Zhong Irene Wang¹, Joon Yul Choi¹, Siyuan Hu², Yingying Tang¹, TingYu Su^1,2, Ingmar Blümcke^1,3, Stephen Jones⁴, Ken Sakaie⁴, Imad Najm¹, and Dan Ma^2
1Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, OH, United States, ²Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States, ³Neuropathology, University of Erlangen, Erlangen, Germany, ⁴Imaging Institute, Cleveland Clinic, Cleveland, OH, United States

Focal cortical dysplasia (FCD) is a common pathology underlying medically intractable focal epilepsies. Conventional MRI can be limited in characterizing subtle FCD, due to the lack of quantitative measurements for tissue properties. Here, we proposed a multiparametric machine learning (ML) approach based on high-resolution 3D MR fingerprinting (MRF) to characterize FCD lesions. The ML model showed robust accuracy of 96%, 89%, and 79% to separate FCD from normal cortex, FCD type I from type II, and FCD type IIa from type IIb, respectively. Our findings suggest the usefulness of the multiparametric MRF ML approach to improve noninvasive epilepsy presurgical evaluation.

Yael Jacob¹, Laurel Morris¹, Sarah Rutter¹, Gaurav Verma¹, James Murrough¹, and Priti Balchandani^1
1Icahn School of Medicine at Mount Sinai, New York, NY, United States

Major depressive disorder (MDD) diagnosis, research, and treatment is especially challenging given that current diagnosis entirely depends on clinical symptoms, whereas the underlying brain pathology remains largely unclear. Applying a novel multilayer network analysis, considering communication within functional and structural networks as well as the interactions between them, we found aberrant centrality measures of various brain regions in MDD compared to controls that were not detected using single structural or functional connectomes. In addition, using multilayer network features as predictors in a machine learning algorithm resulted in higher predictive values compared to classification models based on single layer.

Xiaopeng Song¹, Tao Song¹, Chenyanwen Zhu¹, Dost Ongur¹, and Fei Du^1
1Harvard Medical School, BELMONT, MA, United States

Functional segregation, i.e., anticorrelated neural activities, has not been well-explored in fMRI studies. We introduced the Negative Degree Centrality (NDC) method to quantify functional segregation. We found decreased NDC in psychotic disorder patients compared to controls. Positive, negative, and general psychotic symptoms were associated with impaired NDC in three different brain networks respectively. Using NDC and a machine learning approach, we identified two subgroups of patients with distinct recovery trajectories after one-year treatment. Our findings suggested impaired functional segregation in different brain circuits might be the neurobiological mechanisms associated with various psychotic symptoms and outcome heterogeneity in psychotic disorders.

Kelley M. Swanberg¹, Hetty Prinsen², Christopher L. Averill^3,4,5, Leonardo Campos¹, Abhinav V. Kurada¹, John H. Krystal^3,4, Ismene L. Petrakis^3,4, Lynnette A. Averill^3,4,5, Chadi G. Abdallah^4,5, and Christoph Juchem^1,2,6,7
1Biomedical Engineering, Columbia University School of Engineering and Applied Science, New York, NY, United States, ²Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, United States, ³Clinical Neuroscience Division, Department of Veterans Affairs National Center for Posttraumatic Stress Disorder, Veterans Affairs Connecticut Healthcare System, West Haven, CT, United States, ⁴Psychiatry, Yale University School of Medicine, New Haven, CT, United States, ⁵Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, United States, ⁶Radiology, Columbia University Medical Center, New York, NY, United States, ⁷Neurology, Yale University School of Medicine, New Haven, CT, United States

Post-traumatic stress disorder (PTSD) is an anxiety condition evidenced by wide-ranging emotional and cognitive dysfunction. While prefrontal glutamatergic excitotoxicity is thought to contribute to its presentation, no ¹H-MRS studies of PTSD have yet been conducted at 7-Tesla field strength facilitating separation of glutamate from metabolic partner glutamine. Here we apply 7-T ¹H MRS to investigate medial prefrontal (mPFC) concentrations of glutamate and glutamine with GABA, glutathione, and other metabolites in both PTSD and comorbid major depressive disorder (MDD). We show several PTSD-associated abnormalities in mPFC glutamate metabolism that appear to be driven by MDD status when this comorbidity is considered. 

