Magnetic resonance imaging-guided focused ultrasound thalamotomy for essential tremor in a patient with von Willebrand disease: perioperative optimization for patients with coagulopathies. Illustrative case.

BACKGROUND: Essential tremor (ET) is one of the most common movement disorders worldwide. In medically refractory ET, deep brain stimulation (DBS) of the ventral intermediate nucleus of the thalamus is the current standard of care. However, DBS carries an inherent 2% to 3% risk of hemorrhage, a risk that can be much higher in patients with concomitant coagulopathy. Magnetic resonance imaging-guided focused ultrasound (MRgFUS) thalamotomy is a surgical alternative that is highly effective in treating ET, with no reports of intracranial hemorrhage to date. OBSERVATIONS: This is the first documented case of successful MRgFUS thalamotomy in a patient with von Willebrand disease (VWD). A 60-year-old left-handed male had medically refractory ET, VWD type 2B, and a family history of clinically significant hemorrhage after DBS. He underwent right-sided MRgFUS thalamotomy and received a perioperative course of VONVENDI (recombinant von Willebrand factor) to ensure appropriate hemostasis. Postprocedure imaging confirmed a focal lesion in the right thalamus without evidence of hemorrhage. The patient reported 90% improvement of his left-hand tremor and significant improvement in his quality of life without obvious side effects. LESSONS: MRgFUS thalamotomy with peri- and postoperative hematological management is a promising alternative to DBS for patients with underlying coagulopathies.

MR Thermometry during Transcranial MR Imaging-Guided Focused Ultrasound Procedures: A Review.

Interest in transcranial MR imaging-guided focused ultrasound procedures has recently grown. These incisionless procedures enable precise focal ablation of brain tissue using real-time monitoring by MR thermometry. This article will provide an updated review on clinically applicable technical underpinnings and considerations of proton resonance frequency MR thermometry, the most common clinically used MR thermometry sequence.

ELectronic Archimedes spiral Neural Network (ELANN).

The Archimedes spiral is a clinical tool that aids in the diagnosis and monitoring of essential tremor. However, spiral ratings may vary based on experience and training of the rating physician. This study sought to generate an objective standard model for tremor evaluation using convolutional neural networks. One senior movement disorders neurologist (Neurologist 1) with over 30 years of clinical experience used the Bain and Findley Spirography Rating Scale to rate 1653 Archimedes spiral images from 46 essential tremor patients (mild to severe tremor) and 75 control subjects (no to mild tremor). Neurologist 1's labels were used as the reference standard to train the model. After training the model, a randomly selected subset of spiral testing data was re-evaluated by Neurologist 1, by a second senior movement disorders neurologist (Neurologist 2) with over 27 years of clinical experience, and by our model. Cohen's Weighted Kappa 95% confidence intervals were calculated from all rater comparisons to determine if our model performs with the same proficiency as two senior movement disorders neurologists. The Cohen's Weighted Kappa 95% confidence intervals for the agreement between the reference standard scores and Neurologist 1's rerated scores, for the agreement between the reference standard scores and Neurologist 2's scores, and for the agreement between the reference standard scores and our model's scores were 0.93-0.98, 0.86-0.94, and 0.89-0.96, respectively. With overlapping Cohen's Weighted Kappa 95% confidence intervals for all agreement comparisons, we demonstrate that our model evaluates spirals with the same proficiency as two senior movement disorders neurologists.

Improving tremor response to focused ultrasound thalamotomy.

