Novel Automatic Segmentation Approach for Early Brain Tumour Detection: Comparative Evaluation with AI Approaches | Chapter 5 | Medical Science: Updates and Prospects Vol. 1

 

Background: Automatic object detection in medical images is a crucial step in the diagnostic process. The problem of detecting brain tumours at an early stage is well advanced with deep learning algorithms (DLA) such as convolutional neural networks (CNN). The issue lies in the fact that these algorithms necessitate a training phase involving a large database of several hundred images, which can be time-consuming and require complex computational infrastructure.

 

Objective: This study aimed to comprehensively evaluate a proposed method, which relies on an active contour algorithm, for identifying and distinguishing brain tumours in magnetic resonance images.

 

Methods: The proposed algorithm was tested using brain images from the BRATS Challenges 2021, specifically focusing on glioma tumours. The proposed segmentation method is made up of an active contour algorithm, an anisotropic diffusion filter for pre-processing, active contour segmentation (Chan-Vese), and morphological operations for segmentation refinement.

 

Results: Its performance was evaluated using various metrics, such as accuracy, precision, sensitivity, specificity, Jaccard index, Dice index, and Hausdorff distance. The proposed method exhibited higher performance measures than most classical image segmentation methods and was comparable to the deep learning methods. These results indicate its ability to detect brain tumours accurately and rapidly.

 

Conclusion: The results section provided both numerical and visual insights into the similarity between segmented and ground truth tumour areas. The findings of this study highlighted the potential of computer-based methods in improving brain tumour identification using magnetic resonance imaging. Future work must validate the efficacy of these segmentation approaches across different brain tumour categories and improve computing efficiency to integrate the technology into potential clinical processes.

 

 

Author(s) Details

Mohammed Almijalli
Department of Biomedical Technology, College of Applied Medical Sciences, King Saud University, Riyadh 11433, Saudi Arabia.

 

Faten A. Almusayib
Department of Biomedical Technology, College of Applied Medical Sciences, King Saud University, Riyadh 11433, Saudi Arabia.

 

Ghala F. Albugami
Department of Biomedical Technology, College of Applied Medical Sciences, King Saud University, Riyadh 11433, Saudi Arabia.

 

Ziyad Aloqalaa
Department of Biomedical Technology, College of Applied Medical Sciences, King Saud University, Riyadh 11433, Saudi Arabia.

 

Omar Altwijri
Department of Biomedical Technology, College of Applied Medical Sciences, King Saud University, Riyadh 11433, Saudi Arabia.

 

Ali S. Saad
Department of Biomedical Technology, College of Applied Medical Sciences, King Saud University, Riyadh 11433, Saudi Arabia.

 

 

Please see the book here :- https://doi.org/10.9734/bpi/msup/v1/6551

Myocardial Fibrosis: Unveiling the Hidden Scars of the Heart| Chapter 2 | Medicine and Medical Research: New Perspectives Vol. 6

Myocardial fibrosis is regarded as a significant pathological process in the development of heart illness, as well as a potential target for future therapies. Despite this knowledge, fibrosis is not routinely assessed in clinical practice. This is primarily due to the difficulties in obtaining an accurate non-invasive assessment of fibrosis. Moreover, there is a clear discrepancy between the clinical understanding of myocardial fibrosis, where fibrosis is predominately studied with comparatively low-resolution medical imaging technologies like Echocardiography, Computed Tomography (CT), or Magnetic Resonance Imaging (MRI), and the detailed visualisation possible in basic science laboratories using molecularly specific fluorescence microscopes at the microscopic and nanoscopic scales.

 

Current medical imaging technologies for assessing fibrosis, including echocardiography and MRI, provide valuable information but are limited by their resolution and specificity. While these modalities are essential in the clinical setting, they fall short of capturing the intricate details of fibrotic changes at the cellular and molecular levels. This gap highlights the need for greater microscopic and nanoscopic analysis of human tissue, which can be addressed through the increased utilisation of human tissue available from endomyocardial biopsies and cardiac surgeries.

