ImageCAS: A large-scale dataset and benchmark for coronary artery segmentation based on computed tomography angiography images.

Cardiovascular disease (CVD) accounts for about half of non-communicable diseases. Vessel stenosis in the coronary artery is considered to be the major risk of CVD. Computed tomography angiography (CTA) is one of the widely used noninvasive imaging modalities in coronary artery diagnosis due to its superior image resolution. Clinically, segmentation of coronary arteries is essential for the diagnosis and quantification of coronary artery disease. Recently, a variety of works have been proposed to address this problem. However, on one hand, most works rely on in-house datasets, and only a few works published their datasets to the public which only contain tens of images. On the other hand, their source code have not been published, and most follow-up works have not made comparison with existing works, which makes it difficult to judge the effectiveness of the methods and hinders the further exploration of this challenging yet critical problem in the community. In this paper, we propose a large-scale dataset for coronary artery segmentation on CTA images. In addition, we have implemented a benchmark in which we have tried our best to implement several typical existing methods. Furthermore, we propose a strong baseline method which combines multi-scale patch fusion and two-stage processing to extract the details of vessels. Comprehensive experiments show that the proposed method achieves better performance than existing works on the proposed large-scale dataset. The benchmark and the dataset are published at https://github.com/XiaoweiXu/ImageCAS-A-Large-Scale-Dataset-and-Benchmark-for-Coronary-Artery-Segmentation-based-on-CT.

Predictive performance of the perivascular fat attenuation index for interventional antegrade percutaneous coronary intervention for chronic total occlusion.

OBJECTIVES: This study aimed to investigate the association between the perivascular fat attenuation index (FAI) and the success of the antegrade percutaneous coronary intervention (PCI) for chronic total occlusion (CTO). METHODS: This study evaluated patients with only one CTO lesion observed on conventional coronary angiography (CAG) who underwent coronary computed tomography angiography (CCTA) < 1 month before CAG, from 2018 to 2019. The clinical data, CCTA-based CTO lesion morphologic characteristics, and perivascular FAI of CTO lesions were recorded and analysed. RESULTS: In total, 156 patients with CTOs were enrolled in this study. Successful antegrade PCI (A-PCI) was achieved in 105 CTO lesions (67.3%). The perivascular FAI of the failed A-PCI group was significantly lower than the successful A-PCI group (-84.76 ± 10.44 Hounsfield unit (HU) vs. -67.54 ± 9.94 HU; p < 0.001), and the cut-off value determined by the receiver operating characteristic (ROC) curve was -77.50 HU. Multivariable analysis revealed no statistical significance in the clinical data, FAI ≤ -77.50 HU (odds ratio (OR): 33.96), negative remodeling (OR: 4.36), severe calcification degree (OR: 4.43) and occlusion length ≥ 20.25 mm (OR: 3.89) were independent predictors of A-PCI failure. The prediction performance of combining the three morphologic characteristics (severe calcification, occlusion length ≥ 20.25 mm, and negative remodeling) with FAI ≤ -77.50 HU was better than that of the three morphologic characteristics alone (0.93 versus 0.77, p < 0.001). CONCLUSIONS: As a non-invasive index for detecting coronary inflammation, FAI complements indicators based on coronary CTA well and may be helpful for choosing appropriate interventional strategies. KEY POINTS: • Perivascular FAI of CTO was significantly higher in the failed A-PCI group. • The combination of FAI with other morphological predictors showed higher predictive performance of failed A-PCI for CTOs. • FAI is a good complement to indicators based on coronary CTA.

Seizures in children undergoing extracorporeal membrane oxygenation: a systematic review and meta-analysis.

