Diffusion MRI: apparent diffusion coefficient (ADC) values in the normal brain and a classification of brain disorders based on ADC values

Tutorial: a guide to diffusion MRI and structural connectomics

Diffusion magnetic resonance imaging (dMRI) is a versatile imaging technique that has gained popularity thanks to its sensitive ability to measure displacement of water molecules within a living tissue on a micrometer scale. Although dMRI has been around since the early 1990s, its applications are constantly evolving, primarily regarding the inference of structural connectomics from nerve fiber trajectories. However, these applications require expertise in image processing and statistics, and it can be difficult for a newcomer to choose an appropriate pipeline to fit their research needs, not least because dMRI is such a flexible methodology that dozens of acquisition and analysis pipelines have been developed over the years. This introductory guide is designed for graduate students and researchers in the neuroscience community who are interested in integrating this new methodology regardless of their background in neuroimaging and computational tools. The guide provides a brief overview of the basic dMRI methodologies but focuses on its applications in neuroplasticity and connectomics. The guide starts with dMRI experimental designs and a complete step-by-step pipeline for structural connectomics. The following section covers the basics of dMRI, including parameters and clinical applications (apparent diffusion coefficient, mean diffusivity, fractional anisotropy and microscopic fractional anisotropy), as well as different approaches and models. The final section focuses on structural connectomics, covering subjects from fiber tracking (techniques, evaluation and limitations) to structural networks (constructing, analyzing and visualizing a network).

Comparison of apparent diffusion coefficient (ADC) values obtained by echo planar imaging diffusion-weighted imaging (DWI) and radial acquisition regime DWI in low field MRI systems: A phantom study

INTRODUCTION

Diffusion-weighted imaging (DWI) with radial acquisition regime (RADAR; RADAR-DWI) is a fast spin echo (FSE)-based DWI imaging technique that is known to be robust to magnetic susceptibility artifacts and distortions as compared with echo planar imaging DWI (EPI-DWI). Several reports have suggested that the apparent diffusion coefficient (ADC) values obtained with FSE-based DWI are different from those obtained with EPI-DWI. The purpose of this study was to create phantoms that mimic the T2 and ADC values of various tissues and to demonstrate the ADC values obtained with RADAR-DWI and EPI-DWI in low-field magnetic resonance imaging (MRI) systems.

METHODS

Several phantoms were created using sucrose and manganese (II) chloride tetrahydrate mimicking various tissues. RADAR-DWI and EPI-DWI were used to scan the phantoms, and the obtained ADC values were compared.

RESULTS

The ADC values obtained with RADAR-DWI were significantly higher than those obtained with EPI-DWI for all phantoms (P < 0.05). The ADC values obtained by RADAR-DWI ranged from 0.70 ± 0.01 to 1.21 ± 0.02 ( × 10-3mm2s-1). Meanwhile, the ADC values obtained with EPI-DWI ranged from 0.59 ± 0.01 to 1.08 ± 0.05 ( × 10-3mm2s-1).

CONCLUSIONS

We created phantoms mimicking T2 and ADC values of various tissues and demonstrated the differences in ADC values obtained with RADAR-DWI and EPI-DWI using low-field MRI systems.

IMPLICATIONS FOR PRACTICE

ADC values obtained by RADAR-DWI are significantly higher than those obtained by EPI-DWI, with different cutoff values for various tumor malignancies between them.

Psychological symptoms and brain activity alterations in women with PCOS and their relation to the reduced quality of life: a narrative review

BACKGROUND

Polycystic ovary syndrome (PCOS) is the most common feminine endocrine disorder, characterized by androgen excess, ovulatory dysfunction, and polycystic ovarian morphology. The negative impact of symptoms on the quality of life (QoL) of patients is still not clear.

PURPOSE

The present review aimed at studying the impact of the symptoms, the psychological symptoms, and brain alterations in women with PCOS.

METHODS

A systematic search was undertaken for studies that assessed the impact of PCOS symptoms on QoL, psychological symptoms, and brain alterations in PCOS patients.

RESULTS

Most of the information about QoL came from psychometric studies, which used culture-based questionnaires. Alterations of sleep quality, body image, and mood disorders can negatively affect the QoL of the patients. Sexual satisfaction and desire were affected by PCOS. Brain imaging studies showed functional alterations that are associated with impairments of visuospatial working memory, episodic and verbal memory, attention, and executive function.

CONCLUSIONS

Several factors can negatively influence the quality of life of the patients, and they are directly related to hyperandrogenism and the risk of infertility. In particular, obesity, hirsutism, acne, and the fear of infertility can have a direct impact on self-esteem and sexual function. Metabolic and psychiatric comorbidities, such as mood, anxiety, and eating disorders, can affect the well-being of the patients. Moreover, specific cognitive alterations, such as impairments in attention and memory, can limit PCOS patients in a series of aspects of daily life.

Model discovery approach enables noninvasive measurement of intra-tumoral fluid transport in dynamic MRI

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a routine method to noninvasively quantify perfusion dynamics in tissues. The standard practice for analyzing DCE-MRI data is to fit an ordinary differential equation to each voxel. Recent advances in data science provide an opportunity to move beyond existing methods to obtain more accurate measurements of fluid properties. Here, we developed a localized convolutional function regression that enables simultaneous measurement of interstitial fluid velocity, diffusion, and perfusion in 3D. We validated the method computationally and experimentally, demonstrating accurate measurement of fluid dynamics in situ and in vivo. Applying the method to human MRIs, we observed tissue-specific differences in fluid dynamics, with an increased fluid velocity in breast cancer as compared to brain cancer. Overall, our method represents an improved strategy for studying interstitial flows and interstitial transport in tumors and patients. We expect that our method will contribute to the better understanding of cancer progression and therapeutic response.

Factors associated with decreasing diffusion-weighted imaging-positive area volume after mechanical thrombectomy in patients with large early ischemic changes

OBJECTIVES

This study aimed to evaluate the factors associated with decreasing diffusion-weighted imaging (DWI) positive areas in patients with large early ischemic changes after mechanical thrombectomy (MT).

MATERIALS AND METHODS

This retrospective single-center clinical study was conducted between January 2013 and December 2022. We included consecutive patients who underwent MT for acute large-vessel occlusion of the anterior circulation with low pretreatment DWI-Alberta Stroke Program Early Computed Tomography Scores (ASPECTS) (0-5), effective recanalization [thrombolysis in cerebral infarction (TICI) 2b or TICI3], and magnetic resonance imaging (MRI) acquired before and after MT. We measured the DWI-positive area volume before and after MT. The primary endpoint was the after/before-MT DWI-positive area-volume ratio.

RESULTS

In total, 28 patients were included in this study. Eight patients (29%) had an after/before-MT DWI-positive area-volume ratio of <1. The median mean apparent diffusion coefficient (ADC) levels of the DWI-positive areas in the groups with a ratio of <1 or >1 were 717 × 10⁶ mm2/s and 637 × 106 mm2/s, respectively (p = 0.011). Multivariate logistic regression analysis showed that ADC level (OR, 1.020 [95% confidence intervals (CIs), 1.001-1.040]; p = 0.040) was an independent predictor of a decreased DWI-positive area after MT. There was a negative correlation between the mean ADC level and the after/before-MT DWI-positive area-volume ratio (p < 0.001, |ρ| = 0.650), and the mean pretreatment ADC cutoff level was 649 × 106 mm2/s (area under the curve (AUC) = 0.806) for predicting a volume ratio of <1.

CONCLUSIONS

The mean ADC level before-MT correlated with the after/before-MT DWI-positive area-volume ratio. A mean pretreatment ADC cutoff level of 649 × 106 mm2/s predicted a decreased DWI-positive area after MT.

Clinico-radiological factors associated with aphasia outcome in post stroke patients: A prospective follow up study from eastern part of India

BACKGROUND

Aphasia is a language disorder acquired secondary to brain damage. This study aims to evaluate clinical and radiological profile of patients with post stroke aphasia and factors affecting its recovery.

METHODS

We conducted a prospective study of patients with first left Middle or Anterior Cerebral Artery infarct or Intracerebral Hemorrhage (ICH) with aphasia admitted within 14 days of stroke onset. Aphasia Quotient (AQ) was assessed at 2 weeks (AQ1) and 3 months (AQ2) using Western Aphasia Battery-Hindi version. Magnetic Resonance Imaging of brain with Diffusion Tensor Imaging (DTI) of bilateral Arcuate Fasciculus (AF) and Corticospinal Tract was done at admission, and stroke volume, Laterality Indices of Fractional Anisotropy (LI-FA), Mean Diffusivity (LI-MD), Radial Diffusivity (LI-RD), Axial Diffusivity (LI-AD) and Apparent Diffusion Coefficient (LI-ADC) were obtained.

RESULTS

36 patients [8 ICH and 28 Acute Ischemic Stroke (AIS)] were included. AQ1 and AQ2 were significantly higher in subcortical stroke than cortical. AQ2 and increase in AQ scores (including its subscores) were significantly higher in ICH than AIS. National Institutes of Health Stroke Scale score at admission and volume of stroke had significant negative correlation with AQ1 and AQ2. Laterality Index of Fractional Anisotropy of Arcuate Fasciculus [LI-FA (AF)] had significant positive correlation with AQ2 and naming score at 3 months. Laterality Index of Mean Diffusivity of Arcuate Fasciculus [LI-MD (AF)] had significant negative correlation with AQ1, AQ2 and all subcomponents of AQ2. Significant positive correlation was seen between improvements in Modified Rankin Scale score and AQ.

CONCLUSION

The study shows that DTI can be used to predict severity of aphasia at follow up and recovery in language and motor functions occur in parallel.