 

The relatively new field of molecular imaging offers a promising solution to this challenge. Molecular imaging techniques aim to translate research findings into clinical practice by non-invasively monitoring the molecular signature of fibrosis in patients. These advanced imaging methods have the potential to provide high-resolution insights into the fibrotic process, enabling more accurate diagnosis, better monitoring of disease progression, and the evaluation of therapeutic interventions.

 

As the understanding of myocardial fibrosis deepens, it becomes clear that bridging the gap between clinical practice and basic research is essential. By integrating advanced imaging technologies and leveraging human tissue samples, the ability to diagnose and treat myocardial fibrosis can be enhanced more effectively. This comprehensive approach holds promise for improving patient outcomes and advancing the field of cardiology.

Author (s) Details

Summer Hassan
Department of Physiology, University of Auckland, Auckland, New Zealand and Auckland City Hospital, Auckland District Health Board, Auckland, New Zealand.

 

Carolyn J Barrett
Department of Physiology, University of Auckland, Auckland, New Zealand.

 

 

David J Crossman
Department of Physiology, University of Auckland, Auckland, New Zealand.

Please see the book here:- https://doi.org/10.9734/bpi/mmrnp/v6/1930

 

Insidious Recurrent Biatrial Myxomas in Carney Complex with a Paucisymptomatic Spinal Melanotic Schwannoma: Advocacy for a Rigorous Multidisciplinary Follow-up to Prevent Dire Complications | Chapter 4 | Medical Science: Trends and Innovations Vol. 12

Carney complex (CNC) is a rare autosomal syndrome resulting from either a dominant inheritance or a sporadic occurrence as a de novo genetic defect. CNC is characterized by a multiple neoplasia syndrome featuring myxomas of the heart, breast nipples, bone, skin, and mucosae and endocrine and nonendocrine, cutaneous, and neural tumors, as well as a variety of abnormal skin pigmentation and a predisposition to cancers such as thyroid, ovaries, pancreas, and liver. A 31-year-old female patient with a previous history of Carney complex and surgical resection for cardiac myxoma and bilateral adrenalectomy at 18 years old and 10 and 11 years old, respectively, was referred to our department with a diagnosis of recurrent Biatrial myxomas incidentally discovered on echography. A magnetic resonance imaging (MRI) confirmed the diagnosis of a tumor protruding into the left ventricle, and the patient underwent a surgical resection of a large left atrial mass and a small right-sided atrial tumor. The atrial mass was incidentally discovered by echography. Diagnosis of bilateral atrial myxomas was confirmed by histologic studies. Postoperative outcome was uneventful, and the patient was discharged on the 7th postoperative day. A few months later, she reported trivial clinical symptoms, suspecting a cervical radiculopathy. MRI confirmed the presence of a compressive cervical spinal cord tumoral mass at the C2-3 level, leading to a surgical excision of the tumor. Histology showed a spinal melanotic schwannoma. At 48-month follow-up, the patient is in good condition and regular echographic follow-up showed a 60% LVEF with neither recurrence of cardiac myxomas nor valve disease. A recent cerebral MRI revealed a normal pituitary gland without any tumoral patterns. This case highlights the risk of unexpected ubiquitary tumor locations and the importance of a rigorous transversal multidisciplinary follow-up to prevent severe complications in patients with Carney complex.

 

Author (s) Details

Daniel Grandmougin
Department of Cardiac Surgery and Heart Transplantation, ILCV Louis Mathieu, CHRU Nancy, Université de Lorraine, France.

 

Tristan Ehrlich
Department of Cardiac Surgery and Heart Transplantation, ILCV Louis Mathieu, CHRU Nancy, Université de Lorraine, France.

 

Teresa Moussu
Cardiology Practice, Hagondange, France.

 

Maxime Hubert
Department of Cardiac Surgery and Heart Transplantation, ILCV Louis Mathieu, CHRU Nancy, Université de Lorraine, France.

 

Benjamin Perin
Department of Cardiac Surgery and Heart Transplantation, ILCV Louis Mathieu, CHRU Nancy, Université de Lorraine, France.

 

Maria Christina Delolme
Department of Anesthesiology, ILCV Louis Mathieu, CHRU Nancy, Université de Lorraine, France.

 

Juan-Pablo Maureira
Department of Cardiac Surgery and Heart Transplantation, ILCV Louis Mathieu, CHRU Nancy, Université de Lorraine, France.

