Functional MRI Techniques Research Articles

Visually driven functional MRI techniques for characterization of optic neuropathy

Optic neuropathies are conditions that cause disease to the optic nerve, and can result in loss of visual acuity and/or visual field defects. An improved understanding of how these conditions affect the entire visual system is warranted, to better predict and/or restore the visual loss. In this article, we review visually-driven functional magnetic resonance imaging (fMRI) studies of optic neuropathies, including glaucoma and optic neuritis (ON); we also discuss traumatic optic neuropathy (TON). Optic neuropathy-related vision loss results in fMRI deficit within the visual cortex, and is often strongly correlated with clinical severity measures. Using predominantly flickering checkerboard stimuli, glaucoma studies indicated retinotopic-specific cortical alteration with more prominent deficits in advanced than in early glaucoma. Some glaucoma studies indicate a reorganized visual cortex. ON studies have indicated that the impacted cortical areas are briefly hyperactive. For ON, brain deficits are greater in the acute stages of the disease, followed by (near) normalization of responses of the LGN, visual cortex, and the dorsal visual stream, but not the ventral extrastriate cortex. Visually-driven fMRI is sensitive, at least in ON, in discriminating patients from controls, as well as the affected eye from the fellow eye within patients. The use of a greater variety of stimuli beyond checkerboards (e.g., visual motion and object recognition) in recent ON studies is encouraging, and needs to continue to disentangle the results in terms of change over time. Finally, visually-driven fMRI has not yet been applied in TON, although preliminary efforts suggest it may be feasible. Future fMRI studies of optic neuropathies should consider using more complex visual stimuli, and inter-regional analysis methods including functional connectivity. We suggest that a more systematic longitudinal comparison of optic neuropathies with advanced fMRI would provide improved diagnostic and prognostic information.

Does liver diffusion tensor imaging (L-DTI) has a role in differentiation of hepatic focal lesions? Analytic study for assessment of the value of L-DTI in differentiating hepatic focal lesions according to LI-RADS

BackgroundMagnetic resonance imaging (MRI) plays an important role in the differentiation of hepatic focal lesions and diagnosis of hepatic malignancy, especially hepatocellular carcinoma which is a major health problem worldwide. Diffusion imaging is a functional MRI technique that became an essential part of MRI study of the liver. Recently, diffusion tensor imaging (DTI) is diffusion variant that can provide more information than conventional diffusion imaging based on the tissue anisotropy. The aim of this study was to present the role of DTI in the assessment and differentiation between hepatic focal lesions.ResultsFifty-one patients having 95 hepatic focal lesions who underwent dynamic MRI with conventional diffusion imaging and DTI acquisition were included in the study. A positive moderate significant correlation was found between Fractional anisotropy (FA) values and Liver Imaging Reporting and Data System (LI-RADS) category while substantial negative significant correlation and moderate negative significant correlation were found between DTI-ADC and DWI-ADC values, respectively, with the LI-RADS category. There was a significant negative correlation between DTI-ADC and FA values. DTI-ADC showed a significant role in differentiation of benign from malignant lesions with cut-off value 0.905 × 10−3 having 88.7% sensitivity and 88.3% specificity compared to 78.5% and 68.7% for DWI-ADC, respectively. Also, it was found that FA value had a significant role in differentiation between benign and malignant lesions with cut-off value 0.34 having 87.1% sensitivity and 73.9% specificity.ConclusionsDTI can be included in liver MRI studies for better tissue characterization as it may perform better than conventional DWI with higher sensitivity and specificity of DTI-ADC and FA values than conventional DWI-ADC.