MRI-guided high-intensity focused ultrasound thalamotomy is an incisionless therapy for essential tremor. To reduce adverse effects, the field has migrated to treating at 2 mm above the anterior commissure-posterior commissure plane. We perform MRI-guided high-intensity focused ultrasound with an advanced imaging targeting technique, four-tract tractography. Four-tract tractography uses diffusion tensor imaging to identify the critical white matter targets for tremor control, the decussating and non-decussating dentatorubrothalamic tracts, while the corticospinal tract and medial lemniscus are identified to be avoided. In some patients, four-tract tractography identified a risk of damaging the medial lemniscus or corticospinal tract if treated at 2 mm superior to the anterior commissure-posterior commissure plane. In these patients, we chose to target 1.2-1.5 mm superior to the anterior commissure-posterior commissure plane. In these patients, post-operative imaging revealed that the focused ultrasound lesion extended into the posterior subthalamic area. This study sought to determine if patients with focused ultrasound lesions that extend into the posterior subthalamic area have a differnce in tremor improvement than those without. Twenty essential tremor patients underwent MRI-guided high-intensity focused ultrasound and were retrospectively classified into two groups. Group 1 included patients with an extension of the thalamic-focused ultrasound lesion into the posterior subthalamic area. Group 2 included patients without extension of the thalamic-focused ultrasound lesion into the posterior subthalamic area. For each patient, the percent change in postural tremor, kinetic tremor and Archimedes spiral scores were calculated between baseline and a 3-month follow-up. Two-tailed Wilcoxon rank-sum tests were used to compare the improvement in tremor scores, the total number of sonications, thermal dose to achieve initial tremor response, and skull density ratio between groups. Group 1 had significantly greater postural, kinetic, and Archimedes spiral score percent improvement than Group 2 (P values: 5.41 × 10-5, 4.87 × 10-4, and 5.41 × 10-5, respectively). Group 1 also required significantly fewer total sonications to control the tremor and a significantly lower thermal dose to achieve tremor response (P values: 6.60 × 10-4 and 1.08 × 10-5, respectively). No significant group differences in skull density ratio were observed (P = 1.0). We do not advocate directly targeting the posterior subthalamic area with MRI-guided high-intensity focused ultrasound because the shape of the focused ultrasound lesion can result in a high risk of adverse effects. However, when focused ultrasound lesions naturally extend from the thalamus into the posterior subthalamic area, they provide greater tremor control than those that only involve the thalamus.

Structural MRI Ratios Fail to Distinguish Progressive Supranuclear Palsy From Parkinson Disease in Individual Patients.

Background and Objectives: Parkinson disease (PD) and progressive supranuclear palsy (PSP) are often difficult to differentiate in the clinic. The MR parkinsonism index (MRPI) has been recommended to assist in making this distinction. We aimed to assess the usefulness of this tool in our real-world practice of movement disorders. Methods: We prospectively obtained MRI scans on consecutive patients with movement disorders with a clinical indication for imaging and obtained measures of MRI regions of interest (ROIs) from our neuroradiologists. The authors reviewed all MRI scans and corrected any errors in the original ROI drawings for this analysis. We retrospectively assigned diagnoses using established consensus criteria from progress notes stored in our electronic medical record. We analyzed the data using multinomial logistic regression models and receiver operating curve analysis to determine the predictive accuracy of the MRI ratios. Results: MRI measures and consensus diagnoses were available on 130 patients with PD, 54 with PSP, and 77 diagnosed as other. The out-of-sample prediction error rate of our 5 regression models ranged from 45% to 59%. The average sensitivity and specificity of the 5 models in the testing sample were 53% and 80%, respectively. The positive predictive value of an MRPI ≥13.55 (the published cutoff) in our patients was 79%. Discussion: These results indicate that MRI measures of brain structures were not effective at predicting diagnosis in individual patients. We conclude that the search for a biomarker that can differentiate PSP from PD must continue.

Errata: Brain tumor IDH, 1p/19q, and MGMT molecular classification using MRI-based deep learning: an initial study on the effect of motion and motion correction.

[This corrects the article DOI: 10.1117/1.JMI.9.1.016001.].

Corrigendum to: A novel fully automated MRI-based deep-learning method for classification of 1p/19q co-deletion status in brain gliomas.

[This corrects the article DOI: 10.1093/noajnl/vdaa066.].

