Diagnostic Tool Research Articles

Diagnostic accuracy of daytime polysomnography: a reappraisal during the COVID-19 era.

Level I conventional polysomnography (PSG), the gold standard for diagnosing obstructive sleep apnea (OSA), requires an overnight stay. This study evaluated the role of daytime PSG as an alternative diagnostic tool. A prospective cohort study was undertaken with consecutive patients with suspected OSA at a tertiary care sleep center. The primary objective was to evaluate the sensitivity and diagnostic accuracy of daytime PSG for diagnosing OSA. The secondary objective was to find out the factors associated with a falsely negative daytime PSG result. All individuals were subjected to level I daytime PSG, done in the sleep lab in the presence of an experienced sleep technician during the daytime from 12 PM to 4 PM. Out of 162 patients, 105 underwent daytime PSG. OSA was diagnosed on daytime PSG in 86.7 out of the 19 remaining patients refused a repeat PSG study. Out of the 12 individuals who underwent the nighttime PSG for confirmatory diagnosis, 10 were diagnosed as OSA (false negatives), and 2 were confirmed as not-OSA (true negatives). The sensitivity, diagnostic accuracy, and negative predictive value of daytime PSG were 89.58%, 89.80%, and 16.67%, respectively. The false negatives had a higher prevalence of mild OSA. Daytime PSG is sensitive in diagnosing OSA and can be considered in individuals with severe symptoms at centers with a high patient load or when the individual wishes to avoid a nighttime study. A negative result in daytime PSG must be followed by conventional overnight PSG for confirmatory diagnosis.

Sliding transformer with uncertainty estimation for vestibular schwannoma automatic segmentation.

Objective.Automated segmentation of vestibular schwannoma (VS) using magnetic resonance imaging (MRI) can enhance clinical efficiency. Though many advanced methods exist for automated VS segmentation, the accuracy is hindered by ambivalent tumor borders and cystic regions in some patients. In addition, these methods provide results that do not indicate segmentation uncertainty, making their translation into clinical workflows difficult due to potential errors. Providing a definitive segmentation result along with segmentation uncertainty or self-confidence is crucial for the conversion of automated segmentation programs to clinical aid diagnostic tools.Approach.To address these issues, we propose a U-shaped cascade transformer structure with a sliding window that utilizes multiple sliding samples, a segmentation head, and an uncertainty head to obtain both the segmentation mask and uncertainty map. We collected multimodal MRI data from 60 clinical patients with VS from Xuanwu Hospital. Each patient case includes T1-weighted images, contrast-enhanced T1-weighted images, T2-weighted images, and a tumor mask. The images exhibit an in-plane resolution ranging from 0.70 × 0.70 to 0.76 × 0.76 mm, an in-plane matrix spanning from 216 × 256 to 284 × 256, a slice thickness varying between 0.50 and 0.80 mm, and a range of slice numbers from 72 to 120.Main results.Extensive experimental results show that our method achieves comparable or higher results than previous state-of-the-art brain tumor segmentation methods. On our collected multimodal MRI dataset of clinical VS, our method achieved the dice similarity coefficient (DSC) of 96.08% ± 1.30. On a publicly available VS dataset, our method achieved the mean DSC of 94.23% ± 2.53.Significance.The method efficiently solves the VS segmentation task while providing an uncertainty map of the segmentation results, which helps clinical experts review the segmentation results more efficiently and helps to transform the automated segmentation program into a clinical aid diagnostic tool.

The relationship between albumin level and the development of acute kidney injury and mortality in critically COVID-19 patients