Julio Ernesto Villalon-Reina¹, Clara Moreau², Talia M Nir¹, Neda Jahanshad¹, Simons Variation in Individuals Project Consortium³, Anne Maillard⁴, David Romascano⁴, Bodgan Draganski⁵, Sarah Lippé⁶, Carrie E Bearden⁷, Paul M Thompson¹, and Sebastien Jacquemont^8
1Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Marina del Rey, CA, United States, ²Institut Pasteur, Université de Paris, Paris, France, ³Simons Foundation, New York, NY, United States, ⁴Service des Troubles du Spectre de l’Autisme et apparentés, Département de psychiatrie, Lausanne University Hospital, Lausanne, Switzerland, ⁵Laboratoire de Recherche en Neuroimagerie, Université de Lausanne, Lausanne, Switzerland, ⁶Psychology Department, University of Montreal, Montreal, QC, Canada, ⁷Departments of Psychiatry and Biobehavioral Sciences and Psychology, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, United States, ⁸University of Montreal, Montreal, QC, Canada

We used Hierarchical Bayesian Regression (HBR) to create a normative model of age-effects on Diffusion Kurtosis Imaging (DKI) measures of the white matter. DKI maps from more than 1,300 healthy subjects (3-78 years) from six sites and eight scanners were used to estimate the normative model across the lifespan enabling the multi-site data integration with HBR.  16p11.2 deletions and duplications showed “mirror effects” on diffusion kurtosis metrics.

Melissa A Prah¹, Jennifer M Connelly¹, and Kathleen M Schmainda^1
1Medical College of Wisconsin, Milwaukee, WI, United States

As treatment response can mimic progressive tumor on standard imaging, clinical outcomes following upfront chemo-radiotherapy in newly diagnosed glioblastoma rely heavily on MGMT promoter methylation status. While MGMT is a reliable marker of outcomes, the purpose of this study was to determine if inclusion of advanced perfusion-MRI derived fractional tumor burden (FTB) volume might better inform survival outcomes. Results revealed that low FTB volume in MGMT unmethylated glioblastoma confers significant survival benefit, approaching that of MGMT methylated glioblastoma. Clinically, combining FTB with MGMT methylation status may identify patients with potentially better outcomes or for whom more aggressive approaches are warranted.

Adrian Grant Paez^1,2, Suraj Rajan^3,4, Alex Y Pantelyat³, Liana I Rosenthal³, Andreia Faria⁵, Xinyuan Miao^2,6, Ted M Dawson³, Peter C. M. van Zijl^1,2, Vidyulata Kamath⁴, and Jun Hua^1,2
1Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States, ²F.M. Kirby Research Center, Kennedy Krieger Institute, Baltimore, MD, United States, ³Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States, ⁴Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States, ⁵Radiology and Radiological Science, Kennedy Krieger Institute, Baltimore, MD, United States, ⁶Johns Hopkins University School of Medicine, Baltimore, MD, United States

We demonstrate significant structural abnormalities in the OB, primary and secondary olfactory brain regions in early PD patients measured by high resolution MRI at 7T. The MRI measures showed significant correlations with behavioral olfactory deficits in the participants.

Vincent Magnotta¹, Jia Xu¹, Jess Fiedorowicz², Aislinn Williams³, Joseph Shaffer⁴, Gary Christensen⁵, Jeffrey Long⁶, Eric Taylor⁷, Leela Sathyaputri¹, Jenny Gringer Richards¹, Gail Harmata³, and John Wemmie^3
1Radiology, University of Iowa, Iowa City, IA, United States, ²Psychiatry, University of Iowa, Ottawa, ON, Canada, ³Psychiatry, University of Iowa, Iowa City, IA, United States, ⁴Biosciences, Kansas City University, Kansas City, MO, United States, ⁵Electrical and Computer Engineering, University of Iowa, Iowa City, IA, United States, ⁶Paychiatry, University of Iowa, Iowa City, IA, United States, ⁷University of Iowa, Iowa City, IA, United States

This study used 31P and 1H MRS to study brain metabolic differences in bipolar disorder. Data from 64 participants with BD and 42 controls was acquired from the right putamen and cerebellar vermis were acquired at 7T. The study observed reduced pHi in support of prior work that has proposed mitochondrial dysfunction in BD where there is an impaired ability to utilize pyruvate in oxidative phosphorylation. A shift from oxidative phosphorylation toward glycolytic energy production likely increases lactate acid, CO2 levels, and free protons resulting in tissue acidosis. This shift in energy production may also lead to increased glutathione.

