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Neurosurgical Focus Jan 2009Spinal vascular malformations (SVMs) are an uncommon, heterogeneous group of vascular anomalies that can render devastating neurological consequences if they are not... (Review)
Review
Spinal vascular malformations (SVMs) are an uncommon, heterogeneous group of vascular anomalies that can render devastating neurological consequences if they are not diagnosed and treated in a timely fashion. Imaging SVMs has always presented a formidable challenge because their clinical and imaging presentations resemble those of neoplasms, demyelination diseases, and infection. Advancements in noninvasive imaging modalities (MR and CT angiography) have increased during the last decade and have improved the ability to accurately diagnose spinal vascular anomalies. In addition, intraoperative imaging techniques have been developed that aid in the intraoperative assessment before, during, and after resection of these lesions with minimal and/or optimal use of spinal digital subtraction angiography. In this report, the authors review recent advancements in the imaging of SVMs that will likely lead to more timely diagnoses and treatment while reducing procedural risk exposure to the patients who harbor these uncommon spinal lesions.
Topics: Central Nervous System Vascular Malformations; Humans; Magnetic Resonance Angiography; Tomography, X-Ray Computed; Vascular Malformations
PubMed: 19119895
DOI: 10.3171/FOC.2009.26.1.E9 -
Bailliere's Best Practice & Research.... Dec 2000It is important to diagnose portal hypertension owing to its devastating complications. Clinicians need to be able to recognize physical signs and symptoms associated... (Review)
Review
It is important to diagnose portal hypertension owing to its devastating complications. Clinicians need to be able to recognize physical signs and symptoms associated with portal hypertensive states. When in doubt, appropriate diagnostic measures need to be performed and a definite diagnosis made. Hepatic venous pressure gradient (HVPG) is often used as a surrogate measurement of portal pressure. HVPG can be obtained safely and conveniently on an outpatient basis. It can also be used to assess efficacy of various treatment modalities. Knowledge of pathophysiology of portal hypertension has provided the basis for further trials in both novel treatment modalities and diagnostic methods.
Topics: Endoscopy, Digestive System; Female; Humans; Hypertension, Portal; Magnetic Resonance Imaging; Male; Sensitivity and Specificity; Tomography, X-Ray Computed; Ultrasonography, Doppler, Duplex
PubMed: 11139344
DOI: 10.1053/bega.2000.0136 -
BMC Oral Health Sep 2022Evaluating the diagnostic efficiency of deep learning models to diagnose vertical root fracture in vivo on cone-beam CT (CBCT) images.
OBJECTIVES
Evaluating the diagnostic efficiency of deep learning models to diagnose vertical root fracture in vivo on cone-beam CT (CBCT) images.
MATERIALS AND METHODS
The CBCT images of 276 teeth (138 VRF teeth and 138 non-VRF teeth) were enrolled and analyzed retrospectively. The diagnostic results of these teeth were confirmed by two chief radiologists. There were two experimental groups: auto-selection group and manual selection group. A total of 552 regions of interest of teeth were cropped in manual selection group and 1118 regions of interest of teeth were cropped in auto-selection group. Three deep learning networks (ResNet50, VGG19 and DenseNet169) were used for diagnosis (3:1 for training and testing). The diagnostic efficiencies (accuracy, sensitivity, specificity, and area under the curve (AUC)) of three networks were calculated in two experiment groups. Meanwhile, 552 teeth images in manual selection group were diagnosed by a radiologist. The diagnostic efficiencies of the three deep learning network models in two experiment groups and the radiologist were calculated.
RESULTS
In manual selection group, ResNet50 presented highest accuracy and sensitivity for diagnosing VRF teeth. The accuracy, sensitivity, specificity and AUC was 97.8%, 97.0%, 98.5%, and 0.99, the radiologist presented accuracy, sensitivity, and specificity as 95.3%, 96.4 and 94.2%. In auto-selection group, ResNet50 presented highest accuracy and sensitivity for diagnosing VRF teeth, the accuracy, sensitivity, specificity and AUC was 91.4%, 92.1%, 90.7% and 0.96.