Large-scale investigation of deep learning approaches for ventilated lung segmentation using multi-nuclear hyperpolarized gas MRI

Respiratory diseases are leading causes of mortality and morbidity worldwide. Pulmonary imaging is an essential component of the diagnosis, treatment planning, monitoring, and treatment assessment of respiratory diseases. Insights into numerous pulmonary pathologies can be gleaned from functional lung MRI techniques. These include hyperpolarized gas ventilation MRI, which enables visualization and quantification of regional lung ventilation with high spatial resolution. Segmentation of the ventilated lung is required to calculate clinically relevant biomarkers. Recent research in deep learning (DL) has shown promising results for numerous segmentation problems. Here, we evaluate several 3D convolutional neural networks to segment ventilated lung regions on hyperpolarized gas MRI scans. The dataset consists of 759 helium-3 (3He) or xenon-129 (129Xe) volumetric scans and corresponding expert segmentations from 341 healthy subjects and patients with a wide range of pathologies. We evaluated segmentation performance for several DL experimental methods via overlap, distance and error metrics and compared them to conventional segmentation methods, namely, spatial fuzzy c-means (SFCM) and K-means clustering. We observed that training on combined 3He and 129Xe MRI scans using a 3D nn-UNet outperformed other DL methods, achieving a mean ± SD Dice coefficient of 0.963 ± 0.018, average boundary Hausdorff distance of 1.505 ± 0.969 mm, Hausdorff 95th percentile of 5.754 ± 6.621 mm and relative error of 0.075 ± 0.039. Moreover, limited differences in performance were observed between 129Xe and 3He scans in the testing set. Combined training on 129Xe and 3He yielded statistically significant improvements over the conventional methods (p < 0.0001). In addition, we observed very strong correlation and agreement between DL and expert segmentations, with Pearson correlation of 0.99 (p < 0.0001) and Bland–Altman bias of − 0.8%. The DL approach evaluated provides accurate, robust and rapid segmentations of ventilated lung regions and successfully excludes non-lung regions such as the airways and artefacts. This approach is expected to eliminate the need for, or significantly reduce, subsequent time-consuming manual editing.

Correlation between functional MRI techniques and early disability in ambulatory patients with relapsing\u2013remitting MS

BackgroundMultiple sclerosis (MS) is a common neurological disorder which can lead to an occasional damage to the central nervous system. Conventional magnetic resonance imaging (cMRI) is an important modality in the diagnosis of MS; however, correlation between cMRI findings and clinical impairment is weak. Non-conventional MRI techniques including apparent diffusion coefficient (ADC) and magnetic resonance spectroscopy (MRS) investigate the metabolic changes over the course of MS and overcome the limits of cMRI.A total of 80 patients with MS and 20 age and sex-matched healthy control subjects were enrolled in this cross-sectional study. Ambulatory patients with relapsing–remitting MS (RRMS) were recruited. Expanded Disability Status Scale (EDSS) was used to assess the disability and the patients were categorized into three groups “no disability”, “minimal disability” and “moderate disability”. All patients underwent cMRI techniques. ADC was measured in MS plaques and in normal appearing white matter (NAWM) adjacent and around the plaque. All metabolites concentrations were expressed as ratios including N-acetyl-aspartate/creatine (NAA/Cr), choline/N-acetyl-aspartate (Cho/NAA) and choline/creatine (Cho/Cr). ADC and metabolite concentrations were measured in the normal white matter of 20 healthy control subjects.ResultsThe study was carried on 80 MS patients [36 males (45%) and 44 females (55%)] and 20 healthy control [8 males (40%) and 12 females (60%)]. The ADC values and MRS parameters in NAWM of patients with MS were significantly different from those of the control group. The number of the plaques on T2 images and black holes were significantly higher at “Minimal disability” group. Most of the enhanced plaques were at the “Moderate disability” group with P value < 0.001. The mean of ADC in the group 1, 2 and 3 of disability was 1.12 ± 0.19, 1.50 ± 0.35, 1.51 ± 0.36, respectively, with P value < 0. 001. In the group 1, 2 and 3 of disability, the mean of NAA/Cr ratio at the plaque was 1.34 ± 0.44, 1.59 ± 0.51 and 1.11 ± 0.15, respectively, with P value equal 0.001.ConclusionThe non-conventional quantitative MRI techniques are useful tools for detection of early disability in MS patients.

