Dataset Information

Radiomics for intracerebral hemorrhage: are all small hematomas benign?

ABSTRACT:

Objectives

We hypothesized that not all small hematomas are benign and that radiomics could predict hematoma expansion (HE) and short-term outcomes in small hematomas.

Methods

We analyzed 313 patients with small (<10 ml) intracerebral hemorrhage (ICH) who underwent baseline non-contrast CT within 6 h of symptom onset between September 2013 and February 2019. Poor outcome was defined as a Glasgow Outcome Scale score ≤3. A radiomic model and a clinical model were built using least absolute shrinkageand selection operator algorithm or multivariate analysis. A combined model that incorporated the developed radiomic score and clinical factors was then constructed. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of these models.

Results

The addition of radiomics to clinical factors significantly improved the prediction performance of HE compared with the clinical model alone in both the training {AUC, 0.762 [95% CI (0.665-0.859)] versus AUC, 0.651 [95% CI (0.556-0.745)], p = 0.007} and test {AUC, 0.776 [95% CI (0.655-0.897) versus AUC, 0.631 [95% CI (0.451-0.810)], p = 0.001} cohorts. Moreover, the radiomic-based model achieved good discrimination ability of poor outcomes in the 3-10 ml group (AUCs 0.720 and 0.701).

Conclusion

Compared with clinical information alone, combined model had greater potential for discriminating between benign and malignant course in patients with small ICH, particularly 3-10 ml hematomas.

Advances in knowledge

Radiomics can be used as a supplement to conventional medical imaging, improving clinical decision-making and facilitating personalized treatment in small ICH.

SUBMITTER: Zhan C

PROVIDER: S-EPMC8011248 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

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Publications

Radiomics for intracerebral hemorrhage: are all small hematomas benign?

Zhan Chenyi C Chen Qian Q Zhang Mingyue M Xiang Yilan Y Chen Jie J Zhu Dongqin D Chen Chao C Xia Tianyi T Yang Yunjun Y

The British journal of radiology 20201217 1119

<h4>Objectives</h4>We hypothesized that not all small hematomas are benign and that radiomics could predict hematoma expansion (HE) and short-term outcomes in small hematomas.<h4>Methods</h4>We analyzed 313 patients with small (<10 ml) intracerebral hemorrhage (ICH) who underwent baseline non-contrast CT within 6 h of symptom onset between September 2013 and February 2019. Poor outcome was defined as a Glasgow Outcome Scale score ≤3. A radiomic model and a clinical model were built using least a ...[more]

PMID: 33332987

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Project description:ObjectiveTo develop and validate radiomics models on non-enhanced CT for discrimination of arteriovenous malformation (AVM) related hematomas from hypertensive intracerebral hematomas.Materials and methodsA total of 571 patients with acute intraparenchymal hematomas and baseline non-enhanced CT scans were retrospectively analyzed, including 297 cases of AVM related hematomas and 274 cases of hypertensive intracerebral hematomas. The patients were divided into training and validation cohorts in a 7:3 ratio with a random seed. A total of 1,688 radiomics features of hematomas were extracted from non-enhanced CT. Then, the least absolute shrinkage and selection operator (LASSO) regression was applied to select features and construct the radiomics models. In this study, a radiomics-based model was constructed that based on the radiomics features only. Furthermore, a combined model was constructed using radiomics features, clinical characteristics and radiological signs by radiologists' evaluation. In addition, we compared predictive performance of the two models for discrimination of AVM related hematomas from hypertensive intracerebral hematomas.ResultsA total of 67 radiomics features were selected to establish radiomics signature via LASSO regression. The radiomics-based model was constructed with 2 classifiers, support vector machine (SVM) and logistic regression (LR). AUCs of the radiomics-based model in the training set were 0.894 and 0.904, in validation set were 0.774 and 0.782 in SVM classifier and LR classifier, respectively. AUCs of the combined model (combined with radiomics, age and calcification) in the training set were 0.976 and 0.981, in validation set were 0.896 and 0.907 in SVM classifier and LR classifier, respectively. The combined model showed greater AUCs than radiomics-based model in both training set and validation set.ConclusionThe combined model using radiomics, age and calcification showed a satisfactory predictive performance for discrimination of AVM related hematomas from hypertensive intracerebral hematomas and hold great potential for personalized clinical decision.

Project description:Background and purposeIntracerebral hemorrhage (ICH) is an acute manifestation of cerebral small vessel disease (CSVD), usually cerebral amyloid angiopathy or hypertensive arteriopathy. CSVD-related imaging findings are associated with increased depression incidence in the general population. Neuroimaging may, therefore, provide insight on depression risk among ICH survivors. We sought to determine whether CSVD CT and magnetic resonance imaging markers are associated with depression risk (before and after ICH), depression remission, and effectiveness of antidepressant treatment.MethodsWe analyzed data from the single-center longitudinal ICH study conducted at Massachusetts General Hospital. Participants underwent CT and magnetic resonance imaging imaging and were followed longitudinally. We extracted information for neuroimaging markers of CSVD subtype and severity. Outcomes of interest included pre-ICH depression, new-onset depression after ICH, resolution of depressive symptoms, and response to antidepressant treatment.ResultsWe followed 612 ICH survivors for a median of 47.2 months. Multiple CSVD-related markers were associated with depression risk. Survivors of cerebral amyloid angiopathy-related lobar ICH were more likely to be diagnosed with depression before ICH (odds ratio, 1.68 [95% CI, 1.14-2.48]) and after ICH (sub-hazard ratio, 1.52 [95% CI, 1.12-2.07]), less likely to achieve remission of depressive symptoms (sub-hazard ratio, 0.69 [95% CI, 0.51-0.94]), and to benefit from antidepressant therapy (P=0.041). Cerebral amyloid angiopathy disease burden on magnetic resonance imaging was associated with depression incidence and treatment resistance (interaction P=0.037), whereas hypertensive arteriopathy disease burden was only associated with depression incidence after ICH.ConclusionsCSVD severity is associated with depression diagnosis, both before and after ICH. Cerebral amyloid angiopathy-related ICH survivors are more likely to experience depression (both before and after ICH) than patients diagnosed with hypertensive arteriopathy-related ICH, and more likely to report persistent depressive symptoms and display resistance to antidepressant treatment.

Dataset Information

Radiomics for intracerebral hemorrhage: are all small hematomas benign?

Objectives

Methods

Results

Conclusion

Advances in knowledge

Publications

Radiomics for intracerebral hemorrhage: are all small hematomas benign?

Similar Datasets

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