Regional Apparent Diffusion Coefficient Research Articles

Children with Congenital Heart Diseases Exhibit Altered Deep Gray Matter Structures.

Children with congenital heart diseases (CHDs) have an increased risk of developing neurologic deficits, even in the absence of apparent brain pathology. The aim of this work was to compare quantitative macro- and microstructural properties of subcortical gray matter structures of pediatric CHD patients with normal appearing brain magnetic resonance imaging to healthy controls. We retrospectively reviewed children with coarctation of the aorta (COA) and hypoplastic left heart syndrome (HLHS) admitted to our hospital. We identified 24pediatric CHD patients (17COA, 7HLHS) with normal-appearing brain MRI. Using an atlas-based approach, the volume and apparent diffusion coefficient (ADC) were determined for the thalamus, caudate, putamen, pallidum, hippocampus, amygdala, nucleus accumbens, cerebral white matter, cerebral cortex, and brainstem. Multivariate statistics were used to compare the extracted values to reference values from 100 typically developing children without any known cardiac or neurological diseases. Multivariate analysis of covariance using the regional ADC and volume values as dependent variables and age and sex as co-variates revealed asignificant difference between pediatric CHD patients and healthy controls (p < 0.001). Post-hoc comparisons demonstrated significantly reduced brain volumes in most subcortical brain regions investigated and elevated ADC values in the thalamus for children with CHD. No significant differences were found comparing children with COA and HLHS. Despite normal appearing brain MRI, children with CHD exhibit wide-spread macro-structural and regional micro-structural differences of subcortical brain structures compared to healthy controls, which could negatively impact neurodevelopment, leading to neurological deficits in childhood and beyond.

Sex differences in normal fetal regional brain apparent diffusion coefficient changes assessed by in utero DWI.

There are differences in the vulnerability of male and female fetal brains to adverse intrauterine exposure, preterm birth, and associated perinatal brain injury. The main objective of this study was to identify any statistically significant difference in the change of apparent diffusion coefficient (ADC) in the intracranial regions of male and female fetuses in the second and third trimesters. Diffusion-weighted imaging (DWI) was performed in 200 fetuses between 20 and 37 gestational ages (GA) with normal results or suspicious results on sonography followed by structural MRI. Pairwise ADC values of the regions of interest (ROIs) were manually delineated on either side of the cerebral white matter: frontal white matter (FWM), parietal white matter (PWM), occipital white matter (OWM), temporal white matter (TWM), basal ganglia (BG), thalamus (THA), cerebellar hemisphere (CBM), and a single measurement in the pons. The changes in these values were studied over the gestational range, along with potential sex differences and asymmetries of the cerebral hemispheres. During the third trimester, ADC values in OWM, TWM, and CBM were significantly higher in male fetuses than those in female fetuses (p < 0.05). After the correction of false-discovery rates (FDR), the difference in CBM was the only statistically significant (p = 0.0032). However, the decreased rate of ADC values in male fetuses in CWM (except for FWM), BG, THA, CBM, and pons was higher than that in female fetuses during the second and third trimesters. We have shown some differences in the intracranial regional ADC changes between male and female fetuses using in utero DWI during the second and third trimesters.

Regional ADC values of the morphologically normal canine brain.

Diffusion-weighted magnetic resonance imaging is increasingly available for investigation of canine brain diseases. Apparent diffusion coefficient (ADC) of normal canine brains is reported only in small numbers of subjects. The aim of the study was to investigate the ADC of different anatomical regions in the morphologically normal brain in a large population of canine patients in clinical setting. Additionally, possible influence on the ADC value of patient-related factors like sex, age and body weight, difference between the left and right side of the cerebral hemispheres, and between gray and white matter were investigated. Brain magnetic resonance studies including diffusion-weighted images of dogs presented at the Vetsuisse Faculty-University Zurich between 2015 and 2020 were reviewed retrospectively. Only morphologically normal brain magnetic resonance studies of dogs presented with neurological signs or non-neurological signs were included. Apparent diffusion coefficient values of 12 regions of interest (ROIs) in each hemisphere and an additional region in the cerebellar vermis were examined in each dog. A total of 321 dogs (including 247 dogs with neurological signs and 62 dogs with non-neurological signs) of various breeds, sex and age were included. Apparent diffusion coefficient significantly varied among most anatomical brain regions. A significantly higher ADC was measured in the gray [median 0.79 (range 0.69-0.90) × 10-3 mm2/s] compared to the white matter [median 0.70 (range 0.63-0.85) × 10-3 mm2/s]. No significant differences were found between the left and right cerebral hemispheres in most of the regions, neither between sexes, different reproductive status, and not consistently between body weight groups. Age was correlated first with a decrease from dogs <1 year of age to middle-age (⩾3 to <8 years) dogs and later with an increase of ADC values in dogs ⩾8 years. Apparent diffusion coefficient values of 25 ROIs were described in 321 morphologically normal canine brains in clinical setting. Apparent diffusion coefficient differences depending on the brain anatomical region are present. Apparent diffusion coefficient differences among age classes are present, likely consistent with brain maturation and aging. The described data can be a reference for future studies in clinical settings on the canine brain.

