MRI Approach Research Articles

Perfusion MRI-based differentiation between early tumor progression and pseudoprogression in glioblastoma and its use in clinical practice

Abstract Background Early treatment effects in patients with glioblastoma are frequently discussed during multidisciplinary team meetings (MDTM), after which a decision regarding (dis)continuation of tumor-targeted treatment is made. This study examined whether a separate and systematic evaluation of perfusion MRI (pMRI) could impact such treatment decisions in the early stage. Methods This retrospective observational study evaluated the diagnostic accuracy for detecting early tumor progression of 4 different approaches including conventional MRI, pMRI with Arterial Spin Labeling (ASL), and/or Dynamic Susceptibility Contrast (DSC) MRI, and compared those to the MDTM evaluation in clinical practice. Results Sixty-five glioblastoma patients with clinical and radiological data until 9 months after irradiation were included. For all approaches, the sensitivity for detecting early true disease progression was poor to moderate (32%–62%). Area under the curve values were comparable (range 0.63–0.74), but highest for the MDTM evaluation (0.74). In the cases of inconclusive MDTM (26%), systematic pMRI evaluation showed a higher sensitivity compared to conventional MRI (respectively, 36% vs 0%), while the specificity was 100% for all MRI approaches. Multivariable regression analysis showed that a lower KPS score (OR = 0.84 [95% CI: 0.77–0.91]) and pMRI indicative of tumor progression (OR = 0.09 [95% CI: 0.02–0.52]) were independently associated with concluding tumor progression at the MDTM. Conclusion MDTM assessment in daily clinical practice has a higher diagnostic accuracy in distinguishing early tumor progression from pseudoprogression compared to a separate, systematic evaluation of pMRI. Systematic evaluation of pMRI might be helpful if the clinical MDTM assessment is uncertain.

Rapid imaging of intravenous gadolinium-based contrast agent (GBCA) entering ventricular cerebrospinal fluid (CSF) through the choroid plexus in healthy human subjects

BackgroundPathways for intravenously administered gadolinium-based-contrast-agents (GBCAs) entering cerebrospinal-fluid (CSF) circulation in the human brain are not well-understood. The blood-CSF-barrier (BCSFB) in choroid-plexus (CP) has long been hypothesized to be a main entry-point for intravenous-GBCAs into CSF. Most existing studies on this topic were performed in animals and human patients with various diseases. Results in healthy human subjects are limited. Besides, most studies were performed using MRI methods with limited temporal resolution and significant partial-volume effects from blood and CSF.MethodsThis study employs the recently developed dynamic-susceptibility-contrast-in-the-CSF (cDSC) MRI approach to measure GBCA-distribution in the CSF immediately and 4 h after intravenous-GBCA administration in healthy subjects. With a temporal resolution of 10 s, cDSC MRI can track GBCA-induced CSF signal changes during the bolus phase, which has not been investigated previously. It employs a long echo-time (TE = 1347 ms) to suppress tissue and blood signals so that pure CSF signal is detected with minimal partial-volume effects. GBCA concentration in the CSF can be estimated from cDSC MRI. In this study, cDSC and FLAIR MRI were performed immediately and 4 h after intravenous GBCA administration in 25 healthy volunteers (age 48.9 ± 19.5 years; 14 females). Paired t-tests were used to compare pre-GBCA and post-GBCA signal changes, and their correlations with age were evaluated using Pearson-correlation-coefficients.ResultsAt ~ 20 s post-GBCA, GBCA-induced cDSC signal changes were detected in the CSF around CP (ΔS/S = − 2.40 ± 0.30%; P < .001) but not in the rest of lateral ventricle (LV). At 4 h, significant GBCA-induced cDSC signal changes were observed in the entire LV (ΔS/S = − 7.58 ± 3.90%; P = .002). FLAIR MRI showed a similar trend. GBCA-induced CSF signal changes did not correlate with age.ConclusionsThese results provided direct imaging evidence that GBCAs can pass the BCSFB in the CP and enter ventricular CSF immediately after intravenous administration in healthy human brains. Besides, our results in healthy subjects established a basis for clinical studies in brain diseases exploiting GBCA-enhanced MRI to detect BCSFB dysfunction.

Pathologic Substrates of Structural Brain Network Resilience and Topology in Parkinson Disease Decedents.