Aims: The impact of the Coronavirus Pandemic, which began in 2019, has considerably diminished; however, its effects still persist. While respiratory symptoms have been prominent during the pandemic, acute kidney disease has emerged as a significant contributor to morbidity and mortality. This study aims to demonstrate that serum albumin levels can serve as a predictor for acute kidney injury (AKI) and mortality, owing to their cost- effectiveness and feasibility for use across various healthcare centers. The goal is to contribute to the reduction of AKI development and mortality rates. Methods: The study was conducted by analyzing data from a total of 350 patients admitted to intensive care units of a training and research hospital due to COVID-19 between March 1, 2020, and April 30, 2021. Of these patients, 179 (51%) were male, and 171 (49%) were female. The data were examined retrospectively. Patients were categorized into two groups based on serum albumin levels: ?2.5 mg/dl (severe hypoalbuminemia) and 2.5-3.5 mg/dl (mild hypoalbuminemia). Subsequently, the patients were further categorized into groups based on the presence or absence of AKI, and these groups were statistically compared. Demographic data, clinical information, and laboratory values of the patients were assessed. The diagnosis of acute kidney injury (AKI) was made according to KDIGO criteria. Data were compared using the SPSS version 24 software. Results: Among the 350 patients included in the study, 115 had serum albumin levels ?2.5 mg/dl (severe hypoalbuminemia), and 235 had levels in the range of 2.5-3.5 mg/dl (mild hypoalbuminemia). Among those who developed AKI, the average albumin level was found to be 2.68 mg/dl, whereas in the group without AKI, the average albumin level was 2.76 mg/dl. Out of the total, 201 (57%) patients developed AKI, and 82% of them experienced mortality. In contrast, among the 149 (43%) patients who did not develop AKI, the mortality rate was 42%. Further subgroup analysis revealed the highest mortality rate of 88% among patients with severe hypoalbuminemia and AKI development. Conversely, the lowest mortality rate of 40% was observed in patients with mild hypoalbuminemia and no AKI. Conclusion: This study aims to establish that low serum albumin levels should be regarded not only as a negative acute-phase reactant but also as a predictive factor for complications including acute kidney disease development and mortality. Lower albumin values are correlated with higher complication rates and increased mortality. Additionally, due to its widespread availability and low cost, serum albumin is a cost-effective diagnostic tool that can be utilized in almost any healthcare setting.

Ocular Pathology and Genetics: Transformative Role of Artificial Intelligence (AI) in Anterior Segment Diseases.

Artificial intelligence (AI) has become a revolutionary influence in the field of ophthalmology, providing unparalleled capabilities in data analysis and pattern recognition. This narrative review delves into the crucial role that AI plays, particularly in the context of anterior segment diseases with a genetic basis. Corneal dystrophies (CDs) exhibit significant genetic diversity, manifested by irregular substance deposition in the cornea. AI-driven diagnostic tools exhibit promising accuracy in the identification and classification of corneal diseases. Importantly, chat generative pre-trained transformer (ChatGPT)-4.0 shows significant advancement over its predecessor, ChatGPT-3.5. In the realm of glaucoma, AI significantly contributes to precise diagnostics through inventive algorithms and machine learning models, surpassing conventional methods. The incorporation of AI in predicting glaucoma progression and its role in augmenting diagnostic efficiency is readily apparent. Additionally, AI-powered models prove beneficial for early identification and risk assessment in cases of congenital cataracts, characterized by diverse inheritance patterns. Machine learning models achieving exceptional discrimination in identifying congenital cataracts underscore AI's remarkable potential. The review concludes by emphasizing the promising implications of AI in managing anterior segment diseases, spanning from early detection to the tailoring of personalized treatment strategies. These advancements signal a paradigm shift in ophthalmic care, offering optimism for enhanced patient outcomes and more streamlined healthcare delivery.

Evaluation of ethanol extract of Allium cepa and fractions on haematological parameters in doxorubicin-induced Cardiotoxicity using Wistar rats