OBJECTIVES: To investigate the incidence of seizures and short-term mortality associated with seizures in children undergoing extracorporeal membrane oxygenation (ECMO). METHODS: PubMed, Embase, and Web of Science were searched from inception to September 2021. Study quality was assessed using the Newcastle-Ottawa Scale. Random effects meta-analysis was conducted. RESULTS: Fourteen studies met the inclusion criteria for quantitative meta-analysis. The cumulative estimate of seizure incidence was 15% (95% CI: 12-17%). Studies using electroencephalography reported a higher incidence of seizures compared with those using electro-clinical criteria (19% vs. 9%, P = 0.034). Furthermore, 75% of seizures were subclinical. Children receiving extracorporeal cardiopulmonary resuscitation (ECPR) exhibited a higher incidence of seizures compared to children with respiratory and cardiac indications. Seizure incidence was higher in patients undergoing venoarterial (VA) ECMO compared with venovenous (VV) ECMO. The pooled odds ratio of mortality was 2.58 (95% CI: 2.25-2.95) in those developed seizures. CONCLUSION: The incidence of seizures in children requiring ECMO was 15% and majority of seizures were subclinical. The incidence of seizures was higher in patients receiving ECPR than in those with respiratory and cardiac indications. Seizures were more frequent in patients undergoing VA ECMO than VV ECMO. Seizures were associated with increased short-term mortality. IMPACT: The incidence of seizures in children undergoing extracorporeal membrane oxygenation (ECMO) was ~15% and majority of the seizures were subclinical. Seizures were associated with increased short-term mortality. Risk factors for seizures were extracorporeal cardiopulmonary resuscitation and venoarterial ECMO. Electroencephalography (EEG) monitoring is recommended in children undergoing ECMO and further studies on the optimal protocol for EEG monitoring are necessary.

The Diagnostic Efficiency of Quantitative Diffusion Weighted Imaging in Differentiating Medulloblastoma from Posterior Fossa Tumors: A Systematic Review and Meta-Analysis.

Medulloblastoma (MB) is considered the most common and highly malignant posterior fossa tumor (PFT) in children. The accurate preoperative diagnosis of MB is beneficial in choosing the appropriate surgical methods and treatment strategies. Diffusion-weighted imaging (DWI) has improved the accuracy of differential diagnosis of posterior fossa tumors. Nonetheless, further studies are needed to confirm its value for clinical application. This study aimed to evaluate the performance of DWI in differentiating MB from other PFT. A literature search was conducted using databases PubMed, Embase, and Web of Science for studies reporting the diagnostic performance of DWI for PFT from January 2000 to January 2022. A bivariate random-effects model was employed to evaluate the pooled sensitivities and specificities. A univariable meta-regression analysis was used to assess relevant factors for heterogeneity, and subgroup analyses were performed. A total of 15 studies with 823 patients were eligible for data extraction. Overall pooled sensitivity and specificity of DWI were 0.94 (95% confident interval [CI]: 0.89-0.97) and 0.94 (95% CI: 0.90-0.96) respectively. The area under the curve (AUC) of DWI was 0.98 (95% CI: 0.96-0.99). Heterogeneity was found in the sensitivity (I2 = 62.59%) and the specificity (I2 = 35.94%). Magnetic field intensity, region of interest definition and DWI diagnostic parameters are the factors that affect the diagnostic performance of DWI. DWI has excellent diagnostic accuracy for differentiating MB from other PFT. Hence, it is necessary to set DWI as a routine examination sequence for posterior fossa tumors.

Magnetic Resonance Imaging Guided Prostate Biopsy in Patients with ≥ One Negative Systematic Transrectal Ultrasound-Guided Biopsy: A Systemic Review and Meta-Analysis.

The present study aimed to compare prostate cancer (PCa) and clinically significant PCa (csPCa) detection sensitivity between magnetic resonance imaging guided-biopsy (MRI-GB) and transrectal ultrasound-guided biopsy (TRUS-GB) in patients with ≥ 1 negative TRUS-GB, and to explore the additive value of TRUS-GB to MRI-GB. The meta-analysis of 18 studies demonstrated that MRI-GB had a similar sensitivity for PCa detection but a higher sensitivity for csPCa than TRUS-GB. In conclusion, there was limited value in combining TRUS-GB with MRI-GB compared with MRI-GB alone for csPCa detection in patients with one or more negative TRUS-GBs that were suspicious of having PCa.

Machine learning to predict post-operative acute kidney injury stage 3 after heart transplantation.

