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Chemical exchange saturation transfer (CEST) is a relatively novel magnetic resonance imaging (MRI) technique with an image contrast designed for in vivo measurement of certain endogenous molecules with protons that are exchangeable with water protons, such as amide proton transfer commonly used for neuro-oncology applications. Recent technological advances have made it feasible to implement CEST on clinical grade scanners within practical acquisition times, creating new opportunities to integrate CEST in clinical workflow. In addition, the majority of CEST applications used in neuro-oncology are performed without the use gadolinium-based contrast agents which are another appealing feature of this technique. This review is written for clinicians involved in neuro-oncologic care (nonphysicists) as the target audience explaining what they need to know as CEST makes its way into practice. The purpose of this article is to (1) review the basic physics and technical principles of CEST MRI, and (2) review the practical applications of CEST in neuro-oncology.

IntroductionAcquisition and pre-processing pipelines for diffusion-weighted imaging (DWI) volumes are resource- and time-consuming. Generating synthetic DWI scalar maps from commonly acquired brain MRI sequences such as fluid-attenuated inversion recovery (FLAIR) could be useful for supplementing datasets. In this work we design and compare GAN-based image translation models for generating DWI scalar maps from FLAIR MRI for the first time.MethodsWe evaluate a pix2pix model, two modified CycleGANs using paired and unpaired data, and a convolutional autoencoder in synthesizing DWI fractional anisotropy (FA) and mean diffusivity (MD) from whole FLAIR volumes. In total, 420 FLAIR and DWI volumes (11,957 images) from multi-center dementia and vascular disease cohorts were used for training/testing. Generated images were evaluated using two groups of metrics: (1) human perception metrics including peak signal-to-noise ratio (PSNR) and structural similarity (SSIM), (2) structural metrics including a newly proposed histogram similarity (Hist-KL) metric and mean squared error (MSE).ResultsPix2pix demonstrated the best performance both quantitatively and qualitatively with mean PSNR, SSIM, and MSE metrics of 23.41 dB, 0.8, 0.004, respectively for MD generation, and 24.05 dB, 0.78, 0.004, respectively for FA generation. The new histogram similarity metric demonstrated sensitivity to differences in fine details between generated and real images with mean pix2pix MD and FA Hist-KL metrics of 11.73 and 3.74, respectively. Detailed analysis of clinically relevant regions of white matter (WM) and gray matter (GM) in the pix2pix images also showed strong significant (p < 0.001) correlations between real and synthetic FA values in both tissue types (R = 0.714 for GM, R = 0.877 for WM).Discussion/conclusionOur results show that pix2pix’s FA and MD models had significantly better structural similarity of tissue structures and fine details than other models, including WM tracts and CSF spaces, between real and generated images. Regional analysis of synthetic volumes showed that synthetic DWI images can not only be used to supplement clinical datasets, but demonstrates potential utility in bypassing or correcting registration in data pre-processing.

Purpose: Magnetic resonance image-guided radiotherapy for intracranial indications is a promising advance; however, uncertainties remain for both target localization after translation-only MR setup and intrafraction motion. This investigation quantified these uncertainties and developed a population-based planning target volume (PTV) model to explore target and organ-at-risk (OAR) volumetric coverage tradeoffs. Methods: Sixty-six patients, 49 with a primary brain tumor and 17 with a post-surgical resection cavity, treated on a 1.5T-based MR-linac across 1329 fractions were included. At each fraction, patients were setup by translation-only fusion of the online T1 MRI to the planning image. Each fusion was independently repeated offline accounting for rotations. The six degree-of-freedom difference between fusions was applied to transform the planning CTV at each fraction (CTVfx). A PTV model parameterized by volumetric CTVfx coverage, proportion of fractions, and proportion of patients was developed. Intrafraction motion was quantified in a 412 fraction subset as the fusion difference between post- and pre-irradiation T1 MRIs. Results: For the left–right/anterior-posterior/superior-inferior axes, mean ± SD of the rotational fusion differences were 0.1 ± 0.8/0.1 ± 0.8/-0.2 ± 0.9°. Covering 98 % of the CTVfx in 95 % of fractions in 95 % of patients required a 3 mm PTV margin. Margin reduction decreased PTV-OAR overlap; for example, the proportion of optic chiasm overlapped by the PTV was reduced up to 23.5 % by margin reduction from 4 mm to 3 mm. Conclusions: An evidence-based PTV model was developed for brain cancer patients treated on the MR-linac. Informed by this model, we have clinically adopted a 3 mm PTV margin for conventionally fractionated intracranial patients.

