-
PeerJ 2023To explore the potential value of magnetic resonance (MR) and computed tomography (CT) enterography in the diagnosis of small intestinal tumor (SIT). (Meta-Analysis)
Meta-Analysis
OBJECTIVE
To explore the potential value of magnetic resonance (MR) and computed tomography (CT) enterography in the diagnosis of small intestinal tumor (SIT).
METHODS
Articles reporting on the diagnosis of SIT by MR and CT enterography deposited in Chinese and foreign literature databases were identified and evaluated using the quality assessment of diagnostic accuracy studies (QUADAS). The diagnostic data extracted from the articles were adopted for meta-analysis using Meta-disc 1.40 software. Analysis was undertaken to compare the sensitivity, specificity, positive and negative likelihood ratios, and the diagnostic odds ratio (DOR) of MR and CT enterography in the diagnosis of SIT. The diagnostic values of the two imaging methods were analyzed by summary receiver operating characteristic (SROC) curves. The meta-analysis was registered at INPLASY (202380053).
RESULTS
A total of eight articles, including 551 cases of SIT were included in this analysis. The pooled sensitivity and specificity of MR enterography were 0.92 (95% CI [0.89-0.95]) and 0.81 (95% CI [0.74-0.86]), respectively, whilst CT enterography had a sensitivity of 0.93 (95% CI [0.90-0.95]) and a specificity of 0.83 (95% CI [0.76-0.88]). For MR enterography, the combined positive likelihood ratio was 4.90 (95% CI [3.50-6.70]), the combined negative likelihood ratio was 0.10 (95% CI [0.07-0.14]), and the area under the receiver operating characteristic curve (AUROC) was 0.940. For CT enterography, the corresponding values were 5.40 (95% CI [3.90-7.40]), 0.08 (95% CI [0.06-0.12]), and 0.950, respectively. When the pretest probability for MR was assumed to be 50%, the posterior probabilities for positive and negative results were calculated as 83% and 9%, respectively. For CT enterography with a pretest probability of 50%, the posterior probabilities of positive and negative results were 84% and 8%, respectively.
CONCLUSION
MR and CT enterography have high accuracy in the diagnosis of SIT and have a valuable role in the diagnosis and management of these tumors.
Topics: Humans; Magnetic Resonance Imaging; Tomography, X-Ray Computed; Sensitivity and Specificity; Intestinal Neoplasms; Magnetic Resonance Spectroscopy
PubMed: 38144202
DOI: 10.7717/peerj.16687 -
Telemedicine Journal and E-health : the... Nov 2023(Meta-Analysis)
Meta-Analysis Review
Topics: Humans; Sensitivity and Specificity; Physical Examination; Diagnosis, Oral
PubMed: 36976779
DOI: 10.1089/tmj.2022.0426 -
CA: a Cancer Journal For Clinicians 2024Current US lung cancer screening recommendations limit eligibility to adults with a pack-year (PY) history of ≥20 years and the first 15 years since quit (YSQ). The... (Review)
Review
Current US lung cancer screening recommendations limit eligibility to adults with a pack-year (PY) history of ≥20 years and the first 15 years since quit (YSQ). The authors conducted a systematic review to better understand lung cancer incidence, risk and mortality among otherwise eligible individuals in this population beyond 15 YSQ. The PubMed and Scopus databases were searched through February 14, 2023, and relevant articles were searched by hand. Included studies examined the relationship between adults with both a ≥20-PY history and ≥15 YSQ and lung cancer diagnosis, mortality, and screening ineligibility. One investigator abstracted data and a second confirmed. Two investigators independently assessed study quality and certainty of evidence (COE) and resolved discordance through consensus. From 2636 titles, 22 studies in 26 articles were included. Three studies provided low COE of elevated lung cancer incidence beyond 15 YSQ, as compared with people who never smoked, and six studies provided moderate COE that the risk of a lung cancer diagnosis after 15 YSQ declines gradually, but with no clinically significant difference just before and after 15 YSQ. Studies examining lung cancer-related disparities suggest that outcomes after 15 YSQ were similar between African American/Black and White participants; increasing YSQ would expand eligibility for African American/Black individuals, but for a significantly larger proportion of White individuals. The authors observed that the risk of lung cancer not only persists beyond 15 YSQ but that, compared with individuals who never smoked, the risk may remain significantly elevated for 2 or 3 decades. Future research of nationally representative samples with consistent reporting across studies is needed, as are better data from which to examine the effects on health disparities across different populations.
