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European Radiology Jan 2024To calculate the pooled diagnostic performances of whole-body [F]FDG PET/MR in M staging of [F]FDG-avid cancer entities. (Meta-Analysis)
Meta-Analysis
OBJECTIVES
To calculate the pooled diagnostic performances of whole-body [F]FDG PET/MR in M staging of [F]FDG-avid cancer entities.
METHODS
A diagnostic meta-analysis was conducted on the [F]FDG PET/MR in M staging, including studies: (1) evaluated [F]FDG PET/MR in detecting distant metastasis; (2) compared[ F]FDG PET/MR with histopathology, follow-up, or asynchronous multimodality imaging as the reference standard; (3) provided data for the whole-body evaluation; (4) provided adequate data to calculate the meta-analytic performances. Pooled performances were calculated with their confidence interval. In addition, forest plots, SROC curves, and likelihood ratio scatterplots were drawn. All analyses were performed using STATA 16.
RESULTS
From 52 eligible studies, 2289 patients and 2072 metastases were entered in the meta-analysis. The whole-body pooled sensitivities were 0.95 (95%CI: 0.91-0.97) and 0.97 (95%CI: 0.91-0.99) at the patient and lesion levels, respectively. The pooled specificities were 0.99 (95%CI: 0.97-1.00) and 0.97 (95%CI: 0.90-0.99), respectively. Additionally, subgroup analyses were performed. The calculated pooled sensitivities for lung, gastrointestinal, breast, and gynecological cancers were 0.90, 0.93, 1.00, and 0.97, respectively. The pooled specificities were 1.00, 0.98, 0.97, and 1.00, respectively. Furthermore, the pooled sensitivities for non-small cell lung, colorectal, and cervical cancers were 0.92, 0.96, and 0.86, respectively. The pooled specificities were 1.00, 0.95, and 1.00, respectively.
CONCLUSION
[F]FDG PET/MR was a highly accurate modality in M staging in the reported [F]FDG-avid malignancies. The results showed high sensitivity and specificity in each reviewed malignancy type. Thus, our findings may help clinicians and patients to be confident about the performance of [F]FDG PET/MR in the clinic.
CLINICAL RELEVANCE STATEMENT
Although [F]FDG PET/MR is not a routine imaging technique in current guidelines, mostly due to its availability and logistic issues, our findings might add to the limited evidence regarding its performance, showing a sensitivity of 0.95 and specificity of 0.97.
KEY POINTS
• The whole-body [F]FDG PET/MR showed high accuracy in detecting distant metastases at both patient and lesion levels. • The pooled sensitivities were 95% and 97% and pooled specificities were 99% and 97% at patient and lesion levels, respectively. • The results suggested that F-FDG PET/MR was a strong modality in the exclusion and confirmation of distant metastases.
Topics: Humans; Fluorodeoxyglucose F18; Radiopharmaceuticals; Sensitivity and Specificity; Multimodal Imaging; Neoplasm Staging; Neoplasms; Positron-Emission Tomography; Positron Emission Tomography Computed Tomography
PubMed: 37535156
DOI: 10.1007/s00330-023-10009-3 -
Oral Surgery, Oral Medicine, Oral... Sep 2023We assessed the efficacy of anti-desmoglein 1 (anti-DSG1) and anti-DSG3 levels by enzyme-linked immunosorbent assay (ELISA) as a preliminary diagnostic test in the... (Observational Study)
Observational Study
Efficacy of anti-desmoglein 1 and anti-desmoglein 3 levels by enzyme-linked immunosorbent assay compared to biopsy of chronic oral ulcerative diseases with positive Nikolsky's sign to diagnose oral pemphigus vulgaris with or without skin involvement: a retrospective institutional observational...
OBJECTIVE
We assessed the efficacy of anti-desmoglein 1 (anti-DSG1) and anti-DSG3 levels by enzyme-linked immunosorbent assay (ELISA) as a preliminary diagnostic test in the diagnosis of oral pemphigus vulgaris (OPV) with or without skin involvement compared to biopsy.