Diagnostic performance of MRI in detecting locally recurrent soft tissue sarcoma: systematic review and meta-analysis.

To systematically review the diagnostic criteria and performance of MRI in detecting locally recurrent soft tissue sarcoma. Medline and Embase were searched for original studies on the diagnostic performance of MRI detecting locally recurrent soft tissue sarcoma. Study quality was assessed using QUADAS-2. Sensitivity and specificity were pooled using a bivariate random-effects model. Ten studies were included. There was a high risk of bias with respect to patient selection in 2 studies and a high risk of bias with respect to flow and timing in 8 studies. The presence of a mass yielded a pooled sensitivity of 80.9% and a pooled specificity of 77.0%. Hyperintensity at T2-weighted imaging yielded a pooled sensitivity of 82.4% and a pooled specificity of 11.0%. Hypo- or isointensity at T1-weighted imaging yielded a pooled sensitivity of 82.0% and a pooled specificity of 14.3%. Contrast enhancement images yielded a pooled sensitivity of 95.9% and a pooled specificity of 12.3%. Low signal mass on the apparent diffusion coefficient (ADC) map yielded a pooled sensitivity of 67.5% and a pooled specificity of 95.3%. Early and rapid arterial phase enhancement at dynamic contrast-enhanced (DCE) MRI yielded a pooled sensitivity of 91.3% and a pooled specificity of 84.7%. The presence of a mass appears a useful criterion to diagnose locally recurrent soft tissue sarcoma. Signal characteristics at standard T2- and T1-weighted imaging and contrast enhancement seem less useful because they lack specificity. Functional MRI techniques, including DWI with ADC mapping and DCE, may help to make a correct diagnosis. • The presence of a mass at MRI appears useful to diagnose locally recurrent soft tissue sarcoma, because both sensitivity and specificity are fairly high. • Signal characteristics at standard T2- and T1-weighted sequences and contrast enhancement suffer from poor specificity. • DWI with ADC mapping and DCE may help to make a correct diagnosis, but further research is needed to better understand the value of these functional MRI techniques.

Diagnostic Value and Clinical Application of Diffusion-Weighted Magnetic Resonance Imaging for Female Pelvic Lesions.

Pelvic inflammatory disease refers to a group of infectious diseases of the female upper genital tract, often caused by ascending infection of vaginitis and cervicitis, causing endometritis, salpingitis, tubo-ovarian abscess, pelvic connective tissue inflammation, and/or pelvic peritonitis. PID is the most common and important infectious disease in nonpregnant women of childbearing age, and inflammation in multiple parts often coexists and affects each other. The functional MRI techniques currently used in pelvic floor muscle injury are magnetic resonance diffusion tensor imaging, T2 mapping, and magnetic resonance elastography. Diffusion tensor imaging is a new imaging and postprocessing technology developed on the basis of magnetic resonance diffusion-weighted imaging. Due to the lack of specificity of clinical symptoms, many subclinical patients are often not detected and diagnosed in time, so it is very difficult to accurately estimate the incidence of PID. This article retrospectively analyzed 72 patients with pelvic inflammatory disease confirmed by surgical pathology from February 2020 to 2022, who had undergone pelvic MRI examination before surgery, including 25 patients with chronic pelvic inflammation (hydrosalpinx), 25 patients with acute pelvic inflammation, and 47 cases (including 21 cases of hydrosalpinx, 19 cases of tubo-ovarian abscess, and 7 cases of pelvic abscess). The age range was 13 to 59 years old. The clinical data and MRI findings were analyzed, the ADC value of the cystic part of the lesion was measured, and the differences in age, maximum diameter of the lesion, thickness of the vessel wall/separation, and the ADC value of the cystic part of chronic and acute pelvic inflammation were compared. In this part of the cases, there were 25 cases of chronic pelvic inflammation and 47 cases of acute pelvic inflammation. The average ADC value of the cystic component of chronic inflammation was significantly higher than that of acute inflammation, which were (2.86 ± 0.20) × 10−3 mm2/s and (1.07 ± 0.38) ×10−3 mm2/s, respectively, P value <0.001.

