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Journal of Visceral Surgery Jun 2020Discovery of an adrenal mass is nowadays a frequent situation. While adrenal tumors can cause a variety of symptoms, more often than not they are diagnosed incidentally... (Review)
Review
Discovery of an adrenal mass is nowadays a frequent situation. While adrenal tumors can cause a variety of symptoms, more often than not they are diagnosed incidentally on imaging exams such as CT-scan or MRI performed for another purpose. However, any retroperitoneal supra-renal mass can have an extra-adrenal origin. Indeed, operated non-adrenal masses initially but wrongly diagnosed as an adrenal disease represent about 3.5% of adrenalectomies. These differential diagnoses principally include retroperitoneal tumors that are malignant in two thirds of cases (lymphomas, sarcomas, neurogenic or germinal tumors), and more rarely vascular anomalies or congenital malformations, which are most frequently left-sided due to the wide variety of anatomical structures surrounding the left adrenal gland. Several lesions can originate from the adrenal gland or be located near the gland (paraganglioma, ganglioneuroma). Even though unilateral adrenalectomy is associated with low morbidity, ignorance of these differential diagnoses can cause ill-adapted management; overly conservative surgery in case of sarcoma is one example. Some of these lesions have characteristic clinical or imaging features (cystic lymphangioma, angiomyolipoma…). In other cases, assessment of hormonal secretion is required and additional exams (MRI, percutaneous biopsy, PET-scan with 18-Fluorodeoxyglucose) can correct an erroneous diagnosis. The above diagnostic approach allows appropriate management (with or without surgery). The purpose of this review was to highlight the main differential diagnoses of adrenal masses, to describe their characteristics, and to discuss their therapeutic management.
Topics: Abdominal Neoplasms; Adrenal Gland Neoplasms; Diagnosis, Differential; Diagnostic Errors; Humans; Retroperitoneal Neoplasms; Soft Tissue Neoplasms
PubMed: 32201083
DOI: 10.1016/j.jviscsurg.2020.02.004 -
European Radiology Aug 2022To evaluate the feasibility and accuracy of diagnosing acute heart failure (HF) with CT pulmonary angiography (CTPA) in emergency department patients.
OBJECTIVES
To evaluate the feasibility and accuracy of diagnosing acute heart failure (HF) with CT pulmonary angiography (CTPA) in emergency department patients.
METHODS
In this retrospective single-center study, we evaluated 150 emergency department patients (mean age 65 ± 17 years) undergoing CTPA with a fixed scan (100 kVp) and contrast media protocol (60 mL, 4 mL/s) who had no pulmonary embolism (PE). Patients were subdivided into training cohort (n = 100) and test cohort (n = 50). Three independent, blinded readers measured the attenuation in the right ventricle (RV) and left ventricle (LV) on axial images. The ratio (HU) and difference (HU) between RV and LV attenuation were calculated. Diagnosis of acute HF was made on the basis of clinical, laboratory, and echocardiography data. Optimal thresholds, sensitivity, and specificity were calculated using the area under the curve (AUC) from receiver operating characteristics analysis.
RESULTS
Fifty-nine of the 150 patients (40%) were diagnosed with acute HF. Attenuation measurements showed an almost perfect interobserver agreement (intraclass correlation coefficient: 0.986, 95%CI: 0.980-0.991). NT-pro BNP exhibited moderate correlations with HU (r = 0.50, p < 0.001) and HU (r = 0.50, p < 0.001). In the training cohort, HU (AUC: 0.89, 95%CI: 0.82-0.95) and HU (AUC: 0.88, 95%CI: 0.81-0.95) showed a very good performance to diagnose HF. Optimal cutoff values were 1.42 for HU (sensitivity 93%; specificity 75%) and 113 for HU (sensitivity 93%; specificity 73%). Applying these thresholds to the test cohort yielded a sensitivity of 89% and 89% and a specificity of 69% and 63% for HU and HU, respectively.
CONCLUSION
In emergency department patients undergoing CTPA and showing no PE, both HU and HU have a high sensitivity for diagnosing acute HF.
