Efficacy of rTMS in treating functional impairment in post-stroke patients: a systematic review and meta-analysis.

BACKGROUND: Most stroke patients suffer from an imbalance in blood supply, which causes severe brain damage leading to functional deficits in motor, sensory, swallowing, cognitive, emotional, and speech functions. Repetitive transcranial magnetic stimulation (rTMS) is thought to restore functions impaired during the stroke process and improve the quality of life of stroke patients. However, the efficacy of rTMS in treating post-stroke function impairment varies significantly. Therefore, we conducted a meta-analysis of the number of patients with effective rTMS in treating post-stroke dysfunction. METHODS: The PubMed, Embase, and Cochrane Library databases were searched. Screening and full-text review were performed by three investigators. Single-group rate meta-analysis was performed on the extracted data using a random variable model. Then subgroup analyses were performed at the levels of stroke acuity (acute, chronic, or subacute); post-stroke symptoms (including upper and lower limb motor function, dysphagia, depression, aphasia); rTMS stimulation site (affected side, unaffected side); and whether or not it was a combination therapy. RESULTS: We obtained 8955 search records, and finally 33 studies (2682 patients) were included in the meta-analysis. The overall analysis found that effective strength (ES) of rTMS was 0.53. In addition, we found that the ES of rTMS from acute/subacute/chronic post-stroke was 0.69, 0.45, and 0.52. We also found that the ES of rTMS using high-frequency stimulation was 0.56, while the ES of rTMS using low-frequency stimulation was 0.53. From post-stroke symptoms, we found that the ES of rTMS in sensory aspects, upper limb functional aspects, swallowing function, and aphasia was 0.50, 0.52, 0.51, and 0.54. And from the site of rTMS stimulation, we found that the ES of rTMS applied to the affected side was 0.51, while the ES applied to the unaffected side was 0.54. What's more, we found that the ES of rTMS applied alone was 0.53, while the ES of rTMS applied in conjunction with other therapeutic modalities was 0.53. CONCLUSIONS: By comparing the results of the data, we recommend rTMS as a treatment option for rehabilitation of functional impairment in patients after stroke. We also recommend that rehabilitation physicians or clinicians use combination therapy as one of the options for patients.

CT radiomics based on different machine learning models for classifying gross tumor volume and normal liver tissue in hepatocellular carcinoma.

BACKGROUND & AIMS: The present study utilized extracted computed tomography radiomics features to classify the gross tumor volume and normal liver tissue in hepatocellular carcinoma by mainstream machine learning methods, aiming to establish an automatic classification model. METHODS: We recruited 104 pathologically confirmed hepatocellular carcinoma patients for this study. GTV and normal liver tissue samples were manually segmented into regions of interest and randomly divided into five-fold cross-validation groups. Dimensionality reduction using LASSO regression. Radiomics models were constructed via logistic regression, support vector machine (SVM), random forest, Xgboost, and Adaboost algorithms. The diagnostic efficacy, discrimination, and calibration of algorithms were verified using area under the receiver operating characteristic curve (AUC) analyses and calibration plot comparison. RESULTS: Seven screened radiomics features excelled at distinguishing the gross tumor area. The Xgboost machine learning algorithm had the best discrimination and comprehensive diagnostic performance with an AUC of 0.9975 [95% confidence interval (CI): 0.9973-0.9978] and mean MCC of 0.9369. SVM had the second best discrimination and diagnostic performance with an AUC of 0.9846 (95% CI: 0.9835- 0.9857), mean Matthews correlation coefficient (MCC)of 0.9105, and a better calibration. All other algorithms showed an excellent ability to distinguish between gross tumor area and normal liver tissue (mean AUC 0.9825, 0.9861,0.9727,0.9644 for Adaboost, random forest, logistic regression, naivem Bayes algorithm respectively). CONCLUSION: CT radiomics based on machine learning algorithms can accurately classify GTV and normal liver tissue, while the Xgboost and SVM algorithms served as the best complementary algorithms.

Performance of [18F]FDG PET/CT versus FAPI PET/CT for lung cancer assessment: a systematic review and meta-analysis.