A Pictorial Review of PI-RADS v2.0 and PI-RADS v2.1: What Changed?

Prostate cancer (PCa) is the most common cancer among Canadian men (excluding nonmelanoma skin cancers) and is the third leading cause of death from cancer in men in Canada. It is estimated that, in 2020, 23,300 men will be diagnosed with PCa, representing 20% of all new cancer cases in men.1 The recommended technique being used for the detection and risk stratification of PCa is multiparametric MRI (mpMRI), which includes high-resolution T2-weighted (T2W) images to depict prostate anatomy and two functional MRI techniques, including diffusion-weighted imaging (DWI) to display cell density and dynamic contrast-enhanced MRI (DCE) that shows vascularity.2

Blood Oxygen Level Dependent Magnetic Resonance Imaging Tissue Perfusion Protocol for Reliable Differentiation of Patients with Peripheral Artery Disease and Healthy Controls: Vascular Imaging

Introduction: While peripheral artery disease (PAD) is a clinical diagnosis, further characterisation of the ischaemic state is mainly based on imaging that delineates the arterial vasculature. There is currently no established imaging technique that directly quantifies the crucial pathophysiological process in PAD (i.e., tissue perfusion in the lower limb). Blood oxygenation level dependent magnetic resonance imaging (BOLD-MRI) is a non-invasive functional MRI technique that allows for the quantification of skeletal muscle perfusion without the use of contrast agents.

Added value of diffusion-weighted MRI in assessment of pleural lesions

BackgroundThere are many causes of pleural disease including variable benign and malignant etiologies. DWI is a non-enhanced functional MRI technique that allows qualitative and quantitative characterization of tissues based on their water molecules diffusivity. The aim of this study was to evaluate the diagnostic value of DWI-MRI in detection and characterization of pleural diseases and its capability in differentiating benign from malignant pleural lesions.ResultsConventional MRI was able to discriminate benign from malignant lesions by using morphological features (contour and thickness) with sensitivity 89.29%, specificity 76%, positive predictive value 89%, negative predictive value 76.92%, and accuracy 85.37%. ADC value as a quantitative parameter of DWI found that ADC values of malignant pleural diseases were significantly lower than that of benign lesions (P < 0.001). Hence, we discovered that using ADC mean value of 1.68 × 10-3 mm2/s as a cutoff value can differentiate malignant from benign pleural diseases with sensitivity 89.3%, specificity 100%, positive predictive value 100%, negative predictive value 81.2%, and accuracy 92.68% (P < 0.001).ConclusionAlthough DWI-MRI is unable to differentiate between malignant and benign pleural effusion, its combined morphological and functional information provide valid non-invasive method to accurately characterize pleural soft tissue diseases differentiating benign from malignant lesions with higher specificity and accuracy than conventional MRI.

New imaging modalities to distinguish rare uterine mesenchymal cancers from benign uterine lesions.

Uterine sarcomas are rare and are often challenging to differentiate on imaging from benign mimics, such as leiomyoma. As functional MRI techniques have improved and new adjuncts, such as machine learning and texture analysis, are now being investigated, it is helpful to be aware of the current literature on imaging features that may sometimes allow for preoperative distinction. MRI, with both conventional and functional imaging, is the modality of choice for evaluating uterine mesenchymal tumors, especially in differentiating uterine leiomyosarcoma from leiomyoma through validated diagnostic algorithms. MRI is sometimes helpful in differentiating high-grade stromal sarcoma from low-grade stromal sarcoma or differentiating endometrial stromal sarcoma from endometrial carcinoma. However, imaging remains nonspecific for evaluating rarer neoplasms, such as uterine tumor resembling ovarian sex cord tumor or perivascular epithelioid cell tumor, primarily because of the small number and power of relevant studies. Through advances in MRI techniques and novel investigational imaging adjuncts, such as machine learning and texture analysis, imaging differentiation of malignant from benign uterine mesenchymal tumors has improved and could help reduce morbidity relating to misdiagnosis or diagnostic delays.