 

 

Please see the book here:- https://doi.org/10.9734/bpi/msti/v12/4790

Role of Magnetic Resonance Imaging (MRI) in Diagnosing and Classifying Mullerian Duct Anomalies: A Case Series | Chapter 7 | Medical Science: Trends and Innovations Vol. 1

Background: The pair of mullerian ducts in females is responsible for the development of the female reproductive system, namely, fallopian tubes, uterus, cervix, and upper part of the vagina. Mullerian duct anomalies (MDAs) arise from the aberrant development of the uterus, cervix, and vagina, impacting the potential for successful conception and full-term pregnancy. This category encompasses a diverse range of developmental defects, leading to a spectrum of clinical presentations such as amenorrhea, infertility, recurrent miscarriages, intrauterine growth retardation, malposition of the fetus, preterm labor, and retained placenta.

Case(s): In this study, 17 cases of MDA are presented with a wide array of clinical manifestations. The varied symptoms included amenorrhea, infertility, repeated miscarriages, intrauterine growth retardation, malposition of the fetus, preterm labor, and retained placenta. Accurate categorization of these cases is crucial for determining the appropriate surgical intervention. While ultrasonography aids in the initial diagnosis of MDA, our focus on accurate classification necessitates the use of magnetic resonance imaging (MRI).

Conclusion: The findings underscore the significance of MRI in precisely categorizing MDA, and facilitating effective management strategies. The 17 cases presented demonstrate the diverse spectrum of MDA manifestations, emphasizing the need for tailored surgical interventions for successful conception and optimal pregnancy outcomes. The use of MRI proves instrumental in guiding clinical decisions, offering a comprehensive understanding of MDA, and informing targeted interventions to enhance reproductive success. Female infertility can be attributed to MDA, and in many cases of MDA, appropriate surgery can lead to successful conception. Furthermore, in some cases, surgery cannot lead to conception. Thus, correct classification of individual cases with MRI is essential for not only successful conception through appropriate surgery but also for avoidance of unnecessary surgical intervention.

 

Author (s) Details

Bhavya Kataria
Department of Radiodiagnosis, Atal Bihari Vajpayee Institute of Medical Sciences, Dr. Ram Manohar Lohia Hospital, New Delhi, India.

 

Shibani Mehra
Department of Radiodiagnosis, Atal Bihari Vajpayee Institute of Medical Sciences, Dr. Ram Manohar Lohia Hospital, New Delhi, India.

 

 

Please see the book here:- https://doi.org/10.9734/bpi/msti/v1/4000

Leveraging Artificial Intelligence for Brain Tumor Classification | Chapter 3 | Science and Technology: Developments and Applications Vol. 5

Brain cancer, characterized by the uncontrolled growth of abnormal cells in the brain, is a severe neurological disorder that can be either primary or metastatic. Early detection and accurate classification of brain tumors are crucial for effective management and improved patient outcomes. Brain tumors are classified based on various factors such as their nature, cell origin, grade, and progression stage. Traditional methods of detection, segmentation, and classification are time-consuming, require extensive expertise, and are prone to errors. Artificial Intelligence (AI), including its subtypes Machine Learning (ML) and Deep Learning (DL), holds promise for improving accuracy and expediting detection. AI-based technologies can be categorized into binary classification (e.g., determining whether a tumor is malignant or benign) and multimodal classification (e.g., categorizing tumors into various types). Most AI applications in brain tumor classification focus on radiological images, particularly Magnetic Resonance Imaging (MRI).

AI-based technologies must achieve high accuracy to be effectively integrated into real-life clinical practice. This chapter summarizes the current advances in AI techniques for brain tumor classification, highlighting their potential and ongoing challenges.

 

Author (s) Details

 

Adham Al-Rahbi
Sultan Qaboos University, College of Medicine and Health Sciences, Muscat, P.O. Box-35, Postal Code 123, Sultanate of Oman.

Tariq Al-Saadi
Department of Neurosurgery, Khoula Hospital, Muscat, P.O. Box-35, Postal Code 123, Sultanate of Oman and Department of Neurosurgery, Cedars-Sinai Medical Centre, 8700 Beverly Blvd, Los Angeles, CA 90048, USA.

