Systematic review with radiomics quality score of cholangiocarcinoma: an EuSoMII Radiomics Auditing Group Initiative

Cannella, Roberto; Vernuccio, Federica; Klontzas, Michail E.; Ponsiglione, Andrea; Petrash, Ekaterina; Ugga, Lorenzo; Santos, Daniel Pinto dos; Cuocolo, Renato

doi:10.1186/s13244-023-01365-1

Cited by 10 publications

(8 citation statements)

References 64 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Upon comparison with radiomics meta-analyses in other fields, we observed that the quality of radiomics studies is a widely concern. For instance, a review of cholangiocarcinoma encompassing 38 original studies reported a median RQS of 9, amounting to just 25.0% of the total RQS ( 52 ). Similarly, a review focusing on ovarian imaging, which included 63 studies, found a median RQS of 6, corresponding to 30.6% of the total RQS, indicating lower scoring ( 53 ).…”

Section: Discussionmentioning

confidence: 99%

“…Variations in study populations, methodologies, and the choice of utilizing first-pass effect recirculation results or multiple recirculation results for predicting MTB also could contribute to the inter-study heterogeneity. Indeed, previous studies have emphasized that radiomics studies are heterogeneous in various areas ( 52 – 55 , 59 , 61 , 62 ). Subgroup analysis may partially address this heterogeneity.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Current status and quality of radiomics studies for predicting outcome in acute ischemic stroke patients: a systematic review and meta-analysis

Kong,

Zhang

2024

Front. Neurol.

View full text Add to dashboard Cite

BackgroundPre-treatment prediction of reperfusion and long-term prognosis in acute ischemic stroke (AIS) patients is crucial for effective treatment and decision-making. Recent studies have demonstrated that the inclusion of radiomics data can improve the performance of predictive models. This paper reviews published studies focused on radiomics-based prediction of reperfusion and long-term prognosis in AIS patients.MethodsWe systematically searched PubMed, Web of Science, and Cochrane databases up to September 9, 2023, for studies on radiomics-based prediction of AIS patient outcomes. The methodological quality of the included studies was evaluated using the phase classification criteria, the radiomics quality scoring (RQS) tool, and the Prediction model Risk Of Bias Assessment Tool (PROBAST). Two separate meta-analyses were performed of these studies that predict long-term prognosis and reperfusion in AIS patients.ResultsSixteen studies with sample sizes ranging from 67 to 3,001 were identified. Ten studies were classified as phase II, and the remaining were categorized as phase 0 (n = 2), phase I (n = 1), and phase III (n = 3). The mean RQS score of all studies was 39.41%, ranging from 5.56 to 75%. Most studies (87.5%, 14/16) were at high risk of bias due to their retrospective design. The remaining two studies were categorized as low risk and unclear risk, respectively. The pooled area under the curve (AUC) was 0.88 [95% confidence interval (CI) 0.84–0.92] for predicting the long-term prognosis and 0.80 (95% CI 0.74–0.86) for predicting reperfusion in AIS.ConclusionRadiomics has the potential to predict immediate reperfusion and long-term outcomes in AIS patients. Further external validation and evaluation within the clinical workflow can facilitate personalized treatment for AIS patients. This systematic review provides valuable insights for optimizing radiomics prediction systems for both reperfusion and long-term outcomes in AIS patients.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023461671, identifier CRD42023461671.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Current status and quality of radiomics studies for predicting outcome in acute ischemic stroke patients: a systematic review and meta-analysis

Kong,

Zhang

2024

Front. Neurol.

View full text Add to dashboard Cite

show abstract

“…According to a systematic review about cholangiocarcinoma, the highest RQS was 18, and there were only 7 studies (18.4%) with ≥ 15 scores. Thirty (79.0%) studies were performed at one institution, and all the included studies were conducted retrospectively [ 44 ]. For our study, patients from two centers were included retrospectively.…”

Section: Discussionmentioning

confidence: 99%

“…For our study, patients from two centers were included retrospectively. Moreover, the most common study aims included differential diagnosis against other hepatic lesions, prediction of survival after surgical resection, prediction of lymph node metastases, and prediction of therapeutic response to radioembolization [ 44 ]. Currently, none of the studies covered the prediction of TLSs.…”

Section: Discussionmentioning

confidence: 99%

A CT-based radiomics approach to predict intra-tumoral tertiary lymphoid structures and recurrence of intrahepatic cholangiocarcinoma