Imaging of the dopamine system with focus on pharmacological MRI and neuromelanin imaging

The dopamine system in the brain is involved in a variety of neurologic and psychiatric disorders, such as Parkinson’s disease, attention-deficit/hyperactivity disorder and psychosis. Different aspects of the dopamine system can be visualized and measured with positron emission tomography (PET) and single photon emission computed tomography (SPECT), including dopamine receptors, dopamine transporters, and dopamine release. New developments in MR imaging also provide proxy measures of the dopamine system in the brain, offering alternatives with the advantages MR imaging, i.e. no radiation, lower costs, usually less invasive and time consuming. This review will give an overview of these developments with a focus on the most developed techniques: pharmacological MRI (phMRI) and neuromelanin sensitive MRI (NM-MRI). PhMRI is a collective term for functional MRI techniques that administer a pharmacological challenge to assess its effects on brain hemodynamics. By doing so, it indirectly assesses brain neurotransmitter function such as dopamine function. NM-MRI is an upcoming MRI technique that enables in vivo visualization and semi-quantification of neuromelanin in the substantia nigra. Neuromelanin is located in the cell bodies of dopaminergic neurons of the nigrostriatal pathway and can be used as a proxy measure for long term dopamine function or degeneration of dopaminergic neurons. Both techniques are still primarily used in clinical research, but there is promise for clinical application, in particular for NM-MRI in dopaminergic neurodegenerative diseases like Parkinson’s disease.

A Noninvasive Method for Quantifying Cerebral Metabolic Rate of Oxygen by Hybrid PET/MRI: Validation in a Porcine Model.

The gold standard for imaging the cerebral metabolic rate of oxygen (CMRO2) is positron emission tomography (PET); however, it is an invasive and complex procedure that also requires correction for recirculating 15O-H2O and the blood-borne activity. We propose a noninvasive reference-based hybrid PET/magnetic resonance imaging (MRI) method that uses functional MRI techniques to calibrate 15O-O2-PET data. Here, PET/MR imaging of oxidative metabolism (PMROx) was validated in an animal model by comparison to PET-alone measurements. Additionally, we investigated if the MRI-perfusion technique arterial spin labelling (ASL) could be used to further simplify PMROx by replacing 15O-H2O-PET, and if the PMROx was sensitive to anesthetics-induced changes in metabolism. Methods: 15O-H2O and 15O-O2 PET data were acquired in a hybrid PET/MR scanner (3 T Siemens Biograph mMR), together with simultaneous functional MRI (OxFlow and ASL), from juvenile pigs (n = 9). Animals were anesthetized with 3% isoflurane and 6 mL/kg/h propofol for the validation experiments and arterial sampling was performed for PET-alone measurements. PMROx estimates were obtained using whole-brain (WB) CMRO2 from OxFlow and local cerebral blood flow (CBF) from either noninvasive 15O-H2O-PET or ASL (PMROxASL). Changes in metabolism were investigated by increasing the propofol infusion to 20 mL/kg/h. Results: Good agreement and correlation were observed between regional CMRO2 measurements from PMROx and PET-alone. No significant differences were found between OxFlow and PET-only measurements of WB oxygen extraction fraction (0.30 ± 0.09 and 0.31 ± 0.09) and CBF (54.1 ± 16.7 and 56.6 ± 21.0 mL/100 g/min), or between PMROx and PET-only CMRO2 estimates (1.89 ± 0.16 and 1.81 ± 0.10 mLO2/100 g/min). Moreover, PMROx and PMROxASL were sensitive to propofol-induced reduction in CMRO2 Conclusion: This study provides initial validation of a noninvasive PET/MRI technique that circumvents many of the complexities of PET CMRO2 imaging. PMROx does not require arterial sampling and has the potential to reduce PET imaging to 15O-O2 only; however, future validation involving human participants are required.

