient medical records. Intracranial volume-adjusted regional volumes per side utilizing automated volumetric analysis (NeuroQuant®) were used to calculate total volume, laterality index, and side-independent asymmetry. Covariates included age, sex, LOC, and days from injury. Limbic volumetrics did not relate to symptom presentation, except the (-) association between headache presence and thalamus volume (adjusted odds ratio = 0.51, 95% confidence interval = 0.32, 0.85). Headache, balance problems, anxiety, and depression persistence was (-) associated with thalamus volume (hazard ratio (HR) 1.25 to 1.94). Longer persistence of balance problems was associated with (-) lateral orbitofrontal cortex volume (HR = 1.33) and (+) asymmetry of the hippocampus (HR = 0.27). Persistence of cognitive deficits was associated with (+) asymmetry in the caudal anterior cingulate (HR = 0.67). Depression persistence was associated with (+) asymmetry in the isthmus of the cingulate gyrus (HR = 5.39). Persistence of anxiety was associated with (-) volume of the parahippocampal gyrus (HR = 1.67), orbitofrontal cortex (HR > 1.97), and right-biased laterality of the entorhinal cortex (HR = 0.52). Conclusions: Relative volume and asymmetry of the limbic system structures in patients with mTBI are associated with the persistence of symptoms, particularly anxiety. The conclusions of this study are limited by the absence of a reference group with no mTBI.

Pretransplant cardiac stress testing and transplant wait time in kidney transplantation candidates.

OBJECTIVE: Routine screening for cardiovascular disease before kidney transplantation remains controversial. This study aims to compare cardiac testing rates in patients with end-stage renal disease, referred and not referred for transplantation, and assess the impact of testing on transplant wait times. METHODS: This is a retrospective cohort study of 22 687 end-stage renal disease patients from 2011 to 2022, within an integrated health system. Cardiac testing patterns, and the association between cardiac testing and transplant wait times and post-transplant mortality were evaluated. RESULTS: Of 22 687 patients (median age 66 years, 41.1% female), 6.9% received kidney transplants, and 21.0% underwent evaluation. Compared with dialysis patients, transplant patients had a 5.6 times higher rate of stress nuclear myocardial perfusion imaging with single-photon emission (rate ratio (RR) 5.64, 95% CI 5.37 to 5.92), a 6.5 times higher rate of stress echocardiogram (RR 6.51, 95% CI 5.65 to 7.51) and 16% higher cardiac catheterisation (RR 1.16, 95% CI 1.06 to 1.27). In contrast, revascularisation rates were significantly lower in transplant patients (RR 0.46, 95% CI 0.36 to 0.58). Transplant wait times were longer for patients who underwent stress testing (median 474 days with no testing vs 1053 days with testing) and revascularisation (1796 days for percutaneous intervention and 2164 days for coronary artery bypass surgery). No significant association was observed with 1-year post-transplant mortality (adjusted OR 1.99, 95% CI 0.46 to 8.56). CONCLUSIONS: This study found a higher rate of cardiac testing in dialysis patients evaluated for kidney transplants. Cardiac testing was associated with longer transplant wait time, but no association was observed between testing and post-transplant mortality.

Contrast-enhanced ultrasound image sequences based on radiomics analysis for diagnosis of metastatic cervical lymph nodes from thyroid cancer.

Background: Thyroid cancer (TC) prone to cervical lymph node (CLN) metastasis both before and after surgery. Ultrasonography (US) is the first-line imaging method for evaluating the thyroid gland and CLNs. However, this assessment relies mainly on the subjective judgment of the sonographer and is very much dependent on the sonographer's experience. This prospective study was designed to construct a machine learning model based on contrast-enhanced ultrasound (CEUS) videos of CLNs to predict the risk of CLN metastasis in patients with TC. Methods: Patients who were proposed for surgical treatment due to TC from August 2019 to May 2020 were prospectively included. All patients underwent US of CLNs suspected of metastasis, and a 2-minute imaging video was recorded. After target tracking, feature extraction, and feature selection through the lymph node imaging video, three machine learning models, namely, support vector machine, linear discriminant analysis (LDA), and decision tree (DT), were constructed, and the sensitivity, specificity, and accuracy of each model for diagnosing lymph nodes were calculated by leave-one-out cross-validation (LOOCV). Results: A total of 75 lymph nodes were included in the study, with 42 benign cases and 33 malignant cases. Among the machine learning models constructed, the support vector machine had the best diagnostic efficacy, with a sensitivity of 93.0%, a specificity of 93.8%, and an accuracy of 93.3%. Conclusions: The machine learning model based on US video is helpful for the diagnosis of whether metastasis occurs in the CLNs of TC patients.