KEY POINTS
• Heart failure is a common differential diagnosis in patients undergoing CT pulmonary angiography. • In emergency department patients undergoing CT pulmonary angiography and showing no pulmonary embolism, attenuation differences of the left and right ventricle have a high sensitivity for diagnosing acute heart failure.
Topics: Aged; Aged, 80 and over; Angiography; Computed Tomography Angiography; Feasibility Studies; Heart Failure; Humans; Middle Aged; Pulmonary Embolism; Retrospective Studies; Sensitivity and Specificity; Tomography, X-Ray Computed
PubMed: 35294585
DOI: 10.1007/s00330-022-08676-9 -
International Journal of Infectious... Jul 2020Diagnosing pulmonary blastomycosis (PB) requires the detection of Blastomyces dermatitidis in pulmonary secretions or tissue, which can be achieved via bronchoscopic...
OBJECTIVES
Diagnosing pulmonary blastomycosis (PB) requires the detection of Blastomyces dermatitidis in pulmonary secretions or tissue, which can be achieved via bronchoscopic procedures like bronchoalveolar lavage (BAL) or brush and transbronchial biopsy (TBBx). This descriptive study retrieved the data of PB that was diagnosed by bronchoscopy to define which bronchoscopic procedure produced the highest yield.
METHODS
Retrospectively, all patients diagnosed with PB via bronchoscopic approach were identified. Non-invasive BAL was referred to when performed first in the order of bronchoscopic procedures, and invasive BAL was used when it was performed after other bronchoscopic procedures.
RESULTS
A total of 111 patients were included in the study. BAL produced the highest yield of all bronchoscopic procedures (>87%), regardless if it was performed first in order (non-invasive, 87.3%) or not (invasive BAL, 89.6%) (p = 0.43). Performing bronchoscopy and BAL earlier in the course of the disease resulted in a significantly better diagnostic yield.
CONCLUSIONS
BAL is probably enough to diagnose PB. Also, it had the best yield when performed earlier, regardless of whether it was performed first in order or not. BAL culture had a better yield in detecting Blastomyces dermatitidis over fungal stain and cytology.
Topics: Adolescent; Adult; Aged; Aged, 80 and over; Blastomycosis; Bronchoalveolar Lavage; Bronchoscopy; Female; Humans; Male; Middle Aged; Retrospective Studies; Young Adult
PubMed: 32371194
DOI: 10.1016/j.ijid.2020.04.077 -
BMC Medical Informatics and Decision... Jun 2020Early warning scores (EWS) have been developed as clinical prognostication tools to identify acutely deteriorating patients. In the past few years, there has been a...
BACKGROUND
Early warning scores (EWS) have been developed as clinical prognostication tools to identify acutely deteriorating patients. In the past few years, there has been a proliferation of studies that describe the development and validation of novel machine learning-based EWS. Systematic reviews of published studies which focus on evaluating performance of both well-established and novel EWS have shown conflicting conclusions. A possible reason is the heterogeneity in validation methods applied. In this review, we aim to examine the methodologies and metrics used in studies which perform EWS validation.
METHODS
A systematic review of all eligible studies from the MEDLINE database and other sources, was performed. Studies were eligible if they performed validation on at least one EWS and reported associations between EWS scores and inpatient mortality, intensive care unit (ICU) transfers, or cardiac arrest (CA) of adults. Two reviewers independently did a full-text review and performed data abstraction by using standardized data-worksheet based on the TRIPOD (Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis) checklist. Meta-analysis was not performed due to heterogeneity.
RESULTS
The key differences in validation methodologies identified were (1) validation dataset used, (2) outcomes of interest, (3) case definition, time of EWS use and aggregation methods, and (4) handling of missing values. In terms of case definition, among the 48 eligible studies, 34 used the patient episode case definition while 12 used the observation set case definition, and 2 did the validation using both case definitions. Of those that used the patient episode case definition, 18 studies validated the EWS at a single point of time, mostly using the first recorded observation. The review also found more than 10 different performance metrics reported among the studies.
CONCLUSIONS
Methodologies and performance metrics used in studies performing validation on EWS were heterogeneous hence making it difficult to interpret and compare EWS performance. Standardizing EWS validation methodology and reporting can potentially address this issue.