Diagnostic algorithm for glioma grading using dynamic susceptibility contrast‑enhanced magnetic resonance perfusion and proton magnetic resonance spectroscopy

The present retrospective study aimed to investigate the diagnostic capacity of and design a diagnostic algorithm for dynamic susceptibility contrast-enhanced MRI (DSCE-MRI) and proton magnetic resonance spectroscopy (1H-MRS) in grading low-grade glioma (LGG) and high-grade glioma (HGG). This retrospective study enrolled 57 patients, of which 14 had LGG and 43 had HGG, five had World Health Organization grade 1, nine had grade 2, 20 had grade 3 and 23 had grade 4 glioma. All subjects underwent a standard 3T MRI brain tumor protocol with conventional MRI (cMRI) and advanced techniques, including DSCE-MRI and 1H-MRS. The associations of grade categorization with parameters in tumor and peritumor regions in the DSCE-MRI were examined, including tumor relative cerebral blood volume (TrCBV) and peripheral relative (Pr)CBV, as well as Tr and Pr cerebral blood flow (CBF) and 1H-MRS, including the creatine (Cr) and N-acetyl aspartate (NAA) ratios of choline (Cho), i.e. the TCho/NAA, PCho/NAA, TCho/Cr and PCho/Cr metabolite ratios. The data were compared using the Mann-Whitney U-test, independent samples t-test, Chi-square test, Fisher's exact test and receiver operating characteristic curve analyses. Decision tree analysis established an algorithm based on cutoffs for specified significant parameters. The PrCBF had the highest performance in the preoperative prediction of histological glioma grading, followed by the TrCBV, PrCBF, TrCBV, PCho/NAA, PCho/Cr, TCho/NAA and TCho/Cr. An algorithm based on TrCBV, PrCBF and TCho/Cr had a diagnostic accuracy of 100% for LGG and 90.7% for HGG and a misclassification risk of 7%. The cutoffs (sensitivity and specificity) were 2.48 (86 and 100%) for TrCBV, 1.26 (83.7 and 100%) for PrCBF and 3.18 (69.8 and 78.6%) for TCho/Cr. In conclusion, the diagnostic algorithm using TrCBV, PrCBF and TCho/Cr values, which were obtained from DSCE-MRI and 1H-MRS, increased diagnostic accuracy to 100% for LGGs and 90.7% for HGGs compared to previous studies using conventional MRI. This non-invasive advanced MRI diagnostic algorithm is recommended for clinical application for constructing preoperative strategies and prognosis of patients with glioma.

NTMS based tractography and segmental diffusion analysis in patients with brainstem gliomas: Risk stratification and clinical potential

Introduction

Surgery on the brainstem level is associated with a high-risk of postoperative morbidity. Recently, we have introduced the combination of navigated transcranial magnetic stimulation (nTMS) and diffusion tensor imaging (DTI) tractography to define functionally relevant motor fibers tracts on the brainstem level to support operative planning and risk stratification in brainstem cavernomas.

Research question

Evaluate this method and assess it's clinical impact for the surgery of brainstem gliomas.

Material and methods

Patients with brainstem gliomas were examined preoperatively with motor nTMS and DTI tractography. A fractional anisotropy (FA) value of 75% of the individual FA threshold (FAT) was used to track descending corticospinal (CST) and -bulbar tracts (CBT). The distance between the tumor and the somatotopic tracts (hand, leg, face) was measured and diffusion parameters were correlated to the patients' outcome.

Results

12 patients were enrolled in this study, of which 6 underwent surgical resection, 5 received a stereotactic biopsy and 1 patient received conservative treatment. In all patients nTMS mapping and somatotopic tractography were performed successfully. Low FA values correlated with clinical symptoms revealing tract alteration by the tumor (p = 0.049). A tumor-tract distance (TTD) above 2 mm was the critical limit to achieve a safe complete tumor resection.

Discussion and conclusion

nTMS based DTI tractography combined with local diffusion analysis is a valuable tool for preoperative visualization and functional assessment of relevant motor fiber tracts, improving planning of safe entry corridors and perioperative risk stratification in brainstem gliomas tumors. This technique allows for customized treatment strategy to maximize patients' safety.

Status epilepticus in BRAF-related cardio-facio-cutaneous syndrome: Focus on neuroimaging clues to physiopathology

OBJECTIVE

Cardio-facio-cutaneous syndrome (CFC) is a genetic disorder due to variants affecting genes coding key proteins of the Ras/MAPK signaling pathway. Among the different features of CFC, neurological involvement, including cerebral malformations and epilepsy, represents a common and clinically relevant aspect. Status epilepticus (SE) is a recurrent feature, especially in a specific subgroup of CFC patients with developmental and epileptic encephalopathy (DEE) and history of severe pharmacoresistant epilepsy. Here we dissect the features of SE in CFC patients with a particular focus on longitudinal magnetic resonance imaging (MRI) findings to identify clinical-radiological patterns and discuss the underlying physiopathology.

METHODS

We retrospectively analyzed clinical, electroencephalogram (EEG), and MRI data collected in a single center from a cohort of 23 patients with CFC carrying pathogenic BRAF variants who experienced SE during a 5-year period.

RESULTS

Seven episodes of SE were documented in 5 CFC patients who underwent EEG and MRI at baseline. MRI was performed during SE/within 72 hours from SE termination in 5/7 events. Acute/early post-ictal MRI findings showed heterogenous abnormalities: restricted diffusion in 2/7, focal area of pcASL perfusion change in 2/7, focal cortical T2/FLAIR hyperintensity in 2/7. Follow-up images were available for 4/7 SE. No acute changes were detected in 2/7 (MRI performed 4 days after SE termination).

SIGNIFICANCE

Acute focal neuroimaging changes concomitant with ictal EEG focus were present in 5/7 episodes, though with different findings. The heterogeneous patterns suggest different contributing factors, possibly including the presence of focal cortical malformations and autoinflammation. When cytotoxic edema is revealed by MRI, it can be followed by permanent structural damage, as already observed in other genetic conditions. A better understanding of the physiopathology will provide access to targeted treatments allowing to prevent long-term adverse neurological outcome.

PLAIN LANGUAGE SUMMARY

Cardio-facio-cutaneous syndrome is a genetic disorder that often causes prolonged seizures known as status epilepticus. This study has a focus on electroclinical and neuroimaging patterns in patients with cardio-facio-cutaneous syndrome. During these status epilepticus episodes, we found different abnormal brain imaging patterns in patients, indicating various causes like brain malformations and inflammation. Understanding these patterns could help doctors find specific treatments, protecting cardio-facio-cutaneous syndrome patients from long-term brain damage.

Convolutional network denoising for acceleration of multi-shot diffusion MRI

Multi-shot echo planar imaging is a promising technique to reduce geometric distortions and increase spatial resolution in diffusion-weighted MRI (DWI), at the expense of increased scan time. Moreover, performing DWI in the body requires multiple repetitions to obtain sufficient signal-to-noise ratio, which further increases the scan time. This work proposes to reduce the number of repetitions and perform denoising of high b-value images using a convolutional network denoising trained on single-shot DWI to accelerate the acquisition of multi-shot DWI. Convolutional network denoising is demonstrated to accelerate the acquisition of 2-shot DWI by a factor of 4 compared to the clinical standard on patients with rectal cancer. Image quality was evaluated using qualitative scores from expert body radiologists between accelerated and non-accelerated acquisition. Additionally, the effect of convolutional network denoising on each image quality score was analyzed using a Wilcoxon signed-rank test. Convolutional network denoising would enable to increase the number of shots without increasing scan time for significant geometric artifact reduction and spatial resolution increase.

A narrative review of the effects of dexamethasone on traumatic brain injury in clinical and animal studies: focusing on inflammation

Traumatic brain injury (TBI) is a type of brain injury resulting from a sudden physical force to the head. TBI can range from mild, such as a concussion, to severe, which might result in long-term complications or even death. The initial impact or primary injury to the brain is followed by neuroinflammation, excitotoxicity, and oxidative stress, which are the hallmarks of the secondary injury phase, that can further damage the brain tissue. Dexamethasone (DXM) has neuroprotective effects. It reduces neuroinflammation, a critical factor in secondary injury-associated neuronal damage. DXM can also suppress the microglia activation and infiltrated macrophages, which are responsible for producing pro-inflammatory cytokines that contribute to neuroinflammation. Considering the outcomes of this research, some of the effects of DXM on TBI include: (1) DXM-loaded hydrogels reduce apoptosis, neuroinflammation, and lesion volume and improves neuronal cell survival and motor performance, (2) DXM treatment elevates the levels of Ndufs2, Gria3, MAOB, and Ndufv2 in the hippocampus following TBI, (3) DXM decreases the quantity of circulating endothelial progenitor cells, (4) DXM reduces the expression of IL1, (5) DXM suppresses the infiltration of RhoA + cells into primary lesions of TBI and (6) DXM treatment led to an increase in fractional anisotropy values and a decrease in apparent diffusion coefficient values, indicating improved white matter integrity. According to the study, the findings show that DXM treatment has neuroprotective effects in TBI. This indicates that DXM is a promising therapeutic approach to treating TBI.

Progressive Changes in Cerebral Apparent Diffusion Values in Fabry Disease: A 5-Year Follow-up MRI Study

BACKGROUND AND PURPOSE

White matter lesions are commonly found in patients with Fabry disease. Existing studies have shown elevated diffusivity in healthy-appearing brain regions that are commonly associated with white matter lesions, suggesting that DWI could help detect white matter lesions at an earlier stage This study explores whether diffusivity changes precede white matter lesion formation in a cohort of patients with Fabry disease undergoing yearly MR imaging examinations during a 5-year period.

MATERIALS AND METHODS

T1-weighted anatomic, FLAIR, and DWI scans of 48 patients with Fabry disease (23 women; median age, 44 years; range, 15-69 years) were retrospectively included. White matter lesions and tissue probability maps were segmented and, together with ADC maps, were transformed into standard space. ADC values were determined within lesions before and after detection on FLAIR images and compared with normal-appearing white matter ADC. By means of linear mixed-effects modeling, changes in ADC and ΔADC (relative to normal-appearing white matter) across time were investigated.