 

Please see the book here:- https://doi.org/10.9734/bpi/stda/v5/1964

A Radiologist’s Analysis in Comparing the Diagnostic Efficacy of CT and MRI for Staging of Paediatric Renal Tumours— A Report from a Tertiary Care Hospital | Chapter 12 | Medical Research and Its Applications Vol. 3

 

Background and Objective: Approximately 7% of all paediatric malignant tumors are renal tumors [1]. Most of these are Wilms tumors or nephroblastomas. Less than 10% of primary renal neoplasms and less than 1% of all paediatric cancers are non-Wilms tumors, which include renal cell carcinoma (RCC), clear cell sarcoma, malignant rhabdoid tumour, malignant cystic nephroma, mesoblastic nephroma, and renal medullary carcinoma [2]. This is a very diverse set of malignancies, with each having a unique prognosis, treatment regimen, and relationship to genetic predispositions. In order to treat these uncommon tumors, diagnosis and staging is crucial. Even while every tumour exhibits unique radiologic characteristics, there is a significant amount of overlap. As a result, imaging like computed tomography and magnetic resonance imaging may be crucial for making the right diagnosis and prescribing the right course of action. However, the two modalities have different advantages and disadvantages in the staging of renal tumours. The objective of the study is to compare the diagnostic performance of CT and MRI for the local staging of paediatric renal tumours.

Materials and Methods: The study population was derived from our hospital Medical College Kolkata and Hospital. Baseline abdominal imaging was performed with both CT and MRI.A retrospective review was done with 50 renal tumour cases selected and planned for nephrectomy over a study period of one year from October 2022 to November 2023. Each case was evaluated for capsular penetration, lymph node metastasis, tumour thrombus, preoperative tumour rupture, and synchronous contralateral lesions. The surgical and pathological findings were the reference gold standard.

Results: The sensitivity of CT and MRI for detecting capsular penetration was 70% and 60%, respectively (P=0.73), while specificity was 84.3% and 84% (P=1.0). The sensitivity of CT and MRI for detecting lymph node metastasis was 80% and 53% (P=0.22), and specificity was 88% and 92% (P=1.0). Synchronous contralateral lesions were identified by CT in 5/12 cases and by MRI in 8/12 cases.

Conclusion: CT and MRI have similar diagnostic performance for detection of lymph node metastasis and capsular penetration. MRI was more accurate in detecting contralateral synchronous lesions. Hence either modality can be used for initial loco–regional staging of paediatric renal tumours.

 

Author(s)details:-

 

Debarpita Datta
Department of Radiodiagnosis, Medical College Kolkata and Hospital, Kolkata, India.

 

Debashis Dakshit
Department of Radiodiagnosis, Medical College Kolkata and Hospital, Kolkata, India.

 

Arup Maity
Department of Radiodiagnosis, Medical College Kolkata and Hospital, Kolkata, India.

 

Please See the book here :-  https://doi.org/10.9734/bpi/mria/v3/449

Knee Osteoarthritis Detection Using a Machine Learning Method from Magnetic Resonance Imaging: A 3-D Independent Component Analysis-Based Approach | Chapter 9 | Theory and Applications of Engineering Research Vol. 2

In this chapter, a machine learning-based knee Osteoarthritis (OA) detection system from magnetic resonance (MR) images is proposed. This system is capable of detecting the presence of OA considering two classification categories: ‘non-OA’ and ‘OA’. OA is one of the most prevalent condition resulting to disability particularly in elderly population. OA is the most common articular disease of the developed world and a leading cause of chronic disability, mainly as a consequence of the knee OA and/or hip OA. Nowadays, medical images such as MR images are widely used for the OA diagnosis. For this, a medical specialist analyzes medical images by measuring the changes and in particular for knee OA, the changes in the compartment of the tibio-femoral cartilage. The proposed method consists mainly of both a data processing module and binary classification module, which process the 3-D data from MR images. In this study, we present a novel knee OA diagnostic approach that can identify the condition using magnetic resonance MR images using the Support Vector Machine (SVM) algorithm. Our suggested method is predicated on using 3-D data from MR scans of an actual cohort and the Independent Component Analysis (ICA) technique. The experimental results showed that our ICA-SVM machine learning model achieved 86% of testing accuracy with both 72% of specificity and 100% of sensitivity, once trained with a small MR image dataset. Furthermore, a benchmark evaluation was performed. The results suggest that using a larger and more diverse dataset could ensure the robustness of the proposed method. In future works, we will study the complementary use of ICA components from MR images and a convolutional neural network (CNN) to try to achieve better predictive rates in supervised learning using a larger dataset.