Topics: Adult; Benchmarking; Early Warning Score; Heart Arrest; Humans; Intensive Care Units; Prognosis; Prospective Studies
PubMed: 32552702
DOI: 10.1186/s12911-020-01144-8 -
Pediatric Emergency Care Nov 2021This study aimed to investigate the feasibility of point-of-care ultrasound (POCUS) for diagnosing hypertrophic pyloric stenosis (HPS) in the emergency department (ED).
OBJECTIVES
This study aimed to investigate the feasibility of point-of-care ultrasound (POCUS) for diagnosing hypertrophic pyloric stenosis (HPS) in the emergency department (ED).
METHODS
A retrospective study was conducted in infants aged younger than 90 days who were brought to the ED due to vomiting between January 2015 and December 2019. Of these, infants who were clinically suspected of having HPS and underwent ultrasound were included and categorized into 3 groups: POCUS only, POCUS followed by radiologist-performed ultrasound (RADUS), and RADUS only. All confirmative diagnoses of HPS were made by RADUS. The diagnostic performance of POCUS was analyzed, and the ED patient flow was compared between the POCUS-performed (POCUS only or POCUS followed by RADUS) and RADUS-only groups.
RESULTS
Overall, 171 patients with a median age of 34 days were included. Of these, 79 patients (46.2%) underwent POCUS only, and none had HPS; 50 patients (29.2%) underwent POCUS followed by RADUS; and 42 patients (24.5%) underwent RADUS only. Overall, 41 patients (24.0%) were diagnosed with HPS, and POCUS showed a sensitivity of 96.6% and specificity of 94.0%. In the total cohort, length of stay in the ED (EDLOS) was shorter in the POCUS-performed group than in the RADUS-only group (2.6 vs 3.8 hours, P = 0.015). Among non-HPS patients, time to disposition (1.8 vs 2.7 hours, P = 0.005) and EDLOS (2.0 vs 3.0 hours, P = 0.004) were shorter in the POCUS-performed group than in the RADUS-only group. Performing POCUS followed by RADUS did not significantly delay the treatment among HPS patients.
CONCLUSIONS
Point-of-care ultrasound is accurate and useful for diagnosing HPS and improved the ED patient flow by reducing EDLOS and door-to-disposition time in non-HPS patients.
Topics: Emergency Service, Hospital; Feasibility Studies; Humans; Infant; Point-of-Care Systems; Pyloric Stenosis, Hypertrophic; Retrospective Studies; Ultrasonography
PubMed: 34550920
DOI: 10.1097/PEC.0000000000002532 -
Frontiers in Immunology 2023Though copy number variants (CNVs) have been suggested to play a significant role in inborn errors of immunity (IEI), the precise nature of this role remains largely...
PURPOSE
Though copy number variants (CNVs) have been suggested to play a significant role in inborn errors of immunity (IEI), the precise nature of this role remains largely unexplored. We sought to determine the diagnostic contribution of CNVs using genome-wide chromosomal microarray analysis (CMA) in children with IEI.
METHODS
We performed exome sequencing (ES) and CMA for 332 unrelated pediatric probands referred for evaluation of IEI. The analysis included primary, secondary, and incidental findings.
RESULTS
Of the 332 probands, 134 (40.4%) received molecular diagnoses. Of these, 116/134 (86.6%) were diagnosed by ES alone. An additional 15/134 (11.2%) were diagnosed by CMA alone, including two likely changes. Three (2.2%) participants had diagnostic molecular findings from both ES and CMA, including two compound heterozygotes and one participant with two distinct diagnoses. Half of the participants with CMA contribution to diagnosis had CNVs in at least one non-immune gene, highlighting the clinical complexity of these cases. Overall, CMA contributed to 18/134 diagnoses (13.4%), increasing the overall diagnostic yield by 15.5% beyond ES alone.
CONCLUSION
Pairing ES and CMA can provide a comprehensive evaluation to clarify the complex factors that contribute to both immune and non-immune phenotypes. Such a combined approach to genetic testing helps untangle complex phenotypes, not only by clarifying the differential diagnosis, but in some cases by identifying multiple diagnoses contributing to the overall clinical presentation.