Interactions between subcortical vascular disease and dementia due to Alzheimer’s disease (AD) are unclear, and clinical overlap between the diseases makes diagnosis challenging. Existing studies have shown regional microstructural changes specific to each disease, and that textures in fluid-attenuated inversion recovery (FLAIR) MRI images may characterize abnormalities in tissue microstructure. This work aims to investigate regional FLAIR biomarkers that can differentiate dementia cohorts with and without subcortical vascular disease. FLAIR and diffusion MRI (dMRI) volumes were obtained in 65 mild cognitive impairment (MCI), 21 AD, 44 subcortical vascular MCI (scVMCI), 22 Mixed etiology, and 48 healthy elderly patients. FLAIR texture and intensity biomarkers were extracted from the normal appearing brain matter (NABM), WML penumbra, blood supply territory (BST), and white matter tract regions of each patient. All FLAIR biomarkers were correlated to dMRI metrics in each region and global WML load, and biomarker means between groups were compared using ANOVA. Binary classifications were performed using Random Forest classifiers to investigate the predictive nature of the regional biomarkers, and SHAP feature analysis was performed to further investigate optimal regions of interest for differentiating disease groups. The regional FLAIR biomarkers were strongly correlated to MD, while all biomarker regions but white matter tracts were strongly correlated to WML burden. Classification between Mixed disease and healthy, AD, and scVMCI patients yielded accuracies of 97%, 81%, and 72% respectively using WM tract biomarkers. Classification between scVMCI and healthy, MCI, and AD patients yielded accuracies of 89%, 84%, and 79% respectively using penumbra biomarkers. Only the classification between AD and healthy patients had optimal results using NABM biomarkers. This work presents novel regional FLAIR biomarkers that may quantify white matter degeneration related to subcortical vascular disease, and which indicate that investigating degeneration in specific regions may be more important than assessing global WML burden in vascular disease groups.

Background and Purpose: To quantitatively compare the recurrence patterns of glioblastoma (isocitrate dehydrogenase-wild type) versus grade 4 isocitrate dehydrogenase-mutant astrocytoma (wild type isocitrate dehydrogenase and mutant isocitrate dehydrogenase, respectively) following primary chemoradiation. Materials and Methods: A retrospective matched cohort of 22 wild type isocitrate dehydrogenase and 22 mutant isocitrate dehydrogenase patients were matched by sex, extent of resection, and corpus callosum involvement. The recurrent gross tumor volume was compared to the original gross tumor volume and clinical target volume contours from radiotherapy planning. Failure patterns were quantified by the incidence and volume of the recurrent gross tumor volume outside the gross tumor volume and clinical target volume, and positional differences of the recurrent gross tumor volume centroid from the gross tumor volume and clinical target volume. Results: The gross tumor volume was smaller for wild type isocitrate dehydrogenase patients compared to the mutant isocitrate dehydrogenase cohort (mean ± SD: 46.5 ± 26.0 cm 3 vs 72.2 ± 45.4 cm 3 , P = .026). The recurrent gross tumor volume was 10.7 ± 26.9 cm 3 and 46.9 ± 55.0 cm 3 smaller than the gross tumor volume for the same groups ( P = .018). The recurrent gross tumor volume extended outside the gross tumor volume in 22 (100%) and 15 (68%) ( P = .009) of wild type isocitrate dehydrogenase and mutant isocitrate dehydrogenase patients, respectively; however, the volume of recurrent gross tumor volume outside the gross tumor volume was not significantly different (12.4 ± 16.1 cm 3 vs 8.4 ± 14.2 cm 3 , P = .443). The recurrent gross tumor volume centroid was within 5.7 mm of the closest gross tumor volume edge for 21 (95%) and 22 (100%) of wild type isocitrate dehydrogenase and mutant isocitrate dehydrogenase patients, respectively. Conclusion: The recurrent gross tumor volume extended beyond the gross tumor volume less often in mutant isocitrate dehydrogenase patients possibly implying a differential response to chemoradiotherapy and suggesting isocitrate dehydrogenase status might be used to personalize radiotherapy. The results require validation in prospective randomized trials.