RESULTS

ADC was significantly higher within white matter lesions compared with normal-appearing white matter (P < .01), even before detection on FLAIR images. ADC and ΔADC were significantly affected by sex, showing higher values in men (60.1 [95% CI, 23.8-96.3] ×10-6mm2/s and 35.1 [95% CI, 6.0-64.2] ×10-6mm2/s), respectively. ΔADC increased faster in men compared with women (0.99 [95% CI, 0.27-1.71] ×10-6mm2/s/month). ΔADC increased with time even when only considering data from before detection (0.57 [95% CI, 0.01-1.14] ×10-6mm2/s/month).

CONCLUSIONS

Our results indicate that in Fabry disease, changes in diffusion precede the formation of white matter lesions and that microstructural changes progress faster in men compared with women. These findings suggest that DWI may be of predictive value for white matter lesion formation in Fabry disease.

Microstructural Changes in the Spinothalamic Tract of CPSS Patients: Preliminary Results from a Single-Center Diffusion-Weighted Magnetic Resonance Imaging Study

INTRODUCTION

Chronic pain after spinal surgery (CPSS), formerly known as failed back surgery syndrome, encompasses a variety of highly incapacitating chronic pain syndromes emerging after spinal surgery. The intractability of CPSS makes objective parameters that could aid classification and treatment essential. In this study, we investigated the use of cerebral diffusion-weighted magnetic resonance imaging.

METHODS

Cerebral 3T diffusion-weighted (DW-) MRI data from adult CPSS patients were assessed and compared with those of healthy controls matched by age and gender. Only imaging data without relevant artefacts or significant pathologies were included. Apparent diffusion coefficient (ADC) maps were calculated from the b0 and b1000 values using nonlinear regression. After skull stripping and affine registration of all imaging data, ADC values for fifteen anatomical regions were calculated and analyzed with independent samples T-tests.

RESULTS

A total of 32 subjects were included (sixteen CPSS patients and sixteen controls). The mean ADC value of the spinothalamic tract was found to be significantly higher in CPSS patients compared with in healthy controls (p = 0.013). The other anatomical regions did not show statistically different ADC values between the two groups.

CONCLUSION

Our results suggest that patients suffering from CPSS are subject to microstructural changes, predominantly within the cerebral spinothalamic tract. Additional research could possibly lead to imaging biomarkers derived from ADC values in CPSS patients.

Texture feature analysis of MRI-ADC images to differentiate glioma grades using machine learning techniques

Apparent diffusion coefficient (ADC) of magnetic resonance imaging (MRI) is an indispensable imaging technique in clinical neuroimaging that quantitatively assesses the diffusivity of water molecules within tissues using diffusion-weighted imaging (DWI). This study focuses on developing a robust machine learning (ML) model to predict the aggressiveness of gliomas according to World Health Organization (WHO) grading by analyzing patients' demographics, higher-order moments, and grey level co-occurrence matrix (GLCM) texture features of ADC. A population of 722 labeled MRI-ADC brain image slices from 88 human subjects was selected, where gliomas are labeled as glioblastoma multiforme (WHO-IV), high-grade glioma (WHO-III), and low-grade glioma (WHO I-II). Images were acquired using 3T-MR systems and a region of interest (ROI) was delineated manually over tumor areas. Skewness, kurtosis, and statistical texture features of GLCM (mean, variance, energy, entropy, contrast, homogeneity, correlation, prominence, and shade) were calculated using ADC values within ROI. The ANOVA f-test was utilized to select the best features to train an ML model. The data set was split into training (70%) and testing (30%) sets. The train set was fed into several ML algorithms and selected most promising ML algorithm using K-fold cross-validation. The hyper-parameters of the selected algorithm were optimized using random grid search technique. Finally, the performance of the developed model was assessed by calculating accuracy, precision, recall, and F1 values reported for the test set. According to the ANOVA f-test, three attributes; patient gender (1.48), GLCM energy (9.48), and correlation (13.86) that performed minimum scores were excluded from the dataset. Among the tested algorithms, the random forest classifier(0.8772 ± 0.0237) performed the highest mean-cross-validation score and selected to build the ML model which was able to predict tumor categories with an accuracy of 88.14% over the test set. The study concludes that the developed ML model using the above features except for patient gender, GLCM energy, and correlation, has high prediction accuracy in glioma grading. Therefore, the outcomes of this study enable to development of advanced tumor classification applications that assist in the decision-making process in a real-time clinical environment.

Calcium electroporation in cutaneous metastases - A non-randomised phase II multicentre clinical trial

BACKGROUND

Cutaneous metastases can cause distressing symptoms and be challenging to treat. Local therapies are essential in management. Calcium electroporation uses calcium and electrical pulses to selectively kill cancer cells. This multicentre study aimed to define response in cutaneous metastases across different cancer types.

METHODS

Patients with tumours ≤3 cm of any histology were included (stable or progressing on current therapy ≥2 months), at three centres. Tumours were treated with 220 mM calcium chloride injection and manual application of eight 0.1 ms pulses with 1 kV/cm and 1Hz with a handheld electrode, in local or general anaesthesia. Clinical response was evaluated after 1, 2, 3, 4, 5, 6, and 12 months. Primary endpoint was response at two months. The overall response rate (ORR) was partial- and complete responses of treated tumours. MR-imaging and qualitative interviews were performed in respective subsets.

RESULTS

Nineteen patients with disseminated cancer (breast n = 4, lung n = 5, pancreatic n = 1, colorectal n = 2, gastric n = 1, and endometrial cancer n = 1) were enrolled, and 58 metastases were treated (50 once, 8 retreated). The ORR was 36% (95% CI 22-53) after two months. Best ORR was 51% (CR 42%; PR 9%). Previous irradiation improved outcomes (p = 0.0004). Adverse events were minimal. Median pain score was reduced after two months (p = 0.017). Treatment may relieve symptoms according to qualitative interviews. MRI showed restriction in treated tissue.

CONCLUSION

The majority of tumours were treated only once with calcium electroporation, achieving an ORR of 36% after two months and best ORR of 51%. Efficacy, symptom-relief and safety support calcium electroporation as a palliative treatment option for cutaneous metastases.

Classification of brain lesions using a machine learning approach with cross-sectional ADC value dynamics

Diffusion-weighted imaging (DWI) and its numerical expression via apparent diffusion coefficient (ADC) values are commonly utilized in non-invasive assessment of various brain pathologies. Although numerous studies have confirmed that ADC values could be pathognomic for various ring-enhancing lesions (RELs), their true potential is yet to be exploited in full. The article was designed to introduce an image analysis method allowing REL recognition independently of either absolute ADC values or specifically defined regions of interest within the evaluated image. For this purpose, the line of interest (LOI) was marked on each ADC map to cross all of the RELs' compartments. Using a machine learning approach, we analyzed the LOI between two representatives of the RELs, namely, brain abscess and glioblastoma (GBM). The diagnostic ability of the selected parameters as predictors for the machine learning algorithms was assessed using two models, the k-NN model and the SVM model with a Gaussian kernel. With the k-NN machine learning method, 80% of the abscesses and 100% of the GBM were classified correctly at high accuracy. Similar results were obtained via the SVM method. The proposed assessment of the LOI offers a new approach for evaluating ADC maps obtained from different RELs and contributing to the standardization of the ADC map assessment.

Finding an effective MRI sequence to visualise the electroporated area in plant-based models by quantitative mapping

Plant-based models can reduce the number of animal studies for electroporation research in medical cancer treatment modalities like irreversible electroporation. Magnetic resonance imaging (MRI) provides volumetric visualisation of electroporated animal or plant tissues; however, contrast behaviour is complex, depending on tissue and sequence parameters. This study numerically analysed contrast between electroporated and non-electroporated tissue at 1.5 T in various MRI sequences (DWI, T1W, T2W, T2*W, PDW, FLAIR) performed 4 h after electroporation in apples (N = 4) and potatoes (N = 8). Sequence parameters (inversion time [TI], echo time [TE], b-value) for optimal contrast and electroporation-mediated changes in T1 and T2 relaxation times and apparent diffusion coefficient (ADC) were determined for potato (N = 4) using quantitative parameter mapping. FLAIR showed the electroporated zone in potatoes with best contrast, whereas no sequence yielded clear visibility in apples. After electroporation, T1 and T2 in potato decreased by 29% ([1245 ± 54 to 886 ± 119] ms) and 12% ([249 ± 17 to 217 ± 12] ms), respectively. ADC increased by 11% ([1303 ± 25 to 1449 ± 28] × 10-6 mm²/s). Optimal contrast was found for TI = 1000 ms, low TE and high b-value. T1 was most sensitive to EP-mediated tissue changes. Future research could use this methodology and findings to obtain high-contrast MR images of electroporated and non-electroporated biological tissues.

Optimized flip angle schemes for the split acquisition of fast spin-echo signals (SPLICE) sequence and application to diffusion-weighted imaging

PURPOSE

The diffusion-weighted SPLICE (split acquisition of fast spin-echo signals) sequence employs split-echo rapid acquisition with relaxation enhancement (RARE) readout to provide images almost free of geometric distortions. However, due to the varying T 2 $$ {}_2 $$ -weighting during k-space traversal, SPLICE suffers from blurring. This work extends a method for controlling the spatial point spread function (PSF) while optimizing the signal-to-noise ratio (SNR) achieved by adjusting the flip angles in the refocusing pulse train of SPLICE.

METHODS

An algorithm based on extended phase graph (EPG) simulations optimizes the flip angles by maximizing SNR for a flexibly chosen predefined target PSF that describes the desired k-space density weighting and spatial resolution. An optimized flip angle scheme and a corresponding post-processing correction filter which together achieve the target PSF was tested by healthy subject brain imaging using a clinical 1.5 T scanner.

RESULTS

Brain images showed a clear and consistent improvement over those obtained with a standard constant flip angle scheme. SNR was increased and apparent diffusion coefficient estimates were more accurate. For a modified Hann k-space weighting example, considerable benefits resulted from acquisition weighting by flip angle control.

CONCLUSION

The presented flexible method for optimizing SPLICE flip angle schemes offers improved MR image quality of geometrically accurate diffusion-weighted images that makes the sequence a strong candidate for radiotherapy planning or stereotactic surgery.