NIMG-50. ASSOCIATION BETWEEN SALINITY, ACIDITY, DIFFUSIVITY, AND HYPOXIA IN HUMAN GLIOMAS USING MULTI-NUCLEAR MRI

Abstract INTRODUCTION Sodium MRI has been recently explored in brain tumors to potentially reveal complementary information with proton MRI about the tumor microenvironment. However, there remains limited investigation combining sodium and quantitative proton MRI techniques. This pilot study explored the associations of sodium MRI with diffusion-, pH-, and hypoxia-weighted MRI biomarkers in gliomas. METHODS Eleven patients with gliomas (n=8 IDH-wild-type; n=3 IDH-mutant) who obtained sodium, anatomical, diffusion-, pH-, and hypoxia-weighted MRI were studied. All images were obtained on a 3T Siemens Prisma with a dedicated multi-nuclear head coil. Regions-of-interest were segmented on the contrast-enhancing (CE) (n=10), FLAIR (n=11), and necrotic regions (n=9). Sodium values were normalized to the mean values of the eyes. Median sodium, apparent diffusion coefficient (ADC), ADC(L) from bimodal histogram analyses, MTRasym (acidity), and R2’ (hypoxia) values were obtained. RESULTS There was increased sodium in necrosis compared to FLAIR regions (mean difference=0.24; P/i&amp;gt;&amp;lt; 0.05) and compared to CE regions (mean difference=0.17; P/i&amp;gt;=0.07). There were significant positive correlations between sodium and ADC in CE (R=0.94; P/i&amp;gt;&amp;lt; 0.0001) and FLAIR regions (ρ=0.77; P/i&amp;gt;&amp;lt; 0.01), but not in necrosis (R=0.44; P/i&amp;gt;=0.24). There was also a significant positive correlation with ADC(L) in CE regions (R=0.90; P&amp;lt; 0.001) but not in FLAIR regions (ρ=0.50; P/i&amp;gt;=0.12). Furthermore, there was a significant positive correlation between sodium and MTRasym in necrosis (R=0.74; P/i&amp;gt;&amp;lt; 0.05) and a positive trend in CE regions (R=0.55; P=0.10). There was also a negative trend between sodium and R2’ in FLAIR regions (ρ=-0.58; P/i&amp;gt;=0.11). CONCLUSIONS Because ADC and ADC(L) are inversely related to cell density, increased sodium in gliomas may reflect increased extracellular space stemming from lower cell density, as sodium concentration is higher extracellularly. Positive associations between sodium and acidity as well as negative associations between sodium and hypoxia may reflect alterations in coupled sodium-pH and sodium-hypoxia homeostasis in gliomas.

Apparent diffusion coefficient values in Modic changes – interobserver reproducibility and relation to Modic type

BackgroundModic Changes (MCs) in the vertebral bone marrow were related to back pain in some studies but have uncertain clinical relevance. Diffusion weighted MRI with apparent diffusion coefficient (ADC)-measurements can add information on bone marrow lesions. However, few have studied ADC measurements in MCs. Further studies require reproducible and valid measurements. We expect valid ADC values to be higher in MC type 1 (oedema type) vs type 3 (sclerotic type) vs type 2 (fatty type). Accordingly, the purpose of this study was to evaluate ADC values in MCs for interobserver reproducibility and relation to MC type.MethodsWe used ADC maps (b 50, 400, 800 s/mm2) from 1.5 T lumbar spine MRI of 90 chronic low back pain patients with MCs in the AIM (Antibiotics In Modic changes)-study. Two radiologists independently measured ADC in fixed-sized regions of interests. Variables were MC-ADC (ADC in MC), MC-ADC% (0% = vertebral body, 100% = cerebrospinal fluid) and MC-ADC-ratio (MC-ADC divided by vertebral body ADC). We calculated mean difference between observers ± limits of agreement (LoA) at separate endplates. The relation between ADC variables and MC type was assessed using linear mixed-effects models and by calculating the area under the receiver operating characteristic curve (AUC).ResultsThe 90 patients (mean age 44 years; 54 women) had 224 MCs Th12-S1 comprising type 1 (n = 111), type 2 (n = 91) and type 3 MC groups (n = 22). All ADC variables had higher predicted mean for type 1 vs 3 vs 2 (p < 0.001 to 0.02): MC-ADC (10− 6 mm2/s) 1201/796/576, MC-ADC% 36/21/14, and MC-ADC-ratio 5.9/4.2/3.1. MC-ADC and MC-ADC% had moderate to high ability to discriminate between the MC type groups (AUC 0.73–0.91). MC-ADC-ratio had low to moderate ability (AUC 0.67–0.85). At L4-S1, widest/narrowest LoA were for MC-ADC 20 ± 407/12 ± 254, MC-ADC% 1.6 ± 18.8/1.4 ± 10.4, and MC-ADC-ratio 0.3 ± 4.3/0.2 ± 3.9. Difference between observers > 50% of their mean value was less frequent for MC-ADC (9% of MCs) vs MC-ADC% and MC-ADC-ratio (17–20%).ConclusionsThe MC-ADC variable (highest mean ADC in the MC) had best interobserver reproducibility, discriminated between MC type groups, and may be used in further research. ADC values differed between MC types as expected from previously reported MC histology.