Topics: Humans; Early Detection of Cancer; Incidence; Lung Neoplasms
PubMed: 37909870
DOI: 10.3322/caac.21808 -
BMC Bioinformatics Oct 2023Recent advancements in computing power and state-of-the-art algorithms have helped in more accessible and accurate diagnosis of numerous diseases. In addition, the...
BACKGROUND
Recent advancements in computing power and state-of-the-art algorithms have helped in more accessible and accurate diagnosis of numerous diseases. In addition, the development of de novo areas in imaging science, such as radiomics and radiogenomics, have been adding more to personalize healthcare to stratify patients better. These techniques associate imaging phenotypes with the related disease genes. Various imaging modalities have been used for years to diagnose breast cancer. Nonetheless, digital breast tomosynthesis (DBT), a state-of-the-art technique, has produced promising results comparatively. DBT, a 3D mammography, is replacing conventional 2D mammography rapidly. This technological advancement is key to AI algorithms for accurately interpreting medical images.
OBJECTIVE AND METHODS
This paper presents a comprehensive review of deep learning (DL), radiomics and radiogenomics in breast image analysis. This review focuses on DBT, its extracted synthetic mammography (SM), and full-field digital mammography (FFDM). Furthermore, this survey provides systematic knowledge about DL, radiomics, and radiogenomics for beginners and advanced-level researchers.
RESULTS
A total of 500 articles were identified, with 30 studies included as the set criteria. Parallel benchmarking of radiomics, radiogenomics, and DL models applied to the DBT images could allow clinicians and researchers alike to have greater awareness as they consider clinical deployment or development of new models. This review provides a comprehensive guide to understanding the current state of early breast cancer detection using DBT images.
CONCLUSION
Using this survey, investigators with various backgrounds can easily seek interdisciplinary science and new DL, radiomics, and radiogenomics directions towards DBT.
Topics: Humans; Female; Deep Learning; Radiographic Image Enhancement; Breast; Breast Neoplasms; Mammography
PubMed: 37884877
DOI: 10.1186/s12859-023-05515-6 -
Respiratory Research Mar 2024The prognostic and theragnostic role of histopathological subsets in systemic sclerosis interstitial lung disease (SSc-ILD) have been largely neglected due to the... (Review)
Review
BACKGROUND
The prognostic and theragnostic role of histopathological subsets in systemic sclerosis interstitial lung disease (SSc-ILD) have been largely neglected due to the paucity of treatment options and the risks associated with surgical lung biopsy. The novel drugs for the treatment of ILDs and the availability of transbronchial cryobiopsy provide a new clinical scenario making lung biopsy more feasible and a pivotal guide for treatment. The aim of our study was to investigate the usefulness of lung biopsy in SSc ILD with a systematic literature review (SLR).
METHODS
PubMed, Embase and Cochrane databases were searched up to June 30, 2023. Search terms included both database-specific controlled vocabulary terms and free-text terms relating to lung biopsy and SSc-ILD diagnostic and prognosis. The SLR was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA). Studies were selected according to the PEO (population, exposure, and outcomes) framework and Quality assessment of diagnostic accuracy studies (QUADAS) were reported.
RESULTS
We selected 14 articles (comprising 364 SSc-ILD patients). The paucity and heterogeneity of the studies prevented a systematic analysis. Diffuse cutaneous SSc was present in 30-100% of cases. Female predominance was observed in all studies (ranging from 64 to 100%). Mean age ranged from 42 to 64 years. Mean FVC was 73.98 (+/-17.3), mean DLCO was 59.49 (+/-16.1). Anti-Scl70 antibodies positivity was detected in 33% of cases (range: 0-69.6). All patients underwent surgical lung biopsies, and multiple lobes were biopsied in a minority of studies (4/14). Poor HRCT-pathologic correlation was reported with HRCT-NSIP showing histopathologic UIP in up to 1/3 of cases. Limited data suggest that SSc-UIP patients may have a worse prognosis and response to immunosuppressive treatment compared to other histopathologic patterns.