Neuroimaging Patterns of Intracranial Infections: Meningitis, Cerebritis, and Their Complications

Neuroimaging provides rapid, noninvasive visualization of central nervous system infections for optimal diagnosis and management. Generalizable and characteristic imaging patterns help radiologists distinguish different types of intracranial infections including meningitis and cerebritis from a variety of bacterial, viral, fungal, and/or parasitic causes. Here, we describe key radiologic patterns of meningeal enhancement and diffusion restriction through profiles of meningitis, cerebritis, abscess, and ventriculitis. We discuss various imaging modalities and recent diagnostic advances such as deep learning through a survey of intracranial pathogens and their radiographic findings. Moreover, we explore critical complications and differential diagnoses of intracranial infections.

The impact of preoperative MRI-based apparent diffusion coefficients on local recurrence and outcome in patients with cerebral metastases

BACKGROUND

Surgery of single cerebral metastases is standard but frequently fails to achieve local tumour control. Reliable predictors for local tumour progression and overall survival are unknown. MRI-based apparent diffusion coefficients (ADC) correlate with tumour cellularity and invasion. The present study analysed a potential relation between the MRI based apparent diffusion coefficients local recurrence and outcome in patients with brain metastases.

METHODS

A retrospective analysis was performed for patients with cerebral metastases and complete surgical resection evaluated by an early postoperative MRI < 72h. Minimal ADC and mean ADC were assessed in preoperative 1,5T-MRI scans by placing regions of interests in the tumour and the peritumoural tissue.

RESULTS

Analysis of the relation between ADC values, local progression and outcome was performed in 86 patients with a mean age of 59 years (range 33-83 years). Primary site was NSCLC in 37.2% of all cases. Despite complete resection 33.7% of all patients suffered from local in-brain-progression. There were no significant differences in ADC values in groups based on histology. In the present cohort, the mean ADCmin and the mean ADCmean within the metastasis did not differ significantly between patients with and without a later local in-brain progression (634 × 10^-6 vs. 661 × 10^-6 mm²/s and 1324 × 10^-6 vs. 1361 × 10^-6 mm²/s; 1100 × 10^-6 vs. 1054 × 10^-6 mm²/s; each p > 0.05). Mean ADC values did not correlate significantly with PFS and OAS.

CONCLUSION

In the present study analysed ADC values had no significant impact on local in brain progression and survival parameters.

MRI-Derived Apparent Diffusion Coefficient of Peri-Prostatic Adipose Tissue Is a Potential Determinant of Prostate Cancer Aggressiveness in Preoperative Setting: A Preliminary Report

Background: The aim of this study was to test the association between periprostatic adipose tissue (PPAT)—apparent diffusion coefficient (ADC) value recorded at multiparametric magnetic resonance imaging (mpMRI) and determinants of prostate cancer (PCa) aggressiveness in the preoperative setting. Methods: Data from 219 consecutive patients undergoing prostate biopsy (PBx) for suspicion of PCa, between January 2020 and June 2022, at our institution were retrospectively evaluated. Only patients who had mpMRI performed before PBx were included. The distribution of demographics and clinical features among PPAT-ADC values up to vs. above the median was studied using both parametric and non-parametric tests, according to variables. Linear and logistic regression models tested the association between PPAT-ADC values and determinants of PCa aggressiveness and the presence of intermediate-high risk PCa, respectively. Results: Of 132 included patients, 76 (58%) had PCa. Median PPAT-ADC was 876 (interquartile range: 654 − 1112) × 10−6 mm2/s. Patients with PPAT-ADC up to the median had a higher rate of PIRADS (Prostate Imaging—Reporting and Data System) 5 lesions (41% vs. 23%, p = 0.032), a higher percentage of PBx positive cores (25% vs. 6%, p = 0.049) and more frequently harbored ISUP (International Society of Urological Pathology) > 1 PCa (50% vs. 28%, p = 0.048). At univariable linear regression analyses, prostate-specific antigen (PSA), PSA density, PIRADS 5, and percentage of PBx positive cores were associated with lower PPAT-ADC values. PPAT-ADC up to the median was an independent predictor for intermediate-high risk PCa (odds ratio: 3.24, 95%CI: 1.17−9.46, p = 0.026) after adjustment for age and body mass index. Conclusions: Lower PPAT-ADC values may be associated with higher biopsy ISUP grade group PCa and a higher percentage of PBx-positive cores. Higher-level studies are needed to confirm these preliminary results.

Radiomic study on preoperative multi-modal magnetic resonance images identifies IDH-mutant TERT promoter-mutant gliomas

OBJECTIVES

Gliomas with comutations of isocitrate dehydrogenase (IDH) genes and telomerase reverse transcriptase (TERT) gene promoter (IDHmut pTERTmut) show distinct biological features and respond to first-line treatment differently in comparison with other gliomas. This study aimed to characterize the IDHmut pTERTmut gliomas in multimodal MRI using the radiomic method and establish a precise diagnostic model identifying this group of gliomas.

METHODS

A total of 140 patients with untreated primary gliomas were admitted between 2016 and 2020 to West China Hospital as a discovery cohort, including 22 IDHmut pTERTmut patients. Thirty-four additional cases from a different hospital were included in the study as an independent validation cohort. A total of 3654 radiomic features were extracted from the preoperative multimodal MRI images (T1c, FLAIR, and ADC maps) and filtered in a data-driven approach. The discovery cohort was split into training and test sets by a 4:1 ratio. A diagnostic model (multilayer perceptron classifier) for detecting the IDHmut pTERTmut gliomas was trained using an automatic machine-learning algorithm named tree-based pipeline optimization tool (TPOT). The most critical radiomic features in the model were identified and visualized.

RESULTS

The model achieved an area under the receiver-operating curve (AUROC) of 0.971 (95% CI, 0.902-1.000), the sensitivity of 0.833 (95% CI, 0.333-1.000), and the specificity of 0.966 (95% CI, 0.931-1.000) in the test set. The area under the precision-recall curve (AUCPR) was 0.754 (95% CI, 0.572-0.833) and the F1 score was 0.833 (95% CI, 0.500-1.000). In the independent validation set, the model reached 0.952 AUROC, 0.714 sensitivity, 0.963 specificity, 0.841 AUCPR, and 0.769 F1 score. MR radiomic features of the IDHmut pTERTmut gliomas represented homogenous low-complexity texture in three modalities.

CONCLUSIONS

An accurate diagnostic model was constructed for detecting IDHmut pTERTmut gliomas using multimodal radiomic features. The most important features were associated with the homogenous simple texture of IDHmut pTERTmut gliomas in MRI images transformed using Laplacian of Gaussian and wavelet filters.

The Role of Apparent Diffusion Coefficient Values in Glioblastoma: Differentiating Tumor Progression Versus Treatment-Related Changes

OBJECTIVE

Glioblastoma represents the most common primary brain malignancy with a median survival of 15 months. Follow-up examinations are crucial to establish the presence of tumor recurrence, as well as treatment-associated changes such as ischemic infarction and radiation effects. Even though magnetic resonance imaging is a valuable tool, a histopathological diagnosis is often required because of imaging overlap between tumor recurrence and treatment associated changes. We set out to measure the apparent diffusion coefficient (ADC) values of the lesions in magnetic resonance imaging scans of treated glioblastoma patients to investigate if ADC values could accurately differentiate between tumor progression, radiation-related changes, and ischemic infarctions.

METHODS

We evaluated ADC values among 3 groups, patients with tumor progression, radiation necrosis, and ischemic infarctions. The regions of interest were placed in the areas of greatest hypointensity among solid lesions using the ADC maps, excluding areas with necrotic, cystic, or hemorrhagic changes. The ADC values of the contralateral normal appearing white matter were also measured as the reference value for each patient. The relative ADC (rADC) values were measured for all 3 groups. Comparison between lesions and normal white matter was evaluated by Wilcoxon signed test.

RESULTS

A total of 157 patients were included in the study; 49 patients classified as tumor progression, 58 patients as radiation necrosis, and 50 patients as ischemic infarctions. The mean ± SD ADC value was 752.8 ± 132.5 for tumor progression, 479.0 ± 105.2 for radiation-related changes, and 250.1 ± 57.2 for ischemic infarctions. The mean ± SD rADC value was 1.07 ± 0.22 for tumor progression, 0.66 ± 0.14 for radiation necrosis, and 0.34 ± 0.08 for ischemic infarctions. The mean rADC values were significantly higher in tumor progression, compared with both radiation necrosis and ischemic changes (P < 0.001).

CONCLUSIONS

The present study demonstrates that ADC values are a helpful tool to differentiate between tumor progression, radiation necrosis, and posttreatment ischemic changes.

Feature extraction from MRI ADC images for brain tumor classification using machine learning techniques

Background

Diffusion-weighted (DW) imaging is a well-recognized magnetic resonance imaging (MRI) technique that is being routinely used in brain examinations in modern clinical radiology practices. This study focuses on extracting demographic and texture features from MRI Apparent Diffusion Coefficient (ADC) images of human brain tumors, identifying the distribution patterns of each feature and applying Machine Learning (ML) techniques to differentiate malignant from benign brain tumors.

Methods

This prospective study was carried out using 1599 labeled MRI brain ADC image slices, 995 malignant, 604 benign from 195 patients who were radiologically diagnosed and histopathologically confirmed as brain tumor patients. The demographics, mean pixel values, skewness, kurtosis, features of Grey Level Co-occurrence Matrix (GLCM), mean, variance, energy, entropy, contrast, homogeneity, correlation, prominence and shade, were extracted from MRI ADC images of each patient. At the feature selection phase, the validity of the extracted features were measured using ANOVA f-test. Then, these features were used as input to several Machine Learning classification algorithms and the respective models were assessed.

Results

According to the results of ANOVA f-test feature selection process, two attributes: skewness (3.34) and GLCM homogeneity (3.45) scored the lowest ANOVA f-test scores. Therefore, both features were excluded in continuation of the experiment. From the different tested ML algorithms, the Random Forest classifier was chosen to build the final ML model, since it presented the highest accuracy. The final model was able to predict malignant and benign neoplasms with an 90.41% accuracy after the hyper parameter tuning process.