In Parkinson disease (PD), α-synuclein spreading through connected brain regions leads to neuronal loss and brain network disruptions. With diffusion-weighted imaging (DWI), it is possible to capture conventional measures of brain network organization and more advanced measures of brain network resilience. We aimed to investigate which neuropathologic processes contribute to regional network topologic changes and brain network resilience in PD. Using a combined postmortem MRI and histopathology approach, PD and control brain donors with available postmortem in situ 3D T1-weighted MRI, DWI, and brain tissue were selected from the Netherlands Brain Bank and Normal Aging Brain Collection Amsterdam. Probabilistic tractography was performed, and conventional network topologic measures of regional eigenvector centrality and clustering coefficient, and brain network resilience (change in global efficiency upon regional node failure) were calculated. PSer129 α-synuclein, phosphorylated-tau, β-amyloid, neurofilament light-chain immunoreactivity, and synaptophysin density were quantified in 8 cortical regions. Group differences and correlations were assessed with rank-based nonparametric tests, with age, sex, and postmortem delay as covariates. Nineteen clinically defined and pathology-confirmed PD (7 F/12 M, 81 ± 7 years) and 15 control (8 F/7 M, 73 ± 9 years) donors were included. With regional conventional measures, we found lower eigenvector centrality only in the parahippocampal gyrus in PD (d = -1.08, 95% CI 0.003-0.010, p = 0.021), which did not associate with underlying pathology. No differences were found in regional clustering coefficient. With the more advanced measure of brain network resilience, we found that the PD brain network was less resilient to node failure of the dorsal anterior insula compared with the control brain network (d = -1.00, 95% CI 0.0012-0.0015, p = 0.018). This change was not directly driven by neuropathologic processes within the dorsal anterior insula or in connected regions but was associated with higher Braak α-synuclein staging (rs = -0.40, p = 0.036). Although our cohort might suffer from selection bias, our results highlight that regional network disturbances are more complex to interpret than previously believed. Regional neuropathologic processes did not drive regional topologic changes, but a global increase in α-synuclein pathology had a widespread effect on brain network reorganization in PD.

MRI Evaluation and Characterization of Ovarian Lesions Based on Ovarian-Adnexal Reporting and Data System MRI.

Background Managing ovarian lesions requires differentiating between benign and malignant cases. The development of a multiparametric MRI approach combining anatomical and functional criteria has led to the creation of the Ovarian-Adnexal Reporting and Data System (O-RADS) MRI scoring system, which enhances diagnostic accuracy. Objectives To study ovarian lesions and their characteristics, along with their risk stratification based on MRI O-RADS. Methods A prospective study used the O-RADS MRI criteria to categorize ovarian lesions. Clinical findings and MRI results were compared with histopathological outcomes to assess diagnostic accuracy. Results We identifiedabdominal pain as the most prevalent clinical finding among our cases (64, 91.43%), followed by a lump in the abdomen (33, 47.5%), dysmenorrhea (33, 47.5%), bleeding per vaginal (15, 21.43%), and weight loss (11, 15.71%). A total of 80 ovarian lesions were examined and characterized on the basis of the O-RADSMRI risk stratification system.Among the 80 ovarian lesions, 54 were histopathologically confirmed ovarian lesions (39 (72.22%) were benign, and 15 (27.77%) were malignant). The most common benign lesions were ovarian serous cystadenoma (28.20%) and ovarian mucinous cystadenoma (20.51%), while the most common malignant lesions were serous carcinoma (33.33%) and mucinous carcinoma (20%). Using the O-RADS MRI scoring system, we categorized six lesions (7.5%) as O-RADS 1 (all benign), 34 lesions (42.50%) as O-RADS 2 (32 benign and 2 malignant), 24 lesions (30%) as O-RADS 3 (23 benign and 1 malignant), seven lesions (8.75%) as O-RADS 4 (four benign and three malignant), and nine lesions (11.25%) as O-RADS 5 (all malignant). Our findings revealed significant differences in the size of lesions, the presence of thick septa, high T2-weighted signal intensity within solid tissue, and patterns of solid component enhancement and wall irregularity between malignant and benign lesions. The MRI cut-off score of ≥4 for malignancy demonstrated a sensitivity of 94.59%, a specificity of 97.5%, an accuracy of 97.62%, a positive predictive value of 94.5%, and a negative predictive value of 97.5%. The positive likelihood ratio was 32.7, while the negative likelihood ratio was 0.025. These results affirm the high diagnostic accuracy of the O-RADS MRI scoring system in distinguishing benign from malignant ovarian lesions. Conclusion The O-RADS MRI score is a highly accurate tool for differentiating between benign and malignant ovarian lesions. Its application can significantly enhance the management and treatment outcomes for patients with adnexal masses. The study confirms the scoring system's high sensitivity, specificity, and overall diagnostic accuracy.