Anatomical and diffusion-weighted imaging of brain abnormalities in third-trimester fetuses with cytomegalovirus infection.

In this study of cytomegalovirus (CMV)-infected fetuses with first-trimester seroconversion, we aimed to evaluate the detection of brain abnormalities using magnetic resonance imaging (MRI) and neurosonography (NSG) in the third trimester, and compare the grading systems of the two modalities. We also evaluated the feasibility of routine use of diffusion-weighted imaging (DWI) fetal MRI and compared the regional apparent diffusion coefficient (ADC) values between CMV-infected fetuses and presumed normal, non-infected fetuses in the third trimester. This was a retrospective review of MRI and NSG scans in fetuses with confirmed first-trimester CMV infection performed between September 2015 and August 2019. Brain abnormalities were recorded and graded using fetal MRI and NSG grading systems to compare the two modalities. To investigate feasibility of DWI, a four-point rating scale (poor, suboptimal, good, excellent) was applied to assess the quality of the images. Quantitative assessment was performed by placing a freehand drawn region of interest in the white matter of the frontal, parietal, temporal and occipital lobes and the basal ganglia, pons and cerebellum to calculate ADC values. Regional ADC measurements were obtained similarly in a control group of fetuses with negative maternal CMV serology in the first trimester, normal brain findings on fetal MRI and normal genetic testing. Fifty-three MRI examinations of 46 fetuses with confirmed first-trimester CMV infection were included. NSG detected 24 of 27 temporal cysts seen on MRI scans, with a sensitivity of 78% and an accuracy of 83%. NSG did not detect abnormal gyration visible on two (4%) MRI scans. Periventricular calcifications were detected on two MRI scans compared with 10 NSG scans. While lenticulostriate vasculopathy was detected on 11 (21%) NSG scans, no fetus demonstrated this finding on MRI. MRI grading correlated significantly with NSG grading of brain abnormalities (P < 0.0001). Eight (15%) of the DWI scans in the CMV cohort were excluded from further analysis because of insufficient quality. The ADC values of CMV-infected fetuses were significantly increased in the frontal (both sides, P < 0.0001), temporal (both sides, P < 0.0001), parietal (left side, P = 0.0378 and right side, P = 0.0014) and occipital (left side, P = 0.0002 and right side, P < 0.0001) lobes and decreased in the pons (P = 0.0085) when compared with non-infected fetuses. The ADC values in the basal ganglia and the cerebellum were not significantly different in CMV-infected fetuses compared with normal controls (all P > 0.05). Temporal and frontal ADC values were higher in CMV-infected fetuses with more severe brain abnormalities compared to fetuses with mild abnormalities. Ultrasound and MRI are complementary during the third trimester in the assessment of brain abnormalities in CMV-infected fetuses, with a significant correlation between the grading systems of the two modalities. On DWI in the third trimester, the ADC values in several brain regions are abnormal in CMV-infected fetuses compared with normal controls. Furthermore, they seem to correlate in the temporal area and, to a lesser extent, frontal area with the severity of brain abnormalities associated with CMV infection. Larger prospective studies are needed for further investigation of the microscopic nature of diffusion abnormalities and correlation of different imaging findings with postnatal outcome. © 2022 International Society of Ultrasound in Obstetrics and Gynecology.

Combination of apparent diffusion coefficient and amplitude-integrated electroencephalogram to predict the outcome of comatose patients with severe traumatic brain injury