Medullary Blood Oxygen Level-Dependent MRI Index (R2*) is Associated with Annual Loss of Kidney Function in Moderate CKD

Background: The estimated glomerular filtration rate (eGFR) is frequently used to monitor progression of kidney disease. Multiple values have to be obtained, sometimes over years to determine the rate of decline in kidney function. Recent data suggest that functional MRI (fMRI) methods may be able to predict loss of eGFR. In a prior study, baseline data with multi-parametric MRI in individuals with diabetes and moderate CKD was reported. This report extends our prior observations in order to evaluate the temporal variability of the fMRI measurements over 36 months and their association with annual change in eGFR. Methods: Twenty-four subjects with moderate CKD completed 3 sets of MRI scans over a 36-month period. Blood oxygenation level-dependent (BOLD), arterial spin labeling perfusion, and diffusion MRI images were acquired using a 3 T scanner. Coefficients of variation was used to evaluate variability between subjects at each time point and temporal variability within each subject. We have conducted mixed effects models to examine the trajectory change in GFR over time using time and MRI variables as fixed effects and baseline intercept as random effect. Associations of MRI image markers with annual change in eGFR were evaluated. Results: Multi-parametric functional renal MRI techniques in individuals with moderate CKD showed higher temporal variability in R2* of medulla compared to healthy individuals. This was consistent with the significant lower R2* in medulla observed at 36 months compared to baseline values. The results of linear mixed model showing that R2*_Medulla was the only predictor associated with change in eGFR over time. Furthermore, a significant association of medullary R2* with annual loss of eGFR was observed at all the 3 time points. Conclusions: The lower R2* values and the higher temporal variability in the renal medulla over time suggest the ability to monitor progressive CKD. These were confirmed by the fact that reduced medullary R2* was associated with higher annual loss in eGFR. These data collectively emphasize the need for inclusion of medulla in the analysis of renal BOLD MRI studies.

The Role of Functional MRI in The Evaluation of The Treated Head and Neck Squamous Cell Carcinoma

Background: The diffusion-weighted imaging (DWI) with apparent diffusion coefficient (ADC) map and the dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) constitute the functional MRI technique with many oncological applications as it can define tissue microstructure and characterize the post-treatment changes from a recurrent tumor in treated head and neck squamous cell carcinoma (HNSCC). Objective: To evaluate the role of the DWI, ADC map and DCE-MRI for characterization of post-treatment changes and recurrent tumors in patients with treated HNSCC. Patients and Methods: Forty-five patients with treated HNSCC were included in this study with mean ages of 59 ± 7.5 years. The patients underwent pre and post-contrast head and neck MRI, DWI with ADC map and DCE-MRI, each study diagnosis was then compared to the patient outcome. Results: The sensitivity and specificity of the qualitative DWI (DW-MRI) (87.5% and 82.8% respectively) were higher than the conventional MRI (75% and 75.9% respectively). The ADC cut-off point for the diagnosis of HNSCC recurrence was 1.095 x10-3 mm2/s with sensitivity and specificity of 87.5%, 86.2% respectively. The DCE- MRI revealed a significant difference in the type of time intensity curve (TIC) between post-treatment changes and recurrent lesion (p-value < 0.0001). Conclusion: The DWI, ADC and the DCE-MRI can be used as a synchronized tool for the differentiation between post-treatment changes and recurrent tumor in treated HNSCC patients.