Cognitive Impairment in Cerebral Small Vessel Disease Is Associated with Corpus Callosum Microstructure Changes Based on Diffusion MRI.

to evaluate microstructural changes in the corpus callosum (CC) using diffusion MRI (D-MRI) approaches in cSVD patients with different severity of CI and reveal the most sensitive correlations of diffusion metrics with CI. the study included 166 cSVD patients (51.8% women; 60.4 ± 7.6 years) and 44 healthy volunteers (65.9% women; 59.6 ± 6.8 years). All subjects underwent D-MRI (3T) with signal (diffusion tensor and kurtosis) and biophysical (neurite orientation dispersion and density imaging, NODDI, white matter tract integrity, WMTI, multicompartment spherical mean technique, MC-SMT) modeling in three CC segments as well as a neuropsychological assessment. in cSVD patients, microstructural changes were found in all CC segments already at the subjective CI stage, which was found to worsen into mild CI and dementia. More pronounced changes were observed in the forceps minor. Among the signal models FA, MD, MK, RD, and RK, as well as among the biophysical models, MC-SMT (EMD, ETR) and WMTI (AWF) metrics exhibited the largest area under the curve (>0.85), characterizing the loss of microstructural integrity, the severity of potential demyelination, and the proportion of intra-axonal water, respectively. Conclusion: the study reveals the relevance of advanced D-MRI approaches for the assessment of brain tissue changes in cSVD. The identified diffusion biomarkers could be used for the clarification and observation of CI progression.

Establishment and validation of a risk stratification model for stroke risk within three years in patients with cerebral small vessel disease using a combined MRI and machine learning algorithm

BackgroundCerebral small vessel disease (CSVD) is a major cause of stroke, particularly in the elderly population, leading to significant morbidity and mortality. Accurate identification of high-risk patients and timing of stroke occurrence plays a crucial role in patient prevention and treatment. The study aimed to establish and validate a risk stratification model for stroke within three years in patients with CSVD using a combined MRI and machine learning algorithm approach. MethodsThe assessment encompassed demographic, clinical, biochemical, and MRI-derived parameters. Correlation analysis, logistic regression, receiver operating characteristic (ROC) curve analysis, and nnet neural network algorithm were employed to evaluate the predictive value of machine learning algorithms and MRI parameters for stroke occurrence within 3 years in patients with CSVD. ResultsMRI-derived parameters, including average WMH volume, perfusion deficit volume, ischemic core volume, microbleed count, and perivascular spaces, exhibited strong correlations with stroke occurrence (P < 0.001). MRI-derived parameters demonstrated high sensitivities (0.719 to 0.906), specificities (0.704 to 0.877), and AUC values (0.815 to 0.871). The combined model of machine learning algorithms and MRI parameters yielded an AUC value of 0.925, indicating significantly high predictive accuracy for identifying the risk of stroke within three years in CSVD patients. ConclusionThe integrated risk stratification model, incorporating machine learning algorithms and MRI parameters, demonstrated strong predictive potential for stroke within three years in patients with CSVD. This model offered valuable insights for personalized interventions and clinical decision-making in the management of CSVD.

Convolution Neural Network Based Deep Learning Approach for MRI Based Brain Tumour Image Detection

Convolution Neural Network Based Deep Learning Approach for MRI Based Brain Tumour Image Detection

Monitoring imatinib decreasing pericyte coverage and HIF-1α level in a colorectal cancer model by an ultrahigh-field multiparametric MRI approach