Topics: Humans; Child; Exome Sequencing; Microarray Analysis; Chromosomes; Genetic Testing; Phenotype
PubMed: 37215141
DOI: 10.3389/fimmu.2023.1172004 -
Statistical Methods in Medical Research Aug 2022A cancer diagnosis is part of a complex stochastic process, which involves patient's characteristics, diagnosing methods, an initial assessment of cancer progression,...
A cancer diagnosis is part of a complex stochastic process, which involves patient's characteristics, diagnosing methods, an initial assessment of cancer progression, treatments and a certain outcome of interest. To evaluate the performance of diagnoses, one needs not only a consistent estimation of the causal effect under a specified regime of diagnoses and treatments but also reliable confidence interval, -value and hypothesis testing of the causal effect. In this article, we identify causal effects under various regimes of diagnoses and treatments by the point effects of diagnoses and treatments and thus are able to estimate and test these causal effects by estimating and testing point effects in the familiar framework of single-point causal inference. Specifically, using data from a Swedish prognosis study of stomach cancer, we estimate and test the causal effects on cancer survival under various regimes of diagnosing and treating hospitals including the optimal regime. We also estimate and test the modification of the causal effect by age. With its simple setting, one can readily extend the example to a large variety of settings in the area of cancer diagnosis: different personal characteristics such as family history, different diagnosing procedures such as multistage screening, and different cancer outcomes such as cancer progression.
Topics: Causality; Early Detection of Cancer; Humans; Neoplasms; Prognosis; Research Design; Treatment Outcome
PubMed: 35509212
DOI: 10.1177/09622802221098429 -
Cancer Medicine Aug 2023Endoscopic ultrasonography-guided fine-needle aspiration/biopsy (EUS-FNA/B) is considered to be a first-line procedure for the pathological diagnosis of pancreatic...
BACKGROUND AND AIMS
Endoscopic ultrasonography-guided fine-needle aspiration/biopsy (EUS-FNA/B) is considered to be a first-line procedure for the pathological diagnosis of pancreatic cancer owing to its high accuracy and low complication rate. The number of new cases of pancreatic ductal adenocarcinoma (PDAC) is increasing, and its accurate pathological diagnosis poses a challenge for cytopathologists. Our aim was to develop a hyperspectral imaging (HSI)-based convolution neural network (CNN) algorithm to aid in the diagnosis of pancreatic EUS-FNA cytology specimens.
METHODS
HSI images were captured of pancreatic EUS-FNA cytological specimens from benign pancreatic tissues (n = 33) and PDAC (n = 39) prepared using a liquid-based cytology method. A CNN was established to test the diagnostic performance, and Attribution Guided Factorization Visualization (AGF-Visualization) was used to visualize the regions of important classification features identified by the model.
RESULTS
A total of 1913 HSI images were obtained. Our ResNet18-SimSiam model achieved an accuracy of 0.9204, sensitivity of 0.9310 and specificity of 0.9123 (area under the curve of 0.9625) when trained on HSI images for the differentiation of PDAC cytological specimens from benign pancreatic cells. AGF-Visualization confirmed that the diagnoses were based on the features of tumor cell nuclei.
CONCLUSIONS
An HSI-based model was developed to diagnose cytological PDAC specimens obtained using EUS-guided sampling. Under the supervision of experienced cytopathologists, we performed multi-staged consecutive in-depth learning of the model. Its superior diagnostic performance could be of value for cytologists when diagnosing PDAC.
Topics: Humans; Endoscopic Ultrasound-Guided Fine Needle Aspiration; Cytology; Deep Learning; Pancreatic Neoplasms; Carcinoma, Pancreatic Ductal
PubMed: 37455599
DOI: 10.1002/cam4.6335 -
Journal of Orthopaedic Surgery and... Dec 2022For knee osteoarthritis, the commonly used radiology severity criteria Kellgren-Lawrence lead to variability among surgeons. Most existing diagnosis models require...
BACKGROUND
For knee osteoarthritis, the commonly used radiology severity criteria Kellgren-Lawrence lead to variability among surgeons. Most existing diagnosis models require preprocessed radiographs and specific equipment.