This research study evaluated the effects of Ethanol extract of Allium cepa (A. cepa) popularly known as Onions and its fractions on haematological parameters in doxorubicin-induced cardiotoxicity using Wistar rats. A total of 45 Wistar rats weighing between 150-200 g were recruited for this study. They were randomly divided into 9 groups of 5 animals each; as follows: Group 1: served as control and received 10 ml /kg/ body weight (b.w) per oral (p.o) of normal saline. Group II: received 3.5 mg / kg b.w intraperitoneal (i.p) of Doxorubicin (Dox). Group III: received 500 mg/kg/ b.w p.o of vitamin E plus Dox. Group IV: received 1000 mg/kg/ b.w of crude extract (C.E) of A. cepa plus Dox. Group V: received 1000 mg/kg b.w of n-Hexane fraction of A. cepa plus Dox. Group VI: received 1000 mg/kg b.w of dichloromethane (DCM) fraction of A. cepa plus Dox. Group VII received 1000 mg/kg b.w of ethyl acetate (E.A) fraction of A. cepa plus Dox. Group VIII: received 1000 mg/kg b.w of methanol (METH) fraction, and Group IX received Combinations of C.E of A. cepa + vitamin E and Dox respectively for 14days. Groups I and II treatments lasted for 14 days, while treatments for groups III-IX lasted for 16 days (making 14 days for respective treatments and additional 2 days for doxorubicin administered once 48 hourly before sacrificing. All substances in this study were administered orally except doxorubicin that was administered intraperitoneally. Haematology results obtained from this study showed Dox administration negatively altered full blood count; Red blood cell (RBC), White blood cell (WBC) and Platelets levels significantly (p<0.05). However, pre-treatment administration with Allium cepa showed significant (p<0.05) improvement of full blood count levels from the effects of singular administration of Dox. Injury to the myocardium was also observed on histological examination in the Dox treated group. Our findings indicate that haematological parameters RBC, WBC, Platelets could be useful diagnostic tools in prediction and evaluation of Cardiotoxicity. Haematology results obtained from this study showed Doxorubicin administration significantly altered (p<0.05) full blood count; Red blood cell (RBC), White blood cell (WBC) and Platelets levels. However, pre-treatment administration with Allium cepa showed significant (p<0.05) improvement of full blood count levels from the effects of singular administration of Doxorubicin. Injury to the myocardium was also observed on histological examination in the Doxorubicin treated group. Our findings indicate that haematological parameters RBC, WBC, Platelets could be useful diagnostic tools in prediction and evaluation of Cardiotoxicity.

PAM‐Engineered Toehold Switches as Input‐Responsive Activators of CRISPR‐Cas12a for Sensing Applications

AbstractThe RNA‐programmed CRISPR effector protein Cas12a has emerged as a powerful tool for gene editing and molecular diagnostics. However, additional bio‐engineering strategies are required to achieve control over Cas12a activity. Here, we show that Toehold Switch DNA hairpins, presenting a rationally designed locked protospacer adjacent motif (PAM) in the loop, can be used to control Cas12a in response to molecular inputs. Reconfiguring the Toehold Switch DNA from a hairpin to a duplex conformation through a strand displacement reaction provides an effective means to modulate the accessibility of the PAM, thereby controlling the binding and cleavage activities of Cas12a. Through this approach, we showcase the potential to trigger downstream Cas12a activity by leveraging proximity‐based strand displacement reactions in response to target binding. By utilizing the trans‐cleavage activity of Cas12a as a signal transduction method, we demonstrate the versatility of our approach for sensing applications. Our system enables rapid, one‐pot detection of IgG antibodies and small molecules with high sensitivity and specificity even within complex matrices. Besides the bioanalytical applications, the switchable PAM‐engineered Toehold Switches serve as programmable tools capable of regulating Cas12a‐based targeting and DNA processing in response to molecular inputs and hold promise for a wide array of biotechnological applications.

PAM-Engineered Toehold Switches as Input-Responsive Activators of CRISPR-Cas12a for Sensing Applications.

The RNA-programmed CRISPR effector protein Cas12a has emerged as a powerful tool for gene editing and molecular diagnostics. However, additional bio-engineering strategies are required to achieve control over Cas12a activity. Here, we show that Toehold Switch DNA hairpins, presenting a rationally designed locked protospacer adjacent motif (PAM) in the loop, can be used to control Cas12a in response to molecular inputs. Reconfiguring the Toehold Switch DNA from a hairpin to a duplex conformation through a strand displacement reaction provides an effective means to modulate the accessibility of the PAM, thereby controlling the binding and cleavage activities of Cas12a. Through this approach, we showcase the potential to trigger downstream Cas12a activity by leveraging proximity-based strand displacement reactions in response to target binding. By utilizing the trans-cleavage activity of Cas12a as a signal transduction method, we demonstrate the versatility of our approach for sensing applications. Our system enables rapid, one-pot detection of IgG antibodies and small molecules with high sensitivity and specificity even within complex matrices. Besides the bioanalytical applications, the switchable PAM-engineered Toehold Switches serve as programmable tools capable of regulating Cas12a-based targeting and DNA processing in response to molecular inputs and hold promise for a wide array of biotechnological applications.