CONCLUSION
In manual selection group, ResNet50 presented higher diagnostic efficiency in diagnosis of in vivo VRF teeth than VGG19, DensenNet169 and radiologist with 2 years of experience. In auto-selection group, Resnet50 also presented higher diagnostic efficiency in diagnosis of in vivo VRF teeth than VGG19 and DensenNet169. This makes it a promising auxiliary diagnostic technique to screen for VRF teeth.
Topics: Cone-Beam Computed Tomography; Deep Learning; Humans; Retrospective Studies; Tooth Fractures; Tooth Root
PubMed: 36064682
DOI: 10.1186/s12903-022-02422-9 -
Journal of Neuroimaging : Official... Jan 2023Alzheimer's disease (AD) is currently diagnosed using a mixture of psychological tests and clinical observations. However, these diagnoses are not perfect, and... (Review)
Review
Alzheimer's disease (AD) is currently diagnosed using a mixture of psychological tests and clinical observations. However, these diagnoses are not perfect, and additional diagnostic tools (e.g., MRI) can help improve our understanding of AD as well as our ability to detect the disease. Accordingly, a large amount of research has been invested into innovative diagnostic methods for AD. Functional MRI (fMRI) is a form of neuroimaging technology that has been used to diagnose AD; however, fMRI is incredibly noisy, complex, and thus lacks clinical use. Nonetheless, recent innovations in deep learning technology could enable the simplified and streamlined analysis of fMRI. Deep learning is a form of artificial intelligence that uses computer algorithms based on human neural networks to solve complex problems. For example, in fMRI research, deep learning models can automatically denoise images and classify AD by detecting patterns in participants' brain scans. In this systematic review, we investigate how fMRI (specifically resting-state fMRI) and deep learning methods are used to diagnose AD. In turn, we outline the common deep neural network, preprocessing, and classification methods used in the literature. We also discuss the accuracy, strengths, limitations, and future direction of fMRI deep learning methods. In turn, we aim to summarize the current field for new researchers, suggest specific areas for future research, and highlight the potential of fMRI to aid AD diagnoses.
Topics: Humans; Alzheimer Disease; Deep Learning; Artificial Intelligence; Magnetic Resonance Imaging; Neuroimaging; Brain
PubMed: 36257926
DOI: 10.1111/jon.13063 -
The Pan African Medical Journal 2019Self-diagnosis and pain management is a worldwide practice. The current study aims to determine the percentage of dental students and interns who self-diagnose and...
INTRODUCTION
Self-diagnosis and pain management is a worldwide practice. The current study aims to determine the percentage of dental students and interns who self-diagnose and manage their dental pain and further establish the proportion of students who depend on various resources for diagnosing and treating their condition.
METHODS
A cross-sectional, self-administered questionnaire-based study was conducted among the dental students in and around Riyadh. The questionnaire consisted of three parts including: part 1-demographic data; part 2-pain and self-diagnosis; part 3-visiting the dentist and managing the pain. The data were analyzed using the Statistical Package for Social Sciences (SPSS version 22.0).
RESULTS
Fifty four percent of the participants were involved in self-diagnosis and managed the pain by themselves. Seventy three percent of the respondents experienced teeth/gum discomfort or any symptoms of an oral health problem, of which 57% searched the symptoms they faced on the internet to arrive at a diagnosis. Besides, 35% of the interns considered internet to be a helpful tool for diagnosing their pain. 16% admitted that they have never visited a dentist.
CONCLUSION
We found that a significant proportion of the participants self-diagnosed by using their background or resorting to the internet, at times consulting a dentist to confirm their diagnosis. The students from the health sciences background should refrain from this practice. Efforts should be made to make the population mindful of the potential risks linked to self-medication and diagnosis. Further research should be done with a larger sample size by including the students and interns from different institutions.
Topics: Cross-Sectional Studies; Diagnostic Self Evaluation; Facial Pain; Female; Humans; Male; Saudi Arabia; Students, Dental; Surveys and Questionnaires; Toothache
PubMed: 32180872
DOI: 10.11604/pamj.2019.34.198.18347 -
Journal of Clinical Pathology Nov 2021An increasing number of small pulmonary nodules are being screened by CT, and an intraoperative diagnosis is necessary for preventing excessive treatment. However, there...