Brain tumor IDH, 1p/19q, and MGMT molecular classification using MRI-based deep learning: an initial study on the effect of motion and motion correction.

Purpose: Deep learning has shown promise for predicting the molecular profiles of gliomas using MR images. Prior to clinical implementation, ensuring robustness to real-world problems, such as patient motion, is crucial. The purpose of this study is to perform a preliminary evaluation on the effects of simulated motion artifact on glioma marker classifier performance and determine if motion correction can restore classification accuracies. Approach: T2w images and molecular information were retrieved from the TCIA and TCGA databases. Simulated motion was added in the k-space domain along the phase encoding direction. Classifier performance for IDH mutation, 1p/19q co-deletion, and MGMT methylation was assessed over the range of 0% to 100% corrupted k-space lines. Rudimentary motion correction networks were trained on the motion-corrupted images. The performance of the three glioma marker classifiers was then evaluated on the motion-corrected images. Results: Glioma marker classifier performance decreased markedly with increasing motion corruption. Applying motion correction effectively restored classification accuracy for even the most motion-corrupted images. For isocitrate dehydrogenase (IDH) classification, 99% accuracy was achieved, exceeding the original performance of the network and representing a new benchmark in non-invasive MRI-based IDH classification. Conclusions: Robust motion correction can facilitate highly accurate deep learning MRI-based molecular marker classification, rivaling invasive tissue-based characterization methods. Motion correction may be able to increase classification accuracy even in the absence of a visible artifact, representing a new strategy for boosting classifier performance.

Focused ultrasound using a novel targeting method four-tract tractography for magnetic resonance-guided high-intensity focused ultrasound targeting.

Magnetic resonance-guided high-intensity focused ultrasound thalamotomy is a Food and Drug Administration-approved treatment for essential tremor. The target, the ventral intermediate nucleus of the thalamus, is not visualized on standard, anatomic MRI sequences. Several recent reports have used diffusion tensor imaging to target the dentato-rubro-thalamic-tract. There is considerable variability in fibre tracking algorithms and what fibres are tracked. Targeting discrete white matter tracts with magnetic resonance-guided high-intensity focused ultrasound is an emerging precision medicine technique that has the promise to improve patient outcomes and reduce treatment times. We provide a technical overview and clinical benefits of our novel, easily implemented advanced tractography method: four-tract tractography. Our method is novel because it targets both the decussating and non-decussating dentato-rubro-thalamic-tracts while avoiding the medial lemniscus and corticospinal tracts. Our method utilizes Food and Drug Administration-approved software and is easily implementable into existing workflows. Initial experience using this approach suggests that it improves patient outcomes by reducing the incidence of adverse effects.

Fundamentals of Radiation Oncology for Treatment of Vertebral Metastases.

The fields of both radiology and radiation oncology have evolved considerably in the past few decades, resulting in an increased ability to delineate between tumor and normal tissue to precisely target and treat vertebral metastases with radiation therapy. These scientific advances have also led to improvements in assessing treatment response and diagnosing toxic effects related to radiation treatment. However, despite technological innovations yielding greatly improved rates of palliative relief and local control of osseous spinal metastases, radiation therapy can still lead to a number of acute and delayed posttreatment complications. Treatment-related adverse effects may include pain flare, esophageal toxic effects, dermatitis, vertebral compression fracture, radiation myelopathy, and myositis, among others. The authors provide an overview of the multidisciplinary approach to the treatment of spinal metastases, indications for surgical management versus radiation therapy, various radiation technologies and techniques (along with their applications for spinal metastases), and current principles of treatment planning for conventional and stereotactic radiation treatment. Different radiologic criteria for assessment of treatment response, recent advances in radiologic imaging, and both common and rare complications related to spinal irradiation are also discussed, along with the imaging characteristics of various adverse effects. Familiarity with these topics will not only assist the diagnostic radiologist in assessing treatment response and diagnosing treatment-related complications but will also allow more effective collaboration between diagnostic radiologists and radiation oncologists to guide management decisions and ensure high-quality patient care. ©RSNA, 2021.

