Vessel wall imaging with advanced flow suppression in the characterization of intracranial aneurysms following flow diversion with Pipeline embolization device

BackgroundHigh-resolution vessel wall MRI (VWI) is increasingly used to characterize intramural disorders of the intracranial vasculature unseen by conventional arteriography.ObjectiveTo evaluate the use of VWI for surveillance of flow diverter (FD) treated aneurysms.Materials and methodsRetrospective study of 28 aneurysms (in 21 patients) treated with a FD (mean 57 years; 14 female). All examinations included VWI and a contemporaneously obtained digital subtraction angiogram. Multiplanar pre- and post-gadolinium 3D, variable flip-angle T1 black-blood VWI was obtained using delay alternating nutation for tailored excitation (DANTE) at 3T. 3D time-of-flight MR angiography (MRA) was also carried out. Images were assessed for in-stent stenosis, aneurysm occlusion, presence and pattern/distribution of aneurysmal or parent vessel gadolinium enhancement.ResultsThe VWI-MRI was performed on average at 361±259 days after the intervention. Follow-up DSA was performed at 338±254 days postintervention. Good or excellent black-blood angiographic quality was recorded in 22/28 (79%) pre-contrast and 21/28 (75%) post-contrast VWI, with no cases excluded for image quality. Aneurysm enhancement was noted in 24/28 (85.7%) aneurysms, including in 79% of angiographically occluded aneurysms and 100% of angiographically non-occluded aneurysms. Enhancement of the stented parent-vessel wall occurred significantly more often when aneurysm enhancement was present (92% vs 33%, p=0.049).ConclusionAdvanced VWI produces excellent depiction of FD-treated aneurysms, with robust evaluation of the parent vessel and aneurysm wall to an extent not achievable with conventional MRI/MRA. Gadolinium enhancement may, however, continue even after enduring catheter angiographic occlusion, confounding interpretation, and requiring cognizance of this potentially prolonged effect in such patients.

Experimental evidence of non-classical brain functions

Exploring unknown quantum systems is an experimental challenge. Recent proposals exploring quantum gravity have suggested circumventing this problem by considering the unknown system as a mediator between two known systems. If such a mediation can locally generate entanglement in the known systems, then the mediator must be non-classical. The same approach may be applicable to other systems, in particular the brain, where speculations about quantum operations in consciousness and cognition have a long history. Translated to the brain, the mediator is then an unknown brain function. For the quantum systems, we could use proton spins of bulk water, which most likely interfere with the any brain function. Entanglement in these spins can be witnessed with multiple quantum coherence (MQC). We based our witness protocol on zero quantum coherence (ZQC) whereby potential signals from local properties were minimised. For short repetitive periods, we found ZQC signals in large parts of the brain, whereby the temporal appearance resembled heartbeat-evoked potentials (HEPs). Similar to HEPs, we also found that the ZQC signal depended on conscious awareness. Consciousness-related signals have, to our knowledge, not yet been reported in NMR. Remarkably, we could exclude local properties as contrast mechanism because (a) the ZQC signals had no correlates known in conventional MRI, and (b) the ZQC signals only appeared if the local properties of the magnetisation, which are complementary to non-local properties, were reduced. Our findings suggest that we may have witnessed entanglement mediated by consciousness-related brain functions. Those brain functions must then operate non-classically, which would mean that consciousness is non-classical.

Differentiation of Cerebral Neoplasms with Vessel Size Imaging (VSI)

Purpose Cerebral neoplasms of various histological origins may show comparable appearances on conventional Magnetic Resonance Imaging (MRI). Vessel size imaging (VSI) is an MRI technique that enables noninvasive assessment of microvasculature by providing quantitative estimates of microvessel size and density. In this study, we evaluated the potential of VSI to differentiate between brain tumor types based on their microvascular morphology. Methods Using a clinical 3T MRI scanner, VSI was performed on 25 patients with cerebral neoplasms, 10 with glioblastoma multiforme (GBM), 8 with primary CNS lymphoma (PCNSL) and 7 with cerebral lung cancer metastasis (MLC). Following the postprocessing of VSI maps, mean vessel diameter (vessel size index, vsi) and microvessel density (Q) were compared across tumors, peritumoral areas, and healthy tissues. Results The MLC tumors have larger and less dense microvasculature compared to PCNSLs in terms of vsi and Q (p = 0.0004 and p < 0.0001, respectively). GBM tumors have higher yet non-significantly different vsi values than PCNSLs (p = 0.065) and non-significant differences in Q. No statistically significant differences in vsi or Q were present between GBMs and MLCs. GBM tumor volume was positively correlated with vsi (r = 0.502, p = 0.0017) and negatively correlated with Q (r = −0.531, p = 0.0007). Conclusion Conventional MRI parameters are helpful in differentiating between PCNSLs, GBMs, and MLCs. Additionally incorporating VSI parameters into the diagnostic protocol could help in further differentiating between PCNSLs and metastases and potentially between PCNSLs and GBMs. Future studies in larger patient cohorts are required to establish diagnostic cut-off values for VSI.