To examine whether the combination of quantitative regional apparent diffusion coefficient (ADC) and amplitude-integrated electroencephalogram (aEEG) can predict the outcome of comatose patients with severe traumatic brain injury (sTBI). A prospective study was conducted. The patients with coma caused by sTBI [Glasgow coma scale (GCS) < 8] admitted to Suqian First Hospital from January 2016 to June 2019 were enrolled. All patients underwent aEEG examination and magnetic resonance imaging (MRI) scan within 1 week after emergency treatment. The ADC values of 9 regions of interest (frontal gray matter and white matter, parietal gray matter and white matter, temporal gray matter and white matter, caudate nucleus of basal ganglia, lenticular nucleus and thalamus) were measured by head MRI, and the mean ADC values of frontal lobe, parietal lobe, temporal lobe and basal ganglia were calculated respectively. According to the follow-up results after 12 months, the differences of each index between patients with poor prognosis [Glasgow outcome score (GOS) 1-2] and patients with good prognosis (GOS 3-5) were compared; the receiver operating characteristic curve (ROC curve) was drawn to evaluate the predictive ability of aEEG and ADC for the good prognosis of patients with sTBI, and the predictive value of the combination of aEEG and ADC. A total of 52 patients with sTBI were enrolled, with mean age of (36.7±13.9) years old, 35 of whom were male. Within 12 months follow-up, 29 patients had achieved favorable outcomes and 23 patients had unfavorable outcome. There were 21, 17 and 14 patients with aEEG, and grade, respectively, and 19, 10 and 0 patients had good prognosis respectively. ADC values of 9 regions of interest in patients with good prognosis were significantly higher than those in patients with poor prognosis (×10-6 mm2/s: 924±107 vs. 531±87 in frontal gray matter, 804±95 vs. 481±74 in frontal white matter, 831±93 vs. 683±72 in temporal gray matter, 726±87 vs. 654±63 in temporal white matter, 767±79 vs. 690±75 in parietal gray matter, 716±84 vs. 642±62 in parietal white matter, 689±70 vs. 465±68 in caudate nucleus, 723±84 vs. 587±71 in lenticular nucleus, 807±79 vs. 497±67 in thalamus, all P < 0.01). ROC curve analysis showed that the area under ROC curve (AUC) of aEEG for predicting good prognosis of sTBI patients was 0.826, when the cut-off value of aEEG was < 1.5, the sensitivity was 94.7% and the specificity was 72.8%. Among the ADC value prediction abilities in the interested areas, the prediction of ADC value in frontal lobe and basal ganglia area were better than that in sTBI patients. AUC was 0.817 and 0.903 respectively. The best cut-off values were > 726×10-6 mm2/s and > 624×10-6 mm2/s respectively, the sensitivity of predicting prognosis were both 100%, and the specificity was 63.4% and 61.8%. A model combining frontal ADC and basal ganglia ADC with aEEG was 91.0% sensitive and 93.7% specific for favorable outcome of sTBI patients. Combination of the quantitative measurement of regional ADC and aEEG may be useful for predicting the outcome of the patients with sTBI.

Early neuroimaging and ultrastructural correlates of injury outcome after neonatal hypoxic-ischaemia.

Hypoxic ischaemia encephalopathy is the major cause of brain injury in new-borns. However, to date, useful biomarkers which may be used to early predict neurodevelopmental impairment for proper commencement of hypothermia therapy is still lacking. This study aimed to determine whether the early neuroimaging characteristics and ultrastructural correlates were associated with different injury progressions and brain damage severity outcomes after neonatal hypoxic ischaemia. Longitudinal 7 T MRI was performed within 6 h, 24 h and 7 days after hypoxic ischaemia in rat pups. The brain damage outcome at 7 days post-hypoxic ischaemia assessed using histopathology and MRI were classified as mild, moderate and severe. We found there was a spectrum of different brain damage severity outcomes after the same duration of hypoxic ischaemia. The severity of brain damage determined using MRI correlated well with that assessed by histopathology. Quantitative MRI characteristics denoting water diffusivity in the tissue showed significant differences in the apparent diffusion coefficient deficit volume and deficit ratios within 6 h, at 24 h and 7 days after hypoxic ischaemia among the 3 different outcome groups. The susceptible brain areas to hypoxic ischaemia were revealed by the temporal changes in regional apparent diffusion coefficient values among three outcome groups. Within 6 h post-hypoxic ischaemia, a larger apparent diffusion coefficient deficit volume and deficit ratios and lower apparent diffusion coefficient values were highly associated with adverse brain damage outcome. In the apparent diffusion coefficient deficit areas detected early after hypoxic ischaemia which were highly associated with severe damage outcome, transmission electron microscopy revealed fragmented nuclei; swollen rough endoplasmic reticulum and degenerating mitochondria in the cortex and prominent myelin loss and axon detraction in the white matter. Taken together, different apparent diffusion coefficient patterns obtained early after hypoxic ischaemia are highly associated with different injury progression leading to different brain damage severity outcomes, suggesting the apparent diffusion coefficient characteristics may be applicable to early identify the high-risk neonates for hypothermia therapy.

Traumatic subaxial cervical spine injury - Improving initial evaluation through correlation of diffusion tensor imaging and subaxial cervical spine injury classification SLIC score.

Background: Traumatic injury to spine and spinal cord represents a devastating condition, with a huge risk for permanent severe disabilities. Predicting the long-term outcome in this type of trauma is a very difficult task being under the influence of a wide spectrum of biomechanical and pathophysiological factors. The advent of magnetic resonance imaging (MRI) structural evaluation of the spinal cord brought critical supplementary data in the initial evaluation of these cases. Although edema and hemorrhage proved to be valuable in predicting the outcome, there is a well-documented discrepancy between MRI findings and clinical status.Methods: We performed diffusion tensor imaging (DTI) MR in 22 symptomatic patients with traumatic cervical spine injuries (mean age 49.6 ± 16, range from 17 to 74 years, 20 males and 2 females). DTI parameters were computed in 15 patients. Regional apparent diffusion coefficient, fractional anisotropy (FA), and fiber length (FL) were calculated in the region of interest defined as the region of maximum structural MR alterations and in the normal cord (above or below the level of the injury). The values for normal and pathological cord were compared. The clinical deficit was assessed with ASIA and subaxial cervical spine injury classification (SLIC) scores. We looked at the correlation between the DTI measures and clinical scores.Results: There is a highly significant difference between normal and pathological spinal cord for all DTI properties measured. There is also a strong correlation between DTI measures and SLIC clinical score, especially for FA. Significant results were obtained for CDA and FL as well although with lesser statistical power.Conclusion: Our results suggest that DTI measures, especially FA, represent a strong indicator of the severity of the traumatic cervical cord injury. It correlates very well with SLCI score and can be used as an additional confirmation of the real degree of level lesioning and as a prognostic factor for the neurological outcome regardless of the choice of treatment.