Probing Cerebral Metabolism with Hyperpolarized 13C Imaging after Opening the Blood-Brain Barrier with Focused Ultrasound.

Transient disruption of the blood-brain barrier (BBB) with focused ultrasound (FUS) is an emerging clinical method to facilitate targeted drug delivery to the brain. The focal noninvasive disruption of the BBB can be applied to promote the local delivery of hyperpolarized substrates. In this study, we investigated the effects of FUS on imaging brain metabolism using two hyperpolarized 13C-labeled substrates in rodents: [1-13C]pyruvate and [1-13C]glycerate. The BBB is a rate-limiting factor for pyruvate delivery to the brain, and glycerate minimally passes through the BBB. First, cerebral imaging with hyperpolarized [1-13C]pyruvate resulted in an increase in total 13C signals (p = 0.05) after disrupting the BBB with FUS. Significantly higher levels of both [1-13C]lactate (lactate/total 13C signals, p = 0.01) and [13C]bicarbonate (p = 0.008) were detected in the FUS-applied brain region as compared to the contralateral FUS-unaffected normal-appearing brain region. The application of FUS without opening the BBB in a separate group of rodents resulted in comparable lactate and bicarbonate productions between the FUS-applied and the contralateral brain regions. Second, 13C imaging with hyperpolarized [1-13C]glycerate after opening the BBB showed increased [1-13C]glycerate delivery to the FUS-applied region (p = 0.04) relative to the contralateral side, and [1-13C]lactate production was consistently detected from the FUS-applied region. Our findings suggest that FUS accelerates the delivery of hyperpolarized molecules across the BBB and provides enhanced sensitivity to detect metabolic products in the brain; therefore, hyperpolarized 13C imaging with FUS may provide new opportunities to study cerebral metabolic pathways as well as various neurological pathologies.

Outcome of Covid-19 Positive Newborns Presenting to a Tertiary Care Hospital.

Neonatal data regarding SARS-CoV-2 is sparse from India. On review of hospital records from April- August, 2020, 18/423 (4.25%) neonates were SARS-CoV-2 RT-PCR positive. 15 (83.3%) neonates recovered and 3 (16.6%) succumbed. Only 50% of the positive babies had positive mothers/ caretakers, a contact could not be traced in others.

Consistent opening of the blood brain barrier using focused ultrasound with constant intravenous infusion of microbubble agent.

The blood brain barrier (BBB) is a major obstacle to the delivery of therapeutics to the brain. Focused ultrasound (FUS) in combination with microbubbles can non-invasively open the BBB in a targeted manner. Bolus intravenous injections of microbubbles are standard practice, but dynamic influx and clearance mechanisms prevent delivery of a uniform dose with time. When multiple targets are selected for sonication in a single treatment, uniform serum concentrations of microbubbles are important for consistent BBB opening. Herein, we show that bubble infusions were able to achieve consistent BBB opening at multiple target sites. FUS exposures were conducted with different Definity microbubble concentrations at various acoustic pressures. To quantify the effects of infusion on BBB opening, we calculated the MRI contrast enhancement rate. When infusions were performed at rates of 7.2 µl microbubbles/kg/min or below, we were able to obtain consistent BBB opening without injury at all pressures. However, when infusion rates exceeded 20 µl/kg/min, signs of injury occurred at pressures from 0.39 to 0.56 MPa. When compared to bolus injections, a bubble infusion offers a more controlled and consistent approach to multi-target BBB disruption.

A novel fully automated MRI-based deep-learning method for classification of 1p/19q co-deletion status in brain gliomas.