BackgroundExcessive pericyte coverage promotes tumor growth, and a downregulation may solve this dilemma. Due to the double-edged sword role of vascular pericytes in tumor microenvironment (TME), indiscriminately decreasing pericyte coverage by imatinib causes poor treatment outcomes. Here, we optimized the use of imatinib in a colorectal cancer (CRC) model in high pericyte-coverage status, and revealed the value of multiparametric magnetic resonance imaging (mpMRI) at 9.4T in monitoring treatment-related changes in pericyte coverage and the TME.MethodsCRC xenograft models were evaluated by histological vascular characterizations and mpMRI. Mice with the highest pericyte coverage were treated with imatinib or saline; then, vascular characterizations, tumor apoptosis and HIF-1α level were analyzed histologically, and alterations in the expression of Bcl-2/bax pathway were assessed through qPCR. The effects of imatinib were monitored by dynamic contrast-enhanced (DCE)-, diffusion-weighted imaging (DWI)- and amide proton transfer chemical exchange saturation transfer (APT CEST)-MRI at 9.4T.ResultsThe DCE- parameters provided a good histologic match the tumor vascular characterizations. In the high pericyte coverage status, imatinib exhibited significant tumor growth inhibition, necrosis increase and pericyte coverage downregulation, and these changes were accompanied by increased vessel permeability, decreased microvessel density (MVD), increased tumor apoptosis and altered gene expression of apoptosis-related Bcl-2/bax pathway. Strategically, a 4-day imatinib effectively decreased pericyte coverage and HIF-1α level, and continuous treatment led to a less marked decrease in pericyte coverage and re-elevated HIF-1α level. Correlation analysis confirmed the feasibility of using mpMRI parameters to monitor imatinib treatment, with DCE-derived Ve and Ktrans being most correlated with pericyte coverage, Ve with vessel permeability, AUC with microvessel density (MVD), DWI-derived ADC with tumor apoptosis, and APT CEST-derived MTRasym at 1 µT with HIF-1α.ConclusionsThese results provided an optimized imatinib regimen to achieve decreasing pericyte coverage and HIF-1α level in the high pericyte-coverage CRC model, and offered an ultrahigh-field multiparametric MRI approach for monitoring pericyte coverage and dynamics response of the TME to treatment.

Back to Bernoulli: a simple formula for trans-stenotic pressure gradients and retrospective estimation of flow rates in cerebral venous disease

BackgroundVenous sinus stenosis can be associated with cerebrovascular disorders. Understanding the role of blood flow disturbances in these disorders is often hampered by the lack of patient-specific flow rates. Our...

Microstructural characterization of multiple sclerosis lesion phenotypes using multiparametric longitudinal analysis

Background and objectivesIn multiple sclerosis (MS), slowly expanding lesions were shown to be associated with worse disability and prognosis. Their timely detection from cross-sectional data at early disease stages could be clinically relevant to inform treatment planning. Here, we propose to use multiparametric, quantitative MRI to allow a better cross-sectional characterization of lesions with different longitudinal phenotypes.MethodsWe analysed T1 and T2 relaxometry maps from a longitudinal cohort of MS patients. Lesions were classified as enlarging, shrinking, new or stable based on their longitudinal volumetric change using a newly developed automated technique. Voxelwise deviations were computed as z-scores by comparing individual patient data to T1, T2 and T2/T1 normative values from healthy subjects. We studied the distribution of microstructural properties inside lesions and within perilesional tissue.Results and conclusionsStable lesions exhibited the highest T1 and T2 z-scores in lesion tissue, while the lowest values were observed for new lesions. Shrinking lesions presented the highest T1 z-scores in the first perilesional ring while enlarging lesions showed the highest T2 z-scores in the same region. Finally, a classification model was trained to predict the longitudinal lesion type based on microstructural metrics and feature importance was assessed. Z-scores estimated in lesion and perilesional tissue from T1, T2 and T2/T1 quantitative maps carry discriminative and complementary information to classify longitudinal lesion phenotypes, hence suggesting that multiparametric MRI approaches are essential for a better understanding of the pathophysiological mechanisms underlying disease activity in MS lesions.

MRI in Postero-Lateral Corner Injuries of the Knee Joint: Clinical-Radiological Correlation

Abstract Background The posterolateral corner (PLC) was once regarded as the “dark side of the knee” owing to the complex and variable anatomy superimposed on the inconsistent terminology used in the literature to describe the structures in this region. Aim of the Work To describe the role of MRI in assessment of posteriolateral corner injury of knee joint. Patients and Methods This cross sectional study was conducted in department of Radiology in Ain Shams University, the data collected from database to reach sample size number and enrolled data of 20 patients in period was 18-24 months. Results We were able to show that the MRI procedure we gave accurately visualises the majority of the complex individual components of the posterolateral knee, as well as damage to these structures, in this investigation. When the diagnosis of grade III injuries to the posterolateral knee is in doubt, we believe that MRI of the posterolateral knee is a useful complement to the surgeon. In our capacity to correctly diagnose damaged structures on MRI, there were no clear differences between acute and chronic knee injuries. On MRI, avulsions or tears of the direct arm or anterior arm insertion off the fibular styloid show focal discontinuity, nonvisualization, increased signal intensity, or proximal retraction, often with a contemporaneous bone avulsion. The damage pattern can also be seen in axial and sagittal views. Conclusion When posterolateral rotatory instability is suspected, the MRI approaches that described for visualizing particular injuries to the posterolateral knee will almost always reveal the bulk of the affected structures. When a posterolateral knee injury is assessed on MRI, using a special MRI protocol that covers the full fibular head and styloid on all imaging sequences will help in identifying these structures.