BACKGROUND: Acute kidney injury (AKI) stage 3, one of the most severe complications in patients with heart transplantation (HT), is associated with substantial morbidity and mortality. We aimed to develop a machine learning (ML) model to predict post-transplant AKI stage 3 based on preoperative and perioperative features. METHODS: Data from 107 consecutive HT recipients in the provincial center between 2018 and 2020 were included for analysis. Logistic regression with L2 regularization was used for the ML model building. The predictive performance of the ML model was assessed using the area under the curve (AUC) in tenfold stratified cross-validation and was compared with that of the Cleveland-clinical model. RESULTS: Post-transplant AKI occurred in 76 (71.0%) patients including 15 (14.0%) stage 1, 18 (16.8%) stage 2, and 43 (40.2%) stage 3 cases. The top six features selected for the ML model to predicate AKI stage 3 were serum cystatin C, estimated glomerular filtration rate (eGFR), right atrial long-axis dimension, left atrial anteroposterior dimension, serum creatinine (SCr) and FVII. The predictive performance of the ML model (AUC: 0.821; 95% confidence interval [CI]: 0.740-0.901) was significantly higher compared with that of the Cleveland-clinical model (AUC: 0.654; 95% [CI]: 0.545-0.763, p < 0.05). CONCLUSIONS: The ML model, which achieved an effective predictive performance for post-transplant AKI stage 3, may be helpful for timely intervention to improve the patient's prognosis.

Angiopep-2 as an Exogenous Chemical Exchange Saturation Transfer Contrast Agent in Diagnosis of Alzheimer's Disease.

Background: Chemical exchange saturation transfer (CEST) is a novel imaging modality in clinical practice and scientific research. Angiopep-2 is an artificial peptide that can penetrate blood-brain barrier. The aim of this study was to explore the feasibility of Angiopep-2 serving as an exogenous CEST contrast. Methods: Phantoms of Angiopep-2 with different concentrations were prepared and then scanned using the 7.0T small animal MRI scanner. Different parameters including saturation powers and saturation duration were used to achieve the optimal CEST effect, and the optimal parameters were finally selected based on Z-spectra, asymmetric spectra, and phantom CEST imaging. CEST scanning of dimethyl sulfoxide (DMSO), the substance helping Angiopep-2 to be dissolved in water, was performed to exclude its contribution for the CEST effect. Results: A broad dip was observed from 2.5 to 3.5 ppm in the Z-spectra of Angiopep-2 phantoms. The most robust CEST was generated at 3.2 ppm when using formula (M -3.2ppm - M +3.2ppm)/M -3.2ppm. The CEST effect of Angiopep-2 was concentration dependent; the effect increased as the concentration increased. In addition, the CEST effect was more obvious as the saturation power increased and peaked at 5.5 µT, and the CEST effect increased as the saturation duration increased. DMSO showed nearly 0% of the CEST effect at 3.2 ppm. Conclusions: Our results demonstrate that Angiopep-2 can act as an excellent exogenous CEST contrast. As it can penetrate blood-brain barrier and bind amyloid-ß protein, amyloid-ß targeting CEST, with Angiopep-2 as an exogenous contrast agent, can be potentially used as a novel imaging modality for early diagnosis of Alzheimer's disease. Collectively, Angiopep-2 may play a critical role in early diagnosis of Alzheimer's disease.

Whole-Body MRI Is an Effective Imaging Modality for Hematological Malignancy Treatment Response Assessment: A Systematic Review and Meta-Analysis.