The use of atomic absorption technology as a diagnostic and monitoring tool for some diseases: A review between 2010 and 2022

Atomic absorption technology is considered one of the important technologies in many different scientific fields because it is of a specification and diagnosis nature. Therefore, we decided to make a review about this technology over the years from 2010 to 2022 and the studies that used this technology in the fields of chemistry, physics, and medicine, and it's very important relationship in diagnosing the levels of element concentrations. Necessary, trace, toxic, etc. We have found that it is very effective in this aspect and provides scientific research with many relevant positives. Therefore, we advise researchers to use it and to delve into broader fields by using it in more comprehensive and advanced research and to work on developing the technology in terms of work and diagnosis.

Skinly: A novel handheld IoT device for validating biophysical skin characteristics.

Recent advancements in artificial intelligence have revolutionized dermatological diagnostics. These technologies, particularly machine learning (ML), including deep learning (DL), have shown accuracy equivalent or even superior to human experts in diagnosing skin conditions like melanoma. With the integration of ML, including DL, the development of at home skin analysis devices has become feasible. To this end, we introduced the Skinly system, a handheld device capable of evaluating various personal skin characteristics noninvasively. Equipped with a moisture sensor and a multi-light-source camera, Skinly can assess age-related skin parameters and specific skin properties. Utilizing state-of-the-art DL, Skinly processed vast amounts of images efficiently. The Skinly system's efficacy was validated both in the lab and at home, comparing its results to established "gold standard" methods. Our findings revealed that the Skinly device can accurately measure age-associated parameters, that is, facial age, skin evenness, and wrinkles. Furthermore, Skinly produced data consistent with established devices for parameters like glossiness, skin tone, redness, and porphyrin levels. A separate study was conducted to evaluate the effects of two moisturizing formulations on skin hydration in laboratory studies with standard instrumentation and at home with Skinly. Thanks to its capability for multi-parameter measurements, the Skinly device, combined with its smartphone application, holds the potential to replace more expensive, time-consuming diagnostic tools. Collectively, the Skinly device opens new avenues in dermatological research, offering a reliable, versatile tool for comprehensive skin analysis.

Overcoming Operational Challenges: A Case Study of MRI Functionality in Resource-Scarce Regions

Magnetic resonance imaging(MRI) is a veritable radiological diagnostic tool for the in-depth diagnosis of various ailment involving virtually all organ systems of the human body. The machinery for this radiological investigation tool is quite huge and needs installation in a spacious, well ventilated and air-conditioned room. It also must have verified working alternative power source as the essential lithium gas needed for its proper working must be kept cool at all times, and the environment where the MRI equipment is installed must always be kept at an ambient room temperature. This requirement means that a regular power supply must be assured as the lack of it may impact negatively on the functional ability of the equipment, which was procured at a great cost, its installation and maintenance also at a great deal of scarce fund. So, all care must be put in place not to endanger the perfect workings of the MRI equipment. Angry hospital workers deliberately shut off the electrical and water supply to the MRI unit in protest, aiming to force management to address their grievances. However, this action had severe consequences for the MRI machine, as its cooling system for the essential helium gas was disrupted, leading to gas depletion from the cannisters. This incident underscores the critical need for uninterrupted power and cooling systems in MRI installations to ensure their proper functioning and avoid costly damage.

The Role of Medical Microbiologists in Advancing the Frontiers of Travel Medicine

The essential role of medical microbiologists in the field of travel medicine becomes apparent amidst the escalating challenges faced by our world. This article highlights their indispensable contributions to safeguarding global health during travel. Medical microbiologists play a pivotal part in defending against infectious threats encountered during travel, identifying and characterizing novel pathogens, developing rapid diagnostic tools, and spearheading outbreak investigations for early detection and containment. Their active involvement in vaccine development and surveillance is critical for ensuring the safety of travelers, and they address vaccine hesitancy through educational initiatives and advocacy. Moreover, they combat the growing issue of antimicrobial resistance, influencing travel health guidelines and promoting prudent antimicrobial use to minimize resistance risks. Collaboration is paramount in tackling global health threats, and medical microbiologists facilitate the exchange of information, reinforcing global surveillance networks to respond effectively to emerging infections. Their role in training the next generation of experts ensures a sustainable and knowledgeable workforce in travel medicine. As we navigate the continually evolving landscape of travel, the expertise of medical microbiologists becomes increasingly vital. Their dedication to advancing travel medicine through research, education, and collaborative efforts ensures that travel remains a positive force, promoting exploration while mitigating health risks. Recognizing and supporting their endeavors contribute to building a safer and healthier future for travelers and communities worldwide.