Fluid-attenuated inversion recovery (FLAIR) MRI has emerged as an important sequence for the analysis of cerebrovascular (CVD) and Alzheimer's disease (AD). Large-scale, automated cross-sectional and longitudinal cerebral biomarker extraction from FLAIR datasets could progress disease characterization, improve disease monitoring, and help to determine optimal intervention times. Despite this, most automated biomarker extraction algorithms are designed for T1-weighted or multi-modal inputs. In this work, automated tools were used to extract biomarkers from large, FLAIR-only datasets to evaluate the feasibility of this sequence to characterize healthy, AD, and CVD subjects in a similar manner to traditional approaches. Total brain volume (TBV), cerebrospinal fluid (CSF) volume, and white matter lesion (WML) volume was measured for the cross-sectional biomarkers and the corresponding annual rates of change over multiple scans represented the longitudinal biomarkers. Biomarkers were extracted from two dementia cohorts (4356 vol, 162 233 images) and one vascular disease cohort (869 vol, 42 850 images) using deep learning-based segmentation algorithms designed specifically for FLAIR. Biomarkers from all cohorts were summarized using descriptive statistics, correlation analysis, and ANCOVA to assess differences in diagnostic labels while accounting for demographic and acquisition factors. Biomarkers from FLAIR MRI had similar trends with those extracted from traditional modalities in the literature for characterizing healthy, AD, and CVD subjects. This demonstrates that FLAIR MRI can be used for end-to-end analysis of large AD and CVD datasets, which can lower acquisition costs, simplify clinical translation, and reduce measurement error associated with multi-modal approaches.

Students wishing to study engineering, mathematics and physics at Iranian universities are only graduates of high school mathematics- physics majors. Over the past two decades, there has been a significant reduction in the number of students choosing mathematics-physics major in high schools and, as a result, the number of applicants in the mathematics-physics major of the national university entrance exam has been reduced. This trend has led to a decrease in engineering applicants and a drop in their quality of academic level. Elite high school students do not show much desire to choose mathematics-physics major in high schools due to the numerous employment opportunities of graduates of experimental science major, especially medicine. This, in addition to reducing the number of applicants entering mathematics-physics major, but also has declined the quality of science of applicants entering engineering fields. The Society of Engineering Education of Iran organized a roundtable to investigate the reasons for this situation, and the material that I presented in this roundtable will be discussed in this article.

Each organization and institution is formed in the context of the necessity and need in the substrate of the social changes of its duration, and grows with the continuity of interaction with the same community that emerged from it. The higher education system will also be upgraded with a proper understanding of its position and mission, while paying attention to national needs along with developments in the global system. In the Twenty-year Program Document, Iran was aimed to be ranked first in science and technology as well as economic in Southwest Asia. Major efforts of the government and decision-makers of the country were to achieve this goal. This important will not be achieved except by materially and spiritual investment and the development of scientific infrastructures with a fundamental transformation in the country's higher education system. IR Iran Academy of Sciences, together with other institutions that have influenced the development of the macro policies of higher education, and the commitment to their long-standing role in the advancement of science and knowledge, need to pay attention to the importance of empowering the country's higher education system