OBJECTIVES: To evaluate the diagnostic accuracy of whole-body MRI (WB-MRI) for assessment of hematological malignancies' therapeutic response. METHODS: PubMed, Embase, and Web of Science were searched up to August 2021 to identify studies reporting the diagnostic performance of WB-MRI for the assessment of hematological malignancies' treatment response. A bivariate random-effects model was applied for the generation of the pooled diagnostic performance. RESULTS: Fourteen studies with 457 patients with lymphoma, multiple myeloma, and sarcoma (very small proportion) were analyzed. Overall pooled sensitivity and specificity of WB-MRI were 0.88 (95% CI: 0.73-0.95) and 0.86 (95% CI: 0.73-0.93), respectively. Studies using whole-body diffusion-weighted imaging (WB-DWI) showed higher sensitivity than those that did not (0.94 vs. 0.55, p = 0.02). The pooled concordance rate of WB-MRI to assess hematological malignancies' treatment response with reference standard was 0.78 (95% CI: 0.59-0.96). WB-MRI and PET/CT showed similar diagnostic performance (sensitivity [0.83 vs. 0.92, p = 0.11] and specificity [0.87 vs. 0.76, p = 0.73]). CONCLUSION: WB-MRI has high diagnostic performance for hematological malignancies' treatment response assessment. The adding of WB-DWI is strongly associated with increased sensitivity.

Machine Learning to Predict Long-Term Cardiac-Relative Prognosis in Patients With Extra-Cardiac Vascular Disease.

Aim: Patients with ischemic stroke (IS), transient ischemic attack (TIA), and/or peripheral artery disease (PAD) represent a population with an increased risk of coronary artery disease. Prognostic risk assessment to identify those with the highest risk that may benefit from more intensified treatment remains challenging. To explore the feasibility and capability of machine learning (ML) to predict long-term adverse cardiac-related prognosis in patients with IS, TIA, and/or PAD. Methods: We analyzed 636 consecutive patients with a history of IS, TIA, and/or PAD. All patients underwent a coronary CT angiography (CCTA) scan. Thirty-five clinical data and 34 CCTA metrics underwent automated feature selection for ML model boosting. The clinical outcome included all-cause mortality (ACM) and major adverse cardiac events (MACE) (ACM, unstable angina requiring hospitalization, non-fatal myocardial infarction (MI), and revascularization 90 days after the index CCTA). Results: During the follow-up of 3.9 ± 1.6 years, 21 patients had unstable angina requiring hospitalization, eight had a MI, 23 had revascularization and 13 deaths. ML demonstrated a significant higher area-under-curve compared with the modified Duke index (MDI), segment stenosis score (SSS), segment involvement score (SIS), and Framingham risk score (FRS) for the prediction of ACM (ML:0.92 vs. MDI:0.66, SSS:0.68, SIS:0.67, FRS:0.51, all P < 0.001) and MACE (ML:0.84 vs. MDI:0.82, SSS:0.76, SIS:0.73, FRS:0.53, all P < 0.05). Conclusion: Among the patients with IS, TIA, and/or PAD, ML demonstrated a better capability of predicting ACM and MCAE than clinical scores and CCTA metrics.

A meta-analysis of the added value of diffusion weighted imaging in combination with contrast-enhanced magnetic resonance imaging for the diagnosis of small hepatocellular carcinoma lesser or equal to 2 cm.

Diffusion weighted imaging (DWI) has been found to increase the sensitivity in the diagnosis of small hepatocellular carcinoma (HCC), although additional studies are required to confirm its value. The aim of the present study was to explore the diagnostic performance of DWI combined with contrast-enhanced magnetic resonance imaging (MRI) for small HCC by performing a meta-analysis. Literature databases (PubMed, Embase, Web of Science and Cochrane Library databases) were searched to identify studies reporting the sensitivity and specificity of MRI with DWI for the diagnosis of small HCCs. Pooled sensitivity and specificity were generated using a bivariate random effect model. Multilevel mixed-effects logistic regression analysis was used to examine the value of DWI combined with conventional MRI. A total of 837 small HCCs and 545 benign liver lesions from 10 studies were included. The overall sensitivity and specificity of DWI combined with contrast-enhanced MRI was 0.88 (95% CI, 0.80-0.93) and 0.90 (95% CI, 0.81-0.95), respectively. Compared with that in contrast-enhanced MRI, DWI with contrast-enhanced MRI had a significantly higher sensitivity for the diagnosis of small HCC (P=0.01) while there was no significant difference in the specificity (P=0.603). The present meta-analysis suggests that DWI combined with contrast-enhanced MRI may increase the sensitivity, whilst maintaining high specificity for the diagnosis of small HCCs with a diameter ≤2 cm.

Novel nanomedicine with a chemical-exchange saturation transfer effect for breast cancer treatment in vivo.

