Optimizing Prostate Imaging Practices in Saudi Arabian Hospitals: A Comprehensive Analysis of PI-RADS Compliance in Multiparametric MRI.

BACKGROUND: Prostate cancer, a significant contributor to male cancer mortality globally, demands improved diagnostic strategies. In Saudi Arabia, where the incidence is expected to double, this study assessed the compliance of multiparametric MRI (mpMRI) practices with Prostate Imaging-Reporting and Data System version 2 (PI-RADS v2) guidelines across diverse healthcare institutions. METHODS: A survey was distributed to the radiology departments of all tertiary referral hospitals in Saudi Arabia (n=60) to assess their compliance with the technical specifications outlined in PI-RADS v2. Statistical analysis included chi-square, Fisher exact, ANOVA, and Student t-tests to examine the collected data. RESULTS: The study revealed an overall commendable compliance rate of 95.23%. However, significant variations were observed in technical parameters, particularly between 1.5 Tesla and 3 Tesla scanners and tertiary versus non-tertiary hospitals. Notable adherence in certain sequences contrasted with discrepancies in T2-weighted and diffusion-weighted imaging parameters. CONCLUSION: These findings underscore the need for nuanced approaches to optimize prostate imaging protocols, considering field strength and institutional differences. The study contributes to the ongoing refinement of standardized mpMRI practices, aiming to enhance diagnostic accuracy and improve clinical outcomes in prostate cancer.

Synthesis of N,N'-alkylidene bisamides and Suzuki-Miyaura coupling reaction derivatives with Pd organometallic catalyst anchored to channels of mesoporous silica MCM-41.

At first, an organometallic catalyst namely, Pd-DPyE@MCM-41@MNP was prepared through magnetic (Fe3O4) nanoparticles-doped into channels of mesoporous silica MCM-41 and then, anchoring a novel complex composed of di(4-pyridyl)ethylene and palladium on the inner surface of the support. This immobilized catalyst was successfully identified via VSM, ICP-OES, TEM, FTIR, TGA, SEM, BET, XRD, EDX and elemental mapping analyses. After that, it was used as a versatile, heterogeneous, and magnetically reproducible catalyst in the generation of N,N'-alkylidene bisamides (1a-13a, 8-20 min, 90-98%, 50 °C, solvent-free) and Suzuki-Miyaura coupling (SMC) reaction derivatives (1b-26b, 10-140 min, 86-98%, 60 °C, PEG-400). The VSM plot of Pd-DPyE@MCM-41@MNP displays that this nanocatalyst can be easily recycled by applying an external magnetic field. In both synthetic paths, this nanocatalyst was reused at least seven times without palladium leaching and significantly reducing its catalytic performance. Also, stability and heterogeneous nature of catalyst were approved via ICP-OES technique and hot filtration test.

Long non-coding RNA (lncRNA) PVT1 in drug resistance of cancers: Focus on pathological mechanisms.

According to estimates, cancer will be the leading cause of death globally in 2022, accounting for 9.6 million deaths. At present, the three main therapeutic modalities utilized to treat cancer are radiation therapy, chemotherapy, and surgery. However, during treatment, tumor cells resistant to chemotherapy may arise. Drug resistance remains a major oppose since it often leads to therapeutic failure. Furthermore, the term "acquired drug resistance" describes the situation where tumor cells already display drug resistance before undergoing chemotherapy. However, little is still known about the basic mechanisms underlying chemotherapy-induced drug resistance. The development of new technologies and bioinformatics has led to the discovery of additional genes associated with drug resistance. Long noncoding RNA plasmacytoma variant translocation 1 (PVT1) has been linked to an increased risk of cancer, according to a growing body of research. Apart from biological functions associated with cell division, development, pluripotency, and cell cycle, lncRNA PVT1 contributes significantly to the regulation of various aspects of genome function, such as transcription, splicing, and epigenetics. The article will address the mechanism by which lncRNA PVT1 influences drug resistance in cancer cells.

Artificial intelligence in cancer diagnosis: Opportunities and challenges.

Since cancer is one of the world's top causes of death, early diagnosis is critical to improving patient outcomes. Artificial intelligence (AI) has become a viable technique for cancer diagnosis by using machine learning algorithms to examine large volumes of data for accurate and efficient diagnosis. AI has the potential to alter the way cancer is detected fundamentally. Still, it has several disadvantages, such as requiring a large amount of data, technological limitations, and ethical concerns. This overview looks at the possibilities and restrictions of AI in cancer detection, as well as current applications and possible future developments. We can better understand how to use AI to improve patient outcomes and reduce cancer mortality rates by looking at its potential for cancer detection.

Investigating the Feasibility of Predicting KRAS Status, Tumor Staging, and Extramural Venous Invasion in Colorectal Cancer Using Inter-Platform Magnetic Resonance Imaging Radiomic Features.