Author(s) Details:

Marco Oyarzo Huichaqueo,
School of Engineering, Rovira i Virgili University, 43007, Tarragona, Spain.

Please see the link here: https://stm.bookpi.org/TAER-V2/article/view/13114

Use of 7-Tesla Magnetic Resonance Imaging: The Future Perspectives | Chapter 4 | Advances and Challenges in Science and Technology Vol. 5

 Neuroimaging utilizing the 7-Tesla (7T) magnetic reverberation (MR) system is rapidly win popularity later being approved for dispassionate use in the European Union and the USA. This trend is the same for working MR imaging (MRI). The basic advantages of 7T over lower magnetic fields are allure higher signal-to-blast and contrast-to-noise percentages, which provide extreme-resolution procurements and better contrast, making it easier to discover lesions and structural changes in brain disorders. 7-Tesla (T) scanning in of documents is the latest top in the rapidly changeful development of magnetic reverberation imaging (MRI), a method that makes three-dimensional figures of internal organs. The 7-Tesla's extreme-strong bait about 140,000 times as strong as the Earth's magnetic field of currents— yields spectacular countenances of the human brain at a judgment of about 1/5 of a millimetre. Another advantage is the capability to measure a large group of Neuro Chemical by virtue of the raised spectral resolution.

Author(s) Details:

R. K. Tripuraneni,
Konaseema Institute of Medical Sciences, Amalapuram, East Godavari District, Andhra Pradesh, India.

Please see the link here: https://stm.bookpi.org/ACST-V5/article/view/12243

Assessment of Iron Burden and Siderosis-related Complications in Patients with Transfusion-dependent Thalassaemia | Chapter 12 | Research Highlights in Disease and Health Research Vol. 8

 Objective: Herein, we aim to determine the iron burden and siderosis-related complications with patients accompanying transfusion-dependent thalassaemia (TDT). We still aim to explore the advantage of cardiac T2* magnetic resonance (MR) to envision potential cardiac complications between patients with TDT.Methods: We acted a cross-sectional study reviewing healing records of 75 TDT patients in Hospital Tuanku Fauziah, Perlis, Malaysia. A total of 151 reports from drawing resonance (MR) T2* performed from 1 January 2015 till 31 December 2021 were reproduced together with appropriate biochemical markers and echocardiogram results that were performed inside the same twelve-month period.Results: We found a moderate correlation 'tween serum ferritin and myocardial (r=0.356, p<0.001), and liver iron loading (r=0.572, p<0.001). There was a moderate equating between antitoxin ferritin and serum ALT (r=0.462, p<0.001), AST (r=0.465, p<0.001), magnesium (p=-0.276, p=0.002) and phosphate (r=-0.221, p=0.014). All patients had sane ejection part, 43 (28.5%) had raised pulmonary artery pressure and nobody had evidence of diastolic dysfunction. There was no predictive changing to predict cardiac complications with our pool of TDT patients.Conclusion: The significant equating between antitoxin ferritin and myocardial/liver iron loading should prompt direct chelation strategy for fear that clinical complications between patients accompanying TDT.

Author(s) Details:

Karniza Khalid,
Specialised Diagnostic Centre, Institute for Medical Research, National Institutes of Health, Kuala Lumpur, Ministry of Health Malaysia, Malaysia.

Nordiyana Azmi,
Department of Paediatrics, Hospital Tuanku Fauziah, Perlis, Ministry of Health Malaysia, Malaysia.

Irma Liyana Mushaddik,
Clinical Research Centre, Hospital Tuanku Fauziah, Perlis, Ministry of Health Malaysia, Malaysia.