Evolution of treatment for unspecific back pain: From past to future.

Unspecific back pain (UBP) has long puzzled medical professionals. Historically, back pain (BP) was often attributed to mystical causes, treated with incantations or herbal concoctions. The Middle Ages shifted towards empirical practices, though still intertwined with superstition, using methods like leeches and bloodletting. The Renaissance introduced systematic healthcare approaches, laying the foundation for modern medicine. The 20th century saw significant advancements with diagnostic imaging, pharmacotherapy, physical therapy, and surgical interventions, though UBP remained elusive. Recent decades have seen a paradigm shift towards multidisciplinary approaches, addressing BP's multifactorial nature through holistic methods considering biomechanical, psychosocial, and lifestyle factors. This shift integrates quantitative research with hermeneutic interpretation, emphasizing evidence-based guidelines. Non-pharmacological interventions such as exercise therapy, electrotherapy, cognitive behavioral therapy, and mindfulness-based stress reduction have gained prominence, empowering individuals in their recovery. Technological innovations like virtual reality and artificial intelligence offer personalized treatment plans, optimizing outcomes. The future of BP treatment holds promise with advancements in regenerative medicine, neuromodulation, telemedicine, and remote monitoring platforms, enhancing accessibility and continuity of care, especially in underserved communities. However, challenges such as the opioid epidemic and healthcare disparities remain, necessitating judicious prescribing practices and equitable resource distribution. The evolving treatment landscape for UBP reflects the dynamic interplay between scientific progress, clinical innovation, and societal needs, aiming to alleviate the burden of back pain and improve quality of life.

Cysteine cathepsins: From diagnosis to targeted therapy of cancer.

Cysteine cathepsins are a fascinating group of proteolytic enzymes that play diverse and crucial roles in numerous biological processes, both in health and disease. Understanding these proteases is essential for uncovering novel insights into the underlying mechanisms of a wide range of disorders, such as cancer. Cysteine cathepsins influence cancer biology by participating in processes such as extracellular matrix degradation, angiogenesis, immune evasion, and apoptosis. In this comprehensive review, we explore foundational research that illuminates the diverse and intricate roles of cysteine cathepsins as diagnostic markers and therapeutic targets for cancer. This review aims to provide valuable insights into the clinical relevance of cysteine cathepsins and explore their capacity to advance personalised and targeted medical interventions in oncology.

Sonographic findings associated with complications in pediatric patients with septic arthritis.

OBJECTIVES: Ultrasound is a valuable tool for diagnosing septic arthritis and guiding the development of treatment plans. This study aimed to identify sonographic findings associated with complications in septic arthritis. METHODS: Twelve patients aged <5 years diagnosed with septic arthritis were classified into two groups: those with and without complications. Complications were defined as the destruction of the epiphyseal bone head and metaphysis bone cortex. The following sonographic findings were compared between the two groups using Fisher's exact test: synovial membrane thickness, joint effusion, diminished hyperechoic foci within the epiphyseal bone head, and diminished smooth metaphyseal bone cortex. RESULTS: Overall, 4 of 12 patients developed complications. Joint effusion and synovial membrane thickening were detected in all patients with septic arthritis. The incidence of diminished hyperechoic foci within the epiphyseal bone head was significantly different between the two groups (presence/absence in patients with complications vs. without = 3/1 vs. 0/8, p = 0.018). The incidence of diminished smooth metaphyseal bone cortex was higher in patients with complications than in those without; however, this difference was not statistically significant (presence/absence in patients with complications vs. without = 4/0 vs. 3/5, p = 0.081). CONCLUSION: Ultrasound proved to be an effective diagnostic tool for septic arthritis and also demonstrated its potential in predicting complications of septic arthritis in the pediatric population.

The current and upcoming era of radiomics in phaeochromocytoma and paraganglioma.

The topic of the diagnosis of phaeochromocytomas remains highly relevant because of advances in laboratory diagnostics, genetics, and therapeutic options and also the development of imaging methods. Computed tomography still represents an essential tool in clinical practice, especially in incidentally discovered adrenal masses; it allows morphological evaluation, including size, shape, necrosis, and unenhanced attenuation. More advanced post-processing tools to analyse digital images, such as texture analysis and radiomics, are currently being studied. Radiomic features utilise digital image pixels to calculate parameters and relations undetectable by the human eye. On the other hand, the amount of radiomic data requires massive computer capacity. Radiomics, together with machine learning and artificial intelligence in general, has the potential to improve not only the differential diagnosis but also the prediction of complications and therapy outcomes of phaeochromocytomas in the future. Currently, the potential of radiomics and machine learning does not match expectations and awaits its fulfilment.