Gradient of microstructural damage along the dentato-thalamo-cortical tract in Friedreich ataxia.

The dentato-thalamo-cortical tract (DTT) is the main cerebellar efferent pathway. Degeneration of the DTT is a core feature of Friedreich ataxia (FRDA). However, it remains unclear whether DTT disruption is spatially specific, with some segments being more impacted than others. This study aimed to investigate microstructural integrity along the DTT in FRDA using a profilometry diffusion MRI (dMRI) approach. MRI data from 45 individuals with FRDA (mean age: 33.2 ± 13.2, Male/Female: 26/19) and 37 healthy controls (mean age: 36.5 ± 12.7, Male/Female:18/19) were included in this cross-sectional multicenter study. A profilometry analysis was performed on dMRI data by first using tractography to define the DTT as the white matter pathway connecting the dentate nucleus to the contralateral motor cortex. The tract was then divided into 100 segments, and dMRI metrics of microstructural integrity (fractional anisotropy, mean diffusivity and radial diffusivity) at each segment were compared between groups. The process was replicated on the arcuate fasciculus for comparison. Across all diffusion metrics, the region of the DTT connecting the dentate nucleus and thalamus was more impacted in FRDA than downstream cerebral sections from the thalamus to the cortex. The arcuate fasciculus was minimally impacted. Our study further expands the current knowledge about brain involvement in FRDA, showing that microstructural abnormalities within the DTT are weighted to early segments of the tract (i.e., the superior cerebellar peduncle). These findings are consistent with the hypothesis of DTT undergoing anterograde degeneration arising from the dentate nuclei and progressing to the primary motor cortex.

Cerebrospinal Fluid-In Gradient of Cortical and Deep Gray Matter Damage in Multiple Sclerosis.

A CSF-in gradient in cortical and thalamic gray matter (GM) damage has been found in multiple sclerosis (MS). We concomitantly explored the patterns of cortical, thalamic, and caudate microstructural abnormalities at progressive distances from CSF using a multiparametric MRI approach. For this cross-sectional study, from 3T 3D T1-weighted scans, we sampled cortical layers at 25%-50%-75% depths from pial surface and thalamic and caudate bands at 2-3-4 voxels from the ventricular-GM interface. Using linear mixed models, we tested between-group comparisons of magnetization transfer ratio (MTR) and R2* layer-specific z-scores, CSF-in across-layer z-score changes, and their correlations with clinical (disease duration and disability) and structural (focal lesions, brain, and choroid plexus volume) MRI measures. We enrolled 52 patients with MS (33 relapsing-remitting [RRMS], 19 progressive [PMS], mean age: 46.4 years, median disease duration: 15.1 years, median: EDSS 2.0) and 70 controls (mean age 41.5 ± 12.8). Compared with controls, RRMS showed lower MTR values in the outer and middle cortical layers (false-discovery rate [FDR]-p ≤ 0.025) and lower R2* values in all 3 cortical layers (FDR-p ≤ 0.016). PMS had lower MTR values in the outer and middle cortical (FDR-p ≤ 0.016) and thalamic (FDR-p ≤ 0.048) layers, and in the outer caudate layer (FDR-p = 0.024). They showed lower R2* values in the outer cortical layer (FDR-p = 0.003) and in the outer thalamic layer (FDR-p = 0.046) and higher R2* values in all 3 caudate layers (FDR-p ≤ 0.031). Both RRMS and PMS had a gradient of damage, with lower values closer to the CSF, for cortical (FDR-p ≤ 0.002) and thalamic (FDR-p ≤ 0.042) MTR. PMS showed a gradient of damage for cortical R2* (FDR-p = 0.005), thalamic R2* (FDR-p = 0.004), and caudate MTR (FDR-p ≤ 0.013). Lower MTR and R2* of outer cortical, thalamic, and caudate layers and steeper gradient of damage toward the CSF were significantly associated with older age, higher T2-hyperintense white matter lesion volume, higher thalamic lesion volume, and lower brain volume (β ≥ 0.08, all FDR-p ≤ 0.040). Lower MTR of outer caudate layer was associated with more severe disability (β = -0.26, FDR-p = 0.040). No correlations with choroid plexus volume were found. CSF-in damage gradients are heterogeneous among different GM regions and through MS course, possibly reflecting different dynamics of demyelination and iron loss/accumulation.