Ahmad Afnan Mohamad Puad,
Department of Internal Medicine, Hospital Tuanku Fauziah, Perlis, Ministry of Health Malaysia, Malaysia

Siti Akma Ishak,
Department of Paediatrics, Hospital Tuanku Fauziah, Perlis, Ministry of Health Malaysia, Malaysia.

Please see the link here: https://stm.bookpi.org/RHDHR-V8/article/view/10853

Structural Changes in Brain MRI Associated with Psychogenic Functional Non-epileptic Seizures | Chapter 8 | Research Developments in Medicine and Medical Science Vol. 1

 Psychogenic non-epileptic seizures (PNES) are a all-encompassing health issue. They include altered awareness, drooping or stiff collapse, and shaking limb motions. PNES are episodic working neurological syndromes that seem like epileptic seizures but are not. PNES is one of the three most governing transitory deficit of consciousness diagnoses. Neurologists see PNES usually as functional syndromes. PNES is usually misdiagnosed, resulting in the delay of appropriate subjective treatment. The study proposed to assess the structural changes in the intelligence in patients accompanying PNES.This retrospective examining cross-sectional study was conducted at the Department of Medicine and Neurology, Ayub Teaching hospital, Abbottabad, from October, 2020 to September, 2021. The healing records of 42 patients accompanying confirmed PNES were gathered and inspected retrospectively.The average age of the patients (predictable difference) was 34 (±9) years, and the average age at onset was 31.6 (±5.8) age. Three patients (7%) had a certain epilepsy family history. 24 (47.6%) cases with intellect MRI scans reported abnormal verdicts, while 22 (52.4%) had normal image studies. The majority of sufferers with abnormal MRIs had silvery matter nonspecific changes (50%), Mesial material sclerosis (15%), and cysts (15%). Age at the beginning of PNES (p = 0.04), duration of PNES (p=0.01), contributing epilepsy (p = 0.05), Generalized engine seizures (p= 0.03), and focal motor seizures (p= 0.02) were powerfully linked accompanying aberrant brain MRI verdicts. Patients with PNES have a bigger-than-average prevalence of anatomical intelligence abnormalities. These judgments support the growing evidence that PNES is a brain disorder alternatively a medical puzzle.

Author(s) Details:

Imran Khawaja,
Department of Internal Medicine, Ayub Teaching Hospital, Abbottabad, Pakistan.

Please see the link here: https://stm.bookpi.org/RDMMS-V1/article/view/9625

Advances in Neuroimaging Research of Electroconvulsive Therapy in Depression| Chapter 6 | Current Innovations in Medicine and Medical Science Vol. 8

 The aim of electroconvulsive therapy (ECT) is to responsibility disease symptoms avoid a small amount of energetic current through the patient's head, inducing convulsions throughout the corpse.  Although its treatment machine is yet unknown, electroshock therapy can significantly responsibility the clinical symptoms of sufferers with serious despair. This review summarizes the recent progress in neuroimaging research on ECT for bigger depression. Due to the swift advancement of neuroimaging technology, it is immediately necessary to investigate the neurobiological machines underlying major cavity from the perspectives of intellect structure, function, and metabolism. Research has proved that electroconvulsive therapy can, to a certain extent, correct patients' brain function, absorption, and even brain building.  Currently, an increasing number of neuroimaging studies adopt miscellaneous neuroimaging techniques including working magnetic resonance image (fMRI), positron emission tomography (PET), drawing resonance spectroscopy (MRS), structural drawing resonance imaging (sMRI) and spread tensor imaging (DTI) to reveal the affecting animate nerve organs effects of ECT. Based on the neuroimaging studies, this review desires that the neurobiological mechanism of ECT may search out modulate the functional endeavor and connectivity or neural fundamental plasticity in distinguishing brain regions to the rational level, to achieve the therapeutic effect.

Author(s) Details:

Xin-Ke Li,
College of Medical Informatics, Chongqing Medical University, Chongqing-400016, P.R.China.

Hai-Tang Qiu,
Mental Health Center, the First Affiliated Hospital of Chongqing Medical University, Chongqing-400016, P.R. China.