METHODS
All enrolled patients diagnosed with KOA who met the criteria were obtained from **** Hospital. This study included 2579 images shot from posterior-anterior X-rays of 2,378 patients. We used RefineDet to train and validate this deep learning-based diagnostic model. After developing the model, 823 images of 697 patients were enrolled as the test set. The whole test set was assessed by up to 5 surgeons and this diagnostic model. To evaluate the model's performance we compared the results of the model with the KOA severity diagnoses of surgeons based on K-L scales.
RESULTS
Compared to the diagnoses of surgeons, the model achieved an overall accuracy of 0.977. Its sensitivity (recall) for K-L 0 to 4 was 1.0, 0.972, 0.979, 0.983 and 0.989, respectively; for these diagnoses, the specificity of this model was 0.992, 0.997, 0.994, 0.991 and 0.995. The precision and F1-score were 0.5 and 0.667 for K-L 0, 0.914 and 0.930 for K-L 1, 0.978 and 0.971 for K-L 2, 0.981 and 0.974 for K-L 3, and 0.988 and 0.985 for K-L 4, respectively. All K-L scales perform AUC > 0.90. The quadratic weighted Kappa coefficient between the diagnostic model and surgeons was 0.815 (P < 0.01, 95% CI 0.727-0.903). The performance of the model is comparable to the clinical diagnosis of KOA. This model improved the efficiency and avoided cumbersome image preprocessing.
CONCLUSION
The deep learning-based diagnostic model can be used to assess the severity of KOA in portable devices according to the Kellgren-Lawrence scale. On the premise of improving diagnostic efficiency, the results are highly reliable and reproducible.
Topics: Humans; Osteoarthritis, Knee; Deep Learning; Radiography; Knee Joint
PubMed: 36514158
DOI: 10.1186/s13018-022-03429-2 -
Folia Neuropathologica 2021This study has assessed the diagnostic ability of oligodendrocyte-2 (Olig2), CD99, and epithelial membrane antigen (EMA) immunohistochemical stains to diagnose...
INTRODUCTION
This study has assessed the diagnostic ability of oligodendrocyte-2 (Olig2), CD99, and epithelial membrane antigen (EMA) immunohistochemical stains to diagnose oligodendroglial-like neoplasms as central neurocytoma, ependymoma, or oligodendroglioma.
MATERIAL AND METHODS
An immunohistochemistry (IHC) panel of Olig2, EMA, and CD99 was performed on 18 central neurocytomas, 46 ependymomas, and 28 oligodendrogliomas. A quantitative labelling index of stained tumor cells was assessed using a scoring system, and its diagnostic predictability was evaluated with multinomial logistic regression.
RESULTS
Significant differences in IHC expression patterns were observed between all tumor groups (p < 0.001). The labeling indices of the histochemical expression of Olig2, EMA, and CD99 were related to diagnostic predictability. Olig2 was unlikely to differentiate ependymoma from central neurocytoma (p = 0.154), while EMA and CD99 were significant in diagnosing these two tumors (p < 0.05). Olig2 was a specific marker of oligodendroglioma, differentiating it from ependymoma and central neurocytoma (p 0.05), but CD99 significantly differentiated ependymoma from oligodendroglioma (p = 0.022). These labelling indices were used to re-assess the diagnostic accuracy, regardless of tumor location and histology, and yielded significantly different tumor diagnoses.
CONCLUSIONS
The IHC panel of Olig2, EMA, and CD99 should be used to differentiate oligodendroglial-like neoplasms. Olig2 is a specific IHC marker to diagnose oligodendroglioma and differentiate it from ependymoma and central neurocytoma. Lack of Olig2 expression rules out oligodendroglioma and suggests the diagnosis of ependymoma rather than central neurocytoma if the EMA labelling index shows diffuse/partial expression. CD99 is considered a sensitive marker for ependymoma but not central neurocytoma.
Topics: 12E7 Antigen; Biomarkers, Tumor; Brain Neoplasms; Ependymoma; Humans; Mucin-1; Neurocytoma; Oligodendrocyte Transcription Factor 2; Oligodendroglia; Oligodendroglioma
PubMed: 34628794
DOI: 10.5114/fn.2021.108526