Conclusions

This study concludes that the above mentioned features (except skewness and GLCM homogeneity) are informative to identify and differentiate malignant from benign brain tumors. Moreover, they enable the development of a high-performance ML model that has the ability to assist in the decision-making steps of brain tumor diagnosis process, prior to attempting invasive diagnostic procedures, such as brain biopsies.

Developmental pattern of association fibers and their interaction with associated cortical microstructures in 0-5-month-old infants

Association fibers connect the cortical regions and experience rapid development involving myelination and axonal growth during infancy. Yet, the spatiotemporal patterns of microstructural changes along these tracts, as well as the developmental interaction between the white matter (WM) tracts and the cortical gray matter (cGM) connected to them, are mostly unknown during infancy. In this study, we performed a diffusion MRI-based tractography and microstructure study in a cohort of 89 healthy preterm-born infants with gestational age at birth between 28.1∼36.4 weeks and postmenstrual age at scan between 39.9∼59.9 weeks. Results revealed that several C-shaped fibers, such as the arcuate fasciculus, cingulum, and uncinate fasciculus, demonstrated symmetrical along-tract profiles; and the horizontally oriented running fibers, including the inferior fronto-occipital fasciculus and the inferior longitudinal fasciculus, demonstrated an anterior-posterior developmental gradient. This study characterized the along-tract profiles using fixel-based analysis and revealed that the fiber cross-section (FC) of all five association fibers demonstrated a fluctuating increase with age, while the fiber density (FD) monotonically increase with age. NODDI was utilized to analyze the microstructural development of cGM and indicated cGM connected to the anterior end of the association fibers developed faster than that of the posterior end during 0-5 months. Notably, a mediation analysis was used to explore the relation between the development of WM and associated cGM, and demonstrated a partial mediation effect of FD in WM on the development of intracellular volume (ICV) in cGM and a full mediation effect of ICV on the growth of FD in most fibers, suggesting a predominant mediation of cGM on the WM development. Furthermore, for assessing whether those results were biased by prematurity, we compared preterm- and term-born neonates with matched scan age, gender, and multiple births from the developing human connectome project (dHCP) dataset to assess the effect of preterm-birth, and the results indicated a similar developmental pattern of the association fibers and their attached cGM. These findings presented a comprehensive picture of the major association fibers during early infancy and deciphered the developmental interaction between WM and cGM in this period.

Glioblastoma Stem-like Cell Detection Using Perfusion and Diffusion MRI

Simple Summary

Glioblastoma stem-like cells (GSCs) are known to be aggressive and radio-resistant and proliferate heterogeneously in preferred environments. Additionally, quantitative diffusion and perfusion MRI biomarkers provide insight into the tissue micro-environment. This study assessed the sensitivity of these imaging biomarkers to GSCs in the hyperintensities-FLAIR region, where relapses may occur. A total of 16 patients underwent an MRI session and biopsies were extracted to study the GSCs. In vivo and in vitro biomarkers were compared and both Apparent Diffusion Coefficient (ADC) and relative Cerebral Blood Volume (rCBV) MRI metrics were found to be good predictors of GSCs presence and aggressiveness.

Abstract

Purpose: With current gold standard treatment, which associates maximum safe surgery and chemo-radiation, the large majority of glioblastoma patients relapse within a year in the peritumoral non contrast-enhanced region (NCE). A subpopulation of glioblastoma stem-like cells (GSC) are known to be particularly radio-resistant and aggressive, and are thus suspected to be the cause of these relapses. Previous studies have shown that their distribution is heterogeneous in the NCE compartment, but no study exists on the sensitivity of medical imaging for localizing these cells. In this work, we propose to study the magnetic resonance (MR) signature of these infiltrative cells. Methods: In the context of a clinical trial on 16 glioblastoma patients, relative Cerebral Blood Volume (rCBV) and Apparent Diffusion Coefficient (ADC) were measured in a preoperative diffusion and perfusion MRI examination. During surgery, two biopsies were extracted using image-guidance in the hyperintensities-FLAIR region. GSC subpopulation was quantified within the biopsies and then cultivated in selective conditions to determine their density and aggressiveness. Results: Low ADC was found to be a good predictor of the time to GSC neurospheres formation in vitro. In addition, GSCs were found in higher concentrations in areas with high rCBV. Conclusions: This study confirms that GSCs have a critical role for glioblastoma aggressiveness and supports the idea that peritumoral sites with low ADC or high rCBV should be preferably removed when possible during surgery and targeted by radiotherapy.

Does diffusion weighted imaging have a prognostic value in differentiating gynecological diseases?

INTRODUCTION

Apparent diffusion coefficient (ADC) values are effective in the diagnosis of different gynecological lesions.

METHODS

A retrospective evaluation was made of 12 patients with uterine cervix carcinoma and 151 patients with uterine lesions, comprising endometrial cancer, endometrial polyps, carcinosarcoma, submucous myoma, adenomyosis, endometrial hyperplasia, gestational trophoblastic neoplasm (GTN), and leiomyomas. As a control group, 20 healthy volunteers with normal endometrium and normal cervix were also evaluated. In three series, one-shot, spin echo, echo planar, b = 1000 s/mm² value and diffusion-weighted imaging (DWI) were applied to all subjects and ADC values were obtained.

RESULTS

The mean ADC values of Group 1 (Endometrial carcinoma) were lower than those of all the other groups (P < 0.001) and the mean ADC value of group 6 (GTN) was higher than that all other groups (P < 0.001). A statistically significant difference was found between the groups in terms of the lesion-myometrium ADC ratios (P < 0.001).

CONCLUSION

There are few studies in literature related to ADC measurements in GTN. The ADC values of GTN were found to be significantly higher than the other uterine lesions. These results will aid in the design of future studies and might be used to guide management of patients with GTN.

IMPLICATIONS FOR PRACTICE

Diffusion-weighted MRI seems to be a promising imaging technique in differentiating different uterine lesions.

Breath-Hold Diving-Related Decompression Sickness with Brain Involvement: From Neuroimaging to Pathophysiology

Central nervous system involvement related to decompression sickness (DCS) is a very rare complication of breath-hold diving. So far, it has been postulated that repeated dives with short surface intervals represent a key factor in the development of breath-holding-related DCS. We report the case of a breath-hold diver who, after repeated immersion, developed DCS with brain involvement. After treatment in a hyperbaric chamber, there was a clinical improvement in the symptoms. Magnetic resonance imaging of the brain showed hyperintense lesions in long-time repetition sequences (FLAIR, T2WI) in the left frontal and right temporal lobes. Diffusion-weighted imaging (DWI) sequences and the apparent diffusion coefficient (ADC) map were characteristic of vasogenic edema, allowing us to exclude the ischemic nature of the process. These findings, together with the acute clinical presentation, the resolution of lesions in evolutionary radiological controls and the possible involvement of blood–brain barrier/endothelial dysfunction in DCS, could suggest a new form of posterior reversible encephalopathy syndrome (PRES)-like presentation of DCS. This would represent a novel mechanism to explain the pathophysiology of this entity. We conducted a literature review, analyzing the pathophysiological and neuroimaging characteristics of DCS in breath-hold diving based on a case of this rare disease.

DTI Abnormalities Related to Glioblastoma: A Prospective Comparative Study with Metastasis and Healthy Subjects

(1) Background: Glioblastoma multiforme (GBM) shows complex mechanisms of spreading of the tumor cells, up to remote areas, and little is still known of these mechanisms, thus we focused on MRI abnormalities observable in the tumor and the brain adjacent to the lesion, up to the contralateral hemisphere, with a special interest on tensor diffusion imaging informing on white matter architecture; (2) Material and Methods: volumes, macroscopic volume (MV), brain-adjacent-tumor (BAT) volume and abnormal color-coded DTI volume (aCCV), and region-of-interest samples (probe volumes, ipsi, and contra lateral to the lesion), with their MRI characteristics, apparent diffusion coefficient (ADC), fractional anisotropy (FA) values, and number of fibers (DTI fiber tracking) were analyzed in patients suffering GBM (n = 15) and metastasis (n = 9), and healthy subjects (n = 15), using ad hoc statistical methods (type I error = 5%) (3) Results: GBM volumes were larger than metastasis volumes, aCCV being larger in GBM and BAT ADC was higher in metastasis, ADC decreased centripetally in metastasis, FA increased centripetally either in GBM or metastasis, MV and BAT FA values were higher in GBM, ipsi FA values of GBM ROIs were higher than those of metastasis, and the GBM ipsi number of fibers was higher than the GBM contra number of fibers; (4) Conclusions: The MV, BAT and especially the aCCV, as well as their related water diffusion characteristics, could be useful biomarkers in oncology and functional oncology.

Correlation of Hemispatial Neglect with White Matter Tract Integrity: A DTI Study

We investigated the diffusion tensor image (DTI) parameters of superior longitudinal fasciculus (SLF) and inferior fronto-occipital fasciculus (IFOF), and their relationships with hemispatial neglect. Thirteen patients with first-ever ischemic stroke who had the right hemispheric lesion were included. Neglect was assessed using the Albert test and figure discrimination test of Motor-free Visual Perception Test 3 (MVPT-3). The SLF and IFOF were separated by diffusion tensor tractography (DTT) and tract volume (TV) was calculated. We measured the fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values in the total area, seed region of interest (ROI), and target ROI, respectively. Among thirteen patients, seven demonstrated signs of hemispatial neglect on neglect test. Tractography reconstruction showed significantly low TV of the right IFOF in patients with hemispatial neglect. FA values of the right SLF and the right IFOF were significantly lower in neglect patients. ADC values were not significantly different in two groups. This study suggests that damage of SLF and IFOF is associated with hemispatial neglect in right hemispheric stroke patients. DTI may be useful for predicting the severities of hemispatial neglect using values such as TV and FA of each tract.