Non-invasive tools for inflammatory bowel disease: A systematic review and meta-analysis of biochemical markers and intestinal ultrasound compared to endoscopy

Despite endoscopy's gold standard status, non-invasive tools are revolutionizing Inflammatory Bowel Disease (IBD) management. This systematic review and meta-analysis compared the diagnostic accuracy of biochemical markers, intestinal ultrasound (US), and endoscopy in adults with IBD. This systematic review and meta-analysis aimed to compare the diagnostic accuracy of fecal calprotectin, C-Reactive Protein (CRP), Erythrocyte Sedimentation Rate (ESR), and bowel wall thickness measured by US with endoscopy in IBD patients. We searched electronic databases for most recent studies published between 2012 and 2023, identifying 25 studies comparing at least one non-invasive tool with endoscopy. We pooled sensitivity and specificity for relevant outcomes and conducted subgroup analyses to explore heterogeneity. 25 studies (n=5872 patients) met inclusion criteria. Fecal calprotectin emerged as a powerful diagnostic tool, with pooled sensitivity of 92.5% and specificity of 85.1% for IBD. But it’s performance was less consistent in differentiating active vs. inactive disease and predicting flares. Intestinal US proved reliable for diagnosis, particularly in Crohn's disease (pooled sensitivity 86.3%, specificity 78.9%), and showed promise in assessing activity and predicting treatment response. C-Reactive Protein and Erythrocyte Sedimentation Rate, though less accurate, provided additional information about disease status. Combining calprotectin and US further enhanced prediction accuracy, while decision tree analysis incorporating clinical data and both tools maximized prediction in ulcerative colitis. Non-invasive tools offer invaluable insights for IBD management, complementing and potentially reducing reliance on endoscopy. Standardizing methodologies and developing more specific markers, potentially aided by AI, holds immense potential for personalized, effective IBD care. This evolving landscape paves the way for a future where patients actively participate in their journey, empowered by the growing arsenal of non-invasive tools.

공학계열 전공역량 진단도구의 타당화 연구 : 의학공학계열 사례를 중심으로

공학계열 전공역량 진단도구의 타당화 연구 : 의학공학계열 사례를 중심으로

Fine-needle aspiration diagnosis of secondary malignant tumors of the thyroid gland: A single-institution experience of 17 cases.

Fine-needle aspiration (FNA) is the most commonly used preoperative pathological diagnostic tool for thyroid tumors. Secondary malignant tumors of the thyroid gland account for less than 3% of all thyroid malignancies. The aim of this study was to investigate the types and cytopathological features of secondary thyroid tumors, evaluate diagnostic pitfalls in FNA. Cases of secondary thyroid tumors diagnosed in the Department of Pathology of Shaanxi Provincial People's Hospital were collected, and their clinical data, cytologic features, immunohistochemical results, and histopathological diagnoses were summarized. The study included 17 cases (8 males and 9 females) with a mean age of 60.4 ± 9.4 years (range, 45-83 years). Six cases had a known history of primary malignancy prior to FNA aspiration diagnosis. The most common organs of origin were the lungs (5 cases, 3 adenocarcinoma, and 2 small-cell carcinoma) and esophagus (5 cases, 3 squamous-cell carcinoma, 1 adenocarcinoma, and 1 small-cell carcinoma). The next most common was squamous-cell carcinoma of the larynx (3 cases), and gastric tumor (2 cases), including 1 lymphoma and 1 adenocarcinoma. Cell blocks and immunohistochemistry were performed in 12 of these cases. Comparison of the impact of positive history and IHC availability on the accuracy of pathologic diagnosis showed that both were statistically significant. FNA is an effective means of diagnosing secondary malignancies of the thyroid, in which knowledge of the patient's history of malignancy is essential, and the use of cell blocks and immunohistochemistry helps to clarify the pathological diagnosis.