BACKGROUND: Nanomedicine is a promising new approach to cancer treatment that avoids the disadvantages of traditional chemotherapy and improves therapeutic indices. However, the lack of a real-time visualization imaging technology to monitor drug distribution greatly limits its clinical application. Image-tracked drug delivery is of great clinical interest; it is useful for identifying those patients for whom the therapy is more likely to be beneficial. This paper discusses a novel nanomedicine that displays features of nanoparticles and facilitates functional magnetic resonance imaging but is challenging to prepare. RESULTS: To achieve this goal, we synthesized an acylamino-containing amphiphilic block copolymer (polyethylene glycol-polyacrylamide-polyacetonitrile, PEG-b-P(AM-co-AN)) by reversible addition-fragmentation chain transfer (RAFT) polymerization. The PEG-b-P(AM-co-AN) has chemical exchange saturation transfer (CEST) effects, which enable the use of CEST imaging for monitoring nanocarrier accumulation and providing molecular information of pathological tissues. Based on PEG-b-P(AM-co-AN), a new nanomedicine PEG-PAM-PAN@DOX was constructed by nano-precipitation. The self-assembling nature of PEG-PAM-PAN@DOX made the synthesis effective, straightforward, and biocompatible. In vitro studies demonstrate decreased cytotoxicity of PEG-PAM-PAN@DOX compared to free doxorubicin (half-maximal inhibitory concentration (IC50), mean ~ 0.62 µg/mL vs. ~ 5 µg/mL), and the nanomedicine more efficiently entered the cytoplasm and nucleus of cancer cells to kill them. Further, in vivo animal experiments showed that the nanomedicine developed was not only effective against breast cancer, but also displayed an excellent sensitive CEST effect for monitoring drug accumulation (at about 0.5 ppm) in tumor areas. The CEST signal of post-injection 2 h was significantly higher than that of pre-injection (2.17 ± 0.88% vs. 0. 09 ± 0.75%, p < 0.01). CONCLUSIONS: The nanomedicine with CEST imaging reflects the characterization of tumors and therapeutic functions has great potential medical applications.

Imaging of glutamate in acute traumatic brain injury using chemical exchange saturation transfer.

BACKGROUND: Chemical exchange saturation transfer (CEST) is an important contrast mechanism in the field of magnetic resonance imaging. Herein, we used CEST for glutamate (GluCEST) imaging to evaluate the Glu alterations in acute mild to moderate traumatic brain injury (TBI) and correlated such alterations with the cognitive outcome at 1-month postinjury. METHODS: Thirty-two patients with well-documented mild-to-moderate TBI and 15 healthy controls (HC group) underwent 3.0-Tesla magnetic resonance imaging (MRI) with GluCEST, and magnetic resonance spectroscopy (MRS) scans. The Montreal Cognitive Assessment (MoCA) examination was administered to all study subjects at 1-month postinjury for cognitive outcome acquisition and divided TBI patients into patients with good cognitive outcome (GCO group) and with poor cognitive outcome (PCO group). RESULTS: The GluCEST% values for the occipital gray matter (OGM) and bilateral parietooccipital white matter (PWM) were higher in the PCO group compared with the HC and GCO groups (P<0.05), whereas the GluCEST% value showed no significant differences between the GCO and HC groups (P>0.05). In comparison with HCs, TBI patients had a significantly increased GluCEST% value for the OGM and bilateral PWM (P<0.05). GluCEST performed better than MRS in the prediction of cognitive outcome for TBI patients (P<0.05). CONCLUSIONS: Glu is significantly increased in acute TBI and strongly correlates with the cognitive outcome at 1month postinjury. GluCEST may supply new insight into TBI and help to improve the accuracy of short-term outcome prediction.

Brain Amide Proton Transfer Imaging of Rat With Alzheimer's Disease Using Saturation With Frequency Alternating RF Irradiation Method.

