Entwicklung und Validierung der in vivo zeitharmonischen Ultraschall-Elastografie des menschlichen Gehirns für die klinische Anwendung

Motivation: In neurology, the determination of intracranial pressure (ICP) is of central importance for the diagnosis of brain damage. However, reliable ICP measurements are realized by invasive techniques such as lumbar puncture or surgically implanted pressure probes. Cerebral stiffness (CS) measured by elastography could be a parameter sensitive to ICP variations. However, CS is currently measured exclusively by magnetic resonance elastography, which is associated with long examinations and limited availability. Time harmonic shear wave excitation used in magnetic resonance elastography combined with transcranial ultrasound (cerebral THE) can provide reproducible and stable elastograms over a large field-of-view in real-time. Initial applications of cerebral THE in healthy volunteers during performance of the Valsalva maneuver demonstrated sensitivity of CS to blood flow and pressure changes in the brain. The goal of this PhD project was to optimize and validate cerebral THE that I previously developed to quantify CS, identify it as a marker of cerebral perfusion, and provide initial evidence for the potential clinical application of the method as a noninvasive technique for estimating ICP. Methods: To this end, I conducted two studies in healthy volunteers aimed at artificial manipulation of cerebral blood flow: (i) I investigated the effect of hypercapnia during breathing of carbon dioxide-enriched gas and (ii) the effect of dehydration and oral rehydration on CS measured by cerebral THE. Finally, I applied cerebral THE in a pilot clinical study in patients with idiopathic intracranial hypertension (IIH) who underwent lumbar puncture (LP) along with invasive quantification of cerebrospinal fluid (CSF) opening pressure and, if necessary, CSF drainage. Results: Hypercapnia increased CS by 6 ± 4% above baseline. In contrast, dehydration of healthy volunteers resulted in a decrease in CS of 4 ± 2%, whereas CS returned to baseline after oral rehydration. In patients with IIH, CS was 16 ± 5% higher than in healthy volunteers and correlated positively with CSF opening pressure (r = 0:69, p < 0:001). Approximately 30 min after LP, patients’ CS values were within the range of CS values in healthy volunteers. Conclusion: Cerebral THE proved to be a reproducible, stable imaging technique for real-time determination of CS. This project demonstrated that changes in CS are closely associated with changes in cerebral perfusion and ICP. These results suggest that cerebral THE may be a promising noninvasive diagnostic tool for determining ICP in routine clinical practice.Motivation: In der Neurologie ist die Bestimmung des intrakraniellen Drucks (ICP) von zentraler Bedeutung für die Diagnose von Hirnschäden. Zuverlässige ICP-Messungen werden jedoch durch invasive Techniken wie die Lumbalpunktion oder chirurgisch implantierte Drucksonden realisiert. Die mittels Elastografie gemessene zerebrale Steifigkeit (CS) könnte ein Parameter sein, der empfindlich auf ICP-Schwankungen reagiert. Allerdings wird die CS derzeit ausschließlich mit der Magnetresonanz-Elastografie gemessen, die mit langen Untersuchungen und begrenzter Verfügbarkeit verbunden ist. Zeitharmonische Scherwellenanregung, wie sie in der Magnetresonanz-Elastografie verwendet wird, kombiniert mit transkraniellem Ultraschall (zerebrale THE) kann reproduzierbare, stabile Elastogramme über ein großes Sichtfeld in Echtzeit liefern. Erste Anwendungen der zerebralen THE bei gesunden Probanden während der Durchführung des Valsalva-Manövers zeigten, dass die CS empfindlich auf Blutflussund Druckänderungen im Gehirn reagiert. Ziel dieses Promotionsprojekts war die Optimierung und Validierung der zerebralen THE, welche ich zuvor entwickelt habe, um CS zu quantifizieren, als Marker für zerebrale Perfusion zu identifizieren und erste Beweise für die potenzielle klinische Anwendung der Methode als nichtinvasive Technik zur Abschätzung des ICP zu liefern. Methoden: Zu diesem Zweck führte ich zwei Studien an gesunden Probanden durch, welche die künstliche Manipulation des zerebralen Blutflusses zum Ziel hatten: (i) Ich untersuchte die Auswirkung von Hyperkapnie während der Atmung von mit Kohlendioxid angereichertem Gas und (ii) die Auswirkung von Dehydrierung und oraler Rehydrierung auf die durch zerebrale THE gemessene CS. Schließlich habe ich die zerebrale THE in einer klinischen Pilotstudie bei Patienten mit idiopathischer intrakranieller Hypertension (IIH) angewandt, bei denen eine Lumbalpunktion (LP) zusammen mit einer invasiven Quantifizierung des Liquoröffnungsdrucks und, falls erforderlich, einer Liquordrainage durchgeführt wurde. Ergebnisse: Hyperkapnie erhöhte den CS um 6 4% über den Ausgangswert. Im Gegensatz dazu führte die Dehydratation gesunder Probanden zu einem Rückgang des CS um 4 2%, während der CS nach oraler Rehydrierung wieder den Ausgangswert erreichte. Bei Patienten mit IIH war die CS um 16 5% höher als bei gesunden Probanden und korrelierte positiv mit dem Liquoröffnungsdruck (r = 0:69, p < 0:001). Etwa 30 Minuten nach der LP lagen die CS Werte der Patienten im Bereich der CS Werte gesunder Probanden. Schlussfolgerung: Die zerebrale THE erwies sich als reproduzierbares, stabiles bildgebendes Verfahren zur Echtzeit-Bestimmung der CS. Dieses Projekt zeigte, dass Änderungen des CS eng mit Änderungen der zerebralen Perfusion und des ICP verbunden sind. Diese Ergebnisse deuten darauf hin, dass die zerebrale THE ein vielversprechendes nichtinvasives Diagnoseinstrument zur Bestimmung des ICP in der klinischen Routinepraxis sein könnte