Revisiting the Pathophysiology of Acute Respiratory Distress Syndrome in Burn with Inhalation Injury: A Comprehensive Review

Acute respiratory distress syndrome (ARDS) is a common complication in severe burn patients, arising from inflammatory responses following burns or inhalation injuries. This literature review explores the mechanisms and diagnostic approaches for ARDS in burn patients. Methods involved searching open-access journals using specific keywords on PubMed, Google Scholar, and Elsevier. The review highlights the involvement of various immune cells and cytokines in ARDS pathophysiology, with diagnostic tools including clinical signs, imaging, and bronchoscopy. Therapeutic strategies focus on ventilation and pharmacological interventions targeting inflammation. Further research is needed to better understand ARDS in burn patients, particularly regarding inflammatory markers and pharmacological treatments.

Early Detection of Parkinson Disease Throughbiomedical Speech and Voice Analysis

Parkinson's disease, widely recognized as a neurodegenerative condition characterized by subtle changes in voice, has spurred an investigation into voice analysis for diagnostic purposes. This study is dedicated to the early detection of Parkinson's disease through a comprehensive examination of biomedical speech attributes. Parameters such as fundamental frequency range, jitter, shimmer, noise-to-harmonics ratio, and features derived from nonlinear analysis are considered, alongside variables like status, indicating the presence of neurological disorders, and class for classification purposes. Together, these attributes provide a detailed representation of voice signals, offering valuable insights into both neurological and voice disorders for research purposes. The dataset exhibits promising potential for applications in medical diagnostics and voice analysis. In the pursuit of accurate disease detection, various machine learning methodologies are employed, including Support Vector Machines (SVM), Random Forest (RF), Decision Tree (DT), Neural Networks (NN), and state- of-the-art Convolutional Neural Networks (CNNs). The incorporation of CNNs is pivotal, signifying a significantleap in accuracy of 100%for disease detection. The results showcase a model adept at discerning subtle changesassociated with Parkinson's disease, with SVM achieving 96%, Decision Tree demonstrating a perfect 100%, Neural Network attaining 98%, and Random Forest showcasing an accuracy of 99%. This innovative approach not only transforms early Parkinson's disease identification through voice analysis, setting a precision benchmark, but also underscores the transformative potential of cutting-edge technologies in healthcare practices. The study positions the model as a reliable diagnostic tool, capable of advancing medical diagnosticsthrough the seamless integration of biomedical research and machine learning, contributing to the broader fieldof neurodegenerative disease diagnostics.

Telehealth Physiotherapy: A Game-Changer in Healthcare

Telehealth physiotherapy, also known as virtual physiotherapy or remote physical therapy, has emerged as a transformative force in healthcare. This chapter explores the concept of telehealth physiotherapy, delving into its benefits, challenges, and its role in modern healthcare. The rise of telehealth physiotherapy, catalyzed by the COVID-19 pandemic, has brought about several advantages. It enhances accessibility, particularly for those in remote or underserved areas, eliminates travel-related inconveniences, and ensures the continuity of care even during emergencies or lockdowns. Moreover, telehealth proves to be cost-effective and offers real-time monitoring, thereby boosting patient engagement and reducing waiting times for appointments. However, telehealth physiotherapy is not without its challenges. Technological barriers, the limitations of hands-on assessments, patient privacy, and data security issues, as well as the complexity of insurance and reimbursement policies, all pose significant hurdles. Some conditions may necessitate advanced diagnostic tools, which are not readily available through telehealth. Additionally, the scope of telehealth is not universal, and it may not be suitable for all physiotherapy cases, especially those requiring intensive, hands-on interventions. In conclusion, telehealth physiotherapy holds immense promise as a valuable tool in modern healthcare. As technology continues to evolve and regulatory frameworks adapt, telehealth physiotherapy is poised to become an integral part of physiotherapy practice, ensuring that patients receive the care they need, regardless of their geographical location or circumstances. This chapter highlights the transformative potential of telehealth in physiotherapy and underscores the need for its continued development and integration into healthcare systems worldwide. Keywords: telehealth physiotherapy, healthcare, virtual physiotherapy, remote areas