PURPOSE: This article aims to compare the diagnostic performance of 18-fluorodeoxyglucose ([18F]FDG) PET/CT and fibroblast activating protein inhibitor (FAPI) PET/CT in the assessment of primary tumors, lymph nodes, and distant metastases in lung cancer patients. METHODS: A systematic search was conducted on the Cochrane Library, Embase, and PubMed/MEDLINE databases from inception until November 1, 2022. Included studies assessed the use of FAPI PET/CT and [18F]FDG PET/CT in patients with lung cancer. The Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool was used to evaluate the risk of bias. A random variable model was used to analyze the diagnostic tests of the two imaging modalities. RESULTS: The sensitivity of FAPI PET/CT in detecting primary lung cancer lesions was 0.98 (95% CI: 0.88-1.00), while the sensitivity of [18F]FDG PET/CT was 0.99 (95% CI: 0.74-1.00). For the detection of metastatic lesions (lymph node metastases and distant metastases), FAPI PET/CT had a sensitivity of 0.99 (95% CI: 0.90-1.00), while the sensitivity of [18F]FDG PET/CT was 0.77 (95% CI: 0.66-0.85). However, the specificity of the two imaging modalities could not be assessed due to the lack of sufficient information on pertinent true negatives. CONCLUSION: In the diagnosis of metastatic lung cancer lesions, FAPI PET/CT demonstrated a higher sensitivity compared to [18F]FDG PET/CT. Therefore, FAPI PET/CT may be considered an alternative imaging modality for the assessment of primary lung cancer tumors, lymph node metastases, and distant metastases. CLINICAL RELEVANCE STATEMENT: FAPI may be an alternative to [18F]FDG in the assessment of primary lung cancer tumors, lymph node metastases, and distant metastases, which plays a very important role in treatment. KEY POINTS: • This article is to compare the performance of [18F]FDG PET/CT with FAPI PET/CT in the assessment of primary tumors, lymph nodes, and distant metastases in lung cancer. • However, FAPI PET/CT has a higher sensitivity for the diagnostic assessment of metastatic lung cancer lesions.

18F­FDG PET/CT based radiomics features improve prediction of prognosis: multiple machine learning algorithms and multimodality applications for multiple myeloma.

PURPOSE: Multiple myeloma (MM), the second most hematological malignancy, have been studied extensively in the prognosis of the clinical parameters, however there are only a few studies have discussed the role of dual modalities and multiple algorithms of 18F-FDG (18F-fluorodeoxyglucose) PET/CT based radiomics signatures for prognosis in MM patients. We hope to deeply mine the utility of raiomics data in the prognosis of MM. METHODS: We extensively explored the predictive ability and clinical decision-making ability of different combination image data of PET, CT, clinical parameters and six machine learning algorithms, Cox proportional hazards model (Cox), linear gradient boosting models based on Cox's partial likelihood (GB-Cox), Cox model by likelihood based boosting (CoxBoost), generalized boosted regression modelling (GBM), random forests for survival model (RFS) and support vector regression for censored data model (SVCR). And the model evaluation methods include Harrell concordance index, time dependent receiver operating characteristic (ROC) curve, and decision curve analysis (DCA). RESULTS: We finally confirmed 5 PET based features, and 4 CT based features, as well as 6 clinical derived features significantly related to progression free survival (PFS) and we included them in the model construction. In various modalities combinations, RSF and GBM algorithms significantly improved the accuracy and clinical net benefit of predicting prognosis compared with other algorithms. For all combinations of various modalities based models, single-modality PET based prognostic models' performance was outperformed baseline clinical parameters based models, while the performance of models of PET and CT combined with clinical parameters was significantly improved in various algorithms. CONCLUSION: 18F­FDG PET/CT based radiomics models implemented with machine learning algorithms can significantly improve the clinical prediction of progress and increased clinical benefits providing prospects for clinical prognostic stratification for precision treatment as well as new research areas.

[68Ga]Ga-FAPI PET for the evaluation of digestive system tumors: systematic review and meta-analysis.

