An anatomico-radiological study of an accessory mandibular foramen on the medial mandibular surface

Unnamed foramina are known to be present in the mandible. The present research paper reports the presence of an accessory foramen on the medial surface of the mandible, highlighting its anatomico-radiological details. Accessory foramina in the mandible have been known to transmit branches of nerves supplying the roots of the teeth. Nerve block techniques by local anaesthetics might fail if any of these nerves or their branches pass through these accessory foramina and thus escape the nerve block. Dental surgeons performing extractions should be aware of accessory foramina on the mandible and thus plan anaesthesia at an appropriate anatomical site. The presence of such foramina might also be an alternate route for tumour spread following radiation therapy. Precise knowledge and awareness of such accessory mandibular foramina would therefore be important for dental surgeons performing nerve block and also for oncologists in planning radiation therapy

Unusual Branching Pattern of the Lateral Cord of the Brachial Plexus Associated with Neurovascular Compression : Case report

The brachial plexus consists of a network of nerves that innervates the upper limbs and its musculature. We report a rare formation of the lateral cord of the brachial plexus observed during the dissection of a 47-year-old male cadaver at the Department of Anatomy, Vardhman Mahavir Medical College, New Delhi, India, in 2016. The lateral cord was exceptionally long with twin lateral pectoral nerves and twin lateral roots of the median nerve. The proximal lateral root of the median nerve was thin in comparison to the medial root of the median nerve. The distal lateral root of the median nerve was thicker and followed an unusual course through the coracobrachialis muscle. In the lower third of the arm, the median nerve and the brachial artery—along with its vena comitans—spanned through the brachialis muscle. Surgeons, anaesthesiologists, radiologists and anatomists should be aware of such anatomical variations as they may result in neurovascular compression

A supernumerary maxillary tooth: its topographical anatomy and its clinical implications

A supernumerary tooth was detected in the left maxilla during an osteology teaching session with undergraduate medical students. Supernumerary teeth have previously been detected in individuals who have approached a dental surgeon with a complaint and who have then been diagnosed by X-ray. Asymptomatic cases are frequently not diagnosed in time and it is only the malalignment or delayed eruption of the tooth which raises the suspicion that this type of dental anomaly is present. The present paper highlights the anatomico-radiological study of a supernumerary maxillary tooth in a bone specimen and describes its clinical implications. Precise anatomical details of the supernumerary maxillary tooth might be of significant clinical interest to dental and maxillofacial surgeons in drawing up a plan for orthodontic treatment and may thus minimise the possible complications involved

Spectroscopy of laser-produced plasmas: setting up of high-performance laser-induced breakdown spectroscopy system

It is a well-known fact that laser-induced breakdown spectroscopy (LIBS) has emerged as one of the best analytical techniques for multi-elemental compositional analysis of samples. We report assembling and optimization of LIBS set up using high resolution and broad-range echelle spectrograph coupled to an intensified charge coupled device (ICCD) to detect and quantify trace elements in environmental and clinical samples. Effects of variations of experimental parameters on spectroscopy signals of copper and brass are reported. Preliminary results of some plasma diagnostic calculations using recorded time-resolved optical emission signals are also reported for brass samples

Deep Learning Paradigm and Its Bias for Coronary Artery Wall Segmentation in Intravascular Ultrasound Scans: A Closer Look

Background and motivation: Coronary artery disease (CAD) has the highest mortality rate; therefore, its diagnosis is vital. Intravascular ultrasound (IVUS) is a high-resolution imaging solution that can image coronary arteries, but the diagnosis software via wall segmentation and quantification has been evolving. In this study, a deep learning (DL) paradigm was explored along with its bias. Methods: Using a PRISMA model, 145 best UNet-based and non-UNet-based methods for wall segmentation were selected and analyzed for their characteristics and scientific and clinical validation. This study computed the coronary wall thickness by estimating the inner and outer borders of the coronary artery IVUS cross-sectional scans. Further, the review explored the bias in the DL system for the first time when it comes to wall segmentation in IVUS scans. Three bias methods, namely (i) ranking, (ii) radial, and (iii) regional area, were applied and compared using a Venn diagram. Finally, the study presented explainable AI (XAI) paradigms in the DL framework. Findings and conclusions: UNet provides a powerful paradigm for the segmentation of coronary walls in IVUS scans due to its ability to extract automated features at different scales in encoders, reconstruct the segmented image using decoders, and embed the variants in skip connections. Most of the research was hampered by a lack of motivation for XAI and pruned AI (PAI) models. None of the UNet models met the criteria for bias-free design. For clinical assessment and settings, it is necessary to move from a paper-to-practice approach

