• Title/Summary/Keyword: Meta-analysis: Functional MRI

Search Result 3, Processing Time 0.021 seconds

Functional Magnetic Resonance Imaging in the Diagnosis of Locally Recurrent Prostate Cancer: Are All Pulse Sequences Helpful?

  • Liao, Xiao-Li;Wei, Jun-Bao;Li, Yong-Qiang;Zhong, Jian-Hong;Liao, Cheng-Cheng;Wei, Chang-Yuan
    • Korean Journal of Radiology
    • /
    • v.19 no.6
    • /
    • pp.1110-1118
    • /
    • 2018
  • Objective: To perform a meta-analysis to quantitatively assess functional magnetic resonance imaging (MRI) in the diagnosis of locally recurrent prostate cancer. Materials and Methods: A comprehensive search of the PubMed, Embase, Cochrane Central Register of Controlled Trials, and Cochrane Database of Systematic Reviews was conducted from January 1, 1995 to December 31, 2016. Diagnostic accuracy was quantitatively pooled for all studies by using hierarchical logistic regression modeling, including bivariate modeling and hierarchical summary receiver operating characteristic (HSROC) curves (AUCs). The Z test was used to determine whether adding functional MRI to T2-weighted imaging (T2WI) results in significantly increased diagnostic sensitivity and specificity. Results: Meta-analysis of 13 studies involving 826 patients who underwent radical prostatectomy showed a pooled sensitivity and specificity of 91%, and the AUC was 0.96. Meta-analysis of 7 studies involving 329 patients who underwent radiotherapy showed a pooled sensitivity of 80% and specificity of 81%, and the AUC was 0.88. Meta-analysis of 11 studies reporting 1669 sextant biopsies from patients who underwent radiotherapy showed a pooled sensitivity of 54% and specificity of 91%, and the AUC was 0.85. Sensitivity after radiotherapy was significantly higher when diffusion-weighted MRI data were combined with T2WI than when only T2WI results were used. This was true when meta-analysis was performed on a per-patient basis (p = 0.027) or per sextant biopsy (p = 0.046). A similar result was found when $^1H$-magnetic resonance spectroscopy ($^1H$-MRS) data were combined with T2WI and sextant biopsy was the unit of analysis (p = 0.036). Conclusion: Functional MRI data may not strengthen the ability of T2WI to detect locally recurrent prostate cancer in patients who have undergone radical prostatectomy. By contrast, diffusion-weight MRI and $^1H$-MRS data may improve the sensitivity of T2WI for patients who have undergone radiotherapy.

A fMRI Meta-analysis on Neuroimaging Studies of Basic Emotions (기본정서 뇌 영상 연구의 fMRI 메타분석)

  • Kim, Gwang-Su;Han, Mi-Ra;Bak, Byung-Gee
    • Science of Emotion and Sensibility
    • /
    • v.20 no.4
    • /
    • pp.15-30
    • /
    • 2017
  • The purpose of this study was to verify the basic emotion theory based on the emotion-related research using functional brain imaging technology. For this purpose, a meta-analysis on the functional magnetic resonance imaging (fMRI) studies was performed. Six individual emotions-joy, happiness, fear, anger, disgust, sadness-were selected. In order to collect the fMRI data of individual emotions, we searched the electronic journals such as Medline, PsychInfo, PubMed for the past 10 years. fMRI experiment data aimed at healthy subjects for 6 emotions were collected, and only studies reported in Talairach or MNI standard coordinate system were included. In order to eliminate the difference between Talairach and MNI coordinate systems, we analyzed fMRI data based on the Talairach coordinate system. A meta-analysis using GingerALE 2.3 program adopting the activation likelihood estimates (ALE) techniques was performed. In this study, we confirmed that the individual emotions are associated with consistent and distinguishable regional brain responses within the framework of the basic emotion theory. The conclusion of this study of the brain areas associated with each individual emotional reaction was substantially consistent with the results of existing review articles. Finally, the limitations of this study and some suggestions for the future research were presented.

Cardiac CT for Measurement of Right Ventricular Volume and Function in Comparison with Cardiac MRI: A Meta-Analysis

  • Jin Young Kim;Young Joo Suh;Kyunghwa Han;Young Jin Kim;Byoung Wook Choi
    • Korean Journal of Radiology
    • /
    • v.21 no.4
    • /
    • pp.450-461
    • /
    • 2020
  • Objective: We performed a meta-analysis to evaluate the agreement of cardiac computed tomography (CT) with cardiac magnetic resonance imaging (CMRI) in the assessment of right ventricle (RV) volume and functional parameters. Materials and Methods: PubMed, EMBASE, and Cochrane library were systematically searched for studies that compared CT with CMRI as the reference standard for measurement of the following RV parameters: end-diastolic volume (EDV), end-systolic volume (ESV), stroke volume (SV), or ejection fraction (EF). Meta-analytic methods were utilized to determine the pooled weighted bias, limits of agreement (LOA), and correlation coefficient (r) between CT and CMRI. Heterogeneity was also assessed. Subgroup analyses were performed based on the probable factors affecting measurement of RV volume: CT contrast protocol, number of CT slices, CT reconstruction interval, CT volumetry, and segmentation methods. Results: A total of 766 patients from 20 studies were included. Pooled bias and LOA were 3.1 mL (-5.7 to 11.8 mL), 3.6 mL (-4.0 to 11.2 mL), -0.4 mL (5.7 to 5.0 mL), and -1.8% (-5.7 to 2.2%) for EDV, ESV, SV, and EF, respectively. Pooled correlation coefficients were very strong for the RV parameters (r = 0.87-0.93). Heterogeneity was observed in the studies (I2 > 50%, p < 0.1). In the subgroup analysis, an RV-dedicated contrast protocol, ≥ 64 CT slices, CT volumetry with the Simpson's method, and inclusion of the papillary muscle and trabeculation had a lower pooled bias and narrower LOA. Conclusion: Cardiac CT accurately measures RV volume and function, with an acceptable range of bias and LOA and strong correlation with CMRI findings. The RV-dedicated CT contrast protocol, ≥ 64 CT slices, and use of the same CT volumetry method as CMRI can improve agreement with CMRI.