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.

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.