Miguel Farinha¹, Conceição Amado², and Joana Cabral^3,4,5
1Instituto Superior Técnico, University of Lisbon, Lisbon, Portugal, ²Department of Mathematics and CEMAT, Instituto Superior Técnico, University of Lisbon, Lisbon, Portugal, ³Life and Health Sciences Research Institute, School of Medicine, University of Minho, Braga, Portugal, ⁴Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, United Kingdom, ⁵Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark

We investigate differences between the dynamic exploration of resting-state functional connectivity (FC) states using fMRI data from 71 schizophrenia (SZ) patients and 74 healthy controls (HCs) by employing the Leading Eigenvector Dynamics Analysis (LEiDA) method to provide potential biomarkers of this disorder. We found a reduced ability of SZ patients to access and remain in a state of global BOLD phase coherence. Functionally meaningful states presented increased occurrence, limiting probability and altered dynamic transitions in SZ patients. These findings expose pronounced differences between SZ patients and HCs - supporting and developing current knowledge regarding disrupted brain dynamics in schizophrenia.

Johannes Devos¹, Ronald Peeters¹, and Philippe Demaerel^2
1Radiology, UZ Leuven, Leuven, Belgium, ²Neuroradiology, UZ Leuven, Leuven, Belgium

Dynamical susceptibility contrast (DSC) and arterial spin labeling (ASL) are MRI techniques to quantify brain tissue perfusion. A voxel-wise analysis in 23 patients showed a moderate to strong linear relationship between tumoral cerebral blood flow measured by 2D echo planar imaging, pseudo-continuous  ASL (pCASL) and leakage corrected, cerebral blood volume measurements by DSC. Additionally, mean and 90th percentile of tumor perfusion of all patients showed a strong linear relationship. In conclusion, 2D EPI pCASL is a viable alternative to DSC for perfusion measurements of brain tumors.

Nadya Pyatigorskaya¹, Arnaud Pellerin², Maya Kalife³, Laura Rozenblum-Beddok⁴, Marc Bertaux², Marine Soret², Lydia Yahia-cherif³, and Aurélie Kas^2
1CENIR, ICM, Paris, France, ²Pitié-Salpêtrière Hospital, APHP, Sorbonne universite, Paris, France, ³ICM, Paris, France, ⁴Pitié Salpêtrière, APHP, Paris, France

We aimed at investigating the methods based on coupling of of amino-acid metabolism (18F-DOPA-PET) measurements and cerebral blood flow (CBF) maps  to evaluate the diagnostic performance of PET/MRI in glioma imaging. Tumor isocontour maps and T-maps were created using SPM and metabolic/perfusion abnormalities were evaluated with the asymmetry index z-score. SPM map analysis of significant-size clusters and semi-quantitative evaluation were performed and compared to gold standard diagnosis. Both the tumor isocontour maps and T-maps showed the highest specificity for ASL and sensitivity for 18F-DOPA analysis, allowing high diagnostic performance in differentiating between progression and radionecrosis particularly in high-grade treated gliomas.

Gergely Bertalan¹, Julia Onken², Simone Schwedler³, Bernd Hamm¹, Georg Bohner³, and Edzard Wiener^3
1Radiology, Charité - Universitätsmedizin Berlin, Berlin, Germany, ²Neurosurgery, Charité - Universitätsmedizin Berlin, Berlin, Germany, ³Neuroradiology, Charité - Universitätsmedizin Berlin, Berlin, Germany

Conventional MRI such as T2 and FLAIR do not show sub-regional intensity changes in peritumoral infiltration zone of glioblastoma and cannot visualize tumor margins. Here, we implemented a new method for sub-volumetric analysis of glioblastoma and investigated T1 and T2 relaxation properties in the peritumoral infiltration zone. The results show a decrease in T1 and T2 relaxation times as a function of distance from the contrast-enhanced T1 solid tumor region to the periphery. Our method may help to better select regions for biopsy, to determine the surgical resection margin and improve radiation therapy planning and post-therapeutic progress controls.

Alba Segura Amil^1,2, T.A. Khoa Nguyen^1,2, Andreas Nowacki¹, and Claudio Pollo^1
1Department of Neurosurgery, University Hospital Bern, Bern, Switzerland, ²ARTORG Center for Biomedical Engineering, University of Bern, Bern, Switzerland

Deep brain stimulation is an effective treatment in advanced Parkinson’s disease. The aim of the study was to determine activation thresholds for the hyperdirect pathway and corticospinal tract to control motor symptoms and avoid the appearance of side effects. Patient-specific whole brain tractograpy, DBS leads reconstruction, and generation of volumes of tissue activated were performed in 20 Parkinson patients. The activation threshold for the hyperdirect pathway was 60%, and for the corticospinal was 4%. For newly generated volumes of tissue activated, the average prediction error for the hyperdirect pathway was 1 mA and for the corticospinal tract was 1.5 mA.