Status of Health Management Education in India: Past, Present, and Future

This article provides a perspective on the evolution of health management education in India, its current state and the way forward. Health management originated in India in response to the administrative needs of the healthcare system, which is now moving toward institutional care, away from its earlier form of home healthcare. As this field evolved over time, new roles emerged for health management professionals. Several articles have been published in the past describing the state and growth in the field of health management education. This article emphasizes the need to rationalize the sector and shape its future to suit the needs of over a billion people, who use the services of multiple organizations, directly or indirectly in a highly dynamic healthcare environment. We have identified the various challenges that affect the sector today; filling vacant positions, matching jobs with training, and changes in curricula required to achieve good matches. Solutions to address these challenges have also been considered, which in our view could be a way forward in this sector

Flow-resolution Enhancement in Electrophoretic NMR Using De-noising and Linear Prediction

Detection of electrophoretic motion of ionic species using multi-dimensional Electrophoretic NMR (nD-ENMR) has demonstrated the potential to distinguish signals from two molecules in a solution mixture without their physical separation. Therefore, this technique may be applied for simultaneous structure determination of proteins and protein conformations, even during their biochemical interactions. Indeed, this has been achieved by introducing an additional dimension of electrophoretic mobility to the conventional multi-dimensional NMR by applying an external DC electric field. Consequently, the protein spectra are differently modulated by their electrophoretic mobilities in the electrophoretic flow dimension. Unfortunately, spectral resolution in the flow dimension has been limited by severe signal truncations due to the limited DC electric field available before onset of heating-induced convection. Linear prediction, which have been widely used for high-resolution spectral estimation from finite Fourier samples, have already been proposed to extend the truncated ENMR flow oscillation curves. However, we found that the spectral quality of linear prediction deteriorates as the spectral S/N decreases. To alleviate this problem, we have denoised the ENMR data using low pass filters prior to linear prediction. This technique has lead to improved resolution in the electrophoretic flow dimension. The approach was applied to analyze a 2D ENMR data matrix obtained from a mixture solution of two proteins ubiquitin and bovine serum albumin (BSA) in D2O

Evaluation of cancer outcome assessment using MRI: A review of deep-learning methods

Accurate evaluation of tumor response to treatment is critical to allow personalized treatment regimens according to the predicted response and to support clinical trials investigating new therapeutic agents by providing them with an accurate response indicator. Recent advances in medical imaging, computer hardware, and machine-learning algorithms have resulted in the increased use of these tools in the field of medicine as a whole and specifically in cancer imaging for detection and characterization of malignant lesions, prognosis, and assessment of treatment response. Among the currently available imaging techniques, magnetic resonance imaging (MRI) plays an important role in the evaluation of treatment assessment of many cancers, given its superior soft-tissue contrast and its ability to allow multiplanar imaging and functional evaluation. In recent years, deep learning (DL) has become an active area of research, paving the way for computer-assisted clinical and radiological decision support. DL can uncover associations between imaging features that cannot be visually identified by the naked eye and pertinent clinical outcomes. The aim of this review is to highlight the use of DL in the evaluation of tumor response assessed on MRI. In this review, we will first provide an overview of common DL architectures used in medical imaging research in general. Then, we will review the studies to date that have applied DL to magnetic resonance imaging for the task of treatment response assessment. Finally, we will discuss the challenges and opportunities of using DL within the clinical workflow

Magnetic resonance spectroscopic imaging in gliomas: clinical diagnosis and radiotherapy planning

The reprogramming of cellular metabolism is a hallmark of cancer diagnosis and prognosis. Proton magnetic resonance spectroscopic imaging (MRSI) is a non-invasive diagnostic technique for investigating brain metabolism to establish cancer diagnosis and IDH gene mutation diagnosis as well as facilitate pre-operative planning and treatment response monitoring. By allowing tissue metabolism to be quantified, MRSI provides added value to conventional MRI. MRSI can generate metabolite maps from a single volume or multiple volume elements within the whole brain. Metabolites such as NAA, Cho and Cr, as well as their ratios Cho:NAA ratio and Cho:Cr ratio, have been used to provide tumor diagnosis and aid in radiation therapy planning as well as treatment assessment. In addition to these common metabolites, 2-hydroxygluterate (2HG) has also been quantified using MRSI following the recent discovery of IDH mutations in gliomas. This has opened up targeted drug development to inhibit the mutant IDH pathway. This review provides guidance on MRSI in brain gliomas, including its acquisition, analysis methods, and evolving clinical applications

The global burden of adolescent and young adult cancer in 2019 : a systematic analysis for the Global Burden of Disease Study 2019

