Systemic-pulmonary collateral supply associated with clinical severity of chronic thromboembolic pulmonary hypertension: a study using intra-aortic computed tomography angiography
ConclusionsPV enhancement measured by intra-aortic CT angiography reflects clinical severity and pulmonary perfusion defects in CTEPH.Key Points•Intra-aortic CT angiography demonstrated heterogeneous enhancement within the pulmonary vasculature, showing collaterals from the systemic arteries to the pulmonary circulation in CTEPH.•The degree of systemic-pulmonary collateral development was significantly correlated with the clinical severity of CTEPH and may be used to evaluate disease progression.•The distribution of systemic-pulmonary collaterals is positively correlated with perfusion defects in the lung segments in...
Source: European Radiology - April 14, 2022 Category: Radiology Source Type: research

Deep learning –based automatic segmentation of meningioma from multiparametric MRI for preoperative meningioma differentiation using radiomic features: a multicentre study
ConclusionsThe developed deep learning –based segmentation method enables automatic and accurate extraction of meningioma from multiparametric MR images and can help deploy radiomics for preoperative meningioma differentiation in clinical practice.Key Points• A deep learning–based method was developed for automatic segmentation of meningioma from multiparametric MR images.• The automatic segmentation method enabled accurate extraction of meningiomas and yielded radiomic features that were highly consistent with those that were obtained using manual segmentation.• High-grade meningiomas were preoperatively differe...
Source: European Radiology - April 14, 2022 Category: Radiology Source Type: research

Radiology artificial intelligence: a systematic review and evaluation of methods (RAISE)
ConclusionThis systematic review has surveyed the major advances in AI as applied to clinical radiology.Key Points• While there are many papers reporting expert-level results by using deep learning in radiology, most apply only a narrow range of techniques to a narrow selection of use cases.• The literature is dominated by retrospective cohort studies with limited external validation with high potential for bias.• The recent advent of AI extensions to systematic reporting guidelines and prospective trial registration along with a focus on external validation and explanations show potential for translation of the hype...
Source: European Radiology - April 14, 2022 Category: Radiology Source Type: research

Breast cancer imaging with glucosamine CEST (chemical exchange saturation transfer) MRI: first human experience
ConclusionThe results of this initial feasibility study indicate the potential of GlcN CEST MRI to diagnose breast cancer in a clinical setup.Key Points• GlcN CEST MRI method is demonstrated for its the ability to differentiate between breast tumor lesions and the surrounding tissue, based on the differential accumulation of the GlcN in the tumors.• GlcN CEST imaging may be used to identify metabolic active malignant breast tumors without using a Gd contrast agent.• The GlcN CEST MRI method may be considered for use in a clinical setup for breast cancer detection and should be tested as a complementary method to conv...
Source: European Radiology - April 14, 2022 Category: Radiology Source Type: research

Breast MRI for “the Masses”
(Source: European Radiology)
Source: European Radiology - April 14, 2022 Category: Radiology Source Type: research

Correction to: Comparison between spleen and liver stiffness measurements by sound touch elastography for diagnosing cirrhosis at different aminotransferase levels: a prospective multicenter study
(Source: European Radiology)
Source: European Radiology - April 12, 2022 Category: Radiology Source Type: research

Development and evaluation of machine learning models based on X-ray radiomics for the classification and differentiation of malignant and benign bone tumors
ConclusionsAn ANN combining radiomic features and demographic information showed the best performance in distinguishing between benign and malignant bone lesions. The model showed lower accuracy compared to specialized radiologists, while accuracy was higher or similar compared to residents.Key Points• The developed machine learning model could differentiate benign from malignant bone tumors using radiography with an AUC of 0.90 on the external test set.• Machine learning models that used radiomic features or demographic information alone performed worse than those that used both radiomic features and demographic info...
Source: European Radiology - April 9, 2022 Category: Radiology Source Type: research

FLAIR vascular hyperintensities predict functional outcome after endovascular thrombectomy in patients with large ischemic cores
ConclusionsIn stroke patients with large-volume infarcts, good collaterals as measured by the FVH –ASPECTS rating system are associated with improved outcomes and may help select patients for reperfusion therapy.Key Points• Endovascular thrombectomy can allow almost 1 in 2 patients with large infarct cores to achieve good functional outcome (modified Rankin Scale [mRS] of 0–3) and 1 in 3 patients to regain functional independence (mRS 0–2) at 3 months.• The extent of FVH score (as reflected by FLAIR vascular hyperintensity [FVH]–Alberta Stroke Program Early CT Score [ASPECTS] values) is associated with function...
Source: European Radiology - April 8, 2022 Category: Radiology Source Type: research