Treatment response assessment of acute pyelonephritis: A multi-reader DWI-based MRI approach

PurposeTo evaluate the diagnostic accuracy of a structured reporting score (SRS) in treatment response assessment for acute pyelonephritis (APN) using a diffusion-weighted imaging (DWI) -based MRI approach. Additionally, we explored the influence of reader experience on the interpretation of SRS and DWI, including lesion conspicuity and measurements of Apparent Diffusion Coefficient (ADC) maps. MethodsFollow-up DWI-based MRIs of 36 patients treated for APN between September 2021 and June 2023 were retrospectively reviewed by three readers. Follow-up blood inflammatory markers were used as reference standard. Treatment response was assessed using a structured reporting score (SRS). Each reader assigned a score from 1 to 3 to the "conspicuity" of the residual disease on DWI. Quantitative ADC measurements were compared with the Mann-Whitney U test. Descriptive statistics and Intraclass Correlation Coefficient (ICC) were calculated. ResultsThe diagnostic accuracy of SRS was 80.6 %, 76.9 %, and 72.2 % for the Reader 1, 2, and 3 respectively. ICC decreased from 0.82 (Reader 1 and 2), to 0.68 when considering all readers. The average conspicuity varied between 2.3 and 2.7. ADC values were significantly higher in complete responders for Reader 1 and 2 (153.5-154.5 vs 107.7-116.2, p < 0.001). The ICC was good (0.89) for Reader 1 and 2 and moderate (0.60) when considering all readers. ConclusionsTreatment response of pyelonephritis can be accurately assessed by a DWI-based MRI, potentially avoiding unnecessary contrast agent administration and radiation exposure. SRS and DWI analysis showed a good inter-observer agreement but a certain learning curve may be necessary for less expert readers.

Assessing renal interstitial fibrosis using compartmental, non-compartmental, and model-free diffusion MRI approaches

ObjectiveTo assess renal interstitial fibrosis (IF) using diffusion MRI approaches, and explore whether corticomedullary difference (CMD) of diffusion parameters, combination among MRI parameters, or combination with estimated glomerular filtration rate (eGFR) benefit IF evaluation.MethodsForty-two patients with chronic kidney disease were included, undergoing MRI examinations. MRI parameters from apparent diffusion coefficient (ADC), intra-voxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI), and diffusion-relaxation correlated spectrum imaging (DR-CSI) were obtained both for renal cortex and medulla. CMD of these parameters was calculated. Pathological IF scores (1–3) were obtained by biopsy. Patients were divided into mild (IF = 1, n = 23) and moderate-severe fibrosis (IF = 2–3, n = 19) groups. Group comparisons for MRI parameters were performed. Diagnostic performances were assessed by the receiver operator’s curve analysis for discriminating mild from moderate-severe IF patients.ResultsSignificant inter-group differences existed for cortical ADC, IVIM-D, IVIM-f, DKI-MD, DR-CSI VB, and DR-CSI VC. Significant inter-group differences existed in ΔADC, ΔMD, ΔVB, ΔVC, ΔQB, and ΔQC. Among the cortical MRI parameters, VB displayed the highest AUC = 0.849, while ADC, f, and MD also showed AUC > 0.8. After combining cortical value and CMD, the diagnostic performances of the MRI parameters were slightly improved except for IVIM-D. Combining VB with f brings the best performance (AUC = 0.903) among MRI bi-variant models. A combination of cortical VB, ΔADC, and eGFR brought obvious improvement in diagnostic performance (AUC 0.963 vs 0.879, specificity 0.826 vs 0.896, and sensitivity 1.000 vs 0.842) than eGFR alone.ConclusionOur study shows promising results for the assessment of renal IF using diffusion MRI approaches.Critical relevance statementOur study explores the non-invasive assessment of renal IF, an independent and effective predictor of renal outcomes, by comparing and combining diffusion MRI approaches including compartmental, non-compartmental, and model-free approaches.Key PointsSignificant difference exists for diffusion parameters between mild and moderate-severe IF.Generally, cortical parameters show better performance than corresponding CMD.Bi-variant model lifts the diagnostic performance for assessing IF.Graphical

A decay-modeled compressed sensing reconstruction approach for non-Cartesian hyperpolarized 129Xe MRI.