Magnetic Resonance Spectroscopy of Hypoxic-Ischemic Encephalopathy After Cardiac Arrest

BACKGROUND AND OBJECTIVES

To correlate brain metabolites with clinical outcome using magnetic resonance spectroscopy (MRS) in patients undergoing targeted temperature management (TTM) after cardiac arrest and assess their relationships to MRI and EEG variables.

METHODS

A prospective cohort of 50 patients was studied. The primary outcome was coma recovery to follow commands. Comparison of MRS measures in the posterior cingulate gyrus, parietal white matter, basal ganglia, and brainstem were also made to 25 normative controls.

RESULTS

Fourteen of 50 patients achieved coma recovery before hospital discharge. There was a significant decrease in total N-acetylaspartate (NAA/Cr) and an increase in lactate/creatine (Lac/Cr) in patients who did not recover, with changes most prominent in the posterior cingulate gyrus. Patients who recovered had decrease in NAA/Cr as compared to controls. NAA/Cr had a strong monotonic relationship with MRI cortical apparent diffusion coefficient (ADC); Lac level exponentially increased with decreasing ADC. EEG suppression/burst suppression was strongly associated with Lac elevation.

DISCUSSION

NAA and Lac changes are associated with clinical/MRI/EEG changes consistent with hypoxic-ischemic encephalopathy (HIE) and are most prominent in the posterior cingulate gyrus. NAA/Cr decrease observed in patients with good outcomes suggests mild HIE in patients asymptomatic at hospital discharge. The appearance of cortical Lac represents a deterioration of aerobic energy metabolism and is associated with EEG background suppression, synaptic transmission failure, and severe, potentially irreversible HIE.

CLASSIFICATION OF EVIDENCE

This study provides Class IV evidence that in patients undergoing TTM after cardiac arrest, brain MRS-determined decrease in total NAA/Cr and an increase in Lac/Cr are associated with an increased risk of not recovering.

Magnetic Resonance Imaging in (Near-)Term Infants with Hypoxic-Ischemic Encephalopathy

Hypoxic-ischemic encephalopathy (HIE) is a major cause of neurological sequelae in (near-)term newborns. Despite the use of therapeutic hypothermia, a significant number of newborns still experience impaired neurodevelopment. Neuroimaging is the standard of care in infants with HIE to determine the timing and nature of the injury, guide further treatment decisions, and predict neurodevelopmental outcomes. Cranial ultrasonography is a helpful noninvasive tool to assess the brain before initiation of hypothermia to look for abnormalities suggestive of HIE mimics or antenatal onset of injury. Magnetic resonance imaging (MRI) which includes diffusion-weighted imaging has, however, become the gold standard to assess brain injury in infants with HIE, and has an excellent prognostic utility. Magnetic resonance spectroscopy provides complementary metabolic information and has also been shown to be a reliable prognostic biomarker. Advanced imaging modalities, including diffusion tensor imaging and arterial spin labeling, are increasingly being used to gain further information about the etiology and prognosis of brain injury. Over the past decades, tremendous progress has been made in the field of neonatal neuroimaging. In this review, the main brain injury patterns of infants with HIE, the application of conventional and advanced MRI techniques in these newborns, and HIE mimics, will be described.

Advanced magnetic resonance imaging findings of cerebellar hemangioblastomas: A report of three cases and a literature review

On conventional magnetic resonance imaging (MRI), hemangioblastomas typically appear as mural nodules with an adjacent surrounding cyst or a solid mass in the cerebellum. However, hemangioblastomas sometimes cannot be reliably distinguished using this imaging technique from other tumors, especially pilocytic astrocytomas and metastatic tumors, because of their similar imaging findings and locations. Herein, we report three cases of cerebellar hemangioblastomas and review their findings on conventional and advanced MRI, including diffusion-weighted imaging (DWI), dynamic susceptibility-weighted contrast-enhanced perfusion-weighted imaging (DSC-PWI), and magnetic resonance spectroscopy (MRS). Solid contrast-enhanced lesions of hemangioblastomas showed increased apparent diffusion coefficient values on DWI, increased relative cerebral blood volume ratio on DSC-PWI, and high lipid/lactate peak on MRS. Therefore, advanced MRI techniques can be helpful in understanding the pathological and metabolic changes of hemangioblastomas and may be useful for their characterization.

Three-dimensional reduced field-of-view imaging (3D-rFOVI)

PURPOSE

This study aimed at developing a 3D reduced field-of-view imaging (3D-rFOVI) technique using a 2D radiofrequency (RF) pulse, and demonstrating its ability to achieve isotropic high spatial resolution and reduced image distortion in echo planar imaging (EPI).

METHODS

The proposed 3D-rFOVI technique takes advantage of a 2D RF pulse to excite a slab along the conventional slice-selection direction (i.e., z-direction) while limiting the spatial extent along the phase-encoded direction (i.e., y-direction) within the slab. The slab is phase-encoded in both through-slab and in-slab phase-encoded directions. The 3D-rFOVI technique was implemented at 3T in gradient-echo and spin-echo EPI pulse sequences for functional MRI (fMRI) and diffusion-weighted imaging (DWI), respectively. 3D-rFOVI experiments were performed on a phantom and human brain to illustrate image distortion reduction, as well as isotropic high spatial resolution, in comparison with 3D full-FOV imaging.

RESULTS

In both the phantom and the human brain, image voxel dislocation was substantially reduced by 3D-rFOVI when compared with full-FOV imaging. In the fMRI experiment with visual stimulation, 3D isotropic spatial resolution of (2 × 2 × 2 mm³ ) was achieved with an adequate signal-to-noise ratio (81.5) and blood oxygen level-dependent (BOLD) contrast (2.5%). In the DWI experiment, diffusion-weighted brain images with an isotropic resolution of (1 × 1 × 1 mm³ ) was obtained without appreciable image distortion.

CONCLUSION

This study indicates that 3D-rFOVI is a viable approach to 3D neuroimaging over a zoomed region.

Applications of artificial intelligence for DWI and PWI data processing in acute ischemic stroke: Current practices and future directions

Multimodal Magnetic Resonance Imaging (MRI) techniques of Perfusion-Weighted Imaging (PWI) and Diffusion-Weighted Imaging (DWI) data are integral parts of the diagnostic workup in the acute stroke setting. The visual interpretation of PWI/DWI data is the most likely procedure to triage Acute Ischemic Stroke (AIS) patients who will access reperfusion therapy, especially in those exceeding 6 h of stroke onset. In fact, this process defines two classes of tissue: the ischemic core, which is presumed to be irreversibly damaged, visualized on DWI data and the penumbra which is the reversibly injured brain tissue around the ischemic tissue, visualized on PWI data. AIS patients with a large ischemic penumbra and limited infarction core have a high probability of benefiting from endovascular treatment. However, it is a tedious and time-consuming procedure. Consequently, it is subject to high inter- and intra-observer variability. Thus, the assessment of the potential risks and benefits of endovascular treatment is uncertain. Fast, accurate and automatic post-processing of PWI and DWI data is important for clinical diagnosis and is necessary to help the decision making for therapy. Therefore, an automated procedure that identifies stroke slices, stroke hemisphere, segments stroke regions in DWI, and measures hypoperfused tissue in PWI enhances considerably the reproducibility and the accuracy of stroke assessment. In this work, we draw an overview of several applications of Artificial Intelligence (AI) for the automation processing and their potential contributions in clinical practices. We compare the current approaches among each other's with respect to some key requirements.

Clinical applications of diffusion-weighted sequence in brain imaging: beyond stroke

Diffusion-weighted imaging (DWI) is a well-established MRI sequence for diagnosing early stroke and provides therapeutic implications. However, DWI yields pertinent information in various other brain pathologies and helps establish a specific diagnosis and management of other central nervous system disorders. Some of these conditions can present with acute changes in neurological status and mimic stroke. This review will focus briefly on diffusion imaging techniques, followed by a more comprehensive description of the utility of DWI in common neurological entities beyond stroke.

Apparent diffusion coefficient is associated with seizure outcome after magnetic resonance-guided laser interstitial thermal therapy for mesial temporal lobe epilepsy

BACKGROUND

Magnetic resonance-guided laser interstitial thermal therapy (MRgLiTT) is becoming a first-line surgical therapy for mesial temporal lobe epilepsy (mTLE) due to good seizure control and low complication risk. However, seizure outcomes after MRgLiTT remain highly variable and there is a need to improve patient selection and post-operative prognostication. In this retrospective study, we investigated whether the pre-operative MRI-derived apparent diffusion coefficient (ADC), used as a marker of tissue pathology in the mesial temporal structures could help predict seizure outcome.

METHODS

Thirty-five patients who underwent MRgLiTT at our institution between 2014 and 2019 were included in the study. Demographic and clinical data were retrospectively collected. Seizure outcome was defined as good (ILAE Class I-II) and poor (ILAE Class III-VI). Volumetrics were performed on pre-ablation hippocampus and amygdala. Ablation volumes, and the proportion of ablated hippocampus and amygdala calculated via their respective mean voxel-wise ADC intensities were quantified from pre-operative and intra-operative post-ablation MRIs and statistically compared between the two outcome cohorts. Univarate and multivariate regression analysis was performed to identify demographic, clinical, and radiographic predictors of seizure outcome.

RESULTS

Mean age at LiTT was 36 years and 14 (40 %) were female. Mean follow-up duration was 1.90 ± 0.17 years. Twenty-seven (77 %) patients had mesial temporal sclerosis. There was no significant difference in the ablation volumes and proportion of ablated volume of hippocampus and amygdala between the two outcome groups. Patients with good seizure outcome had significantly higher normalized ADC intensities in the ablated mesial temporal structures compared to those with poor outcome (0.01 ± 0.08 vs.-0.29 ± 0.06; p = 0.015).

CONCLUSIONS

mTLE patients with higher ADC intensities in the ablated regions of the hippocampus and the amygdala are more likely to have good seizure outcome following MRgLiTT. Our results suggest that pre-operative ADC analysis may improve both patient selection and epileptogenic zone targeting during MRgLiTT. Further investigation with large, prospective cohorts is needed to validate the clinical utility of ADC in improving seizure outcome following MRgLiTT.