BACKGROUND: One of the most important recent discoveries in brain glioma biology has been the identification of the isocitrate dehydrogenase (IDH) mutation and 1p/19q co-deletion status as markers for therapy and prognosis. 1p/19q co-deletion is the defining genomic marker for oligodendrogliomas and confers a better prognosis and treatment response than gliomas without it. Our group has previously developed a highly accurate deep-learning network for determining IDH mutation status using T2-weighted (T2w) MRI only. The purpose of this study was to develop a similar 1p/19q deep-learning classification network. METHODS: Multiparametric brain MRI and corresponding genomic information were obtained for 368 subjects from The Cancer Imaging Archive and The Cancer Genome Atlas. 1p/19 co-deletions were present in 130 subjects. Two-hundred and thirty-eight subjects were non-co-deleted. A T2w image-only network (1p/19q-net) was developed to perform 1p/19q co-deletion status classification and simultaneous single-label tumor segmentation using 3D-Dense-UNets. Three-fold cross-validation was performed to generalize the network performance. Receiver operating characteristic analysis was also performed. Dice scores were computed to determine tumor segmentation accuracy. RESULTS: 1p/19q-net demonstrated a mean cross-validation accuracy of 93.46% across the 3 folds (93.4%, 94.35%, and 92.62%, SD = 0.8) in predicting 1p/19q co-deletion status with a sensitivity and specificity of 0.90 ± 0.003 and 0.95 ± 0.01, respectively and a mean area under the curve of 0.95 ± 0.01. The whole tumor segmentation mean Dice score was 0.80 ± 0.007. CONCLUSION: We demonstrate high 1p/19q co-deletion classification accuracy using only T2w MR images. This represents an important milestone toward using MRI to predict glioma histology, prognosis, and response to treatment.

MRI and tractography techniques to localize the ventral intermediate nucleus and dentatorubrothalamic tract for deep brain stimulation and MR-guided focused ultrasound: a narrative review and update.

The thalamic ventral intermediate nucleus (VIM) can be targeted for treatment of tremor by several procedures, including deep brain stimulation (DBS) and, more recently, MR-guided focused ultrasound (MRgFUS). To date, such targeting has relied predominantly on coordinate-based or atlas-based techniques rather than directly targeting the VIM based on imaging features. While general regional differences of features within the thalamus and some related white matter tracts can be distinguished with conventional imaging techniques, internal nuclei such as the VIM are not discretely visualized. Advanced imaging methods such as quantitative susceptibility mapping (QSM) and fast gray matter acquisition T1 inversion recovery (FGATIR) MRI and high-field MRI pulse sequences that improve the ability to image the VIM region are emerging but have not yet been shown to have reliability and accuracy to serve as the primary method of VIM targeting. Currently, the most promising imaging approach to directly identify the VIM region for clinical purposes is MR diffusion tractography.In this review and update, the capabilities and limitations of conventional and emerging advanced methods for evaluation of internal thalamic anatomy are briefly reviewed. The basic principles of tractography most relevant to VIM targeting are provided for familiarization. Next, the key literature to date addressing applications of DTI and tractography for DBS and MRgFUS is summarized, emphasizing use of direct targeting. This literature includes 1-tract (dentatorubrothalamic tract [DRT]), 2-tract (pyramidal and somatosensory), and 3-tract (DRT, pyramidal, and somatosensory) approaches to VIM region localization through tractography.The authors introduce a 3-tract technique used at their institution, illustrating the oblique curved course of the DRT within the inferior thalamus as well as the orientation and relationship of the white matter tracts in the axial plane. The utility of this 3-tract tractography approach to facilitate VIM localization is illustrated with case examples of variable VIM location, targeting superior to the anterior commissure-posterior commissure plane, and treatment in the setting of pathologic derangement of thalamic anatomy. Finally, concepts demonstrated with these case examples and from the prior literature are synthesized to highlight several potential advantages of tractography for VIM region targeting.

Advanced MRI techniques for transcranial high intensity focused ultrasound targeting.