Improved resting state functional connectivity sensitivity and reproducibility using a multiband multi-echo acquisition

Recent advances in functional MRI techniques include multiband (MB) imaging and multi-echo (ME) imaging. In MB imaging multiple slices are acquired simultaneously leading to significant increases in temporal and spatial resolution. Multi-echo imaging enables multiple echoes to be acquired in one shot, where the ME images can be used to denoise the BOLD time series and increase BOLD sensitivity. In this study, resting state fMRI (rs-fMRI) data were collected using a combined MBME sequence and compared to an MB single echo sequence. In total, 29 subjects were imaged, and 18 of them returned within two weeks for repeat imaging. Participants underwent one MBME scan with three echoes and one MB scan with one echo. Both datasets were processed using standard denoising and advanced denoising. Advanced denoising included multi-echo independent component analysis (ME-ICA) for the MBME data and ICA-AROMA for the MB data. Resting state functional connectivity (RSFC) was evaluated using both selective seed-based and whole grey matter (GM) region-of-interest (ROI) based approaches. The reproducibility of connectivity metrics was also analyzed in the repeat subjects. In addition, functional connectivity density (FCD), a data-driven approach that counts the number of significant connections, both within a local cluster and globally, with each voxel was analyzed. Regardless of the standard or advanced denoising technique, all seed-based RSFC was significantly higher for MBME compared to MB. Much more GM ROI combinations showed significantly higher RSFC for MBME vs. MB. Reproducibility, evaluated using the dice coefficient was significantly higher for MBME relative to MB data. Finally, FCD was also higher for MBME vs. MB data. This study showed higher RSFC for MBME vs. MB data using selected seed-based, whole GM ROI-based, and data-driven approaches. Reproducibility found also higher for MBME data. Taken together, these results indicate that MBME is a promising technique for rs-fMRI.

The role of diffusion-weighted MR imaging in assessment of peritoneal lesions: radiologic-pathologic correlation

BackgroundPeritoneal diseases can be caused by a wide spectrum of pathologies including benign, primary, and secondary malignant lesions. Benign peritoneal diseases can mimic malignancies and have overlapping clinical, pathophysiological, and imaging appearances. Biopsy and histological assessment remain the gold standard for characterization of the peritoneal lesions; however, functional MRI techniques like diffusion imaging with quantitative assessment by ADC (apparent diffusion coefficient) measurements can help in the detection and characterization of different peritoneal lesions. The aim of this study was to evaluate the role of diffusion MR imaging in differentiating between benign and malignant peritoneal lesions with correlation to their pathological results.ResultsForty patients with peritoneal lesions were included in the study. According to histopathological results, 20 of them were of benign nature, and the other 20 were malignant. The mean ADC value of the benign lesions was 1.5 ± 0.5 × 10−3 mm2/s while that of malignant lesions was 0.9 ± 0.3 × 10−3 mm2/s with statistically significant difference (p < 0.00001), and a cutoff value of 1.15 × 10−3 mm2/s can be used to differentiate benign and malignant lesions with 85% sensitivity and specificity. In particular, we compared the mean ADC values of the eight cases of peritoneal tuberculosis with that of fourteen cases of peritoneal carcinomatosa, and it was also statistically significant (p < 0.001). However, we did not find a statistically significant difference between the mean ADC value of the benign and malignant cystic peritoneal lesions (p = 0.5).ConclusionDiffusion MR imaging can provide a reliable non-invasive tool that can help in the differentiation between benign and malignant peritoneal lesions using qualitative and quantitative diffusion assessment through ADC measurements with a recommended cutoff value of 1.15 × 10−3 mm2/s.

Modeling of vascular space occupancy and BOLD functional MRI from first principles using real microvascular angiograms.

The vascular space occupancy (VASO) is a functional MRI technique for probing cerebral blood volume changes noninvasively, including during neuronal activation in humans. An important consideration when implementing VASO is the BOLD effect in the signal. Assessing the physical origin of this BOLD contamination and the capabilities of correction methods could improve the quantification of cerebral blood volume changes with VASO. Given the heterogeneity of cerebral microvascular architecture, the vascular geometry within an MRI voxel can influence both BOLD and VASO signals. To investigate this effect, 3D high-resolution images of mouse cerebral vasculature measured with two-photon microscopy were used to model BOLD and VASO signals from first principles using Monte Carlo diffusion of water protons. Quantitative plots of VASO together with intravascular and extravascular BOLD signals as a function of TE at B0 fields 1.5 T to 14 T were obtained. The BOLD contamination of the VASO response was on the order of 50% for gradient echo and 5% for spin echo at 7 T and TE = 6 ms and significantly increased with TE and B0 . Two currently used correction schemes were shown to account for most of this contamination and recover accurate relative signal changes, with optimal correction obtained using TEs as short as possible. These results may provide useful information for optimizing sequence parameters in VASO and BOLD functional MRI, leading the way to a wider application of these techniques in healthy and diseased brain.

