-
Journal of Magnetic Resonance Imaging :... Dec 2023Hepatocellular carcinoma (HCC) can be diagnosed without pathologic confirmation in high-risk patients. Therefore, it is necessary to compare current imaging criteria for... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Hepatocellular carcinoma (HCC) can be diagnosed without pathologic confirmation in high-risk patients. Therefore, it is necessary to compare current imaging criteria for noninvasive-diagnosis of HCC.
PURPOSE
To systematically compare performance of 2018 European Association for the Study of the Liver (EASL) criteria and Liver Imaging Reporting and Data System (LI-RADS) for noninvasive-diagnosis of HCC.
STUDY TYPE
Systematic review and meta-analysis.
SUBJECTS
Eight studies with 2232 observations, including 1617 HCCs.
FIELD STRENGTH/SEQUENCE
1.5 T, 3.0 T/T2-weighted, unenhanced T1-weighted in-/opposed-phases, multiphase T1-weighted imaging.
ASSESSMENT
Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, two reviewers independently reviewed and extracted data, including patient characteristics, index test, reference standard and outcomes, from studies intraindividually comparing the sensitivities and specificities of 2018 EASL-criteria and LR-5 of LI-RADS for HCC. Risk of bias and concerns regarding applicability were evaluated using QUADAS-2 tool. Subgroup analysis was performed based on observation size (≥20 mm, 10-19 mm).
STATISTICAL TESTS
Bivariate random-effects model to calculate pooled per-observation sensitivity and specificity of both imaging criteria, and pooled estimates of intraindividual paired data were compared considering the correlation. Forest and linked-receiver-operating-characteristic plots were drawn, and study heterogeneity was assessed using Q-test and Higgins-index. Publication bias was evaluated by Egger's test. A P-value <0.05 was considered statistically significant, except for heterogeneity (P < 0.10).
RESULTS
The sensitivity for HCC did not differ significantly between the imaging-based diagnosis using EASL-criteria (61%; 95% CI, 50%-73%) and LR-5 (64%; 95% CI, 53%-76%; P = 0.165). The specificities were also not significantly different between EASL-criteria (92%; 95% CI, 89%-94%) and LR-5 (94%; 95% CI, 91%-96%; P = 0.257). In subgroup analysis, no statistically significant differences were identified in the pooled performances between the two criteria for observations ≥20 mm (sensitivity P = 0.065; specificity P = 0.343) or 10-19 mm (sensitivity P > 0.999; specificity P = 0.851). There was no publication bias for EASL (P = 0.396) and LI-RADS (P = 0.526).
DATA CONCLUSION
In the present meta-analysis of paired comparisons, the pooled sensitivities and specificities were not significantly different between 2018 EASL-criteria and LR-5 of LI-RADS for noninvasive-diagnosis of HCC.
EVIDENCE LEVEL
3.
TECHNICAL EFFICACY
Stage 2.
Topics: Humans; Carcinoma, Hepatocellular; Liver Neoplasms; Magnetic Resonance Imaging; Sensitivity and Specificity; Retrospective Studies; Tomography, X-Ray Computed; Contrast Media
PubMed: 37010244
DOI: 10.1002/jmri.28716 -
JAMA Jun 2024Among all US women, breast cancer is the second most common cancer and the second most common cause of cancer death. In 2023, an estimated 43 170 women died of breast...
IMPORTANCE
Among all US women, breast cancer is the second most common cancer and the second most common cause of cancer death. In 2023, an estimated 43 170 women died of breast cancer. Non-Hispanic White women have the highest incidence of breast cancer and non-Hispanic Black women have the highest mortality rate.
OBJECTIVE
The USPSTF commissioned a systematic review to evaluate the comparative effectiveness of different mammography-based breast cancer screening strategies by age to start and stop screening, screening interval, modality, use of supplemental imaging, or personalization of screening for breast cancer on the incidence of and progression to advanced breast cancer, breast cancer morbidity, and breast cancer-specific or all-cause mortality, and collaborative modeling studies to complement the evidence from the review.
POPULATION
Cisgender women and all other persons assigned female at birth aged 40 years or older at average risk of breast cancer.
EVIDENCE ASSESSMENT
The USPSTF concludes with moderate certainty that biennial screening mammography in women aged 40 to 74 years has a moderate net benefit. The USPSTF concludes that the evidence is insufficient to determine the balance of benefits and harms of screening mammography in women 75 years or older and the balance of benefits and harms of supplemental screening for breast cancer with breast ultrasound or magnetic resonance imaging (MRI), regardless of breast density.