STUDY DESIGN
We retrospectively analyzed data collected from 23 patients (mean age 45.13 years) who had presented with chronic oral ulcerations, desquamative gingivitis, and a positive Nikolsky's sign. We performed ELISA, histopathologic examination, and direct immunofluorescence (DIF) and then calculated the sensitivity and specificity of the results of ELISA, histopathology, DIF, and the presence of a positive Nikolsky's sign in diagnosis.
RESULTS
The ELISA results showed that 18 patients had elevated anti-DSG3 levels, of whom 8 also had elevated anti-DSG1 levels. The histopathology results indicated that 18 patients had OPV, of whom 4 had oral lichen planus, and 1 had sub-epithelial blistering disease confirmed to be mucous membrane pemphigoid MMP by DIF. ELISA, histopathology, and DIF had a 100% sensitivity and specificity, and the presence of a positive Nikolsky's sign had a sensitivity and specificity of 100% and 78.26%, respectively.
CONCLUSIONS
Measurement of anti-DSG1 and anti-DSG3 levels by ELISA warrants consideration as a first-line diagnostic test for early detection of OPV with or without skin involvement over biopsy.
Topics: Humans; Middle Aged; Pemphigus; Retrospective Studies; Pilot Projects; Enzyme-Linked Immunosorbent Assay; Oral Ulcer; Stomatitis; Chronic Disease; Cellulitis; Biopsy; Autoantibodies
PubMed: 37507320
DOI: 10.1016/j.oooo.2023.05.016 -
BMC Cancer Nov 2023The pathological diagnosis and prognosis prediction of hepatocellular carcinoma (HCC) is challenging due to the lack of specific biomarkers. This study aimed to validate...
PURPOSE
The pathological diagnosis and prognosis prediction of hepatocellular carcinoma (HCC) is challenging due to the lack of specific biomarkers. This study aimed to validate the diagnostic and prognostic efficiency of Kidney-type glutaminase (GLS1) for HCC in prospective cohorts with a large sample size.
METHODS
A total of 1140 HCC patients were enrolled in our prospective clinical trials. Control cases included 114 nontumour tissues. The registered clinical trial (ChiCTR-DDT-14,005,102, chictr.org.cn) was referred to for the exact protocol. GLS1 immunohistochemistry was performed on the whole tumour section. The diagnostic and prognostic performances of GLS1 was evaluated by the receiver operating characteristic curve and Cox regression model.
RESULTS
The sensitivity, specificity, positive predictive value, negative predictive value, Youden index, and area under the curve of GLS1 for the diagnosis of HCC were 0.746, 0.842, 0.979, 0.249, 0.588, and 0.814, respectively, which could be increased to 0.846, 0.886, 0.987,0.366, 0.732, and 0.921 when combined with glypican 3 (GPC3) and alpha-fetoprotein (AFP), indicating better diagnostic performance. Further, we developed a nomogram with GPC3 and GLS1 for identifying HCC which showed good discrimination and calibration. GLS1 expression was also related with age, T stage, TNM stage, Edmondson-Steiner grade, microvascular invasion, Ki67, VEGFR2, GPC3, and AFP expression in HCC. GLS1 expression was negatively correlated with disease-free survival (P < 0.001) probability of patients with HCC.
CONCLUSIONS
It was validated that GLS1 was a sensitive and specific biomarker for pathological diagnosis of HCC and had prognostic value, thus having practical value for clinical application.
Topics: Humans; Carcinoma, Hepatocellular; alpha-Fetoproteins; Prospective Studies; Liver Neoplasms; Glutaminase; Biomarkers, Tumor; Prognosis; Kidney; Glypicans
PubMed: 37946141
DOI: 10.1186/s12885-023-11601-y -
Pediatric and Developmental Pathology :... Jun 2024Acute appendicitis (AA) is treated primarily surgically with histopathology being the gold standard for confirmation of appendicitis and reported rates of negative...
AIM
Acute appendicitis (AA) is treated primarily surgically with histopathology being the gold standard for confirmation of appendicitis and reported rates of negative appendicectomies (NA) ranging between 3.2% and 19% worldwide and 15.9-20.6% in the UK. NA rates are frequently used to identify poor performing centers as part of a Model Health System and form an integral part of appendicitis scoring systems. This study aims to evaluate the prevalence of negative appendicectomies within our institution and critically analyze the appropriateness of its use as a quality metric and its impact on clinical practice and research.