A Methodology to Compare Biomechanical Simulations With Clinical Brain Imaging Analysis Utilizing Two Blunt Impact Cases

According to the US Defense and Veterans Brain Injury Center (DVBIC) and Centers for Disease Control and Prevention (CDC), mild traumatic brain injury (mTBI) is a common form of head injury. Medical imaging data provides clinical insight into tissue damage/injury and injury severity, and helps medical diagnosis. Computational modeling and simulation can predict the biomechanical characteristics of such injury, and are useful for development of protective equipment. Integration of techniques from computational biomechanics with medical data assessment modalities (e.g., magnetic resonance imaging or MRI) has not yet been used to predict injury, support early medical diagnosis, or assess effectiveness of personal protective equipment. This paper presents a methodology to map computational simulations with clinical data for interpreting blunt impact TBI utilizing two clinically different head injury case studies. MRI modalities, such as T1, T2, diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC), were used for simulation comparisons. The two clinical cases have been reconstructed using finite element analysis to predict head biomechanics based on medical reports documented by a clinician. The findings are mapped to simulation results using image-based clinical analyses of head impact injuries, and modalities that could capture simulation results have been identified. In case 1, the MRI results showed lesions in the brain with skull indentation, while case 2 had lesions in both coup and contrecoup sides with no skull deformation. Simulation data analyses show that different biomechanical measures and thresholds are needed to explain different blunt impact injury modalities; specifically, strain rate threshold corresponds well with brain injury with skull indentation, while minimum pressure threshold corresponds well with coup–contrecoup injury; and DWI has been found to be the most appropriate modality for MRI data interpretation. As the findings from these two cases are substantiated with additional clinical studies, this methodology can be broadly applied as a tool to support injury assessment in head trauma events and to improve countermeasures (e.g., diagnostics and protective equipment design) to mitigate these injuries.

Study protocol designed to investigate tumour response to calcium electroporation in cancers affecting the skin: a non-randomised phase II clinical trial

INTRODUCTION

Skin malignancy is a distressing problem for many patients, and clinical management is challenging. This article describes the protocol for the Calcium Electroporation Response Study (CaEP-R) designed to investigate tumour response to calcium electroporation and is a descriptive guide to calcium electroporation treatment of malignant tumours in the skin. Calcium electroporation is a local treatment that induces supraphysiological intracellular calcium levels by intratumoural calcium administration and application of electrical pulses. The pulses create transient membrane pores allowing diffusion of non-permeant calcium ions into target cells. High calcium levels can kill cancer cells, while normal cells can restore homeostasis. Prior trials with smaller cohorts have found calcium electroporation to be safe and efficient. This trial aims to include a larger multiregional cohort of patients with different cancer diagnoses and also to investigate treatment areas using MRI as well as assess impact on quality of life.

METHODS AND ANALYSIS

This non-randomised phase II multicentre study will investigate response to calcium electroporation in 30 patients with cutaneous or subcutaneous malignancy. Enrolment of 10 patients is planned at three centres: Zealand University Hospital, University Hospital of Southern Denmark and University Hospital Schleswig-Holstein. Response after 2 months was chosen as the primary endpoint based on short-term response rates observed in a prior clinical study. Secondary endpoints include response to treatment using MRI and change in quality of life assessed by questionnaires and qualitative interviews.

ETHICS AND DISSEMINATION

The trial is approved by the Danish Medicines Agency and The Danish Regional Committee on Health Research Ethics. All included patients will receive active treatment (calcium electroporation). Patients can continue systemic treatment during the study, and side effects are expected to be limited. Data will be published in a peer-reviewed journal and made available to the public.

TRIAL REGISTRATION NUMBERS

NCT04225767 and EudraCT no: 2019-004314-34.

Decoding the microstructural properties of white matter using realistic models

Multi-echo gradient echo (ME-GRE) magnetic resonance signal evolution in white matter has a strong dependence on the orientation of myelinated axons with respect to the main static field. Although analytical solutions have been able to predict some of the white matter (WM) signal behaviour of the hollow cylinder model, it has been shown that realistic models of WM offer a better description of the signal behaviour observed. In this work, we present a pipeline to (i) generate realistic 2D WM models with their microstructure based on real axon morphology with adjustable fiber volume fraction (FVF) and g-ratio. We (ii) simulate their interaction with the static magnetic field to be able to simulate their MR signal. For the first time, we (iii) demonstrate that realistic 2D WM models can be used to simulate a MR signal that provides a good approximation of the signal obtained from a real 3D WM model derived from electron microscopy. We then (iv) demonstrate in silico that 2D WM models can be used to predict microstructural parameters in a robust way if ME-GRE multi-orientation data is available and the main fiber orientation in each pixel is known using DTI. A deep learning network was trained and characterized in its ability to recover the desired microstructural parameters such as FVF, g-ratio, free and bound water transverse relaxation and magnetic susceptibility. Finally, the network was trained to recover these micro-structural parameters from an ex vivo dataset acquired in 9 orientations with respect to the magnetic field and 12 echo times. We demonstrate that this is an overdetermined problem and that as few as 3 orientations can already provide comparable results for some of the decoded metrics.

MRI in the evaluation of the azoospermic male

PURPOSE We aimed to show the usefulness of magnetic resonance imaging (MRI) in the evaluation of infertile men and its ability to distinguish obstructive from nonobstructive azoospermia. METHODS Between April 2015 and February 2018, 45 azoospermic men underwent scrotal MRI. We evaluated the images with an emphasis on signal characteristics of the testis and morphologic changes typical for obstruction. Testicular volume (TV), apparent diffusion coefficient (ADC) value, T1 and T2 signal ratios (testis/muscle) were measured for every testis. On the basis of histologic results, patients were divided into two groups: obstructive azoospermia (OA) and nonobstructive azoospermia (NOA). RESULTS Testes of patients in the OA group had significantly lower ADC values (mean 0.876±101 ×10-3 mm2/s) than in the NOA group (mean, 1.114±147 ×10-3 mm2/s). TV was significantly higher in patients with OA (median, 17.61 mL; range, 11.1-38.4 mL) than in those with NOA (median, 10.5 mL; range, 5.2-22.2 mL). ROC analysis showed that both TV and ADC values were highly predictive for distinguishing between OA and NOA patients, with an area under the ROC curve of 0.82 and 0.92 respectively. A cutoff value of ≥12.4 mL could distinguish obstructive from nonobstructive azoospermia with a sensitivity of 92% and specificity of 63%, whereas for ADC measurements a cutoff value of ≥0.952 ×10-3 mm2/s exhibited a sensitivity of 81% and specificity of 90% There was no statistically significant difference in T1 and T2 signal ratios between both groups. Abnormalities typical for obstruction of the male reproductive tract (e.g., dilatation of ejaculatory ducts, prostatic or seminal vesicle cysts) were found in 78% of patients (14/18) in the obstructive group. CONCLUSION Scrotal MRI is a very effective tool for the evaluation of azoospermic men and may provide important information facilitating interventional treatment of infertility.

Imperfect spoiling in variable flip angle T1 mapping at 7T: Quantifying and minimizing impact

Purpose

The variable flip angle (VFA) approach to T₁ mapping assumes perfectly spoiled transverse magnetisation at the end of each repetition time (TR). Despite radiofrequency (RF) and gradient spoiling, this condition is rarely met, leading to erroneous T₁ estimates (T1app). Theoretical corrections can be applied but make assumptions about tissue properties, for example, a global T₂ time. Here, we investigate the effect of imperfect spoiling at 7T and the interaction between the RF and gradient spoiling conditions, additionally accounting for diffusion. We provide guidance on the optimal approach to maximise the accuracy of the T₁ estimate in the context of 3D multi‐echo acquisitions.

Methods

The impact of the spoiling regime was investigated through numerical simulations, phantom and invivo experiments.

Results

The predicted dependence of T1app on tissue properties, system settings, and spoiling conditions was observed in both phantom and in vivo experiments. Diffusion effects modulated the dependence of T1app on both B1+ efficiency and T₂ times.

Conclusion

Error in T1app can be minimized by using an RF spoiling increment and gradient spoiler moment combination that minimizes T₂‐dependence and safeguards image quality. Although the diffusion effect was comparatively small at 7T, correction factors accounting for this effect are recommended.

Click here for author‐reader discussions

Brain injury in children with diabetic ketoacidosis: Review of the literature and a proposed pathophysiologic pathway for the development of cerebral edema

Cerebral edema (CE) is a potentially devastating complication of diabetic ketoacidosis (DKA) that almost exclusively occurs in children. Since its first description in 1936, numerous risk factors have been identified; however, there continues to be uncertainty concerning the mechanisms that lead to its development. Currently, the most widely accepted hypothesis posits that CE occurs as a result of ischemia-reperfusion injury, with inflammation and impaired cerebrovascular autoregulation contributing to its pathogenesis. The role of specific aspects of DKA treatment in the development of CE continues to be controversial. This review critically examines the literature on the pathophysiology of CE and attempts to categorize the findings by types of brain injury that contribute to its development: cytotoxic, vasogenic, and osmotic. Utilizing this scheme, we propose a multifactorial pathway for the development of CE in patients with DKA.

Measurement of Apparent Diffusion Coefficient (ADC) Values of Ependymoma and Medulloblastoma Tumors: a Patient-based Study

Background:

Some brain tumors such as ependymoma and Medulloblastoma have similar MR images which may result to undifferentiated them from each other.

Objective:

This study aimed to compare the apparent diffusion coefficient (ADC) of two different cerebellar pediatric tumors, including ependymoma and medulloblastoma which have shown similar clinical images in conventional magnetic resonance imaging (MRI) methods.

Material and Methods:

In this analytical study, thirty six pediatric patients who were suspected to have the mentioned tumors according to their CT image findings were included in this study. The patients were subjected to conventional MRI protocols followed by diffusion weighted imaging (DWI) and ADC values of the tumors were calculated automatically using MRI scanner software.