RECOMMENDATION
The USPSTF recommends biennial screening mammography for women aged 40 to 74 years. (B recommendation) The USPSTF concludes that the current evidence is insufficient to assess the balance of benefits and harms of screening mammography in women 75 years or older. (I statement) The USPSTF concludes that the current evidence is insufficient to assess the balance of benefits and harms of supplemental screening for breast cancer using breast ultrasonography or MRI in women identified to have dense breasts on an otherwise negative screening mammogram. (I statement).
Topics: Humans; Breast Neoplasms; Female; Mammography; Early Detection of Cancer; Middle Aged; Aged; Adult; Magnetic Resonance Imaging; Age Factors; Ultrasonography, Mammary; United States; Mass Screening
PubMed: 38687503
DOI: 10.1001/jama.2024.5534 -
Graefe's Archive For Clinical and... Jul 2024The aim of this article is to conduct a comprehensive systematic review about the current understandings and differential diagnosis of myopic choroidal... (Review)
Review
PURPOSE
The aim of this article is to conduct a comprehensive systematic review about the current understandings and differential diagnosis of myopic choroidal neovascularization (mCNV) and other several similar diseases, describing their multimodal imaging analysis, prognostic implications, and current types of management.
METHODS
This systematic review was performed based on a search on the PubMed database of relevant papers regarding mCNV and other entities discussed in the paper, according to our current knowledge.
RESULTS
Through the integration of a multimodal imaging approach, especially optical coherence tomography (OCT), along with accurate demographic and clinical assessment, it becomes possible to effectively differentiate mCNV from similar yet heterogeneous entities. These conditions include macular hemorrhage due to new lacquer crack (LC) formation, inflammatory diseases such as punctate inner choroidopathy (PIC)/multifocal choroidits (MFC) and epiphenomenon multiple evanescent white dot syndrome (Epi-MEWDS), neovascular age-related macular degeneration (nAMD), idiopathic CNV (ICNV), dome-shaped macula (DSM) with subretinal fluid, retinal pigment epithelium (RPE) humps, angioid streaks (AS), choroidal rupture (CR), and choroidal osteoma (CO). Each one of these entities will be described and discussed in this article.
CONCLUSION
Myopic choroidal neovascularization is a common retinal condition, especially among young individuals. Accurate diagnosis and differentiation from similar conditions are crucial for effective treatment. Multimodal imaging, particularly OCT, plays a crucial role in precise assessment. Future research should focus on defining biomarkers and distinguishing features to facilitate prompt treatment.
Topics: Humans; Multimodal Imaging; Choroidal Neovascularization; Diagnosis, Differential; Tomography, Optical Coherence; Myopia, Degenerative; Fluorescein Angiography; Choroid; Fundus Oculi
PubMed: 38060000
DOI: 10.1007/s00417-023-06320-w -
Journal of Endocrinological... May 2024The role of overweight and obesity in the development of atrial fibrillation (AF) is well established; however, the differential effect on the occurrence and recurrence... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND AND AIMS
The role of overweight and obesity in the development of atrial fibrillation (AF) is well established; however, the differential effect on the occurrence and recurrence of AF remains uncertain. The aim of this review is to compare the effect of underweight and varying degrees of obesity on onset of AF and in recurrent post-ablation AF, and, when possible, in relation to sex.
METHODS
A systematic literature search was conducted in PubMed, Embase, and Cochrane Library from inception to January 31, 2023. Studies reporting frequency of newly-diagnosed AF and of recurrent post-ablation AF in different BMI categories, were included. 3400 records were screened and 50 met the inclusion criteria. Standardized data search and abstraction were performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) Statement. Data were extracted from the manuscripts and were analyzed using a random effect model. The outcome was the occurrence of AF in population studies and in patients undergoing ablation.
RESULTS
Data from 50 studies were collected, of which 27 for newly-diagnosed AF and 23 for recurrent post-ablation AF, for a total of 15,134,939 patients, of which 15,115,181 in studies on newly-diagnosed AF and 19,758 in studies on recurrent post-ablation AF. Compared to normal weight, the increase in AF was significant (p < 0.01) for overweight, obese, and morbidly obese patients for newly-diagnosed AF, and for obese and morbidly obese patients for recurrent post-ablation AF. Newly-diagnosed AF was more frequent in obese female than obese male patients.