ADC measurements on the Unity MR-linac – A recommendation on behalf of the Elekta Unity MR-linac consortium

Background and purposeDiffusion-weighted imaging (DWI) for treatment response monitoring is feasible on hybrid magnetic resonance linear accelerator (MR-linac) systems. The MRI scanner of the Elekta Unity system has an adjusted design compared to diagnostic scanners. We investigated its impact on measuring the DWI-derived apparent diffusion coefficient (ADC) regarding three aspects: the choice of b-values, the spatial variation of the ADC, and scanning during radiation treatment. The aim of this study is to give recommendations for accurate ADC measurements on Unity systems. Materials and methodsSignal-to-noise ratio (SNR) measurements with increasing b-values were done to determine the highest bvalue that can be measured reliably. The spatial variation of the ADC was assessed on six Unity systems with a cylindrical phantom of 40 cm diameter. The influence of gantry rotation and irradiation was investigated by acquiring DWI images before and during treatment of 11 prostate cancer patients. ResultsOn the Unity system, a maximum b-value of 500 s/mm2 should be used for ADC quantification, as a trade-off between SNR and diffusion weighting. Accurate ADC values were obtained within 7 cm from the iso-center, while outside this region ADC values deviated more than 5%. The ADC was not influenced by the rotating linac or irradiation during treatment. ConclusionWe provide Unity system specific recommendations for measuring the ADC. This will increase the consistency of ADC values acquired in different centers on the Unity system, enabling large cohort studies for biomarker discovery and treatment response monitoring.

Differences in Diffusion-Weighted Imaging and Resting-State Functional Connectivity Between Two Culturally Distinct Populations of Prairie Vole

BackgroundWe used the highly prosocial prairie vole to test the hypothesis that higher-order brain structure—microarchitecture and functional connectivity (FC)—would differ between males from populations with distinctly different levels of prosocial behavior. Specifically, we studied males from Illinois (IL), which display high levels of prosocial behavior, and first generation males from Kansas dams and IL males (KI), which display the lowest level of prosocial behavior and higher aggression. Behavioral differences between these males are associated with overexpression of estrogen receptor alpha in the medial amygdala and bed nucleus of the stria terminalis and neuropeptide expression in the paraventricular nucleus. MethodsWe compared apparent diffusion coefficient, fractional anisotropy, and blood oxygen level–dependent resting-state FC between males. ResultsIL males displayed higher apparent diffusion coefficient in regions associated with prosocial behavior, including the bed nucleus of the stria terminalis, paraventricular nucleus, and anterior thalamic nuclei, while KI males showed higher apparent diffusion coefficient in the brainstem. KI males showed significantly higher fractional anisotropy than IL males in 26 brain regions, with the majority being in the brainstem reticular activating system. IL males showed more blood oxygen level–dependent resting-state FC between the bed nucleus of the stria terminalis, paraventricular nucleus, and medial amygdala along with other brain regions, including the hippocampus and areas associated with social and reward networks. ConclusionsOur results suggest that gray matter microarchitecture and FC may play a role the expression of prosocial behavior and that differences in other brain regions, especially the brainstem, could be involved. The differences between males suggests that this system represents a potentially valuable model system for studying emotional differences and vulnerability to stress and addiction.

In Reply: Early Diffusion Magnetic Resonance Imaging Changes in Normal-Appearing Brain in Pediatric Moyamoya Disease.

BACKGROUND Moyamoya disease often leads to ischemic strokes visible on diffusion-weighted imaging (DWI) and T2-weighted magnetic resonance imaging (MRI) with subsequent cognitive impairment. In adults with moyamoya, apparent diffusion coefficient (ADC) is correlated with regions of steal phenomenon and executive dysfunction prior to white matter changes. OBJECTIVE To investigate quantitative global diffusion changes in pediatric moyamoya patients prior to explicit structural ischemic damage. METHODS We retrospectively reviewed children (<20 yr old) with moyamoya disease and syndrome who underwent bypass surgery at our institution. We identified 29 children with normal structural preoperative MRI and without findings of cortical infarction or chronic white matter ischemic changes. DWI datasets were used to calculate ADC maps for each subject as well as for 60 age-matched healthy controls. Using an atlas-based approach, the cerebral white matter, cerebral cortex, thalamus, caudate, putamen, pallidum, hippocampus, amygdala, nucleus accumbens, and brainstem were segmented in each DWI dataset and used to calculate regional volumes and ADC values. RESULTS Multivariate analysis of covariance using the regional ADC and volume values as dependent variables and age and gender as covariates revealed a significant difference between the groups (P < .001). Post hoc analysis demonstrated significantly elevated ADC values for children with moyamoya in the cerebral cortex, white matter, caudate, putamen, and nucleus accumbens. No significant volume differences were found. CONCLUSION Prior to having bypass surgery, and in the absence of imaging evidence of ischemic stroke, children with moyamoya exhibit cerebral diffusion changes. These findings could reflect microstructural changes stemming from exhaustion of cerebrovascular reserve.

