Magnetic Resonance Imaging for Surveillance of Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis.
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ABSTRACT:
SUBMITTER: Kim DH
PROVIDER: S-EPMC8469328 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:We aimed to determine the performance of surveillance abbreviated magnetic resonance imaging (AMRI) for detecting hepatocellular carcinoma (HCC), and to compare the performance of surveillance AMRI according to different protocols. Original research studies reporting the performance of surveillance AMRI for the detection of HCC were identified in MEDLINE, EMBASE, and Cochrane databases. The pooled sensitivity and specificity of surveillance AMRI were calculated using a hierarchical model. The pooled sensitivity and specificity of contrast-enhanced hepatobiliary phase (HBP)-AMRI and non-contrast (NC)-AMRI were calculated and compared using bivariate meta-regression. Ten studies, including 1547 patients, reported the accuracy of surveillance AMRI. The pooled sensitivity and specificity of surveillance AMRI for detecting any-stage HCC were 86% (95% confidence interval (CI), 80-90%; I2 = 0%) and 96% (95% CI, 93-98%; I2 = 80.5%), respectively. HBP-AMRI showed a significantly higher sensitivity for detecting HCC than NC-AMRI (87% vs. 82%), but significantly lower specificity (93% vs. 98%) (p = 0.03). Study quality and MRI magnet field strength were factors significantly associated with study heterogeneity (p ≤ 0.01). In conclusion, surveillance AMRI showed good overall diagnostic performance for detecting HCC. HBP-AMRI had significantly higher sensitivity for detecting HCC than NC-AMRI, but lower specificity.
| S-EPMC8231787 | biostudies-literature
Project description:Background/aimsUltrasonography has a low sensitivity for detecting early-stage hepatocellular carcinoma (HCC) in cirrhotic patients. Non-contrast abbreviated magnetic resonance imaging (aMRI) demonstrated a comparable performance to that of magnetic resonance imaging without the risk of contrast media exposure and at a lower cost than that of full diagnostic MRI. We aimed to investigate the cost-effectiveness of non-contrast aMRI for HCC surveillance in cirrhotic patients, using ultrasonography with alpha-fetoprotein (AFP) as a reference.MethodsCost-utility analysis was performed using a Markov model in Thailand and the United States. Incremental cost-effectiveness ratios were calculated using the total costs and quality-adjusted life years (QALYs) gained in each strategy. Surveillance protocols were considered cost-effective based on a willingness-to-pay value of $4,665 (160,000 Thai Baht) in Thailand and $50,000 in the United States.ResultsaMRI was cost-effective in both countries with incremental cost-effectiveness ratios of $3,667/QALY in Thailand and $37,062/QALY in the United States. Patient-level microsimulations showed consistent findings that aMRI was cost-effective in both countries. By probabilistic sensitivity analysis, aMRI was found to be more cost-effective than combined ultrasonography and AFP with a probability of 0.77 in Thailand and 0.98 in the United States. By sensitivity analyses, annual HCC incidence was revealed as the most influential factor affecting cost-effectiveness. The cost-effectiveness of aMRI increased in settings with a higher HCC incidence. At a higher HCC incidence, aMRI would remain cost-effective at a higher aMRI-to-ultrasonography with AFP cost ratio.ConclusionsCompared to ultrasonography with AFP, non-contrast aMRI is a cost-effective strategy for HCC surveillance and may be useful for such surveillance in cirrhotic patients, especially in those with high HCC risks.
| S-EPMC10791494 | biostudies-literature
Project description:Objectives(1) To assess the methodological quality of radiomics studies investigating histological subtypes, therapy response, and survival in patients with renal cell carcinoma (RCC) and (2) to determine the risk of bias in these radiomics studies.MethodsIn this systematic review, literature published since 2000 on radiomics in RCC was included and assessed for methodological quality using the Radiomics Quality Score. The risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies tool and a meta-analysis of radiomics studies focusing on differentiating between angiomyolipoma without visible fat and RCC was performed.ResultsFifty-seven studies investigating the use of radiomics in renal cancer were identified, including 4590 patients in total. The average Radiomics Quality Score was 3.41 (9.4% of total) with good inter-rater agreement (ICC 0.96, 95% CI 0.93-0.98). Three studies validated results with an independent dataset, one used a publically available validation dataset. None of the studies shared the code, images, or regions of interest. The meta-analysis showed moderate heterogeneity among the included studies and an odds ratio of 6.24 (95% CI 4.27-9.12; p < 0.001) for the differentiation of angiomyolipoma without visible fat from RCC.ConclusionsRadiomics algorithms show promise for answering clinical questions where subjective interpretation is challenging or not established. However, the generalizability of findings to prospective cohorts needs to be demonstrated in future trials for progression towards clinical translation. Improved sharing of methods including code and images could facilitate independent validation of radiomics signatures.Key points• Studies achieved an average Radiomics Quality Score of 10.8%. Common reasons for low Radiomics Quality Scores were unvalidated results, retrospective study design, absence of open science, and insufficient control for multiple comparisons. • A previous training phase allowed reaching almost perfect inter-rater agreement in the application of the Radiomics Quality Score. • Meta-analysis of radiomics studies distinguishing angiomyolipoma without visible fat from renal cell carcinoma show moderate diagnostic odds ratios of 6.24 and moderate methodological diversity.