CONCLUSION
The effect of increased BMI was greater on the onset of AF, and obese women were more affected than men.
Topics: Humans; Atrial Fibrillation; Obesity; Recurrence; Catheter Ablation; Body Mass Index; Postoperative Complications; Risk Factors; Female
PubMed: 37962809
DOI: 10.1007/s40618-023-02225-x -
Journal of Medical Internet Research Oct 2023Frailty syndrome (FS) is one of the most common noncommunicable diseases, which is associated with lower physical and mental capacities in older adults. FS diagnosis is... (Review)
Review
BACKGROUND
Frailty syndrome (FS) is one of the most common noncommunicable diseases, which is associated with lower physical and mental capacities in older adults. FS diagnosis is mostly focused on biological variables; however, it is likely that this diagnosis could fail owing to the high biological variability in this syndrome. Therefore, artificial intelligence (AI) could be a potential strategy to identify and diagnose this complex and multifactorial geriatric syndrome.
OBJECTIVE
The objective of this scoping review was to analyze the existing scientific evidence on the use of AI for the identification and diagnosis of FS in older adults, as well as to identify which model provides enhanced accuracy, sensitivity, specificity, and area under the curve (AUC).
METHODS
A search was conducted using PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines on various databases: PubMed, Web of Science, Scopus, and Google Scholar. The search strategy followed Population/Problem, Intervention, Comparison, and Outcome (PICO) criteria with the population being older adults; intervention being AI; comparison being compared or not to other diagnostic methods; and outcome being FS with reported sensitivity, specificity, accuracy, or AUC values. The results were synthesized through information extraction and are presented in tables.
RESULTS
We identified 26 studies that met the inclusion criteria, 6 of which had a data set over 2000 and 3 with data sets below 100. Machine learning was the most widely used type of AI, employed in 18 studies. Moreover, of the 26 included studies, 9 used clinical data, with clinical histories being the most frequently used data type in this category. The remaining 17 studies used nonclinical data, most frequently involving activity monitoring using an inertial sensor in clinical and nonclinical contexts. Regarding the performance of each AI model, 10 studies achieved a value of precision, sensitivity, specificity, or AUC ≥90.
CONCLUSIONS
The findings of this scoping review clarify the overall status of recent studies using AI to identify and diagnose FS. Moreover, the findings show that the combined use of AI using clinical data along with nonclinical information such as the kinematics of inertial sensors that monitor activities in a nonclinical context could be an appropriate tool for the identification and diagnosis of FS. Nevertheless, some possible limitations of the evidence included in the review could be small sample sizes, heterogeneity of study designs, and lack of standardization in the AI models and diagnostic criteria used across studies. Future research is needed to validate AI systems with diverse data sources for diagnosing FS. AI should be used as a decision support tool for identifying FS, with data quality and privacy addressed, and the tool should be regularly monitored for performance after being integrated in clinical practice.
Topics: Humans; Aged; Artificial Intelligence; Frail Elderly; Frailty; Machine Learning; Area Under Curve
PubMed: 37862082
DOI: 10.2196/47346 -
Clinical and Experimental Medicine Oct 2023Breast cancer was the fourth leading cause of cancer-related death worldwide, and early mammography screening could decrease the breast cancer mortality. Artificial... (Meta-Analysis)
Meta-Analysis
Breast cancer was the fourth leading cause of cancer-related death worldwide, and early mammography screening could decrease the breast cancer mortality. Artificial intelligence (AI)-assisted diagnose system based on machine learning (ML) methods can help improve the screening accuracy and efficacy. This study aimed to systematically review and make a meta-analysis on the diagnostic accuracy of mammography diagnosis of breast cancer through various ML methods. Springer Link, Science Direct (Elsevier), IEEE Xplore, PubMed and Web of Science were searched for relevant studies published from January 2000 to September 2021. The study was registered with the PROSPERO International Prospective Register of Systematic Reviews (protocol no. CRD42021284227). A Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) was used to assess the included studies, and reporting was evaluated using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA). The pooled summary estimates for sensitivity, specificity, the area under the receiver operating characteristic curve (AUC) for three ML methods (convolutional neural network [CNN], artificial neural network [ANN], support vector machine [SVM]) were calculated. A total of 32 studies with 23,804 images were included in the meta-analysis. The overall pooled estimate for sensitivity, specificity and AUC was 0.914 [95% CI 0.868-0.945], 0.916 [95% CI 0.873-0.945] and 0.945 for mammography diagnosis of breast cancer through three ML methods. The pooled sensitivity, specificity and AUC of CNN were 0.961 [95% CI 0.886-0.988], 0.950 [95% CI 0.924-0.967] and 0.974. The pooled sensitivity, specificity and AUC of ANN were 0.837 [95% CI 0.772-0.886], 0.894 [95% CI 0.764-0.957] and 0.881. The pooled sensitivity, specificity and AUC of SVM were 0.889 [95% CI 0.807-0.939], 0.843 [95% CI 0.724-0.916] and 0.913. Machine learning methods (especially CNN) show excellent performance in mammography diagnosis of breast cancer screening based on retrospective studies. More rigorous prospective studies are needed to evaluate the longitudinal performance of AI.