60 Precision Medicine in Developmental Pediatrics: Image-based Classification of Children with Autism Spectrum Disorder using Deep Learning

Abstract Introduction/Background Autism spectrum disorder (ASD) is a neurodevelopmental disorder resulting in challenges with social communication, sensory differences, and repetitive and restricted patterns of behavior. ASD affects approximately 1 in 66 children in North America, with boys being affected four times more frequently than girls. Currently, diagnosis is made primarily based on clinical features and no robust biomarker for ASD diagnosis has been identified. Potential image-based biomarkers to aid ASD diagnosis may include structural properties of deep gray matter regions in the brain. Objectives The primary objective of this work was to investigate if children with ASD show micro- and macrostructural alterations in deep gray matter structures compared to neurotypical children, and if these biomarkers can be used for an automatic ASD classification using deep learning. Design/Methods Quantitative apparent diffusion coefficient (ADC) magnetic resonance imaging data was obtained from 23 boys with ASD ages 0.8 – 19.6 years (mean 7.6 years) and 39 neurotypical boys ages 0.3 – 17.75 years (mean 7.6 years). An atlas-based method was used for volumetric analysis and extraction of median ADC values for each subject within the cerebral cortex, hippocampus, thalamus, caudate, putamen, globus pallidus, amygdala, and nucleus accumbens. The extracted quantitative regional volumetric and median ADC values were then used for the development and evaluation of an automatic classification method using an artificial neural network. Results The classification model was evaluated using 10-fold cross validation resulting in an overall accuracy of 76%, which is considerably better than chance level (62%). Specifically, 33 neurotypical boys were correctly classified, whereas 6 neurotypical boys were incorrectly classified. For the ASD group, 14 boys were correctly classified, while 9 boys were incorrectly classified. This translates to a precision of 70% for the children with ASD and 79% for neurotypical boys. Conclusion To the best of our knowledge, this is the first method to classify children with ASD using micro- and macrostructural properties of deep gray matter structures in the brain. The first results of the proposed deep learning method to identify children with ASD using image-based biomarkers are promising and could serve as the platform to create a more accurate and robust deep learning model for clinical application.

Early Diffusion Magnetic Resonance Imaging Changes in Normal-Appearing Brain in Pediatric Moyamoya Disease.

Moyamoya disease often leads to ischemic strokes visible on diffusion-weighted imaging (DWI) and T2-weighted magnetic resonance imaging (MRI) with subsequent cognitive impairment. In adults with moyamoya, apparent diffusion coefficient (ADC) is correlated with regions of steal phenomenon and executive dysfunction prior to white matter changes. To investigate quantitative global diffusion changes in pediatric moyamoya patients prior to explicit structural ischemic damage. We retrospectively reviewed children (<20 yr old) with moyamoya disease and syndrome who underwent bypass surgery at our institution. We identified 29 children with normal structural preoperative MRI and without findings of cortical infarction or chronic white matter ischemic changes. DWI datasets were used to calculate ADC maps for each subject as well as for 60 age-matched healthy controls. Using an atlas-based approach, the cerebral white matter, cerebral cortex, thalamus, caudate, putamen, pallidum, hippocampus, amygdala, nucleus accumbens, and brainstem were segmented in each DWI dataset and used to calculate regional volumes and ADC values. Multivariate analysis of covariance using the regional ADC and volume values as dependent variables and age and gender as covariates revealed a significant difference between the groups (P<.001). Post hoc analysis demonstrated significantly elevated ADC values for children with moyamoya in the cerebral cortex, white matter, caudate, putamen, and nucleus accumbens. No significant volume differences were found. Prior to having bypass surgery, and in the absence of imaging evidence of ischemic stroke, children with moyamoya exhibit cerebral diffusion changes. These findings could reflect microstructural changes stemming from exhaustion of cerebrovascular reserve.

Susceptibility-Weighted Imaging for Investigating the Effects of Drainage Veins in Cerebellar Infarction