| S-EPMC7248043 | biostudies-literature
Project description:We aimed to systematically evaluate the incidence of inadequate US in hepatocellular carcinoma (HCC) surveillance and determine the risk factors. Original studies reporting the incidence or risk factors for inadequate US were identified in MEDLINE, EMBASE, and the Cochrane database. The pooled incidence of inadequate US was calculated using a random effects model, and subgroup analyses were performed. The pooled odds ratio (OR) was calculated for each risk factor for inadequate US. Six eligible articles were identified from 756 screened articles (4250 patients). The pooled incidence of inadequate US was 21.5%. Significantly higher rates of inadequate US were noted in studies including patients with and without hepatic observations compared with those evaluating only patients with hepatic observations (23.2% vs. 18.8%), studies using US alone compared with US plus alpha-fetoprotein (28.0% vs. 20.8%), and those using pathology and imaging as a reference standard compared with imaging only (23.2% vs. 17.9%). Nonalcoholic steatohepatitis (OR = 2.3 (1.07-4.84)), Child-Pugh B cirrhosis (OR = 2.2 (1.10-4.37)), and high body mass index (OR = 2.2 (1.12-4.24)) were significant risk factors for inadequate US (p ≤ 0.04). In patients at risk of HCC, 21.5% of US surveillance was inadequate. An alternative surveillance modality might be considered in patients with risk factors.
| S-EPMC8397222 | biostudies-literature
Project description:IntroductionRobot-assisted devices have been recently developed for use in prostate biopsy. However, it is possible advantages over standard biopsy remain unclear. We aimed to assess the diagnostic performance and safety of robot-assisted targeted (RA-TB) and systematic prostate biopsies (RA-SB).MethodsA systematic literature search was performed in MEDLINE and Scopus databases. The detailed search strategy is available at Prospero (CRD42021269290). The primary outcome was the clinically significant prostate cancer (PCa) detection rate. The secondary outcomes included the overall detection rate of PCa, cancer detection rate per core, and complications.ResultsThe clinically significant cancer detection rate, overall cancer detection rate, and "per patient" did not significantly differ between RA-TB and RA-SB [OR = 1.02 (95% CI 0.83; 1.26), p = 0.05, I2 = 62% and OR = 0.95 (95% CI 0.78; 1.17), p = 0.17, I2 = 40%, respectively]. There were no differences in the clinically insignificant cancer detection rate "per patient" between RA-TB and RA-SB [OR = 0.81 (95% CI 0.54; 1.21), p = 0.31, I2 = 0%]. RA-TB had a significantly higher cancer detection rate "per core" [OR = 3.01 (95% CI 2.77; 3.27), p < 0.0001, I2 = 96%].ConclusionRA-TB and RA-SB are both technically feasible and have comparable clinical significance and overall PCa detection rates.