Please see the link here: https://stm.bookpi.org/CIMMS-V8/article/view/8723

Survival Analysis of Tumor using 7 Tesla Magnetic Resonance Imaging (MRI): A Statistical Approach | Chapter 5 | Current Practice in Medical Science Vol. 4

Magnetic resonance imaging (MRI) is a potent imaging technique for determining the cause of a stroke and for brain imaging (MRI7). Another form of MRI is ultrahigh frequency-based MRI, which uses a 7 Tesla magnet and is being developed by SIEMENS for improved human imaging. These MRIs are the subject of this study. This article describes an alternative strategy called "interval monitoring," which aims to identify tumour malignancy changes more quickly. The suggested method's theoretical underpinnings and computer implementation are discussed, and the American Cancer Registry is used as an empirical example to illustrate how it might be used in image-based photo science. This approach is frequently used by cancer registries, which is beneficial because patient survival is the first step of cancer therapy. This is a crucial component of its care. On the other hand, conventional techniques of estimating cumulative survival only reveal changes in prognosis after a significant period of time has elapsed. After filtering and skeletonizing a series of MRI images, the GMPLS algorithm finds cancer there. This study reduces the amount of time and money needed to calculate the cancer equation. The desired matrix is generated statistically, and the matrix inverse provides us with a real-time mathematical equation that is specific to each patient. Further survivor analysis is done if the person is injured or dies. The goal of this study is to create a unique mathematical model of a cancer patient, as well as a live cancer health graph and a survivor function that forecasts death.

Author(s) Details:

Adnan Alam Khan,

DHA Suffa University, Sindh Madressatul Islam University Karachi, Pakistan.

Please see the link here: https://stm.bookpi.org/CPMS-V4/article/view/7360

A Pictorial Review on Acute Pancreatitis: Definitions and Diagnosis | Chapter 6 | Emerging Trends in Disease and Health Research Vol. 8

The goal of the current study is to assess the early pancreatic fluid collections seen on MRI after acute pancreatitis. The pancreas, peripancreatic tissues, and other distant organs are frequently affected by the common inflammatory illness known as acute pancreatitis. According to the revised Atlanta categorization from 2012, acute pancreatitis can be mild, moderately severe, or severe. Significant changes have been made to the classification's nomenclature for acute fluid collection. The study also sought to: via computed tomography or magnetic resonance imaging, present an image-rich overview of several morphologic aspects of early-stage (within 4 weeks following symptom start) local sequelae related to acute pancreatitis; to assist the implications for gastrointestinal surgery, to facilitate communication among treating doctors, to clarify complex imaging concepts for pancreatic fluid collections, and to emphasise standardised reporting nomenclature. On the basis of the related morphologic descriptions, radiologists should be fully conversant with the standardised imaging terminology. It is crucial to direct implications of care plans for patients with acute pancreatitis. It is also necessary for correct documentation and reporting of academic research.

Author(s) Details:

Bo Xiao,
Sichuan Key Laboratory of Medical Imaging, Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, Sichuan Province, China.

Please see the link here: https://stm.bookpi.org/ETDHR-V8/article/view/7232

An Overview of Recent Advances on Pathophysiology, Diagnosis and Treatment of Trigeminal Neuralgia | Chapter 04 | New Horizons in Medicine and Medical Research Vol. 2

 Trigeminal Neuralgia (TN) is the most common type of neuropathic face pain, and it has a significant impact on the quality of life of those who suffer from it. The cause of the classic type has been identified as neurovascular conflict (NVC), however TN can be due to various disorders. There is no NVC or other aetiology of TN in the idiopathic form. However, the specific sequence of events and mechanisms that lead to TN remain unknown, although new research suggesting that an inflammatory environment may play a role. The development of novel magnetic resonance imaging (MRI) techniques such as voxel-based morphometry, diffusion tensor imaging, and three-dimensional time-of-flight magnetic resonance angiography has revealed fresh information on the pathophysiology of TN. Furthermore, the use of these enhanced MRI sequences in conjunction with volume-rendering software and neuronavigation techniques had a considerable impact on the surgical outcome of patients undergoing microvascular decompression. TN management is, in fact, pharmacological from the start; nonetheless, TN might gradually grow insensitive to medications, necessitating multimodal treatment. Despite the multiple techniques available, the outcomes are not entirely satisfactory, and the desire for more effective medications led to the development of new compounds and pharmacological procedures. Furthermore, some patients may develop drug resistance, necessitating a surgical surgery or radiation treatment. However, pain recurrence after one or more surgical procedures is common, and other rescue treatments, such as neuromodulation, may be required to manage the symptoms. These observations demonstrate the lack of a thorough understanding of TN pathophysiology. The purpose of this work was to review recent research on pathogenesis, diagnostics, medicinal and surgical treatments, and to discuss major developments in all of these domains.