A novel biomarker panel was proposed to quantify macro and microstructural biomarkers from the normal-appearing brain matter (NABM) in multicentre fluid-attenuation inversion recovery (FLAIR) MRI. The NABM is composed of the white and gray matter regions of the brain, with the lesions and cerebrospinal fluid removed. The primary hypothesis was that NABM biomarkers from FLAIR MRI are related to cognitive outcome as determined by MoCA score. There were three groups of features designed for this task based on 1) texture: microstructural integrity (MII), macrostructural damage (MAD), microstructural damage (MID), 2) intensity: median, skewness, kurtosis and 3) volume: NABM to ICV volume ratio. Biomarkers were extracted from over 1400 imaging volumes from more than 87 centres and unadjusted ANOVA analysis revealed significant differences in means of the MII, MAD, and NABM volume biomarkers across all cognitive groups. In an adjusted ANCOVA model, a significant relationship between MoCA categories was found that was dependent on subject age for MII, MAD, intensity, kurtosis and NABM volume biomarkers. These results demonstrate that structural brain changes in the NABM are related to cognitive outcome (with different relationships depending on the age of the subjects). Therefore these biomarkers have high potential for clinical translation. As a secondary hypothesis, we investigated whether texture features from FLAIR MRI can quantify microstructural changes related to how “structured” or “damaged” the tissue is. Based on correlation analysis with diffusion weighted MRI (dMRI), it was shown that FLAIR MRI texture biomarkers (MII and MAD) had strong correlations to mean diffusivity (MD) which is related to tissue degeneration in the GM and WM regions. As FLAIR MRI is routinely collected for clinical neurological examinations, novel biomarkers from FLAIR MRI could be used to supplement current clinical biomarkers and for monitoring disease progression. Biomarkers could also be used to stratify patients into homogeneous disease subgroups for clinical trials, or to learn more about mechanistic development of dementia disease.

Patients undergoing standard chemoradiation post-resection had MRIs at radiation planning and fractions 10 and 20 of chemoradiation. MRIs were 1.5T and 3D T2-FLAIR, pre- and post-contrast 3D T1-weighted (T1) and echo planar DWI with three b-values (0, 500, and 1000s/mm2) were acquired. T2-FLAIR was coregistered to T1C images. Non-overlapping T1 contrast-enhancing (T1C) and nonenhancing T2-FLAIR hyperintense regions were segmented, with necrotic/cystic regions, the surgical cavity, and large vessels excluded. The simplified IVIM model was used to calculate voxelwise diffusion coefficient (D) and perfusion fraction (f) maps; ADC was calculated using the natural logarithm of b = 1000 over b = 0 images. T1C and T2-FLAIR segmentations were brought into this space, and medians calculated. MGMT promoter methylation status (MGMTPMS), age at diagnosis, and Eastern Cooperative Oncology Group (ECOG) performance status were extracted from electronic medical records. The data were presented, analyzed, and described in the article, “Intravoxel incoherent motion (IVIM) modeling of diffusion MRI during chemoradiation predicts therapeutic response in IDH wildtype Glioblastoma”, published in Radiotherapy and Oncology [1].