AIMS
An increasing number of small pulmonary nodules are being screened by CT, and an intraoperative diagnosis is necessary for preventing excessive treatment. However, there is limited literature on the frozen diagnosis of small sclerosing pneumocytomas (SPs). In particular, tumours smaller than 1 cm are challenging for pathologists performing intraoperative frozen diagnosis.
METHODS
In total, 230 cases of SP were surgically resected between January 2015 and March 2019 at Shanghai Chest Hospital, and of them, 76 cases were smaller than 1 cm. The histology and clinical information of these 76 cases (33.0%, 76/230) were reviewed retrospectively, 54 cases of which were diagnosed intraoperatively, and the pitfalls were summarised. All diagnoses were confirmed on permanent sections and immunohistochemical sections.
RESULTS
Histologically, 78.9% (60/76) of the small SP was dominated by one growth pattern, and solid and papillary growth pattern were the most commonly misdiagnosed circumstances. The rate of intraoperative misdiagnosis of these SP smaller than 1 cm was 11.1% (6/54).
CONCLUSIONS
The main reason for misdiagnosis was failure to recognise the dual cell populations and the cellular atypia. Diagnostic clues include the gross morphology, the presence of dual-cell populations and a hypercellular papillary core, foam cell accumulation in glandular spaces and haemorrhage and haemosiderin on the periphery. In spite of awareness of pitfalls some cases may still be essentially impossible to diagnose on frozen section.
Topics: Adult; Aged; Cytodiagnosis; Diagnosis, Differential; Diagnostic Errors; Female; Frozen Sections; Humans; Intraoperative Period; Lung Neoplasms; Male; Middle Aged; Multiple Pulmonary Nodules; Retrospective Studies; Sclerosis; Sensitivity and Specificity; Solitary Pulmonary Nodule
PubMed: 33782195
DOI: 10.1136/jclinpath-2020-206729 -
Enfermedades Infecciosas Y... 2009Acute gastrointestinal tract infections are among the most common infectious diseases. In the present review, the different methods of diagnosing gastrointestinal... (Review)
Review
Acute gastrointestinal tract infections are among the most common infectious diseases. In the present review, the different methods of diagnosing gastrointestinal infections caused by bacteria, viruses, and parasites are examined. Stool culture is the method of choice for diagnosing bacterial intestinal infections; however, infections caused by Clostridium difficile can be diagnosed by detection of toxins A and B in stools, and infections caused by diarrheagenic Escherichia coli by PCR detection of specific virulence factor genes harbored by several E. coli pathotypes. The techniques used to diagnose viral gastrointestinal infections include detection of viral antigens and nucleic acids. Finally, gastrointestinal infections caused by parasites can be diagnosed by testing for trophozoites and cysts of protozoa, or larvae and eggs of helminths in stools by direct microscopic examination, with concentration techniques, or by specific stains.
Topics: Adult; Aged; Animals; Child, Preschool; Cross Infection; Feces; Female; Gastroenteritis; Gastrointestinal Diseases; Humans; Infant; Intestinal Diseases, Parasitic; Male; Microbiological Techniques; Parasitology; Virology
PubMed: 19477556
DOI: 10.1016/j.eimc.2008.11.009 -
JCO Oncology Practice Jan 2021Approximately 13% of the US population report mobility disability. People with mobility disability experience healthcare disparities, including lower rates of cancer...
PURPOSE
Approximately 13% of the US population report mobility disability. People with mobility disability experience healthcare disparities, including lower rates of cancer screening and substandard cancer care compared with nondisabled people. We explored clinicians' reports of aspects of diagnosing and treating three common cancer types among persons with pre-existing mobility disability.
METHODS
We used standard diagnosis codes and natural language processing to screen electronic health records (EHR) in the Research Patient Data Repository for patients with pre-existing chronic mobility impairment who were newly diagnosed with one of three common cancers (colorectal, prostate, and non-Hodgkin lymphoma) between 2005 and 2017. We eliminated numerous cases whose EHRs lacked essential information. We reviewed EHRs of 27 cases, using conventional content analysis to identify themes concerning their cancer diagnoses and treatments.