| S-EPMC9954527 | biostudies-literature
Project description:ObjectiveTo determine the accuracy of MR imaging with gadoxetic acid disodium (Gd-EOB-DTPA) for the detection of hepatocelluar carcinoma (HCC).Materials and methodsA systematic search was performed in PUBMED, EMBASE, Web of Science, Cochrane Library and the Chinese Biomedical Literature Database up to March 2013 to identify studies about evaluation of Gd-EOB-DTPA enhanced MR imaging in patients suspected of having HCC. The data were extracted to perform heterogeneity test and threshold effect test and to calculate sensitivity, specificity, diagnostic odds ratio, predictive value, and areas under summary receiver operating characteristic curve (AUC).ResultsFrom 601 citations, 10 were included in the meta-analysis. The methodological quality of the 10 studies was good. Overall HCC: There was significant heterogeneity in the pooled analysis (I(2) = 69.4%, P = 0.0005), and the pooled weighted values were determined to be sensitivity: 0.91 (95% confidence interval (CI): 0.89, 0. 93); specificity: 0.95 (95% CI: 0.94, 0.96); diagnostic odds ratio: 169.94 (95% CI: 108.84, 265.36); positive likelihood ratio: 15.75 (95% CI: 7.45, 33.31); negative likelihood ratio: 0.10 (95% CI: 0.06, 0.15). The AUC was 0.9778. HCC in cirrhosis: The estimates were to be sensitivity: 0.91 (95% CI: 0.88, 0.93); specificity: 0.93 (95% CI: 0.89, 0.95); diagnostic odds ratio: 234.24 (95% CI: 33.47, 1639.25); positive likelihood ratio: 15.08 (95% CI: 2.20, 103.40); negative likelihood ratio: 0.08 (95% CI: 0.03, 0.21). The AUC was 0.9814. ≤20 mm HCC: The AUC was 0.9936. There was no notable publication bias.ConclusionsThis meta-analysis suggests that MR imaging with Gd-EOB-DTPA has high diagnostic accuracy for the detection of HCC, especially for ≤20 mm HCC. This technique shows good prospect in diagnosis of HCC.
| S-EPMC3744536 | biostudies-literature
Project description:BackgroundAutomated brain tumor identification facilitates diagnosis and treatment planning. We evaluate the performance of traditional machine learning (TML) and deep learning (DL) in brain tumor detection and segmentation, using MRI.MethodsA systematic literature search from January 2000 to May 8, 2021 was conducted. Study quality was assessed using the Checklist for Artificial Intelligence in Medical Imaging (CLAIM). Detection meta-analysis was performed using a unified hierarchical model. Segmentation studies were evaluated using a random effects model. Sensitivity analysis was performed for externally validated studies.ResultsOf 224 studies included in the systematic review, 46 segmentation and 38 detection studies were eligible for meta-analysis. In detection, DL achieved a lower false positive rate compared to TML; 0.018 (95% CI, 0.011 to 0.028) and 0.048 (0.032 to 0.072) (P < .001), respectively. In segmentation, DL had a higher dice similarity coefficient (DSC), particularly for tumor core (TC); 0.80 (0.77 to 0.83) and 0.63 (0.56 to 0.71) (P < .001), persisting on sensitivity analysis. Both manual and automated whole tumor (WT) segmentation had "good" (DSC ≥ 0.70) performance. Manual TC segmentation was superior to automated; 0.78 (0.69 to 0.86) and 0.64 (0.53 to 0.74) (P = .014), respectively. Only 30% of studies reported external validation.ConclusionsThe comparable performance of automated to manual WT segmentation supports its integration into clinical practice. However, manual outperformance for sub-compartmental segmentation highlights the need for further development of automated methods in this area. Compared to TML, DL provided superior performance for detection and sub-compartmental segmentation. Improvements in the quality and design of studies, including external validation, are required for the interpretability and generalizability of automated models.
| S-EPMC9234754 | biostudies-literature
Project description:BackgroundContrast-enhanced mammography (CEM) and contrast-enhanced magnetic resonance imaging (CE-MRI) are commonly used in the screening of breast cancer. The present systematic review aimed to summarize, critically analyse, and meta-analyse the available evidence regarding the role of CE-MRI and CEM in the early detection, diagnosis, and preoperative assessment of breast cancer.MethodsThe search was performed on PubMed, Google Scholar, and Web of Science on 28 July 2021 using the following terms "breast cancer", "preoperative staging", "contrast-enhanced mammography", "contrast-enhanced spectral mammography", "contrast enhanced digital mammography", "contrast-enhanced breast magnetic resonance imaging" "CEM", "CESM", "CEDM", and "CE-MRI". We selected only those papers comparing the clinical efficacy of CEM and CE-MRI. The study quality was assessed using the QUADAS-2 criteria. The pooled sensitivities and specificity of CEM and CE-MRI were computed using a random-effects model directly from the STATA "metaprop" command. The between-study statistical heterogeneity was tested (I2-statistics).ResultsNineteen studies were selected for this systematic review. Fifteen studies (1315 patients) were included in the metanalysis. Both CEM and CE-MRI detect breast lesions with a high sensitivity, without a significant difference in performance (97% and 96%, respectively).ConclusionsOur findings confirm the potential of CEM as a supplemental screening imaging modality, even for intermediate-risk women, including females with dense breasts and a history of breast cancer.