Purpose of review: Use of gadolinium-based contrast agents (GBCA) in renal impairment is controversial, with physician and patient apprehension in acute kidney injury (AKI), chronic kidney disease (CKD), and dialysis because of concerns regarding nephrogenic systemic fibrosis (NSF). The position that GBCA are absolutely contraindicated in AKI, category G4 and G5 CKD (estimated glomerular filtration rate [eGFR] < 30 mL/min/1.73 m 2 ), and dialysis-dependent patients is outdated and may limit access to clinically necessary contrast-enhanced magnetic resonance imaging (MRI) examinations. This review and clinical practice guideline addresses the discrepancy between existing Canadian guidelines regarding use of GBCA in renal impairment and NSF. Sources of information: Published literature (including clinical trials, retrospective cohort series, review articles, and case reports), online registries, and direct manufacturer databases were searched for reported cases of NSF by class and specific GBCA and exposed patient population. Methods: A comprehensive review was conducted identifying cases of NSF and their association to class of GBCA, specific GBCA used, patient, and dose (when this information was available). Based on the available literature, consensus guidelines were developed by an expert panel of radiologists and nephrologists. Key findings: In patients with category G2 or G3 CKD (eGFR ≥ 30 and < 60 mL/min/1.73 m 2 ), administration of standard doses of GBCA is safe and no additional precautions are necessary. In patients with AKI, with category G4 or G5 CKD (eGFR < 30 mL/min/1.73 m 2 ) or on dialysis, administration of GBCA should be considered individually and alternative imaging modalities utilized whenever possible. If GBCA are necessary, newer GBCA may be administered with patient consent obtained by a physician (or their delegate) citing an exceedingly low risk (much less than 1%) of developing NSF. Standard GBCA dosing should be used; half or quarter dosing is not recommended and repeat injections should be avoided. Dialysis-dependent patients should receive dialysis; however, initiating dialysis or switching from peritoneal to hemodialysis to reduce the risk of NSF is unproven. Use of a macrocyclic ionic instead of macrocyclic nonionic GBCA or macrocyclic instead of newer linear GBCA to further prevent NSF is unproven. Gadopentetate dimeglumine, gadodiamide, and gadoversetamide remain absolutely contraindicated in patients with AKI, those with category G4 or G5 CKD, or those on dialysis. The panel agreed that screening for renal disease is important but less critical when using macrocyclic and newer linear GBCA. Monitoring for and reporting of potential cases of NSF in patients with AKI or CKD who have received GBCA is recommended. Limitations: Limited available literature (number of injections and use in renal impairment) regarding the use of gadoxetate disodium. Limited, but growing and generally high-quality, number of clinical trials evaluating GBCA administration in renal impairment. Limited data regarding the topic of Gadolinium deposition in the brain, particularly as it related to patients with renal impairment. Implications: In patients with AKI and category G4 and G5 CKD (eGFR < 30 mL/min/1.73 m 2 ) and in dialysis-dependent patients who require GBCA-enhanced MRI, GBCA can be administered with exceedingly low risk of causing NSF when using macrocyclic agents and newer linear agents at routine doses.

In this paper, we provided our critical views on restructuring the Electrical Engineering education at bachelor¬,s level in Iran. We particularly discussed the conclusions and suggestions that are resulted from a study at Sharif University of Technology. Their approach to the problem, main ideas in restructuring, suggested new courses, and new syllabuses for old titles are critically analyzed. The main concerns are as follows: Curriculum planning at national level demands for a large poll of ideas at the same level; the suggested framework seems to be too rigid; there is only a little room for technical electives; the number and content of newly suggested courses does not match the rapid changes in the field; and the content of the newly suggested courses for first two semester are not consistent with students’ knowledge at those levels. We think many of these problems are due to insisting too much on keeping subprograms at bachelor level. Maybe it is time to remove subprograms and rescheduling the bachelor of Electrical Engineering as a three years program, followed by a two years advanced program. A three year program is more consistent with quarter-based system as compared with semester-based system. The former is more consistent with Iranian New Year holidays as well.

This paper considers the national infrastructure for science and research affairs. The focus is on research, researcher and its direct or indirect relationship with the scientific movement by the country. Based on this, a pyramidal structure is depicted which clarifies the research system. Research is not viewed as an individualized task, but as a systematic process that involves a wide range of subjects like determination of national strategies, the role of universities, managing solution of a scientific problem and evaluation of the results. This view of the subject illuminates the way that the organizations and individuals should interact during the process of scientific development. Based on this view, some important principles are emphasized for the national scientific planning that can result in a balanced scientific motion and increased motivation and awareness of the individuals. As a solution which is based on these principles, formation of a national virtual center for scientific research interactions is recommended.

This paper introduces a new holder with application on digital control systems. This holder is a combination of fractional order hold (FROH) and zero-order hold (ZOH) that has the capability of both holders and a frequency response better than both of ZOH and FROH. For the stability of zeros of the sampled system two theorems are stated and proved with the assumption that the sampling period is very small. Also simulation results are studied to show the effectiveness of the proposed holder and better performance results in comparison with ZOH and FROH.