PATIENTS AND METHODS
Data analysis from a prospective dataset of pediatric appendicitis patients between 2015 and 2021 in a tertiary center in the UK was performed. Detailed analysis of negative appendicectomies was performed and further stratified by two distinct age and gender groups looking at the incidence of NA and the classification of non-histologically normal appendix specimens.
RESULTS
In our series, 819 patients met inclusion criteria, 736 (89.9%) had acute appendicitis. Our overall institutional negative appendicectomy rate was 10.1% (83 patients) with the breakdown as follows: 65 histologically normal appendix (7.9%), 10 Enterobius vermicularis, 3 eosinophilic appendicitis, 2 neoplasms, 1 isolated faecolith, 1 fibrous obliteration of the lumen, and 1 peri-appendiceal inflammation.
CONCLUSION
Our negative appendicectomy rate is below established UK pediatric NA rates. This rate ranges from 7.9% to 10.1% depending on the definition of NA utilized. A single standard pathological definition for histological acute appendicitis is required when being used as a comparative quality metric. Centers engaged in clinical research should be aware of variations in NA definitions both in scoring systems and individual centers to avoid skewing derived results.
PubMed: 38845117
DOI: 10.1177/10935266241255281 -
Cancer Biomarkers : Section a of... 2024Breast cancer is one of the leading causes of death in women worldwide. Histopathology analysis of breast tissue is an essential tool for diagnosing and staging breast... (Review)
Review
BACKGROUND
Breast cancer is one of the leading causes of death in women worldwide. Histopathology analysis of breast tissue is an essential tool for diagnosing and staging breast cancer. In recent years, there has been a significant increase in research exploring the use of deep-learning approaches for breast cancer detection from histopathology images.
OBJECTIVE
To provide an overview of the current state-of-the-art technologies in automated breast cancer detection in histopathology images using deep learning techniques.
METHODS
This review focuses on the use of deep learning algorithms for the detection and classification of breast cancer from histopathology images. We provide an overview of publicly available histopathology image datasets for breast cancer detection. We also highlight the strengths and weaknesses of these architectures and their performance on different histopathology image datasets. Finally, we discuss the challenges associated with using deep learning techniques for breast cancer detection, including the need for large and diverse datasets and the interpretability of deep learning models.
RESULTS
Deep learning techniques have shown great promise in accurately detecting and classifying breast cancer from histopathology images. Although the accuracy levels vary depending on the specific data set, image pre-processing techniques, and deep learning architecture used, these results highlight the potential of deep learning algorithms in improving the accuracy and efficiency of breast cancer detection from histopathology images.
CONCLUSION
This review has presented a thorough account of the current state-of-the-art techniques for detecting breast cancer using histopathology images. The integration of machine learning and deep learning algorithms has demonstrated promising results in accurately identifying breast cancer from histopathology images. The insights gathered from this review can act as a valuable reference for researchers in this field who are developing diagnostic strategies using histopathology images. Overall, the objective of this review is to spark interest among scholars in this complex field and acquaint them with cutting-edge technologies in breast cancer detection using histopathology images.
Topics: Humans; Breast Neoplasms; Deep Learning; Female; Image Processing, Computer-Assisted; Algorithms; Image Interpretation, Computer-Assisted
PubMed: 38517775
DOI: 10.3233/CBM-230251 -
Alzheimer's & Dementia : the Journal of... Nov 2023Neuropathological substrates associated with neurodegeneration occur in brains of the oldest old. How does this affect cognitive performance?
INTRODUCTION
Neuropathological substrates associated with neurodegeneration occur in brains of the oldest old. How does this affect cognitive performance?
METHODS
The 100-plus Study is an ongoing longitudinal cohort study of centenarians who self-report to be cognitively healthy; post mortem brain donation is optional. In 85 centenarian brains, we explored the correlations between the levels of 11 neuropathological substrates with ante mortem performance on 12 neuropsychological tests.