| S-EPMC9406751 | biostudies-literature
Project description:BackgroundThis study aimed to systematically evaluate the value of magnetic resonance imaging (MRI) and magnetic resonance arthrography (MRA) in the diagnosis of acetabular labral tears.MethodsDatabases including PubMed, Embase, Cochrane Library, Web of Science, CBM, CNKI, WanFang Data, and VIP were electronically searched to collect relevant studies on magnetic resonance in the diagnosis of acetabular labral tears from inception to September 1, 2021. Two reviewers independently screened the literature, extracted data, and assessed the risk of bias in the included studies by using the Quality Assessment of Diagnostic Accuracy Studies 2 tool. RevMan 5.3, Meta Disc 1.4, and Stata SE 15.0 were used to investigate the diagnostic value of magnetic resonance in patients with acetabular labral tears.ResultsA total of 29 articles were included, involving 1385 participants and 1367 hips. The results of the meta-analysis showed that the pooled sensitivity, pooled specificity, pooled positive likelihood ratio, pooled negative likelihood ratio, pooled diagnostic odds ratio, area under the curve of the summary receiver operating characteristic, and Q* of MRI for diagnosing acetabular labral tears were 0.77 (95% confidence interval [CI], 0.75-0.80), 0.74 (95% CI, 0.68-0.80), 2.19 (95% CI, 1.76-2.73), 0.48 (95% CI, 0.36-0.65), 4.86 (95% CI, 3.44-6.86), 0.75, and 0.69, respectively. The pooled sensitivity, pooled specificity, pooled positive likelihood ratio, pooled negative likelihood ratio, pooled diagnostic odds ratio, area under the curve of the summary receiver operating characteristic, and Q* of MRA for diagnosing acetabular labral tears were 0.87 (95% CI, 0.84-0.89), 0.64 (95% CI, 0.57-0.71), 2.23 (95% CI, 1.57-3.16), 0.21 (95% CI, 0.16-0.27), 10.47 (95% CI, 7.09-15.48), 0.89, and 0.82, respectively.ConclusionMRI has high diagnostic efficacy for acetabular labral tears, and MRA has even higher diagnostic efficacy. Due to the limited quality and quantity of the included studies, the above results should be further validated.
| S-EPMC9981430 | biostudies-literature
Project description:BackgroundAs the volume and fidelity of magnetic resonance imaging (MRI) of the brain increase, observation of incidental findings may also increase. We performed a systematic review and meta-analysis to determine the prevalence of various incidental findings.MethodsPubMed/MEDLINE, EMBASE and SCOPUS were searched from inception to May 24, 2021. We identified 6536 citations and included 35 reports of 34 studies, comprising 40,777 participants. A meta-analysis of proportions was performed, and age-stratified estimates for each finding were derived from age-adjusted non-linear models.ResultsVascular abnormalities were observed in 423/35,706 participants (9.1/1000 scans, 95%CI 5.2-14.2), ranging from 2/1000 scans (95%CI 0-7) in 1-year-olds to 16/1000 scans (95%CI 1-43) in 80-year-olds. Of these, 204/34,306 were aneurysms (3.1/1000 scans, 95%CI 1-6.3), which ranged from 0/1000 scans (95%CI 0-5) at 1 year of age to 6/1000 scans (95%CI 3-9) at 60 years. Neoplastic abnormalities were observed in 456/39,040 participants (11.9/1000 scans, 95%CI 7.5-17.2), ranging from 0.2/1000 scans (95%CI 0-10) in 1-year-olds to 34/1000 scans (95%CI 12-66) in 80-year-olds. Meningiomas were the most common, in 246/38,076 participants (5.3/1000 scans, 95%CI 2.3-9.5), ranging from 0/1000 scans (95%CI 0-2) in 1-year-olds to 17/1000 scans (95%CI 4-37) in 80-year-olds. Chiari malformations were observed in 109/27,408 participants (3.7/1000 scans, 95%CI 1.8-6.3), pineal cysts in 1176/32,170 (9/1000 scans, 95%CI 1.8-21.4) and arachnoid cysts in 414/36,367 (8.5/1000 scans, 95%CI 5.8-11.8).ConclusionIncidental findings are common on brain MRI and may result in substantial resource expenditure and patient anxiety but are often of little clinical significance.
| S-EPMC9519720 | biostudies-literature