Qualitative and quantitative diagnosis of intramuscular hemangioma subtypes: Diagnostic performance comparison of ESWAN and conventional MRI

Background Preoperative identification of intramuscular hemangioma (IMH) subtypes (capillary hemangioma, cavernous hemangioma, and mixed hemangioma) is urgently necessary. Enhanced T2*-weighted angiography (ESWAN) is sensitive to vessels and metabolites and can be used to diagnose IMH subtypes. Purpose To compare the diagnostic performances of ESWAN and conventional magnetic resonance imaging (MRI) for qualitative and quantitative diagnosis of IMH subtypes. Material and Methods In total, 23 patients with IMHs were examined using conventional MRI and ESWAN. The signal intensity ratios (SIRs) of conventional MRI and ESWAN were measured. Results There was no significant difference for volume among the three subtypes ( P = 0.124, P = 0.145). Various shapes and MRI signals were shown in the three subtypes of IMH. There was no significant difference for SIRs of conventional MRI ( P = 0.558, P = 0.259, P = 0.385, P = 0.347). However, there was a significant difference for SIRs of ESWAN parameters ( P = 0.050, P < 0.001, P = 0.005, P = 0.002). Capillary hemangiomas can be diagnosed when R2* SIR is <0.912 and intratumoral susceptibility signal (ITSS) percentage is <29.085%. Cavernous hemangiomas should be considered when R2* SIR is >0.912, ITSS percentage >35.226%, and phase SIR >2.536. In addition, mixed hemangiomas should be considered when T2* SIR is >0.662 and R2* SIR <1.618. Conclusion Conventional MRI can only display the volume, shape, and signal of IMHs. 3D-MinIP imaging of ESWAN can show the veins and minor hemorrhage. SIRs of ESWAN parameters including T2* value, R2* value, phase value, and percentage of ITSS can be used to quantitatively diagnose capillary hemangiomas, cavernous hemangiomas, and mixed hemangiomas.

Low-Rank Matrix Denoising Algorithm-Based MRI Image Feature for Therapeutic Effect Evaluation of NCRT on Rectal Cancer

This study aimed to explore the therapeutic effects of neoadjuvant chemoradiotherapy (NCRT) on rectal cancer patients using the MRI based on low-rank matrix denoising algorithm, which was then compared with the postoperative pathological examination to evaluate its application value in tumor staging after NCRT treatment. 15 patients with rectal cancer who met the requirements of radiotherapy and chemotherapy after conventional MRI were selected as the research subjects. The conventional MRI images before and after NCRT treatment were divided in two groups. One group was not processed and set as the conventional group; the other group was processed with low-rank matrix denoising algorithm and set as the optimized group. The two groups of images were observed for the changes in the ADC value and length and thickness of the tumor before and after NCRT treatment. The two groups were compared with the pathological examination for the complete remission of pathology (pCR) after the NCRT treatment and the tumor stage results. The results showed that Root Mean Square Error (RMSE) and Peak Signal to Noise Ratio (PSNR) (18.9121 and 74.9911 dB) after introducing the low-rank matrix denoising algorithm were significantly better than those before (20.1234 and 70.1234 dB) ( P < 0.05 ); there were notable differences in the tumor index data within the two groups before and after NCRT treatment ( P < 0.05 ), indicating that the NCRT treatment was effective. The pathological examination results of pCR data of the two groups were not much different ( P > 0.05 ); the examination results between the two groups were different, but no notable difference was noted ( P < 0.05 ); in the optimized group, there was no notable difference between the MRI results and the pathological examination results ( P < 0.05 ), while in the conventional group, there were notable differences in the MRI results and pathological examination results ( P < 0.05 ). In conclusion, MRI images based on low-rank matrix denoising algorithm are clearer, which can improve the diagnosis rate of patients and better display the changes of the microenvironment after NCRT treatment. It also indicates that NCRT treatment has significant clinical effects in the treatment of rectal cancer patients, which is worth promoting.

A non-invasive, automated diagnosis of Menière’s disease using radiomics and machine learning on conventional magnetic resonance imaging: A multicentric, case-controlled feasibility study

Purpose This study investigated the feasibility of a new image analysis technique (radiomics) on conventional MRI for the computer-aided diagnosis of Menière’s disease. Materials and methods A retrospective, multicentric diagnostic case–control study was performed. This study included 120 patients with unilateral or bilateral Menière’s disease and 140 controls from four centers in the Netherlands and Belgium. Multiple radiomic features were extracted from conventional MRI scans and used to train a machine learning-based, multi-layer perceptron classification model to distinguish patients with Menière’s disease from controls. The primary outcomes were accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the classification model. Results The classification accuracy of the machine learning model on the test set was 82%, with a sensitivity of 83%, and a specificity of 82%. The positive and negative predictive values were 71%, and 90%, respectively. Conclusion The multi-layer perceptron classification model yielded a precise, high-diagnostic performance in identifying patients with Menière’s disease based on radiomic features extracted from conventional T2-weighted MRI scans. In the future, radiomics might serve as a fast and noninvasive decision support system, next to clinical evaluation in the diagnosis of Menière’s disease.

Case Report: Detection of Symptomatic Treatment-Related Changes in a Patient With Anaplastic Oligodendroglioma Using FET PET

Following local and systemic treatment of gliomas, the differentiation between glioma relapse and treatment-related changes such as pseudoprogression or radiation necrosis using conventional MRI is limited. To overcome this limitation, various amino acid PET tracers such as O-[2-(18F)-fluoroethyl]-L-tyrosine (FET) are increasingly used and provide valuable additional clinical information. We here report neuroimaging findings in a clincally symptomatic 53-year-old woman with a recurrent anaplastic oligodendroglioma with MRI findings highly suspicious for tumor progression. In contrast, FET PET imaging suggested treatment-related changes considerably earlier than the regression of contrast enhancement on MRI. In patients with oligodendroglioma, the phenomenon of symptomatic treatment-related changes is not well described, making these imaging findings unique and important for clinical decision-making.