CONCLUSIONS
The data from this SLR clearly show the paucity and heterogeneity of the studies reporting lung biopsy in SSc ILD. Moreover, they highlight the need for further research to address whether the lung biopsy can be helpful to refine prognostic prediction and guide therapeutic choices.
Topics: Humans; Female; Adult; Middle Aged; Male; Lung Diseases, Interstitial; Lung; Scleroderma, Systemic; Biopsy; Prognosis
PubMed: 38521926
DOI: 10.1186/s12931-024-02725-1 -
World Journal of Emergency Surgery :... Sep 2023Acute mesenteric ischaemia (AMI) is a disease with different pathophysiological mechanisms, leading to a life-threatening condition that is difficult to diagnose based... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Acute mesenteric ischaemia (AMI) is a disease with different pathophysiological mechanisms, leading to a life-threatening condition that is difficult to diagnose based solely on clinical signs. Despite widely acknowledged need for biomarkers in diagnosis of AMI, a broad systematic review on all studied biomarkers in different types of AMI is currently lacking. The aim of this study was to estimate the diagnostic accuracy of all potential biomarkers of AMI studied in humans.
METHODS
A systematic literature search in PubMed, The Cochrane Library, Web of Science and Scopus was conducted in December 2022. Studies assessing potential biomarkers of AMI in (at least 10) adult patients and reporting their diagnostic accuracy were included. Meta-analyses of biomarkers' sensitivity, specificity, and positive and negative likelihood ratios were conducted. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed, and the study quality was assessed with the QUADAS-2 tool.
RESULTS
Seventy-five studies including a total of 9914 patients assessed 18 different biomarkers in serum/plasma and one in urine (each reported in at least two studies), which were included in meta-analyses. None of the biomarkers reached a conclusive level for accurate prediction. The best predictive value overall (all studies with any type and stage of AMI pooled) was observed for Ischaemia-modified albumin (2 studies, sensitivity 94.7 and specificity 90.5), interleukin-6 (n = 4, 96.3 and 82.6), procalcitonin (n = 6, 80.1 and 86.7), and intestinal fatty acid-binding protein (I-FABP) measured in serum (n = 16, 73.9 and 90.5) or in urine (n = 4, 87.9 and 78.9). In assessment of transmural mesenteric ischaemia, urinary I-FABP (n = 2, 92.3 and 85.2) and D-dimer (n = 3, 87.6 and 83.6) showed moderate predictive value. Overall risk of bias was high, mainly because of selected study populations and unclear timings of the biomarker measurements after onset of symptoms. Combinations of biomarkers were rarely studied, not allowing meta-analyses.
CONCLUSIONS
None of the studied biomarkers had sufficient sensitivity and specificity to diagnose AMI, although some biomarkers showed moderate predictive accuracy. Future studies should focus on timing of measurements of biomarkers, distinguishing between early stage and transmural necrosis, and between different types of AMI. Additionally, studies on combinations of biomarkers are warranted. PROSPERO registration: CRD42022379341.
Topics: Humans; Adult; Mesenteric Ischemia; Biomarkers; Serum Albumin; Interleukin-6; Necrosis
PubMed: 37658356
DOI: 10.1186/s13017-023-00512-9 -
Rheumatology International Aug 2023General Joint Hypermobility (GJH) is a common condition found in 2-57% of the population. Of those with GJH, 10% suffer from accompanying physical and/or psychological...