Topics: Humans; Female; Breast Neoplasms; Artificial Intelligence; Retrospective Studies; Early Detection of Cancer; Mammography; Machine Learning
PubMed: 36242643
DOI: 10.1007/s10238-022-00895-0 -
Journal of the American Heart... Sep 2023Current recommendations support a personalized sequential approach for cardiac rhythm monitoring to detect atrial fibrillation after embolic stroke of undetermined... (Review)
Review
Current recommendations support a personalized sequential approach for cardiac rhythm monitoring to detect atrial fibrillation after embolic stroke of undetermined source. Several risk stratification scores have been proposed to predict the likelihood of atrial fibrillation after embolic stroke of undetermined source. This systematic review aimed to provide a comprehensive overview of the field by identifying risk scores proposed for this purpose, assessing their characteristics and the cohorts in which they were developed and validated, and scrutinizing their predictive performance. We identified 11 risk scores, of which 4 were externally validated. The most frequent variables included were echocardiographic markers and demographics. The areas under the curve ranged between 0.70 and 0.94. The 3 scores with the highest area under the curve were the Decryptoring (0.94 [95% CI, 0.88-1.00]), newly diagnosed atrial fibrillation (0.87 [95% CI, 0.79-0.94]), and AF-ESUS (Atrial Fibrillation in Embolic Stroke of Undetermined Source) (0.85 [95% CI, 0.80-0.87]), of which only the latter was externally validated. Risk stratification scores can guide a personalized approach for cardiac rhythm monitoring after embolic stroke of undetermined source.
Topics: Humans; Atrial Fibrillation; Embolic Stroke; Echocardiography; Risk Factors; Risk Assessment
PubMed: 37681521
DOI: 10.1161/JAHA.123.030479 -
Journal of Biomedical Optics Jan 2024Cutaneous melanoma (CM) has a high morbidity and mortality rate, but it can be cured if the primary lesion is detected and treated at an early stage. Imaging techniques... (Review)
Review
SIGNIFICANCE
Cutaneous melanoma (CM) has a high morbidity and mortality rate, but it can be cured if the primary lesion is detected and treated at an early stage. Imaging techniques such as photoacoustic (PA) imaging (PAI) have been studied and implemented to aid in the detection and diagnosis of CM.
AIM
Provide an overview of different PAI systems and applications for the study of CM, including the determination of tumor depth/thickness, cancer-related angiogenesis, metastases to lymph nodes, circulating tumor cells (CTCs), virtual histology, and studies using exogenous contrast agents.
APPROACH
A systematic review and classification of different PAI configurations was conducted based on their specific applications for melanoma detection. This review encompasses animal and preclinical studies, offering insights into the future potential of PAI in melanoma diagnosis in the clinic.
RESULTS
PAI holds great clinical potential as a noninvasive technique for melanoma detection and disease management. PA microscopy has predominantly been used to image and study angiogenesis surrounding tumors and provide information on tumor characteristics. Additionally, PA tomography, with its increased penetration depth, has demonstrated its ability to assess melanoma thickness. Both modalities have shown promise in detecting metastases to lymph nodes and CTCs, and an all-optical implementation has been developed to perform virtual histology analyses. Animal and human studies have successfully shown the capability of PAI to detect, visualize, classify, and stage CM.
CONCLUSIONS
PAI is a promising technique for assessing the status of the skin without a surgical procedure. The capability of the modality to image microvasculature, visualize tumor boundaries, detect metastases in lymph nodes, perform fast and label-free histology, and identify CTCs could aid in the early diagnosis and classification of CM, including determination of metastatic status. In addition, it could be useful for monitoring treatment efficacy noninvasively.