RESULTS
Levels of neuropathological substrates varied: we observed levels up to Thal-amyloid beta phase 5, Braak-neurofibrillary tangle (NFT) stage V, Consortium to Establish a Registry for Alzheimer's Disease (CERAD)-neuritic plaque score 3, Thal-cerebral amyloid angiopathy stage 3, Tar-DNA binding protein 43 (TDP-43) stage 3, hippocampal sclerosis stage 1, Braak-Lewy bodies stage 6, atherosclerosis stage 3, cerebral infarcts stage 1, and cerebral atrophy stage 2. Granulovacuolar degeneration occurred in all centenarians. Some high performers had the highest neuropathology scores.
DISCUSSION
Only Braak-NFT stage and limbic-predominant age-related TDP-43 encephalopathy (LATE) pathology associated significantly with performance across multiple cognitive domains. Of all cognitive tests, the clock-drawing test was particularly sensitive to levels of multiple neuropathologies.
Topics: Aged, 80 and over; Humans; Amyloid beta-Peptides; Centenarians; Longitudinal Studies; Alzheimer Disease; Brain; Neurofibrillary Tangles; Neuropathology; Cognition
PubMed: 37092333
DOI: 10.1002/alz.13087 -
Academic Radiology Sep 2023To carry out radiomics analysis/deep convolutional neural network (CNN) based on B-mode ultrasound (BUS) and shear wave elastography (SWE) to predict response to...
RATIONALE AND OBJECTIVES
To carry out radiomics analysis/deep convolutional neural network (CNN) based on B-mode ultrasound (BUS) and shear wave elastography (SWE) to predict response to neoadjuvant chemotherapy (NAC) in breast cancer patients.
MATERIALS AND METHODS
In this prospective study, 255 breast cancer patients who received NAC between September 2016 and December 2021 were included. Radiomics models were designed using a support vector machine classifier based on US images obtained before treatment, including BUS and SWE. And CNN models also were developed using ResNet architecture. The final predictive model was developed by combining the dual-modal US and independently associated clinicopathologic characteristics. The predictive performances of the models were assessed with five-fold cross-validation.
RESULTS
Pretreatment SWE performed better than BUS in predicting the response to NAC for breast cancer for both the CNN and radiomics models (P < 0.001). The predictive results of the CNN models were significantly better than the radiomics models, with AUCs of 0.72 versus 0.69 for BUS and 0.80 versus 0.77 for SWE, respectively (P = 0.003). The CNN model based on the dual-modal US and molecular data exhibited outstanding performance in predicting NAC response, with an accuracy of 83.60% ± 2.63%, a sensitivity of 87.76% ± 6.44%, and a specificity of 77.45% ± 4.38%.
CONCLUSION
The pretreatment CNN model based on the dual-modal US and molecular data achieved excellent performance for predicting the response to chemotherapy in breast cancer. Therefore, this model has the potential to serve as a non-invasive objective biomarker to predict NAC response and aid clinicians with individual treatments.
Topics: Humans; Female; Breast Neoplasms; Deep Learning; Neoadjuvant Therapy; Prospective Studies; Ultrasonography; Retrospective Studies
PubMed: 37270368
DOI: 10.1016/j.acra.2023.03.036 -
JCO Clinical Cancer Informatics Jun 2024Prostate cancer (PCa) represents a highly heterogeneous disease that requires tools to assess oncologic risk and guide patient management and treatment planning. Current...
PURPOSE
Prostate cancer (PCa) represents a highly heterogeneous disease that requires tools to assess oncologic risk and guide patient management and treatment planning. Current models are based on various clinical and pathologic parameters including Gleason grading, which suffers from a high interobserver variability. In this study, we determine whether objective machine learning (ML)-driven histopathology image analysis would aid us in better risk stratification of PCa.
MATERIALS AND METHODS
We propose a deep learning, histopathology image-based risk stratification model that combines clinicopathologic data along with hematoxylin and eosin- and Ki-67-stained histopathology images. We train and test our model, using a five-fold cross-validation strategy, on a data set from 502 treatment-naïve PCa patients who underwent radical prostatectomy (RP) between 2000 and 2012.
RESULTS
We used the concordance index as a measure to evaluate the performance of various risk stratification models. Our risk stratification model on the basis of convolutional neural networks demonstrated superior performance compared with Gleason grading and the Cancer of the Prostate Risk Assessment Post-Surgical risk stratification models. Using our model, 3.9% of the low-risk patients were correctly reclassified to be high-risk and 21.3% of the high-risk patients were correctly reclassified as low-risk.