General Joint Hypermobility (GJH) is a common condition found in 2-57% of the population. Of those with GJH, 10% suffer from accompanying physical and/or psychological symptoms. While the understanding of GJH in the general population is unfolding, its implication in a cohort of children, adolescents and young adults are not yet understood. This systematic review explored GJH's prevalence, tools to measure it, its physical and psychosocial symptoms, with a special interest in aesthetic sports. The CINHAL, MEDLINE, PsycINFO, SPORTDiscus and Scopus databases were searched for relevant studies. Inclusion criteria were (1) Age range of 5-24; (2) Participants had GJH; (3) A measurement for GJH; (4) Studies written in English language. Study screening for title, abstract and full text (when needed) and quality assessment were performed by two independent individuals. 107 studies were included in this review and were thematically grouped into six clusters expressing different foci: (1) GJH's Core Characteristics; (2) Orthopedic; (3) Physical Other; (4) Psychosocial; (5) Treatment and (6) Aesthetic Sports. The review revealed a growing interest in GJH in this cohort in the last decade, especially regarding non-musculoskeletal physical implications and psychosocial aspects. Prevalence varied between different ethnic groups and as a parameter of age, gender and measurement. The most widespread tool to measure GJH was the Beighton scale, with a cut-off varying between 4 and 7. Children show fewer, but similar GJH implication to those in the general population, however, more research on the topic is warranted, especially regarding psychosocial aspects and treatment.
Topics: Child; Young Adult; Humans; Adolescent; Adult; Prevalence; Cross-Sectional Studies; Physical Examination; Joint Instability
PubMed: 37149553
DOI: 10.1007/s00296-023-05338-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 -
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 -
Cancer Medicine Aug 2023Positron emission tomography (PET) images of head and neck squamous cell carcinoma (HNSCC) patients can assess the functional and biochemical processes at cellular... (Meta-Analysis)
Meta-Analysis Review
A systematic review and meta-analysis of predictive and prognostic models for outcome prediction using positron emission tomography radiomics in head and neck squamous cell carcinoma patients.
BACKGROUND
Positron emission tomography (PET) images of head and neck squamous cell carcinoma (HNSCC) patients can assess the functional and biochemical processes at cellular levels. Therefore, PET radiomics-based prediction and prognostic models have the potentials to understand tumour heterogeneity and assist clinicians with diagnosis, prognosis and management of the disease. We conducted a systematic review of published modelling information to evaluate the usefulness of PET radiomics in the prediction and prognosis of HNSCC patients.
METHODS
We searched bibliographic databases (MEDLINE, Embase, Web of Science) from 2010 to 2021 and considered 31 studies with pre-defined inclusion criteria. We followed the CHARMS checklist for data extraction and performed quality assessment using the PROBAST tool. We conducted a meta-analysis to estimate the accuracy of the prediction and prognostic models using the diagnostic odds ratio (DOR) and average C-statistic, respectively.
RESULTS
Manual segmentation method followed by 40% of the maximum standardised uptake value (SUV ) thresholding is a commonly used approach. The area under the receiver operating curves of externally validated prediction models ranged between 0.60-0.87, 0.65-0.86 and 0.62-0.75 for overall survival, distant metastasis and recurrence, respectively. Most studies highlighted an overall high risk of bias (outcome definition, statistical methodologies and external validation of models) and high unclear concern in terms of applicability. The meta-analysis showed the estimated pooled DOR of 6.75 (95% CI: 4.45, 10.23) for prediction models and the C-statistic of 0.71 (95% CI: 0.67, 0.74) for prognostic models.
CONCLUSIONS
Both prediction and prognostic models using clinical variables and PET radiomics demonstrated reliable accuracy for detecting adverse outcomes in HNSCC, suggesting the prospect of PET radiomics in clinical settings for diagnosis, prognosis and management of HNSCC patients. Future studies of prediction and prognostic models should emphasise the quality of reporting, external model validation, generalisability to real clinical scenarios and enhanced reproducibility of results.
Topics: Humans; Squamous Cell Carcinoma of Head and Neck; Prognosis; Reproducibility of Results; Positron-Emission Tomography; Head and Neck Neoplasms; Fluorodeoxyglucose F18
PubMed: 37353996
DOI: 10.1002/cam4.6278