Hyperpolarized 129Xe MRI benefits from non-Cartesian acquisitions that sample k-space efficiently and rapidly. However, their reconstructions are complex and burdened by decay processes unique to hyperpolarized gas. Currently used gridded reconstructions are prone to artifacts caused by magnetization decay and are ill-suited for undersampling. We present a compressed sensing (CS) reconstruction approach that incorporates magnetization decay in the forward model, thereby producing images with increased sharpness and contrast, even in undersampled data. Radio-frequency, T1, and decay processes were incorporated into the forward model and solved using iterative methods including CS. The decay-modeled reconstruction was validated in simulations and then tested in 2D/3D-spiral ventilation and 3D-radial gas-exchange MRI. Quantitative metrics including apparent-SNR and sharpness were compared between gridded, CS, and twofold undersampled CS reconstructions. Observations were validated in gas-exchange data collected from 15 healthy and 25 post-hematopoietic-stem-cell-transplant participants. CS reconstructions in simulations yielded images with threefold increases in accuracy. CS increased sharpness and contrast for ventilation in vivo imaging and showed greater accuracy for undersampled acquisitions. CS improved gas-exchange imaging, particularly in the dissolved-phase where apparent-SNR improved, and structure was made discernable. Finally, CS showed repeatability in important global gas-exchange metrics including median dissolved-gas signal ratio and median angle between real/imaginary components. A non-Cartesian CS reconstruction approach that incorporates hyperpolarized 129Xe decay processes is presented. This approach enables improved image sharpness, contrast, and overall image quality in addition to up-to threefold undersampling. This contribution benefits all hyperpolarized gas MRI through improved accuracy and decreased scan durations.

Serious Game for Dyslexia Screening: Design and Verification

This paper describes the process we undertook to develop a game-based approach to collect data for the diagnosis of dyslexia in children between the ages of 6 and 12 years old. A number of data collection approaches have been used previously such as eye tracking, MRI, EEG and game based approaches. Data collection can be a challenging task, as many of these approaches rely on use of specialized technology and in the case of MRI and EEG approaches, also require the presence of experts. In contrast, game based data collection is less intrusive and does not require the presence of experts or specialized devices. The content of the game in this research work was designed by identifying the problems faced by children with dyslexia in different age groups, designing questions to evaluate these problems and finally, validating the game design through two formative evaluations and with domain experts. This initial study and its statistical analysis showed a significant difference in the performance of children with dyslexia from children without dyslexia when playing the game.

Multiparametric Aging Study Across Adulthood in the Leg Through Quantitative MR Imaging, 1H Spectroscopy, and 31P Spectroscopy at 3T.

Improved characterization of healthy muscle aging is needed to establish early biomarkers in age-related diseases. To quantify age-related changes on multiple MRI and clinical variables evaluated in the same cohort and identify correlations among them. Prospective. 70 healthy subjects (30 men) from 20 to 81 years old. 3T/water T2 (multiecho SE, multi-TE STEAM), water T1 (GRE MR Fingerprinting), fat-fraction (multiecho GRE, multi-TE STEAM), carnosine (PRESS), multicomponent water T2 (ISIS-CPMG SE train), and 31P pulse-acquire spectroscopy. Age- and sex-related changes on: Imaging: fat-fraction (FFMRI), water T1 (T1-H2O), and T2 (T2-H2O-MRI) and their heterogeneities ΔT1-H2O and ΔT2-H2O-MRI in the posterior compartment (PC) and anterior compartment (AC) of the leg. 1H spectroscopy: Carnosine concentration, pH, water T2 components (T2-H2O-CPMG), fat-fraction (FFMRS), and water T2 (T2-H2O-MRS) in the gastrocnemius medialis. 31P spectroscopy: Phosphodiesters (PDE), phosphomonoesters, inorganic phosphates (Pi), and phosphocreatine (PCr) normalized to adenosine triphosphate (ATP) and pH in the calf. Clinical evaluation: Body-mass index (BMI), gait speed (GS), plantar flexion strength, handgrip strength (HS), HS normalized to wrist circumference (HSnorm), physical activity assessment. Multilinear regressions with sex and age as fixed factors. Spearman correlations calculated between variables. Benjamini-Hochberg procedure for false positives reduction (5% rate). A P < 0.05 significance level was used. Significant age-related increases were found for BMI (ρAge = 0.04), HSnorm (ρAge = -0.01), PDE/ATP (ρAge = 2.8 × 10-3), Pi/ATP (ρAge = 2.0 × 10-3), Pi/PCr (ρAge = 0.3 × 10-3), T2-H2O-MRS (ρAge = 0.051 msec), FFMRS (ρAge = 0.036) the intermediate T2-H2O-CPMG component time (ρAge = 0.112 msec), and fraction (ρAge = -0.3 × 10-3); and in both compartments for FFMRI (ρAge = 0.06, PC; ρAge = 0.06, AC), T2-H2O-MRI (ρAge = 0.05, PC; ρAge = 0.05, AC; msec), ΔT2-H2O-MRI (ρAge = 0.02, PC; ρAge = 0.02, AC; msec), T1-H2O (ρAge = 1.08, PC; ρAge = 1.06, AC; msec), and ΔT1-H2O (ρAge = 0.22, PC; ρAge = 0.37, AC; msec). The best age predictors, accounting for sex-related differences, were HSnorm (R2 = 0.52) and PDE/ATP (R2 = 0.44). In both leg compartments, the imaging measures and HSnorm were intercorrelated. In PC, T2-H2O-MRS and FFMRS also showed numerous correlations to the imaging measures. PDE/ATP correlated to T1-H2O, T2-H2O-MRI, ΔT2-H2O-MRI, FFMRI, FFMRS, the intermediate T2-H2O-CPMG, BMI, Pi/PCr, and HSnorm. Our multiparametric MRI approach provided an integrative view of age-related changes in the leg and revealed multiple correlations between these parameters and the normalized HS. 1 TECHNICAL EFFICACY: Stage 3.