Chemotherapy-associated steatohepatitis was concomitant with epicardial adipose tissue volume increasing in breast cancer patients who received neoadjuvant chemotherapy
ConclusionsEAT volume was significantly higher in the BC-NAC group than in the BC-non-NAC group.Key Points•The prevalence of CASH was as high as 42.8% in BC patients.•NAC significantly increased the EAT volume in BC patients.•The liver fat content caused the change of EAT volume through mediating effect. (Source: European Radiology)
Source: European Radiology - April 8, 2022 Category: Radiology Source Type: research

The diffusion MRI signature index is highly correlated with immunohistochemical status and molecular subtype of invasive breast carcinoma
ConclusionsThe DWI S-index showed significantly higher values in invasive carcinomas with immunohistochemical status associated with good prognosis, suggesting its usefulness as a noninvasive imaging biomarker to estimate IHC status and orient treatment.Key Points•The signature index, an advanced diffusion MRI marker, showed good discrimination of immunohistochemical status in invasive breast carcinomas.• The signature index has the potential to differentiate noninvasively invasive breast carcinoma subtypes and appears as an imaging biomarker of prognostic factors and molecular phenotypes (Source: European Radiology)
Source: European Radiology - April 8, 2022 Category: Radiology Source Type: research

Deep learning –based algorithm improved radiologists’ performance in bone metastases detection on CT
ConclusionWith the aid of the algorithm, the overall performance of radiologists in bone metastases detection improved, and the interpretation time decreased at the same time.Key Points•A deep learning –based algorithm for automatic detection of bone metastases on CT was developed.•In the observer study, overall performance of radiologists in bone metastases detection improved significantly with the aid of the algorithm.•Radiologists ’ interpretation time decreased at the same time. (Source: European Radiology)
Source: European Radiology - April 8, 2022 Category: Radiology Source Type: research

Arterial transit artifacts on arterial spin labeling MRI can predict cerebral hyperperfusion after carotid endarterectomy: an initial study
ConclusionsBased on the presence of ATAs, ASL can non-invasively predict cerebral hyperperfusion after CEA in patients with carotid stenosis.Key Points• Carotid near occlusion, opening of posterior communicating arteries with incomplete anterior semicircle, and leptomeningeal collaterals were associated with lower ASL scores.• The ASL score performed better than the degree of stenosis, type of CoW, and leptomeningeal collaterals, as well as the combination of the three factors for the prediction of cerebral hyperperfusion.• For patients with carotid stenosis, preoperative ASL can non-invasively identify patients at h...
Source: European Radiology - April 8, 2022 Category: Radiology Source Type: research

Increased vertebral body area, disc and facet joint degeneration throughout the lumbar spine in patients with lumbosacral transitional vertebrae
ConclusionsLSTV patients, and particularly male patients, have an increased vertebral body CSA compared to non-LSTV patients throughout the lumbar spine. LSTV patients also have more severe disc and facet joint degeneration. The increase in vertebral body area may be contributing to the increased lumbar and facet joint degeneration seen in LSTV patients.Key Points• LSTV patients have increased vertebral body cross-sectional area throughout their lumbar spine compared to non-LSTV patients. This vertebral body area increase was more pronounced in male patients and also apparent in younger patients with LSTV.• LSTV patien...
Source: European Radiology - April 8, 2022 Category: Radiology Source Type: research

Automatic coronary artery segmentation and diagnosis of stenosis by deep learning based on computed tomographic coronary angiography
ConclusionHerein, using a deep learning algorithm, we realized the rapid classification and diagnosis of CAD from CCTA images in two steps. Our deep learning model can automatically segment the coronary artery quickly and accurately and can deliver a diagnosis of ≥ 50% coronary artery stenosis. Artificial intelligence methods such as deep learning have the potential to elevate the efficiency in CCTA image analysis considerably.Key Points• The deep learning model rapidly achieved a high Dice value (0.771 ± 0.0210) in the autosegmentation of coronary arteries using CCTA images.• Based on the segmentation model, we bui...
Source: European Radiology - April 8, 2022 Category: Radiology Source Type: research

Two nomograms for differentiating mass-forming chronic pancreatitis from pancreatic ductal adenocarcinoma in patients with chronic pancreatitis
ConclusionsThe two nomograms reasonably accurately differentiated MFCP from PDAC in patients with CP and hold potential for refining the management of pancreatic masses in CP patients.Key Points•A CT nomogram and a computed tomography-based radiomics nomogram reasonably accurately differentiated mass-forming chronic pancreatitis from pancreatic ductal adenocarcinoma in patients with chronic pancreatitis (CP).•The two nomograms can monitor the cancer risk in patients with CP and hold promise to optimize the management of pancreatic masses in patients with CP. (Source: European Radiology)
Source: European Radiology - April 8, 2022 Category: Radiology Source Type: research