PURPOSE: Digestive system tumors are a group of tumors with high incidence in the world nowadays. The assessment of digestive system tumor metastasis by conventional imaging seems to be unsatisfactory. [68Ga]Ga-FAPI, which has emerged in recent years, seems to be able to evaluate digestive system tumor metastasis. We aimed to summarize the current evidence of [68Ga]Ga-FAPI PET/CT or PET/MR for the assessment of primary tumors, lymph node metastases, and distant metastases in digestive system tumors. Besides, we also aimed to perform a meta-analysis of the sensitivity of [68Ga]Ga-FAPI PET diagnosis to discriminate between digestive system tumors, primary lesions, and non-primary lesions (lymph node metastases and distant metastases). MATERIALS AND METHODS: PubMed, MEDLINE and Cochrane Library databases were searched from the beginning of the database build to August 12, 2022. All studies undergoing [68Ga]Ga-FAPI PET for the evaluation of digestive tumors were included in the screening and review. Screening and full text review was performed by 3 investigators and data extraction was performed by 2 investigators. Risk of bias was examined with the QUADAS-2 criteria. Diagnostic test meta-analysis was performed with a random-effects model. RESULTS: A total of 541 studies were retrieved. Finally, 22 studies were selected for the systematic review and 18 studies were included in the meta-analysis. In the 18 publications, a total of 524 patients with digestive system tumors, 459 primary tumor lesions of digestive system tumors, and 1921 metastatic lesions of digestive system tumors were included in the meta-analysis. Based on patients, the sensitivity of [68Ga]Ga-FAPI PET for the diagnosis of digestive system tumors was 0.98 (95% CI: 0.94-0.99). Based on lesions, the sensitivity of [68Ga]Ga-FAPI PET for the diagnostic evaluation of primary tumor lesions of the digestive system was 0.97 (95% CI: 0.93-0.99); the sensitivity of [68Ga]Ga-FAPI PET for the diagnostic evaluation of non-primary lesions (lymph node metastases and distant metastases) of the digestive system tumors was 0.94 (95% CI: 0.79-0.99). CONCLUSION: [68Ga]Ga-FAPI PET has high accuracy and its sensitivity is at a high level for the diagnostic evaluation of digestive system tumors. Clinicians, nuclear medicine physicians, and radiologists may consider using [68Ga]Ga-FAPI PET/CT or PET/MR in the evaluation of primary tumors, lymph node metastases, and distant metastases in digestive system tumors.

Comparison of 68Ga-FAPI and 18F-FDG PET/CT in the Evaluation of Patients With Newly Diagnosed Non-Small Cell Lung Cancer.

Purpose: Several studies have demonstrated that 68Ga-FAPI PET/CT shows high intratumoral tracer uptake and low normal tissue uptake, allowing for excellent visualization of cancer. The purpose of this study was to compare the ability of 68Ga-FAPI and 18F-FDG PET/CT for the evaluation of newly diagnosed NSCLC. Materials and Methods: A prospective analysis of 28 individuals with histopathologically newly confirmed NSCLC that underwent 68Ga-FAPI and 18F-FDG PET/CT was conducted. The performance of two imaging modalities was compared based upon visual assessment, rates of cancer detection, and semi-quantitative parameters (target-to-background ratio [TBR], maximum standard uptake value [SUVmax]) for both primary tumors and metastases. Results: In total, this study enrolled 28 participants (13 male, 15 female; median age: 60.5 years, range: 34 - 78 years. For primary tumors, 68Ga-FAPI and 18F-FDG PET/CT have similar detection performance (28 vs. 27). However, 68Ga-FAPI PET/CT was found to more effectively evaluate most metastases as compared to 18F-FDG PET/CT. 68Ga-FAPI PET/CT detecting more metastases present within the lymph nodes (53 vs. 49), pleura (8 vs. 7), liver (4 vs. 1), and bone (41 vs. 35). The SUVmax and TBR values for 68Ga-FAPI were substantially superior to those for 18F-FDG in lymph node, pleural, and bone metastases. While the SUVmax for these two imaging approaches was comparable for hepatic metastases, 68Ga-FAPI exhibited a significantly higher TBR in relation to that of 18F-FDG. In addition, 68Ga-FAPI PET/CT demonstrates excellent N (80% [8/10]) and M (92.9% [26/28]) staging accuracy in NSCLC patients. Conclusions: 68Ga-FAPI PET/CT as an examination modality is excellent for evaluation of newly diagnosed NSCLC. 68Ga-FAPI PET/CT improves the detection rates of most metastases and facilitating the superior staging of patients with newly diagnosed NSCLC, relative to that achieved by 18F-FDG PET/CT.