Purpose: Magnetic resonance image-guided radiotherapy for intracranial indications is a promising advance; however, uncertainties remain for both target localization after translation-only MR setup and intrafraction motion. This investigation quantified these uncertainties and developed a population-based planning target volume (PTV) model to explore target and organ-at-risk (OAR) volumetric coverage tradeoffs., Methods: Sixty-six patients, 49 with a primary brain tumor and 17 with a post-surgical resection cavity, treated on a 1.5T-based MR-linac across 1329 fractions were included. At each fraction, patients were setup by translation-only fusion of the online T1 MRI to the planning image. Each fusion was independently repeated offline accounting for rotations. The six degree-of-freedom difference between fusions was applied to transform the planning CTV at each fraction (CTV fx ). A PTV model parameterized by volumetric CTV fx coverage, proportion of fractions, and proportion of patients was developed. Intrafraction motion was quantified in a 412 fraction subset as the fusion difference between post- and pre-irradiation T1 MRIs., Results: For the left-right/anterior-posterior/superior-inferior axes, mean ± SD of the rotational fusion differences were 0.1 ± 0.8/0.1 ± 0.8/-0.2 ± 0.9°. Covering 98 % of the CTV fx in 95 % of fractions in 95 % of patients required a 3 mm PTV margin. Margin reduction decreased PTV-OAR overlap; for example, the proportion of optic chiasm overlapped by the PTV was reduced up to 23.5 % by margin reduction from 4 mm to 3 mm., Conclusions: An evidence-based PTV model was developed for brain cancer patients treated on the MR-linac. Informed by this model, we have clinically adopted a 3 mm PTV margin for conventionally fractionated intracranial patients., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: James Stewart: Employment, Sunnybrook Odette Cancer Centre. Arjun Sahgal: Independent Contractor, Sunnybrook Odette Cancer Centre. Grants or contracts: Elekta AB, Varian. Honoraria for lectures and presentations: Varian (medical advisory group & CNS teaching faculty), Elekta (gamma knife ICON), Elekta AB, BrainLab, AstraZeneca, Medtronic Kyphon, Accuray, Merck, Abbvie, Roche. Meeting and travel support: Elekta AB, Varian, BrainLab. Advisory board participation: VieCure. Other: Board member with International Stereotactic Radiosurgery Society (ISRS), co-chair of AO Spine knowledge forum tumor, member of Elekta MR-Linac research consortium, member of Elekta Spine, member of Elekta Oligometastases and Elekta Linac based SRS consortia. Mahtab M Zadeh: None. Bahareh Moazen: Employment, Sunnybrook Research Institute. Pejman Jabehdar Maralani: Independent Contractor, Sunnybrook Health Sciences Centre. Stephen Breen: Employment, Sunnybrook Odette Cancer Centre. Angus Lau: Employment, Sunnybrook Research Institute. Shawn Binda: Employment, Sunnybrook Odette Cancer Centre. Brain Keller: Employment, Sunnybrook Odette Cancer Centre. Zain Husain: Independent Contractor, Sunnybrook Odette Cancer Centre. Sten Myrehaug: Independent Contractor, Sunnybrook Odette Cancer Centre, Grants or contracts: Ipsen Pharmaceuticals, AAA/Novartis, Consulting fees: AAA/Novartis, Honoraria for lectures and presentations: AAA/Novartis. Jay Detsky: Independent Contractor, Sunnybrook Odette Cancer Centre. Hany Soliman: Independent Contractor, Sunnybrook Odette Cancer Centre. Chia-Lin Tseng: Independent Contractor, Sunnybrook Odette Cancer Centre, Honoraria for lectures and presentations: Elekta AB, Meeting and travel support: Elekta AB, Advisory board participation: Sanofi S.A. Leadership on committee: Elekta AB (brain tumor site group lead for MR-Linac consortium). Mark Ruschin: Employment, Sunnybrook Odette Cancer Centre, Royalties: Elekta AB, Patents: Image-guided multi-source radiotherapy (US7729473B2)., (© 2023 The Authors.)