Background: The phase value of susceptibility weighted imaging (SWI) can quantitatively measure the content of deoxyhemoglobin in veins, thus facilitating understanding of the mechanisms of drainage veins in cerebellar infarction areas. Objectives: To explore the clinical application value of the drainage veins in acute cerebellar infarction. Patients and Methods: SWI was used to measure the phase value of the bilateral cerebellar hemispheres in 30 normal volunteers. In addition, phase values, expressed as Δφ, were analyzed in 18 patients with cerebellar infarction. The scanning sequences included SWI, arterial spin labeling, and diffusion weighted imaging. Results: The phase value of the infarct area was higher than that of the contralateral region (P = 0.001) and was negatively correlated with regional cerebral blood flow in the infarct area (r = -0.433, P = 0.027). However, analysis of the regional cerebral blood flow revealed a positive correlation with the regional apparent diffusion coefficient (r = 0.566, P = 0.003), but the phase value was not correlated with the regional apparent diffusion coefficient of the infarct area (r = -0.293, P = 0.146). Using receiver operating characteristic curve analysis, we determined the phase value of drainage veins and the regional cerebral blood flow value of the critical infarction in the ischemic penumbra of the cerebellar infarction to be 301 spin and 22.25 mL/(min·100g), respectively. Conclusion: Our study showed the relevance of using phase value and its correlation with cerebral blood flow to characterize cerebellar infarction. In addition, our findings suggested possible venous reverse perfusion and venous congestion in the infarcted cerebellar hemisphere, which may be critically related to the development of infarct. Furthermore, our approach using a combination of non-invasive imaging parameters including the susceptibility imaging, cerebral perfusion and diffusion may be helpful in the diagnosis and management of stroke involving the cerebellum.

Multi-parametric arterial spin labelling and diffusion-weighted magnetic resonance imaging in differentiation of grade II and grade III gliomas.

PurposeTo assess arterial spin labelling (ASL) perfusion and diffusion MR imaging (DWI) in the differentiation of grade II from grade III gliomas.Material and methodsA prospective cohort study was done on 36 patients (20 male and 16 female) with diffuse gliomas, who underwent ASL and DWI. Diffuse gliomas were classified into grade II and grade III. Calculation of tumoural blood flow (TBF) and apparent diffusion coefficient (ADC) of the tumoral and peritumoural regions was made. The ROC curve was drawn to differentiate grade II from grade III gliomas.ResultsThere was a significant difference in TBF of tumoural and peritumoural regions of grade II and III gliomas (p = 0.02 and p =0.001, respectively). Selection of 26.1 and 14.8 ml/100 g/min as the cut-off for TBF of tumoural and peritumoural regions differentiated between both groups with area under curve (AUC) of 0.69 and 0.957, and accuracy of 77.8% and 88.9%, respectively. There was small but significant difference in the ADC of tumoural and peritumoural regions between grade II and III gliomas (p = 0.02 for both). The selection of 1.06 and 1.36 × 10-3 mm2/s as the cut-off of ADC of tumoural and peritumoural regions was made, to differentiate grade II from III with AUC of 0.701 and 0.748, and accuracy of 80.6% and 80.6%, respectively. Combined TBF and ADC of tumoural regions revealed an AUC of 0.808 and accuracy of 72.7%. Combined TBF and ADC for peritumoural regions revealed an AUC of 0.96 and accuracy of 94.4%.ConclusionTBF and ADC of tumoural and peritumoural regions are accurate non-invasive methods of differentiation of grade II from grade III gliomas.

Clinical application value of prognosis of nutrition index and apparent diffusion coefficient in patient with hepatocellular carcinoma underwent transarterial chemoembolization

Objective: To explore clinical application value of prognostic nutrition index(PNI) and apparent diffusion coefficient(ADC) in treating hepatic arterial chemoembolization (TACE) of patients with hepatic cell carcinoma (HCC). Methods: A total of 77 patients with HHC of BCLC B were retrospectively analyzed in Dalian Medical University Affiliated Second Hospital who were diagnosed for the first time and received TACE treatment from October 2017 to December 2018, of whom 64 Males, 13 females, mean age was 54±13 years.At 1 month after surgery, TACE efficacy was evaluated according to revised solid tumor evaluation criteria (mRECIST), the enrolled patients were divided into TACE effective group (41 cases, 53.2%) and TACE ineffective group (36 cases, 46.8%) to compare ability of PNI and ability of ADC alone or in combination in evaluating efficacy of TACE and the relationship between these two groups. Results: Overall postoperative PNI of enrolled patients was decreased compared with preoperative PNI, 47.7±6.6 vs 48.3±5.9 (P<0.05), preoperative and postoperative PNI of TACE effective group were all higher than that of TACE ineffective group (49.9±6.0 vs 46.6±5.3, 50.6±5.4 vs 44.4±5.1,all P<0.05), there was no significant difference in PNI between the treatment groups (P>0.05). The value of ADC in postoperative tumor region increased compared with that in preoperative tumor region ((1.43±0.15) ×10(-3) vs (1.28±0.08) ×10(-3) mm(2)/s, P<0.05), the difference between postoperative tumor region ADC value and postoperative normal liver parenchyma had no statistical significance(P>0.05). Overall postoperative PNI and tumor region ADC value of enrolled patients had linear correlation (P<0.05).Threshold value of PNI and ADC value in preoperative prediction were 51.05 and 1.32×10(-3) mm(2)/s; postoperative evaluation threshold value were 50.11 and 1.41×10(-3) mm(2)/s.Postoperative combination of PNI and ADC had the highest value in evaluating TACE efficacy. Conclusions: TACE postoperative PNI and tumor region ADC are related. PNI and tumor region ADC could be used in predicting and evaluating TACE efficacy in HCC patients, combination of these two could further increase the efficiency.