Analysis of contrast-enhanced medical images.

Early detection of human organ diseases is of great importance for the accurate diagnosis and institution of appropriate therapies. This can potentially prevent progression to end-stage disease by detecting precursors that evaluate organ functionality. In addition, it also assists the clinicians for therapy evaluation, tracking diseases progression, and surgery operations. Advances in functional and contrast-enhanced (CE) medical images enabled accurate noninvasive evaluation of organ functionality due to their ability to provide superior anatomical and functional information about the tissue-of-interest. The main objective of this dissertation is to develop a computer-aided diagnostic (CAD) system for analyzing complex data from CE magnetic resonance imaging (MRI). The developed CAD system has been tested in three case studies: (i) early detection of acute renal transplant rejection, (ii) evaluation of myocardial perfusion in patients with ischemic heart disease after heart attack; and (iii), early detection of prostate cancer. However, developing a noninvasive CAD system for the analysis of CE medical images is subject to multiple challenges, including, but are not limited to, image noise and inhomogeneity, nonlinear signal intensity changes of the images over the time course of data acquisition, appearances and shape changes (deformations) of the organ-of-interest during data acquisition, determination of the best features (indexes) that describe the perfusion of a contrast agent (CA) into the tissue. To address these challenges, this dissertation focuses on building new mathematical models and learning techniques that facilitate accurate analysis of CAs perfusion in living organs and include: (i) accurate mathematical models for the segmentation of the object-of-interest, which integrate object shape and appearance features in terms of pixel/voxel-wise image intensities and their spatial interactions; (ii) motion correction techniques that combine both global and local models, which exploit geometric features, rather than image intensities to avoid problems associated with nonlinear intensity variations of the CE images; (iii) fusion of multiple features using the genetic algorithm. The proposed techniques have been integrated into CAD systems that have been tested in, but not limited to, three clinical studies. First, a noninvasive CAD system is proposed for the early and accurate diagnosis of acute renal transplant rejection using dynamic contrast-enhanced MRI (DCE-MRI). Acute rejection–the immunological response of the human immune system to a foreign kidney–is the most sever cause of renal dysfunction among other diagnostic possibilities, including acute tubular necrosis and immune drug toxicity. In the U.S., approximately 17,736 renal transplants are performed annually, and given the limited number of donors, transplanted kidney salvage is an important medical concern. Thus far, biopsy remains the gold standard for the assessment of renal transplant dysfunction, but only as the last resort because of its invasive nature, high cost, and potential morbidity rates. The diagnostic results of the proposed CAD system, based on the analysis of 50 independent in-vivo cases were 96% with a 95% confidence interval. These results clearly demonstrate the promise of the proposed image-based diagnostic CAD system as a supplement to the current technologies, such as nuclear imaging and ultrasonography, to determine the type of kidney dysfunction. Second, a comprehensive CAD system is developed for the characterization of myocardial perfusion and clinical status in heart failure and novel myoregeneration therapy using cardiac first-pass MRI (FP-MRI). Heart failure is considered the most important cause of morbidity and mortality in cardiovascular disease, which affects approximately 6 million U.S. patients annually. Ischemic heart disease is considered the most common underlying cause of heart failure. Therefore, the detection of the heart failure in its earliest forms is essential to prevent its relentless progression to premature death. While current medical studies focus on detecting pathological tissue and assessing contractile function of the diseased heart, this dissertation address the key issue of the effects of the myoregeneration therapy on the associated blood nutrient supply. Quantitative and qualitative assessment in a cohort of 24 perfusion data sets demonstrated the ability of the proposed framework to reveal regional perfusion improvements with therapy, and transmural perfusion differences across the myocardial wall; thus, it can aid in follow-up on treatment for patients undergoing the myoregeneration therapy. Finally, an image-based CAD system for early detection of prostate cancer using DCE-MRI is introduced. Prostate cancer is the most frequently diagnosed malignancy among men and remains the second leading cause of cancer-related death in the USA with more than 238,000 new cases and a mortality rate of about 30,000 in 2013. Therefore, early diagnosis of prostate cancer can improve the effectiveness of treatment and increase the patient’s chance of survival. Currently, needle biopsy is the gold standard for the diagnosis of prostate cancer. However, it is an invasive procedure with high costs and potential morbidity rates. Additionally, it has a higher possibility of producing false positive diagnosis due to relatively small needle biopsy samples. Application of the proposed CAD yield promising results in a cohort of 30 patients that would, in the near future, represent a supplement of the current technologies to determine prostate cancer type. The developed techniques have been compared to the state-of-the-art methods and demonstrated higher accuracy as shown in this dissertation. The proposed models (higher-order spatial interaction models, shape models, motion correction models, and perfusion analysis models) can be used in many of today’s CAD applications for early detection of a variety of diseases and medical conditions, and are expected to notably amplify the accuracy of CAD decisions based on the automated analysis of CE images