COVLIAS 3.0: cloud-based quantized hybrid UNet3+ deep learning for COVID-19 lesion detection in lung computed tomography

Background and noveltyWhen RT-PCR is ineffective in early diagnosis and understanding of COVID-19 severity, Computed Tomography (CT) scans are needed for COVID diagnosis, especially in patients having high ground-glass opacities, consolidations, and crazy paving. Radiologists find the manual method for lesion detection in CT very challenging and tedious. Previously solo deep learning (SDL) was tried but they had low to moderate-level performance. This study presents two new cloud-based quantized deep learning UNet3+ hybrid (HDL) models, which incorporated full-scale skip connections to enhance and improve the detections.MethodologyAnnotations from expert radiologists were used to train one SDL (UNet3+), and two HDL models, namely, VGG-UNet3+ and ResNet-UNet3+. For accuracy, 5-fold cross-validation protocols, training on 3,500 CT scans, and testing on unseen 500 CT scans were adopted in the cloud framework. Two kinds of loss functions were used: Dice Similarity (DS) and binary cross-entropy (BCE). Performance was evaluated using (i) Area error, (ii) DS, (iii) Jaccard Index, (iii) Bland–Altman, and (iv) Correlation plots.ResultsAmong the two HDL models, ResNet-UNet3+ was superior to UNet3+ by 17 and 10% for Dice and BCE loss. The models were further compressed using quantization showing a percentage size reduction of 66.76, 36.64, and 46.23%, respectively, for UNet3+, VGG-UNet3+, and ResNet-UNet3+. Its stability and reliability were proved by statistical tests such as the Mann–Whitney, Paired t-Test, Wilcoxon test, and Friedman test all of which had a p < 0.001.ConclusionFull-scale skip connections of UNet3+ with VGG and ResNet in HDL framework proved the hypothesis showing powerful results improving the detection accuracy of COVID-19

Deep learning approach for cardiovascular disease risk stratification and survival analysis on a Canadian cohort

The quantification of carotid plaque has been routinely used to predict cardiovascular risk in cardiovascular disease (CVD) and coronary artery disease (CAD). To determine how well carotid plaque features predict the likelihood of CAD and cardiovascular (CV) events using deep learning (DL) and compare against the machine learning (ML) paradigm. The participants in this study consisted of 459 individuals who had undergone coronary angiography, contrast-enhanced ultrasonography, and focused carotid B-mode ultrasound. Each patient was tracked for thirty days. The measurements on these patients consisted of maximum plaque height (MPH), total plaque area (TPA), carotid intima-media thickness (cIMT), and intraplaque neovascularization (IPN). CAD risk and CV event stratification were performed by applying eight types of DL-based models. Univariate and multivariate analysis was also conducted to predict the most significant risk predictors. The DL's model effectiveness was evaluated by the area-under-the-curve measurement while the CV event prediction was evaluated using the Cox proportional hazard model (CPHM) and compared against the DL-based concordance index (c-index). IPN showed a substantial ability to predict CV events (p < 0.0001). The best DL system improved by 21% (0.929 vs. 0.762) over the best ML system. DL-based CV event prediction showed a similar to 17% increase in DL-based c-index compared to the CPHM (0.86 vs. 0.73). CAD and CV incidents were linked to IPN and carotid imaging characteristics. For survival analysis and CAD prediction, the DL-based system performs superior to ML-based models

Mortality and pulmonary complications in patients undergoing surgery with perioperative SARS-CoV-2 infection: an international cohort study