Advanced neuroimaging in neuropsychiatric systemic lupus erythematosus.

Purpose of reviewNeuropsychiatric lupus (NPSLE) comprises a disparate collection of syndromes affecting the central and peripheral nervous systems. Progress in the attribution of neuropsychiatric syndromes to SLE-related mechanisms and development of targeted treatment strategies has been impeded by a lack of objective imaging biomarkers that reflect specific neuropsychiatric syndromes and/or pathologic mechanisms. The present review addresses recent publications of neuroimaging techniques in NPSLE.Recent findingsImaging studies grouping all NPSLE syndromes together are unable to differentiate between NPSLE and non-NPSLE. In contrast, diffusion tensor imaging, FDG-PET, resting, and functional MRI techniques in patients with stable non-NPSLE demonstrate abnormal network structural and functional connectivity and regional brain activity in multiple cortical areas involving the limbic system, hippocampus, frontal, parietal, and temporal lobes. Some of these changes associate with impaired cognitive performance or mood disturbance, autoantibodies or inflammatory proteins. Longitudinal data suggest progression over time. DCE-MRI demonstrates increased Blood–brain barrier permeability.SummaryStudy design issues related to patient selection (non-NPSLE vs. NPSLE syndromes, SLE disease activity, medications) are critical for biomarker development. Regional and network structural and functional changes identified with advanced brain imaging techniques in patients with non-NPSLE may be further developed as biomarkers for cognitive and mood disorders attributable to SLE-related mechanisms.

Multiparametric Imaging for the Locoregional Follow-up of Rectal Cancer

To discuss the potential of multiparametric imaging for the locoregional follow-up of rectal cancer by outlining the strengths/weaknesses of anatomical imaging in specific MRI and highlighting the potential of the most relevant functional imaging and novel image post-processing techniques In addition to anatomical imaging, diffusion-weighted imaging (DWI) and PET have been most extensively studied for the locoregional follow-up of rectal cancer. Fewer (and more recent) studies have focused on the use of other functional MRI techniques, advanced post-processing methods such as Radiomics and hybrid imaging (PET-MRI). Anatomical imaging experiences difficulties in the locoregional assessment of rectal cancer after chemoradiotherapy and surgery. Addition of DWI to anatomical MRI has proven its benefit for qualitative response assessment after neoadjuvant chemoradiotherapy. PET mainly has a role for the detection of recurrent disease after surgery and may be valuable for early response prediction. Evidence for multiparametric assessment of PET combined with MRI or hybrid PET-MRI is sparse. More quantitative functional imaging techniques including DCE-MRI and advanced post-processing techniques such as Radiomics have shown potential in research settings to render biomarkers of response but require standardisation and large-scale validation, preferably in trial settings.

Live from the "regulating brain": Harnessing the brain to change emotion.

Live feedback from the brain can empower individuals to change their own brain activity. The premise behind neurofeedback (NF) is that an organism learns to control brain activation and function via contingent feedback. We outline here why this approach can aid emotion regulation research and treatment, and how this is achieved with feedback from the neural circuitry of emotion. The focus is, in particular, on functional MRI (fMRI) and fMRI-inspired mapping techniques that permit the probing of deep brain activation with scalp electroencephalography. The NF approach for self-neuromodulation is discussed with respect to the process-model of emotion regulation. We argue that real-time feedback from brain areas or from circuits can augment neuroscience-based emotion regulation practices and thus provides a promising tool for more precise clinical intervention and the alleviation of emotion dysregulation. (PsycINFO Database Record (c) 2020 APA, all rights reserved).