(1) Background: Colorectal cancer is the third most common type of cancer with a high mortality rate and poor prognosis. The accurate prediction of key genetic mutations, such as the KRAS status, tumor staging, and extramural venous invasion (EMVI), is crucial for guiding personalized treatment decisions and improving patients' outcomes. MRI radiomics was assessed to predict the KRAS status and tumor staging in colorectal cancer patients across different imaging platforms to improve the personalized treatment decisions and outcomes. (2) Methods: Sixty colorectal cancer patients (35M/25F; avg. age 56.3 ± 12.9 years) were treated at an oncology unit. The MRI scans included T2-weighted (T2W) and diffusion-weighted imaging (DWI) or the apparent diffusion coefficient (ADC). The manual segmentation of colorectal cancer was conducted on the T2W and DWI/ADC images. The cohort was split into training and validation sets, and machine learning was used to build predictive models. (3) Results: The neural network (NN) model achieved 73% accuracy and an AUC of 0.71 during training for predicting the KRAS mutation status, while during testing, it achieved 62.5% accuracy and an AUC of 0.68. In the case of tumor grading, the support vector machine (SVM) model excelled with a training accuracy of 72.93% and an AUC of 0.7, and during testing, it reached an accuracy of 72% and an AUC of 0.69. (4) Conclusions: ML models using radiomics from ADC maps and T2-weighted images are effective for distinguishing KRAS genes, tumor grading, and EMVI in colorectal cancer. Standardized protocols are essential to improve MRI radiomics' reliability in clinical practice.

Provision of Safe Anesthesia in Magnetic Resonance Environments: Degree of Compliance with International Guidelines in Saudi Arabia.

BACKGROUND: The lack of local guidelines and regulations for the administration of anesthesia in magnetic resonance imaging (MRI) units presents a potential risk to patient safety in Saudi Arabia. Hence, this study aimed to evaluate the extent to which hospitals in Saudi Arabia follow international guidelines and recommendations for the safe and effective administration of anesthesia in an MRI environment. METHODS: This study used a questionnaire that was distributed to 31 medical facilities in Saudi Arabia that provided anesthesia in MRI units. RESULTS: The findings of the study revealed that the mean compliance with the 17 guidelines across the 31 sites was 77%; 5 of the 31 sites (16.1%) had a compliance rate of less than 50% with the recommended guidelines. Only 19.4% of the institutes provided general safety education. Communication breakdowns between anesthesia providers and MRI teams were reported. CONCLUSIONS: To conclude, this survey highlights the status of anesthesia standards in Saudi Arabian MRI units and emphasizes areas that require better adherence to international guidelines. The results call for targeted interventions, including the formulation of specific national anesthesia guidelines for MRI settings. Communication breakdowns between anesthesia providers and MRI teams were reported at a rate of 83.9% during the administration of a gadolinium contrast agent. There were additional breakdowns, particularly for high-risk patients with implants, such as impaired respirators (74.2%), thus requiring further investigation due to potential safety incidents during MRI procedures. While considering the limitations of this study, such as potential biases and the low response rate, it provides a valuable foundation for refining protocols and promoting standardized practices in Saudi Arabian healthcare.

Direct imaging of glymphatic transport using H217O MRI.

The recently proposed glymphatic pathway for solute transport and waste clearance from the brain has been the focus of intense debate. By exploiting an isotopically enriched MRI tracer, H217O, we directly imaged glymphatic water transport in the rat brain in vivo. Our results reveal glymphatic transport that is dramatically faster and more extensive than previously thought and unlikely to be explained by diffusion alone. Moreover, we confirm the critical role of aquaporin-4 channels in glymphatic transport.

Change in CSF Dynamics Responsible for ICP Elevation After Ischemic Stroke in Rats: a New Mechanism for Unexplained END?

It has been proposed that intracranial pressure (ICP) elevation and collateral failure are responsible for unexplained early neurological deterioration (END) in stroke. The study's aims were to investigate whether cerebral spinal fluid (CSF) dynamics, rather than edema, are responsible for elevation of ICP after ischemic stroke. Permanent middle cerebral artery occlusion (pMCAO) was induced with an intraluminal filament. At 24 h after stroke, baseline ICP was measured and CSF dynamics were probed via a steady-state infusion method. Diffusion-weighted imaging (DWI) and T2-weighted magnetic resonance imaging were performed to define cerebral ischemic damage and the volume of brain swelling. We found that the pMCAO group exhibited a significant increase in CSF outflow resistance (2.27 ± 0.15 mmHg µL-1 min) compared with the sham group (0.93 ± 0.06 mmHg µL-1 min, p = 0.002). There was no correlation between mean ICP at 24 h post-pMCAO and edema (r2 = - 0.03, p = 0.5) or infarct volumes (r2 = 0.09, p = 0.5). However, for the first time, we found a significant correlation between the baseline ICP at 24 h post-stroke and the value of CSF outflow resistance. Results show that CSF outflow resistance, rather than edema, was the mechanism responsible for ICP elevation following ischemic stroke. This challenges current concepts and suggests the possibility that intracranial hypertension may be occurring undetected in a much wider range of stroke patients than is currently considered to be the case. In addition, this further supports the hypothesis that unexplained early neurological deterioration is the result of elevated ICP, leading to reduced collateral flow and cerebral perfusion.