Background: The impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on postoperative recovery needs to be understood to inform clinical decision making during and after the COVID-19 pandemic. This study reports 30-day mortality and pulmonary complication rates in patients with perioperative SARS-CoV-2 infection. Methods: This international, multicentre, cohort study at 235 hospitals in 24 countries included all patients undergoing surgery who had SARS-CoV-2 infection confirmed within 7 days before or 30 days after surgery. The primary outcome measure was 30-day postoperative mortality and was assessed in all enrolled patients. The main secondary outcome measure was pulmonary complications, defined as pneumonia, acute respiratory distress syndrome, or unexpected postoperative ventilation. Findings: This analysis includes 1128 patients who had surgery between Jan 1 and March 31, 2020, of whom 835 (74·0%) had emergency surgery and 280 (24·8%) had elective surgery. SARS-CoV-2 infection was confirmed preoperatively in 294 (26·1%) patients. 30-day mortality was 23·8% (268 of 1128). Pulmonary complications occurred in 577 (51·2%) of 1128 patients; 30-day mortality in these patients was 38·0% (219 of 577), accounting for 81·7% (219 of 268) of all deaths. In adjusted analyses, 30-day mortality was associated with male sex (odds ratio 1·75 [95% CI 1·28–2·40], p\textless0·0001), age 70 years or older versus younger than 70 years (2·30 [1·65–3·22], p\textless0·0001), American Society of Anesthesiologists grades 3–5 versus grades 1–2 (2·35 [1·57–3·53], p\textless0·0001), malignant versus benign or obstetric diagnosis (1·55 [1·01–2·39], p=0·046), emergency versus elective surgery (1·67 [1·06–2·63], p=0·026), and major versus minor surgery (1·52 [1·01–2·31], p=0·047). Interpretation: Postoperative pulmonary complications occur in half of patients with perioperative SARS-CoV-2 infection and are associated with high mortality. Thresholds for surgery during the COVID-19 pandemic should be higher than during normal practice, particularly in men aged 70 years and older. Consideration should be given for postponing non-urgent procedures and promoting non-operative treatment to delay or avoid the need for surgery. Funding: National Institute for Health Research (NIHR), Association of Coloproctology of Great Britain and Ireland, Bowel and Cancer Research, Bowel Disease Research Foundation, Association of Upper Gastrointestinal Surgeons, British Association of Surgical Oncology, British Gynaecological Cancer Society, European Society of Coloproctology, NIHR Academy, Sarcoma UK, Vascular Society for Great Britain and Ireland, and Yorkshire Cancer Research

Further delineation of Malan syndrome

Malan syndrome is an overgrowth disorder described in a limited number of individuals. We aim to delineate the entity by studying a large group of affected individuals. We gathered data on 45 affected individuals with a molecularly confirmed diagnosis through an international collaboration and compared data to the 35 previously reported individuals. Results indicate that height is > 2 SDS in infancy and childhood but in only half of affected adults. Cardinal facial characteristics include long, triangular face, macrocephaly, prominent forehead, everted lower lip, and prominent chin. Intellectual disability is universally present, behaviorally anxiety is characteristic. Malan syndrome is caused by deletions or point mutations of NFIX clustered mostly in exon 2. There is no genotype-phenotype correlation except for an increased risk for epilepsy with 19p13.2 microdeletions. Variants arose de novo, except in one family in which mother was mosaic. Variants causing Malan and Marshall-Smith syndrome can be discerned by differences in the site of stop codon formation. We conclude that Malan syndrome has a well recognizable phenotype that usually can be discerned easily from Marshall–Smith syndrome but rarely there is some overlap. Differentiation from Sotos and Weaver syndrome can be made by clinical evaluation only

Nations within a nation: variations in epidemiological transition across the states of India, 1990–2016 in the Global Burden of Disease Study

18% of the world's population lives in India, and many states of India have populations similar to those of large countries. Action to effectively improve population health in India requires availability of reliable and comprehensive state-level estimates of disease burden and risk factors over time. Such comprehensive estimates have not been available so far for all major diseases and risk factors. Thus, we aimed to estimate the disease burden and risk factors in every state of India as part of the Global Burden of Disease (GBD) Study 2016