RESULTS
Clinicians' notations coalesced around four major themes: (1) patients' health risks raise concerns about diagnostic processes; (2) cancer signs or symptoms can be erroneously attributed to the patient's underlying disabling condition, delaying diagnosis; (3) disability complicates cancer treatment decisions; and (4) problems with equipment accessibility and disability accommodations impede cancer diagnoses.
DISCUSSION
Clinicians view patients with pre-existing mobility disability as often clinically complex, presenting challenges for diagnosing and treating their cancer. Nonetheless, these patients may experience substandard care because of disability-related problems. Given the growing population of people with mobility disability, further efforts to improve care quality and timeliness of diagnosis are warranted.
Topics: Disabled Persons; Early Detection of Cancer; Electronic Health Records; Healthcare Disparities; Humans; Male; Natural Language Processing; Neoplasms
PubMed: 33351675
DOI: 10.1200/OP.20.00378 -
Drug Metabolism and Disposition: the... Apr 2022Nonalcoholic steatohepatitis (NASH) is the progressive form of nonalcoholic fatty liver disease (NAFLD) and is diagnosed by a liver biopsy. Because of the invasiveness... (Review)
Review
Nonalcoholic steatohepatitis (NASH) is the progressive form of nonalcoholic fatty liver disease (NAFLD) and is diagnosed by a liver biopsy. Because of the invasiveness of a biopsy, the majority of patients with NASH are undiagnosed. Additionally, the prevalence of NAFLD and NASH creates the need for a simple screening method to differentiate patients with NAFLD versus NASH. Noninvasive strategies for diagnosing NAFLD versus NASH have been developed, typically relying on imaging techniques and endogenous biomarker panels. However, each technique has limitations, and none can accurately predict the associated functional impairment of drug metabolism and disposition. The function of several drug-metabolizing enzymes and drug transporters has been described in NASH that impacts drug pharmacokinetics. The aim of this review is to give an overview of the existing noninvasive strategies to diagnose NASH and to propose a novel strategy based on altered pharmacokinetics using an exogenous biomarker whose disposition and elimination pathways are directly impacted by disease progression. Altered disposition of safe and relatively inert exogenous compounds may provide the sensitivity and specificity needed to differentiate patients with NAFLD and NASH to facilitate a direct indication of hepatic impairment on drug metabolism and prevent subsequent adverse drug reactions. SIGNIFICANCE STATEMENT: This review provides an overview of the main noninvasive techniques (imaging and panels of biomarkers) used to diagnose NAFLD and NASH along with a biopsy. Pharmacokinetic changes have been identified in NASH, and this review proposes a new approach to predict NASH and the related risk of adverse drug reactions based on the assessment of drug elimination disruption using exogenous biomarkers.
Topics: Biomarkers; Biopsy; Drug-Related Side Effects and Adverse Reactions; Humans; Liver; Non-alcoholic Fatty Liver Disease
PubMed: 34531312
DOI: 10.1124/dmd.121.000413 -
Cells Dec 2022Brain-derived extracellular vesicles (BDEVs) are released from the central nervous system. Brain-related research and diagnostic techniques involving BDEVs have rapidly...
Brain-derived extracellular vesicles (BDEVs) are released from the central nervous system. Brain-related research and diagnostic techniques involving BDEVs have rapidly emerged as a means of diagnosing brain disorders because they are minimally invasive and enable repeatable measurements based on body fluids. However, EVs from various cells and organs are mixed in the blood, acting as potential obstacles for brain diagnostic systems using BDEVs. Therefore, it is important to screen appropriate brain EV markers to isolate BDEVs in blood. Here, we established a strategy for screening potential BDEV biomarkers. To collect various molecular data from the BDEVs, we propose that the sensitivity and specificity of the diagnostic system could be enhanced using machine learning and AI analysis. This BDEV-based diagnostic strategy could be used to diagnose various brain diseases and will help prevent disease through early diagnosis and early treatment.
Topics: Humans; Artificial Intelligence; Biomarkers; Brain; Brain Diseases; Early Diagnosis
PubMed: 36611896
DOI: 10.3390/cells12010102