Xu,

Li,

Yang

et al. 2023

Insights Imaging

View full text Add to dashboard Cite

Purpose To predict the tertiary lymphoid structures (TLSs) status and recurrence-free survival (RFS) of intrahepatic cholangiocarcinoma (ICC) patients using preoperative CT radiomics. Patients and methods A total of 116 ICC patients were included (training: 86; external validation: 30). The enhanced CT images were performed for the radiomics model. The logistic regression analysis was applied for the clinical model. The combined model was based on the clinical and radiomics models. Results A total of 107 radiomics features were extracted, and after being eliminated and selected, six features were combined to establish a radiomics model for TLSs prediction. Arterial phase diffuse hyperenhancement and AJCC 8th stage were combined to construct a clinical model. The combined (radiomics nomogram) model outperformed both the independent radiomics model and clinical model in the training cohort (AUC, 0.85 vs. 0.82 and 0.75, respectively) and was validated in the external validation cohort (AUC, 0.88 vs. 0.86 and 0.71, respectively). Patients in the rad-score no less than −0.76 (low-risk) group showed significantly better RFS than those in the less than −0.76 (high-risk) group (p < 0.001, C-index = 0.678). Patients in the nomogram score no less than −1.16 (low-risk) group showed significantly better RFS than those of the less than −1.16 (high-risk) group (p < 0.001, C-index = 0.723). Conclusions CT radiomics nomogram could serve as a preoperative biomarker of intra-tumoral TLSs status, better than independent radiomics or clinical models; preoperative CT radiomics nomogram achieved accurate stratification for RFS of ICC patients, better than the postoperative pathologic TLSs status. Critical relevance statement The radiomics nomogram showed better performance in predicting TLSs than independent radiomics or clinical models and better prognosis stratification than postoperative pathologic TLSs status in ICC patients, which may facilitate identifying patients benefiting most from surgery and subsequent immunotherapy. Key points • The combined (radiomics nomogram) model consisted of the radiomics model and clinical model (arterial phase diffuse hyperenhancement and AJCC 8th stage). • The radiomics nomogram showed better performance in predicting TLSs than independent radiomics or clinical models in ICC patients. • Preoperative CT radiomics nomogram achieved more accurate stratification for RFS of ICC patients than the postoperative pathologic TLSs status. Graphical Abstract

show abstract

“…Moreover, inter-reader variability and reproducibility of the radiomics features are crucial for the validation of the radiomics model, and they are often missing in current studies. A recent systematic review pointed out that the methodological rigor and quality of radiomics studies are still unsatisfactory in ovarian pathologies, with a reported radiomics quality score of 6, corresponding to 16.7% of the total score, which is lower compared with other fields of research in radiomics studies [169][170][171].…”

Section: Mrimentioning

confidence: 99%

Radiomics in Gynaecological Imaging: A State-of-the-Art Review

Franco,

Vernuccio,

Maino

et al. 2023

Applied Sciences

Self Cite

View full text Add to dashboard Cite

Radiomics is an emerging field of research based on extracting mathematical descriptive features from medical images with the aim of improving diagnostic performance and providing increasing support to clinical decisions. In recent years, a number of studies have been published regarding different possible applications of radiomics in gynaecological imaging. Many fields have been explored, such as tumour diagnosis and staging, differentiation of histological subtypes, assessment of distant metastases, prediction of response to therapy, recurrence, and patients’ outcome. However, several studies are not robust, do not include validation cohorts, or lack reproducibility. On these bases, the purpose of this narrative review is to provide an overview of the most relevant studies in the literature on radiomics in gynaecological imaging. We focused on gynaecological malignancies, particularly endometrial, cervical, mesenchymal, and ovarian malignant pathologies.

show abstract

Systematic review with radiomics quality score of cholangiocarcinoma: an EuSoMII Radiomics Auditing Group Initiative

Cited by 10 publications

References 64 publications

Current status and quality of radiomics studies for predicting outcome in acute ischemic stroke patients: a systematic review and meta-analysis

Current status and quality of radiomics studies for predicting outcome in acute ischemic stroke patients: a systematic review and meta-analysis

A CT-based radiomics approach to predict intra-tumoral tertiary lymphoid structures and recurrence of intrahepatic cholangiocarcinoma

Radiomics in Gynaecological Imaging: A State-of-the-Art Review

Contact Info

Product

Resources

About