Author(S) Details

Nicola Montano
Department of Neuroscience, Neurosurgery Section, Fondazione Policlinico Universitario a Gemelli IRCCS, Università Cattolica del Sacro Cuore, Rome, Italy.

Alessandro Rapisarda
Department of Neuroscience, Neurosurgery Section, Fondazione Policlinico Universitario a Gemelli IRCCS, Università Cattolica del Sacro Cuore, Rome, Italy.

View Book:- https://stm.bookpi.org/NHMMR-V2/article/view/6124

Magnetic Resonance Brain Imaging in Late-Onset Wilson’s Disease: Clinical Features and Review of Literature | Chapter 13 | New Frontiers in Medicine and Medical Research Vol. 4

 Wilson's illness is a hereditary ailment that causes copper buildup in numerous tissues all over the world. Wilson's disease is now divided into early-onset and late-onset Wilson's disease based on the start of symptoms. The “Face of a Giant Panda” sign on magnetic resonance imaging of the brain revealed the distinctive bilateral putamena and midbrain tegmental T2 hyperintensity, which are trustworthy imaging findings of Wilson's illness. This chapter's goal was to go over the clinical and magnetic resonance brain imaging alterations in late-onset Wilson's illness.

Author (S) Details

Noha Abdelfattah Ahmed Madkour
Department of Radiodiagnosis, Kasr Alainy hospital, Cairo University, Cairo, Egypt.

View Book :- https://stm.bookpi.org/NFMMR-V4/article/view/2892

Three Novel Cases of Trilateral Retinoblastoma: An Approach towards Genetic Diagnosis| Chapter 2 | Recent Research Advances in Biology Vol. 10

 The heritable form of retinoblastoma associated with an intracranial tumour that mostly affects the pineal gland as well as the suprasellar or intrasellar region of the brain is known as trilateral retinoblastoma. Because of its rarity, only a few research on the molecular genetics of this tumour have been published, despite the importance of reporting these cases with molecular analyses. This study intends to raise awareness about retinoblastoma early detection and the use of intracranial magnetic resonance imaging to track subsequent cancers, such as trilateral retinoblastoma. More over half of the Because trilateral retinoblastoma is diagnosed by magnetic resonance imaging at the same time as retinoblastoma, baseline screening for trilateral retinoblastoma may be beneficial. In this work, we provide three examples with trilateral retinoblastoma, as well as the molecular data for each proband, as determined by magnetic resonance imaging.

Author (s) Details

Ms. Renata Mendes de Freitas
Department of Genetics and Molecular Biology, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil and The Federal University of Juiz de Fora, Brazil.

View Book :- https://stm.bookpi.org/RRAB-V10/article/view/2132

A Case Report of Concurrent Occurrence of Both Intracranial and Intramedullary Tuberculomas | Chapter 12 | Research Trends and Challenges in Medical Science Vol. 4

Tuberculosis involving spinal cord in the form of intramedullary tuberculoma is uncommon, and the concurrent occurrence of cranial and intramedullary tuberculomas is extremely rare. We report a case of disseminated tuberculoma involving brain and spinal cord with miliary tuberculosis in a 32-year-old male presenting with fever, cerebellar signs and motor weakness of both upper and lower extremities. Based on magnetic resonance imaging and polymerase chain reaction, we diagnosed as tuberculoma. He completely recovered with conventional antituberculous treatment and steroids. The follow-up of the patient showed disappearance of signs and symptoms. 

Author(s) Details
Dr. Chennakesavulu Dara
Department of Medicine, Kurnool Medical College, Kurnool 518002, Andhra Pradesh, India.

View Book :- http://bp.bookpi.org/index.php/bpi/catalog/book/212