Pre-operative apparent diffusion coefficient values and tumour region volumes as prognostic biomarkers in glioblastoma: correlation and progression-free survival analyses

ObjectivesGlioblastoma (GB) contains diverse histologic regions. Apparent diffusion coefficient (ADC) values are surrogates for the degree of number of cells within the tumour regions. Because an assessment of ADC values and volumes within tumour sub-compartments of GB is missing in the literature, we aimed to evaluate these associations.MethodsA retrospective cohort of 48 patients with GB underwent segmentation to calculate tumour region volumes (in cubic centimetre) and ADC values in tumour regions: normal tissue, enhancing tumour, proximal oedema, distal oedema, and necrosis. Correlation, Kaplan-Meier, and Cox hazard regression analyses were performed.ResultsWe found a statistically significant difference among ADC values for tumour regions: F (4, 220) = 166.71 and p ≤ .001 and tumour region volumes (necrosis, enhancing tumour, peritumoural oedema): F (2, 141) = 136.3 and p ≤ .001. Post hoc comparisons indicated that the only significantly different mean score was the peritumoural volume in oedema region (p < .001). We observed a positive significant correlation between ADC of distal oedema and peritumoural volume, r = .418, df = 34, and p = .011. Cox proportional hazards regression analysis considering only tumour region volumes provided an almost significant model: − 2 log-likelihood = 146.066, χ2 (4) = 9.303, and p = .054 with a trend towards significance of the hazard function: p = .067 and HR = 1.077 for the non-enhancing tumour volume.ConclusionsADC values together with volumes of oedema region might have a role as predictors of progression-free survival (PFS) in patients with GB; we recommend a routine MRI assessment with the calculation of these biomarkers in GB.

Vasogenic cerebral edema associated with the disability in activities of daily living in patients with chronic obstructive pulmonary disease.

IntroductionThe aim of this study was to explore whether patients with chronic obstructive pulmonary disease (COPD) develop vasogenic cerebral edema, and whether this edema contributes to the COPD‐related disability.MethodsEighteen stable patients with COPD and 17 matched healthy volunteers were enrolled. Apparent diffusion coefficient (ADC) values were calculated by voxel‐based analysis using DTI‐Studio software based on diffusion tensor imaging. COPD‐related disability was calculated using activities of daily living (ADL) scale.ResultsIn patients with COPD, ADC increased in the white matter fiber tracts including the bilateral anterior cingulum and posterior corpus callosum and in the white matter fibers connecting the bilateral insular cortices, sub‐lobar cortices, and pars triangularis cortices and the left rectus and olfactory gyrus. However, after further controlling for cigarette smoking, the difference in ADC values in the posterior corpus callosum between groups disappeared. Patients with COPD had significantly higher scores in ADL than that in controls. Moreover, ADL scores were positively correlated with the increased regional ADC values.ConclusionVasogenic cerebral edema occurs in patients with COPD. Cigarette smoking may be a risk factor for COPD‐related vasogenic edema. Vasogenic cerebral edema may be related to the COPD‐related ADL impairment.

Low b-value diffusion weighted imaging is promising in the diagnosis of brain death and hypoxic-ischemic injury secondary to cardiopulmonary arrest

BackgroundCardiorespiratory arrest can result in a spectrum of hypoxic ischemic brain injury leading to global hypoperfusion and brain death (BD). Because up to 40% of patients with BD are viable organ donors, avoiding delayed diagnosis of this condition is critical. High b-value diffusion weighted imaging (DWI) measures primarily molecular self-diffusion; however, low b-values are sensitive to perfusion. We investigated the feasibility of low b-value DWI in discriminating the global hypoperfusion of BD and hypoxic ischemic encephalopathy (HIE).MethodsWe retrospectively reviewed cardiorespiratory arrest subjects with a diagnosis of HIE or BD. Inclusion criteria included brain DWI acquired at both low (50 s/mm2) and high (1000–2000 s/mm2) b-values. Automated segmentation was used to determine mean b50 apparent diffusion coefficient (ADC) values in gray and white matter regions. Normal subjects with DWI at both values were used as age- and sex-matched controls.ResultsWe evaluated 64 patients (45 with cardiorespiratory arrest and 19 normal). Cardiorespiratory arrest patients with BD had markedly lower mean b50 ADC in gray matter regions compared with HIE (0.70 ± 0.18 vs. 1.95 ± 0.25 × 10−3 mm2/s, p < 0.001) and normal subjects (vs. 1.79 ± 0.12 × 10−3 mm2/s, p < 0.001). HIE had higher mean b50 ADC compared with normal (1.95 ± 0.25 vs. 1.79 ± 0.12 × 10−3 mm2/s, p = 0.016). There was wide separation of gray matter ADC values in BD subjects compared with age matched normal and HIE subjects. White matter values were also markedly decreased in the BD population, although they were less predictive than gray matter.ConclusionLow b-value DWI is promising for the discrimination of HIE with maintained perfusion and brain death in cardiorespiratory arrest.