Magnetic resonance guided high intensity focused ultrasound is a novel, non-invasive, image-guided procedure that is able to ablate intracranial tissue with submillimetre precision. It is currently FDA approved for essential tremor and tremor dominant Parkinson's disease. The aim of this update is to review the limitations of current landmark-based targeting techniques of the ventral intermediate nucleus and demonstrate the role of emerging imaging techniques that are relevant for both magnetic resonance guided high intensity focused ultrasound and deep brain stimulation. A significant limitation of standard MRI sequences is that the ventral intermediate nucleus, dentatorubrothalamic tract, and other deep brain nuclei cannot be clearly identified. This paper provides original, annotated images demarcating the ventral intermediate nucleus, dentatorubrothalamic tract, and other deep brain nuclei on advanced MRI sequences such as fast grey matter acquisition T1 inversion recovery, quantitative susceptibility mapping, susceptibility weighted imaging, and diffusion tensor imaging tractography. Additionally, the paper reviews clinical efficacy of targeting with these novel MRI techniques when compared to current established landmark-based targeting techniques. The paper has widespread applicability to both deep brain stimulation and magnetic resonance guided high intensity focused ultrasound.

A Fully Automated Deep Learning Network for Brain Tumor Segmentation.

We developed a fully automated method for brain tumor segmentation using deep learning; 285 brain tumor cases with multiparametric magnetic resonance images from the BraTS2018 data set were used. We designed 3 separate 3D-Dense-UNets to simplify the complex multiclass segmentation problem into individual binary-segmentation problems for each subcomponent. We implemented a 3-fold cross-validation to generalize the network's performance. The mean cross-validation Dice-scores for whole tumor (WT), tumor core (TC), and enhancing tumor (ET) segmentations were 0.92, 0.84, and 0.80, respectively. We then retrained the individual binary-segmentation networks using 265 of the 285 cases, with 20 cases held-out for testing. We also tested the network on 46 cases from the BraTS2017 validation data set, 66 cases from the BraTS2018 validation data set, and 52 cases from an independent clinical data set. The average Dice-scores for WT, TC, and ET were 0.90, 0.84, and 0.80, respectively, on the 20 held-out testing cases. The average Dice-scores for WT, TC, and ET on the BraTS2017 validation data set, the BraTS2018 validation data set, and the clinical data set were as follows: 0.90, 0.80, and 0.78; 0.90, 0.82, and 0.80; and 0.85, 0.80, and 0.77, respectively. A fully automated deep learning method was developed to segment brain tumors into their subcomponents, which achieved high prediction accuracy on the BraTS data set and on the independent clinical data set. This method is promising for implementation into a clinical workflow.

Fundamentals of Radiation Oncology for Neurologic Imaging.

Although the physical and biologic principles of radiation therapy have remained relatively unchanged, a technologic renaissance has led to continuous and ever-changing growth in the field of radiation oncology. As a result, medical devices, techniques, and indications have changed considerably during the past 20-30 years. For example, advances in CT and MRI have revolutionized the treatment planning process for a variety of central nervous system diseases, including primary and metastatic tumors, vascular malformations, and inflammatory diseases. The resultant improved ability to delineate normal from abnormal tissue has enabled radiation oncologists to achieve more precise targeting and helped to mitigate treatment-related complications. Nevertheless, posttreatment complications still occur and can pose a diagnostic challenge for radiologists. These complications can be divided into acute, early-delayed, and late-delayed complications on the basis of the time that they manifest after radiation therapy and include leukoencephalopathy, vascular complications, and secondary neoplasms. The different irradiation technologies and applications of these technologies in the brain, current concepts used in treatment planning, and essential roles of the radiation oncologist in the setting of brain disease are reviewed. In addition, relevant imaging findings that can be used to delineate the extent of disease before treatment, and the expected posttreatment imaging changes are described. Common and uncommon complications related to radiation therapy and the associated imaging manifestations also are discussed. Familiarity with these entities may aid the radiologist in making the diagnosis and help guide appropriate management. ©RSNA, 2020.