Brain tumor MRI identification and classification using DWT, PCA and kernel support vector machine

Classification, segmentation, and the identification of the infection region in MRI images of brain tumors are labor-intensive and iterative processes. Numerous anatomical structures of the human body may be envisioned using an image processing theory. With basic imaging methods, it is challenging to see the aberrant human brain's structure. The neurological structure of the human brain may be distinguished and made clearer using the magnetic resonance imaging technique. The MRI approach uses a number of imaging techniques to evaluate and record the human brain’s interior features. In this study, we focused on strategies for noise removal, gray-level co-occurrence matrix (GLCM) extraction of features, and segmentation of brain tumor regions based on Discrete Wavelet Transform (DWT) to minimize complexity and enhance performance. In turn, this reduces any noise that could have been left over after segmentation due to morphological filtering. Brain MRI scans were utilized to test the accuracy of the classification and the location of the tumor using probabilistic neural network classifiers. The classifier's accuracy and position detection were tested using MRI brain imaging. The efficiency of the suggested approach is demonstrated by experimental findings, which showed that normal and diseased tissues could be distinguished from one another from brain MRI scans with about 100% accuracy.

PENCIL imaging: A novel approach for neuromelanin sensitive MRI in Parkinson's disease

BackgroundParkinson's disease (PD) is associated with the loss of neuromelanin (NM) and increased iron in the substantia nigra (SN). Magnetization transfer contrast (MTC) is widely used for NM visualization but has limitations in brain coverage and scan time. This study aimed to develop a new approach called Proton-density Enhanced Neuromelanin Contrast in Low flip angle gradient echo (PENCIL) imaging to visualize NM in the SN. MethodsThis study included 30 PD subjects and 50 healthy controls (HCs) scanned at 3T. PENCIL and MTC images were acquired. NM volume in the SN pars compacta (SNpc), normalized image contrast (Cnorm), and contrast-to-noise ratio (CNR) were calculated. The change of NM volume in the SNpc with age was analyzed using the HC data. A group analysis compared differences between PD subjects and HCs. Receiver operating characteristic (ROC) analysis and area under the curve (AUC) calculations were used to evaluate the diagnostic performance of NM volume and CNR in the SNpc. ResultsPENCIL provided similar visualization and structural information of NM compared to MTC. In HCs, PENCIL showed higher NM volume in the SNpc than MTC, but this difference was not observed in PD subjects. PENCIL had higher CNR, while MTC had higher Cnorm. Both methods revealed a similar pattern of NM volume in SNpc changes with age. There were no significant differences in AUCs between NM volume in SNpc measured by PENCIL and MTC. Both methods exhibited comparable diagnostic performance in this regard. ConclusionsPENCIL imaging provided improved CNR compared to MTC and showed similar diagnostic performance for differentiating PD subjects from HCs. The major advantage is PENCIL has rapid whole-brain coverage and, when using STAGE imaging, offers a one-stop quantitative assessment of tissue properties.