Results:

The mean (± SD) ADC value for ependymoma (1.2± 0.06 ×10^-3 mm²/s) was significantly higher than medulloblastoma (0.87 ± 0.02 ×10^-3 mm²/s) (p = 0.041). Moreover, the maximum ADC value of ependymoma was considerably different in comparison with medulloblastoma (1.4 ×10^-3 mm²/s and 0.96×10^-3 mm²/s, respectively; p = 0.035). Furthermore, the minimum ADC value of ependymoma was higher compared to medulloblastoma (1.0 ×10^-3 mm²/s and 0.61×10^-3 mm²/s, respectively), but there was not significant (p = 0.067).

Conclusion:

Evaluation of ADC values for ependymoma and medulloblastoma is a reliable method to differentiate these two malignancies. This is due to different ADC values reflected during the evaluation.

Neuroimaging Biomarkers and Neurocognitive Outcomes in Pediatric Medulloblastoma Patients: a Systematic Review

Medulloblastoma is a malign posterior fossa brain tumor, mostly occurring in childhood. The CNS-directed chemoradiotherapy treatment can be very harmful to the developing brain and functional outcomes of these patients. However, what the underlying neurotoxic mechanisms are remain inconclusive. Hence, this review summarizes the existing literature on the association between advanced neuroimaging and neurocognitive changes in patients that were treated for pediatric medulloblastoma. The PubMed/Medline database was extensively screened for studies investigating the link between cognitive outcomes and multimodal magnetic resonance (MR) imaging in childhood medulloblastoma survivors. A behavioral meta-analysis was performed on the available IQ scores. A total of 649 studies were screened, of which 22 studies were included. Based on this literature review, we conclude medulloblastoma patients to be at risk for white matter volume loss, more frequent white matter lesions, and changes in white matter microstructure. Such microstructural alterations were associated with lower IQ, which reached the clinical cut-off in survivors across studies. Using functional MR scans, changes in activity were observed in cerebellar areas, associated with working memory and processing speed. Finally, cerebral microbleeds were encountered more often, but these were not associated with cognitive outcomes. Regarding intervention studies, computerized cognitive training was associated with changes in prefrontal and cerebellar activation and physical training might result in microstructural and cortical alterations. Hence, to better define the neural targets for interventions in pediatric medulloblastoma patients, this review suggests working towards neuroimaging-based predictions of cognitive outcomes. To reach this goal, large multimodal prospective imaging studies are highly recommended.

Conventional and Advanced Magnetic Resonance Imaging Features of Supratentorial Extraventricular Ependymomas

OBJECTIVE

To describe the magnetic resonance imaging characteristics of supratentorial ependymomas.

METHODS

The magnetic resonance imaging and computed tomography imaging characteristics of 49 cases of supratentorial ependymomas were analyzed retrospectively. The location, size, degree of perilesional edema, gross appearance, computed tomography attenuation characteristics, T1 and T2 signal intensity characteristics, degree of diffusion restriction, presence of calcification, and hemorrhage were documented for each lesion. The intratumoral susceptibility scores (ITSS), apparent diffusion coefficient (ADC) values, relative cerebral blood volume, and choline/N-acetyl aspartate ratios were documented where available.

RESULTS

The frontal lobe was the most common location with a mean size of 6.37 × 4.8 cm. Severe perilesional edema was evident in 30%. Heterogenous, solid-cystic appearance was present in 96% lesions, with 95% of extraventricular lesions extending from pial surface to the ventricular margin. Calcification was seen in 55% of cases. The ITSS was 3 in 85.7% of lesions. The mean ADC value calculated was 600 × 10 mm/s. The mean relative cerebral blood volume on dynamic susceptibility contrast perfusion was 4.83. The mean choline/N-acetyl aspartate ratio was 5.87. Leptomeningeal dissemination was demonstrable in 5 lesions. Four lesions were abutting the dura with frank dural invasion in one. One patient presented with disseminated disease without evidence of a primary lesion.

CONCLUSIONS

A large lesion with relatively well-defined margins, heterogeneous solid cystic appearance, extending from the pial surface to the ventricular margin, presence of calcification, and ADC values approaching those of white matter should raise a suspicion of supratentorial ependymoma. High ITSS, MR perfusion parameters, and magnetic resonance spectroscopy characteristics are similar to those of other high-grade gliomas.

A Comparison of T2 Relaxation-Based MRI Stroke Timing Methods in Hyperacute Ischemic Stroke Patients: A Pilot Study

Background:

T₂ relaxation-based magnetic resonance imaging (MRI) signals may provide onset time for acute ischemic strokes with an unknown onset. The ability of visual and quantitative MRI-based methods in a cohort of hyperacute ischemic stroke patients was studied.

Methods:

A total of 35 patients underwent 3T (3 Tesla) MRI (<9-hour symptom onset). Diffusion-weighted (DWI), apparent diffusion coefficient (ADC), T₁-weighted (T₁w), T₂-weighted (T₂w), and T₂ relaxation time (T₂) images were acquired. T₂-weighted fluid attenuation inversion recovery (FLAIR) images were acquired for 17 of these patients. Image intensity ratios of the average intensities in ischemic and non-ischemic reference regions were calculated for ADC, DWI, T₂w, T₂ relaxation, and FLAIR images, and optimal image intensity ratio cut-offs were determined. DWI and FLAIR images were assessed visually for DWI/FLAIR mismatch.

Results:

The T₂ relaxation time image intensity ratio was the only parameter with significant correlation with stroke duration (r = 0.49, P = .003), an area under the receiver operating characteristic curve (AUC = 0.77, P < .0001), and an optimal cut-off (T₂ ratio = 1.072) that accurately identified patients within the 4.5-hour thrombolysis treatment window with sensitivity of 0.74 and specificity of 0.74. In the patients with the additional FLAIR, areas under the precision-recall-gain curve (AUPRG) and F₁ scores showed that the T₂ relaxation time ratio (AUPRG = 0.60, F₁ = 0.73) performed considerably better than the FLAIR ratio (AUPRG = 0.39, F₁ = 0.57) and the visual DWI/FLAIR mismatch (F₁ = 0.25).

Conclusions:

Quantitative T₂ relaxation time is the preferred MRI parameter in the assessment of patients with unknown onset for treatment stratification.

Can MRI features differentiate ovarian mucinous carcinoma from mucinous borderline tumor?

PURPOSE

Our purpose was to determine if MRI could be used to distinguish ovarian mucinous carcinoma (MC) from mucinous borderline tumor (MBT).

MATERIALS AND METHODS

This study included 63 consecutive patients with histopathologically proven ovarian mucinous neoplasms (11 MCs and 52 MBTs) who underwent preoperative contrast-enhanced MRI. MRI images were retrospectively reviewed and compared between the 2 pathologies.

RESULTS

The maximum tumor diameters (219.7 ± 80.8 mm vs. 177.4 ± 56.5 mm, p <  0.05) and maximum mural nodule (MN) diameters (41.7 ± 33.8 mm vs. 6.6 ± 8.9 mm, p <  0.01) were significantly larger in MCs than in MBTs. MNs larger than 5 mm (82 % vs. 29 %, p <  0.01) and abnormal ascites (45 % vs. 12 %, p <  0.05) were significantly more frequent in MCs than in MBTs. Apparent diffusion coefficient (ADC) values of MN were significantly lower in MCs than in MBTs (1.20 ± 0.25 × 10^-3 mm²/s vs. 1.61 ± 0.35 × 10^-3 mm²/s, p <  0.05). No significant difference was found in number of loculi, honeycomb sign, stained glass appearance, fluid-fluid level, thickened septa larger than 5 mm, peritoneal dissemination, or T2 hypointense microcysts between MCs and MBTs. T2 hypointense microcysts were observed only in 7 MBTs (13%).

CONCLUSION

MRI findings of these 2 pathologies overlapped considerably. Compared with MBTs, MCs exhibited larger tumor size, larger MN size, and lower ADC values of MN, and MCs more frequently had MNs larger than 5 mm and abnormal ascites. T2 hypointense microcysts might be a specific MRI finding in MBTs.

Evaluation of diffusion-weighted magnetic resonance imaging at 3.0 Tesla for differentiation between intracranial neoplastic and noninfectious inflammatory lesions in dogs

OBJECTIVE

To evaluate the utility of apparent diffusion coefficient (ADC) and fractional anisotropy (FA) values obtained by diffusion-weighted MRI (DWI) at 3.0 T for differentiating intracranial neoplastic lesions from noninfectious inflammatory lesions (NIILs) in dogs.

ANIMALS

54 dogs that met inclusion criteria (ie, had a histologically confirmed intracranial lesion and DWI of the brain performed) with 5 lesion types: meningioma [n = 18], glioma [14], metastatic hemangiosarcoma [3], other metastatic neoplasms [5], and NIIL [14]).

PROCEDURES

Two observers, who were blinded to the histologic diagnoses, independently determined the mean ADC and FA values for each evaluated intracranial lesion on the basis of 3 circular regions of interest on DWI images. Findings were compared among the 5 lesion types, between all neoplasms combined and NIILs, and between the 5 legion types and previously determined values for corresponding locations for neurologically normal dogs.

RESULTS

The mean ADC and FA values did not differ significantly among the 5 lesion types or between all neoplasms combined and NIILs. However, 35% (14/40) of the neoplastic lesions had an ADC value ≥ 1.443 × 10^-3 mm²/s, whereas all NIILs had ADC values < 1.443 × 10^-3 mm²/s. Meningiomas and NIILs had FA values that were significantly lower than those for neurologically normal dogs.

CONCLUSIONS AND CLINICAL RELEVANCE

In this population of dogs, the FA values for meningiomas and NIILs differed significantly from those previously reported for neurologically normal dogs. In addition, an ADC cutoff value of 1.443 × 10^-3 mm²/s appeared to be highly specific for diagnosing neoplastic lesions (vs NIILs), although the sensitivity and accuracy were low.