Navigating the landscape of clinical genetic testing: insights and challenges in rare disease diagnostics

With the rapid evolution of diagnostic tools, particularly next-generation sequencing, the identification of genetic diseases, predominantly those with pediatric-onset, has significantly advanced. However, this progress presents challenges that span from selecting appropriate tests to the final interpretation of results. This review examines various genetic testing methodologies, each with specific indications and characteristics, emphasizing the importance of selecting the appropriate genetic test in clinical practice, taking into account factors like detection range, cost, turnaround time, and specificity of the clinical diagnosis. Interpretation of variants has become more challenging, often requiring further validation and significant resource allocation. Laboratories primarily classify variants based on the American College of Medical Genetics and Genomics and the Association for Clinical Genomic Science guidelines, however, this process has limitations. This review underscores the critical role of clinicians in matching patient phenotypes with reported genes/variants and considering additional factors such as variable expressivity, disease pleiotropy, and incomplete penetrance. These considerations should be aligned with specific gene-disease characteristics and segregation results based on an extended pedigree. In conclusion, this review aims to enhance understanding of the complexities of clinical genetic testing, advocating for a multidisciplinary approach to ensure accurate diagnosis and effective management of rare genetic diseases.

Detection of COVID-19, pneumonia, and tuberculosis from radiographs using AI-driven knowledge distillation

Chest radiography is an essential diagnostic tool for respiratory diseases such as COVID-19, pneumonia, and tuberculosis because it accurately depicts the structures of the chest. However, accurate detection of these diseases from radiographs is a complex task that requires the availability of medical imaging equipment and trained personnel. Conventional deep learning models offer a viable automated solution for this task. However, the high complexity of these models often poses a significant obstacle to their practical deployment within automated medical applications, including mobile apps, web apps, and cloud-based platforms. This study addresses and resolves this dilemma by reducing the complexity of neural networks using knowledge distillation techniques (KDT). The proposed technique trains a neural network on an extensive collection of chest X-ray images and propagates the knowledge to a smaller network capable of real-time detection. To create a comprehensive dataset, we have integrated three popular chest radiograph datasets with chest radiographs for COVID-19, pneumonia, and tuberculosis. Our experiments show that this knowledge distillation approach outperforms conventional deep learning methods in terms of computational complexity and performance for real-time respiratory disease detection. Specifically, our system achieves an impressive average accuracy of 0.97, precision of 0.94, and recall of 0.97.

Appearance of facet joint syndrome in a case of chronic sacroiliitis: Evidenced from quantitative sacroiliac scintigraphy and dual images of SPECT-CT

Lower back pain (LBP) is a global health concern with increasing prevalence, projected to reach 843 million cases by 2050. Lumbar facet joint (LFJ) syndrome contributes significantly to LBP, impacting patient quality of life. Despite its prevalence, a gold standard for accurate and noninvasive diagnosis of LBP has not yet been established, leading to underdiagnosis and inadequate treatment. This case report presents a 57-year-old woman diagnosed with LFJ syndrome and mild sacroiliitis through single-photon emission computed tomography- computed tomography (SPECT-CT) and quantitative sacroiliac scintigraphy (QSS). The patient presented with persistent LBP and hip pain without history of trauma or surgery. Clinical examination revealed lumbar tenderness, limited mobility, and positive Fortin and STORK tests. Whole body bone scan (WBBS) revealed tracer uptake at the sacroiliac (SI) joints and multiple spinal levels, particularly L3-L4. Hybrid SPECT-CT imaging showed heightened bone activity on lumbar spine, confirming degenerative arthropathy of the L3-L4 facet joints, in contrast with minimal evidence obtained from plain radiography and CT images. Furthermore, combining results from SPECT-CT and borderline sacroiliac indices from QSS indicate the presence of chronic degenerative sacroiliitis. Identifying the source of LBP remains challenging. SPECT-CT emerges as a valuable tool for comprehensive evaluation of LBP by combining anatomical and functional imaging of target tissues, allowing increased foci localization and accuracy of diagnosis. QSS can also be utilized as a complement in identifying the presence of chronic lesions of the SI joints. These promising results open opportunities for more research on the efficacy of combined morphological and functional imaging, as well as sacroiliac indices as a complementary diagnostic tool.