CONCLUSION
These findings highlight the importance of ML as an objective tool for histopathology image assessment and patient risk stratification. With further validation on large cohorts, the digital pathology risk classification we propose may be helpful in guiding administration of adjuvant therapy including radiotherapy after RP.
Topics: Humans; Prostatic Neoplasms; Male; Deep Learning; Neoplasm Grading; Risk Assessment; Prostatectomy; Aged; Middle Aged; Image Processing, Computer-Assisted
PubMed: 38900978
DOI: 10.1200/CCI.23.00184 -
Journal of Pediatric Gastroenterology... Nov 2023The diagnostic utility of mucosal biopsies taken during colonoscopy-guided colonic manometry catheter placement is unknown. The aims of our study were to determine the...
OBJECTIVES
The diagnostic utility of mucosal biopsies taken during colonoscopy-guided colonic manometry catheter placement is unknown. The aims of our study were to determine the frequency and histopathology results of mucosal biopsies during these procedures and to assess whether there were any associations between the histology or gross findings with manometry results.
METHODS
We performed a retrospective chart review of children who had a colonic manometry study completed between 2008 and 2020 at a quaternary children's hospital. We captured patient demographics, biopsy locations, histopathology results, gross endoscopy findings, and manometry results. The chi-squared test and when appropriate Fisher exact test was used to evaluate categorical associations.
RESULTS
One hundred forty-eight patients were included. One hundred eighteen (80%) had colonic biopsy and 63 (43%) had ileal biopsy. Colonic histology findings, which patients could have multiple, included lymphonodular hyperplasia (34%), normal (27%), chronic inflammation (24%), melanosis coli (21%), colonic eosinophilia (10%), and acute inflammation (8%). Ileal histology findings included increased Peyer patches (44%), normal (44%), acute inflammation (11%), chronic inflammation (3%), eosinophilia (5%), and eosinophilic ileitis (3%). The majority of acute and chronic inflammation was graded as mild. There were no statistically significant associations of histology to gross endoscopy or manometry findings.
CONCLUSIONS
Colonic biopsies are obtained in the majority of patients presenting for colonic manometry evaluation with ileal biopsies obtained less frequently. Histopathology findings are noted frequently, but the majority are the result of or did not impact clinical care. There were no associations between abnormal histopathology or abnormal gross endoscopy findings with colonic manometry results.
Topics: Child; Humans; Retrospective Studies; Colon; Colonoscopy; Biopsy; Inflammation; Catheters; Manometry; Eosinophilia
PubMed: 37548490
DOI: 10.1097/MPG.0000000000003907 -
Forensic Science, Medicine, and... Sep 2023The autopsy is considered the gold standard in death investigation. Performing an autopsy requires human and material resources that must be programmed in order to meet...
INTRODUCTION AND OBJECTIVES
The autopsy is considered the gold standard in death investigation. Performing an autopsy requires human and material resources that must be programmed in order to meet the demands of the judicial system. However, as far as we know, the cost of forensic autopsy in Spain has not been determined. Thus, the aim of this study was to estimate the cost of a standard autopsy in order to organise Forensic Pathology Services more efficiently.
MATERIAL AND METHODS
A micro-cost analysis was carried out. The nominal group technique was applied using a panel of 10 forensic experts in order to identify and quantify the resources associated with a forensic autopsy.
RESULTS
The results showed that analysis and studies are the most important item in the total cost (54.7%), followed by staff (20.5%), preservation of body (14%), single-use products (7%), equipment and stock (1.6%), cleaning and disinfection (1.5%), facilities maintenance (0.5%) and IT (0.2%).
CONCLUSIONS
The total cost of a standard autopsy was €1501.45, which is lower than the European average. This study is the first in Spain to calculate the unit price of a forensic autopsy by means of micro-cost analysis. This may help to address the way forensic pathology centres are organised at different levels of complexity.
Topics: Humans; Autopsy; Spain; Cause of Death; Forensic Medicine; Forensic Pathology
PubMed: 36342626
DOI: 10.1007/s12024-022-00534-w