Amyloid-ß (Aß) deposits and some proteins play essential roles in the pathogenesis of Alzheimer's disease (AD). Amide proton transfer (APT) imaging, as an imaging modality to detect tissue protein, has shown promising features for the diagnosis of AD disease. In this study, we chose 10 AD model rats as the experimental group and 10 sham-operated rats as the control group. All the rats underwent a Y-maze test before APT image acquisition, using saturation with frequency alternating RF irradiation (APTSAFARI) method on a 7.0 T animal MRI scanner. Compared with the control group, APT (3.5 ppm) values of brain were significantly reduced in AD models (p < 0.002). The APTSAFARI imaging is more significant than APT imaging (p < 0.0001). AD model mice showed spatial learning and memory loss in the Y-maze experiment. In addition, there was significant neuronal loss in the hippocampal CA1 region and cortex compared with sham-operated rats. In conclusion, we demonstrated that APT imaging could potentially provide molecular biomarkers for the non-invasive diagnosis of AD. APTSAFARI MRI could be used as an effective tool to improve the accuracy of diagnosis of AD compared with conventional APT imaging.

Lumbar Spinal Cord Activity and Blood Biochemical Changes in Individuals With Diabetic Peripheral Neuropathy During Electrical Stimulation.

It is difficult to perform an in vivo evaluation of the nerve conduction mechanism in a patient with diabetic peripheral neuropathy (DPN). We aim to explore possible activation differences to enable a further understanding of the nerve conduction mechanisms of diabetic neuropathy and to present a novel clinical method to evaluate nerve injury and recovery. DPN patients (n = 20) and healthy volunteers (n = 20) were included in this study to detect the functional activation of the lumbar spinal cord via electric stimulation. Spinal fMRI data sets were acquired via a single-shot fast spin echo (SSFSE) sequence. A task-related fMRI was performed via low-frequency electrical stimulation. After post-processing, the active voxels and the percentage of signal changes were calculated for the DPN evaluation and the correlations between the blood biochemical indexes, such as glucose, total cholesterol, and hemoglobin A1c were explored. Activation in the DPN patients was primarily observed in the T12 (10/13) vertebral level. The percentage of signal changes in DPN patients was higher than that in the control group (Z = -2.757, P < 0.05). Positive correlation between the percentage of signal changes and the total cholesterol/glucose in the DNP group was found (P < 0.05). Lumbar spinal cord fMRI, based on the SEEP effect, was determined to be feasible. The repetitive activation distribution was primarily located at the T12 vertebral level. Lumbar spinal cord fMRI might be used as a potential tool to assess and reveal the nerve conduction mechanisms in DPN.

APT Weighted MRI as an Effective Imaging Protocol to Predict Clinical Outcome After Acute Ischemic Stroke.

To explore the capability of the amide-proton-transfer weighted (APTW) magnetic resonance imaging (MRI) in the evaluation of clinical neurological deficit at the time of hospitalization and assessment of long-term daily functional outcome for patients with acute ischemic stroke (AIS). We recruited 55 AIS patients with brain MRI acquired within 24-48 h of symptom onset and followed up with their 90-day modified Rankin Scale (mRS) score. APT weighted MRI was performed for all the study subjects to measure APTW signal quantitatively in the acute ischemic area (APTWipsi) and the contralateral side (APTWcont). Change of the APT signal between the acute ischemic region and the contralateral side (ΔAPTW) was calculated. Maximum APTW signal (APTWmax) and minimal APTW signal (APTWmin) were also acquired to demonstrate APTW signals heterogeneity (APTWmax-min). In addition, all the patients were divided into 2 groups according to their 90-day mRS score (good prognosis group with mRS score <2 and poor prognosis group with mRS score ≥2). In the meantime, ΔAPTW of these groups was compared. We found that ΔAPTW was in good correlation with National Institutes of Health Stroke Scale (NIHSS) score (R 2 = 0.578, p < 0.001) and 90-day mRS score (R 2 = 0.55, p < 0.001). There was significant difference of ΔAPTW between patients with good prognosis and patients with poor prognosis. Plus, APTWmax-min was significantly different between two groups. These results suggested that APT weighted MRI could be used as an effective tool to assess the stroke severity and prognosis for patients with AIS, with APTW signal heterogeneity as a possible biomarker.