Topics: Animals; Humans; Melanoma; Skin Neoplasms; Photoacoustic Techniques; Early Detection of Cancer; Tomography, X-Ray Computed
PubMed: 38223680
DOI: 10.1117/1.JBO.29.S1.S11518 -
Journal of Pediatric Hematology/oncology Aug 2023Pediatric cancer patients have an increased risk of stroke. However, there is a knowledge gap regarding stroke in early stages of pediatric cancer. The objective of this...
OBJECTIVE
Pediatric cancer patients have an increased risk of stroke. However, there is a knowledge gap regarding stroke in early stages of pediatric cancer. The objective of this project is to describe the current knowledge on stroke in pediatric cancer patients.
DESIGN
Systematic review.
MATERIALS AND METHODS
After Preferred Reporting Items for Systematic Review and Meta-Analysis guidelines, literature search was conducted in PubMed, Cochrane, and Google Scholar from January 1, 1995, up to February 1, 2022.
RESULTS
A total of 3499 studies were identified, of which 8 met inclusion criteria. The incidence of stroke in pediatric cancer patients varied between 0.47% and 2.9%, and prevalence between 1% and 3%. The risk factors identified were leukemia diagnosis, cranial radiation, thrombocytopenia, coagulopathy, and infection. There was a higher rate of diagnosis with magnetic resonance imaging than with computed tomography scan. Treatment was inconsistent, and patients with cancer were less likely to receive antithrombotic treatment when compared with patients without cancer. The highest mortality was among hemorrhagic stroke. Recurrence rate was 5% to 19%.
CONCLUSIONS
The risk for stroke is increased in the pediatric cancer population and can lead to devastating results. The available reports include few patients, with heterogeneous cancer diagnoses and outcomes. Large-scale multicenter studies are needed, focusing on early diagnosis, risk factors, and management strategies of stroke in children with underlying cancer.
Topics: Child; Humans; Stroke; Neoplasms; Tomography, X-Ray Computed; Hemorrhagic Stroke
PubMed: 36716019
DOI: 10.1097/MPH.0000000000002622 -
Computer Methods and Programs in... Feb 2024Non-alcoholic fatty liver disease (NAFLD) is a common liver disease with a rapidly growing incidence worldwide. For prognostication and therapeutic decisions, it is... (Review)
Review
BACKGROUND AND OBJECTIVES
Non-alcoholic fatty liver disease (NAFLD) is a common liver disease with a rapidly growing incidence worldwide. For prognostication and therapeutic decisions, it is important to distinguish the pathological stages of NAFLD: steatosis, steatohepatitis, and liver fibrosis, which are definitively diagnosed on invasive biopsy. Non-invasive ultrasound (US) imaging, including US elastography technique, and clinical parameters can be used to diagnose and grade NAFLD and its complications. Artificial intelligence (AI) is increasingly being harnessed for developing NAFLD diagnostic models based on clinical, biomarker, or imaging data. In this work, we systemically reviewed the literature for AI-enabled NAFLD diagnostic models based on US (including elastography) and clinical (including serological) data.
METHODS
We performed a comprehensive search on Google Scholar, Scopus, and PubMed search engines for articles published between January 2005 and June 2023 related to AI models for NAFLD diagnosis based on US and/or clinical parameters using the following search terms: "non-alcoholic fatty liver disease", "non-alcoholic steatohepatitis", "deep learning", "machine learning", "artificial intelligence", "ultrasound imaging", "sonography", "clinical information".
RESULTS
We reviewed 64 published models that used either US (including elastography) or clinical data input to detect the presence of NAFLD, non-alcoholic steatohepatitis, and/or fibrosis, and in some cases, the severity of steatosis, inflammation, and/or fibrosis as well. The performances of the published models were summarized, and stratified by data input and algorithms used, which could be broadly divided into machine and deep learning approaches.
CONCLUSION
AI models based on US imaging and clinical data can reliably detect NAFLD and its complications, thereby reducing diagnostic costs and the need for invasive liver biopsy. The models offer advantages of efficiency, accuracy, and accessibility, and serve as virtual assistants for specialists to accelerate disease diagnosis and reduce treatment costs for patients and healthcare systems.
Topics: Humans; Artificial Intelligence; Biomarkers; Biopsy; Liver; Liver Cirrhosis; Non-alcoholic Fatty Liver Disease; Ultrasonography
PubMed: 38008040
DOI: 10.1016/j.cmpb.2023.107932