Background In estimating the global burden of cancer, adolescents and young adults with cancer are often overlooked, despite being a distinct subgroup with unique epidemiology, clinical care needs, and societal impact. Comprehensive estimates of the global cancer burden in adolescents and young adults (aged 15-39 years) are lacking. To address this gap, we analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, with a focus on the outcome of disability-adjusted life-years (DALYs), to inform global cancer control measures in adolescents and young adults. Methods Using the GBD 2019 methodology, international mortality data were collected from vital registration systems, verbal autopsies, and population-based cancer registry inputs modelled with mortality-to-incidence ratios (MIRs). Incidence was computed with mortality estimates and corresponding MIRs. Prevalence estimates were calculated using modelled survival and multiplied by disability weights to obtain years lived with disability (YLDs). Years of life lost (YLLs) were calculated as age-specific cancer deaths multiplied by the standard life expectancy at the age of death. The main outcome was DALYs (the sum of YLLs and YLDs). Estimates were presented globally and by Socio-demographic Index (SDI) quintiles (countries ranked and divided into five equal SDI groups), and all estimates were presented with corresponding 95% uncertainty intervals (UIs). For this analysis, we used the age range of 15-39 years to define adolescents and young adults. Findings There were 1.19 million (95% UI 1.11-1.28) incident cancer cases and 396 000 (370 000-425 000) deaths due to cancer among people aged 15-39 years worldwide in 2019. The highest age-standardised incidence rates occurred in high SDI (59.6 [54.5-65.7] per 100 000 person-years) and high-middle SDI countries (53.2 [48.8-57.9] per 100 000 person-years), while the highest age-standardised mortality rates were in low-middle SDI (14.2 [12.9-15.6] per 100 000 person-years) and middle SDI (13.6 [12.6-14.8] per 100 000 person-years) countries. In 2019, adolescent and young adult cancers contributed 23.5 million (21.9-25.2) DALYs to the global burden of disease, of which 2.7% (1.9-3.6) came from YLDs and 97.3% (96.4-98.1) from YLLs. Cancer was the fourth leading cause of death and tenth leading cause of DALYs in adolescents and young adults globally. Interpretation Adolescent and young adult cancers contributed substantially to the overall adolescent and young adult disease burden globally in 2019. These results provide new insights into the distribution and magnitude of the adolescent and young adult cancer burden around the world. With notable differences observed across SDI settings, these estimates can inform global and country-level cancer control efforts. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd.Peer reviewe

Fat Composition Measured by Proton Spectroscopy: A Breast Cancer Tumor Marker?

Altered metabolism including lipids is an emerging hallmark of breast cancer. The purpose of this study was to investigate if breast cancers exhibit different magnetic resonance spectroscopy (MRS)-based lipid composition than normal fibroglandular tissue (FGT). MRS spectra, using the stimulated echo acquisition mode sequence, were collected with a 3T scanner from patients with suspicious lesions and contralateral normal tissue. Fat peaks at 1.3 + 1.6 ppm (L13 + L16), 2.1 + 2.3 ppm (L21 + L23), 2.8 ppm (L28), 4.1 + 4.3 ppm (L41 + L43), and 5.2 + 5.3 ppm (L52 + L53) were quantified using LCModel software. The saturation index (SI), number of double bods (NBD), mono and polyunsaturated fatty acids (MUFA and PUFA), and mean chain length (MCL) were also computed. Results showed that mean concentrations of all lipid metabolites and PUFA were significantly lower in tumors compared with that of normal FGT (p ≤ 0.002 and 0.04, respectively). The measure best separating normal and tumor tissues after adjusting with multivariable analysis was L21 + L23, which yielded an area under the curve of 0.87 (95% CI: 0.75-0.98). Similar results were obtained between HER2 positive versus HER2 negative tumors. Hence, MRS-based lipid measurements may serve as independent variables in a multivariate approach to increase the specificity of breast cancer characterization

Unusual presentation of keratocystic odontogenic tumor: Two case reports

Keratocystic odontogenic tumor (KOT) is a common odontogenic cyst with aggressive behavior with a high recurrence rate. Features that predict recurrence of KOT are thin friable epithelium which is difficult to enucleate and presence of satellite cysts in the fibrous wall. Most of the lesions grow in an anteroposterior direction without causing any bony expansion. Here, we report two cases of KOT with different clinical presentation

A typical radiographic presentation of osteosarcoma arising from skull and scapula: A rare case report

Osteosarcoma is an aggressive malignant tumor of the bone. It can occur in any bone, but long bones are affected more such as femur (42%), tibia (19%), and humerus (10%), compared to short bones such as skull, head, and neck region (<10%). The typical radiographic appearance of sunray pattern and Codman′s triangle is highly suggestive of osteosarcoma. Early diagnosis and surgical treatment is the key to high survival rate. Here, we present a case with typical radiographic appearance of osteosarcoma arising from skull and scapula in a 25-year-old male patient

Mucocutaneous manifestations of Cowden's syndrome

Cowden's syndrome is an autosomal dominant genodermatosis with variable orofacial and systemic manifestations. Here we present one such classical case of Cowden's syndrome in a 45-year-old female patient with features such as multiple cutaneous papillomatosis, oral fibromas, and fibromas involving multiple organs such as gastrointestinal tract (multiple polyps), thyroid disorders, and breast cancer