Entwicklung und Anwendung der in vivo abdominellen Magnetresonanzelastographie

Magnetic Resonance Elastography (MRE) is a well-established non-invasive imaging technique used to quantify the mechanical properties of tissues in vivo for the diagnosis of liver fibrosis. However, MRE is limited by its spatial resolution, sensitivity to motion artifacts, and insensitivity to metabolic function. Therefore, three studies of abdominal MRE were conducted to improve the quality of mechanical maps for characterizing liver tumors, to correct for motion artifacts induced by breathing, and to implement MRE on a PET/MRI scanner to correlate mechanical liver properties with metabolic functions in small animals through technical improvements in image acquisition and post-processing. High-resolution stiffness (shear wave speed in m/s), wave penetration (penetration rate in m/s), and fluidity (phase of the complex shear modulus in rad) maps were generated using multifrequency MRE, novel actuators, and tomoelastography post-processing. The first study characterized the stiffness and fluidity of a total of 141 liver tumors in 70 patients. The second study analyzed the motion of abdominal organs and its effect on their stiffness using different acquisition paradigms and image registration in 12 subjects. The third study examined the relationship of liver stiffness and wave penetration to central metabolic liver functions in 19 rabbits. Malignant liver tumors were distinguished from the surrounding liver (stiffness area under the curve [AUC]: 0.88 and fluidity AUC: 0.95) and benign tumors (stiffness AUC: 0.85 and fluidity AUC: 0.86) due to their increased stiffness and fluidity. In the second study, no significant differences in stiffness were observed despite significant differences in examination time, organ motion, and image quality with different image acquisition paradigms. Motion correction by image registration increased image sharpness, so that no significant difference was measurable between MRE in free breathing and breath-hold. Healthy rabbit livers showed heterogeneous liver stiffness, such that division into low and high stiffness (>1.6 m/s) groups resulted in significant differences in central metabolic functions. Stiffness and fluidity measured by multifrequency MRE hold promise as quantitative biomarkers for the diagnosis of malignant liver tumors. Abdominal MRE with free breathing, followed by image registration, is recommended as the best balance between fast examination time and good image quality. Additionally, the applicability of abdominal MRE in small animals in a clinical MRI was demonstrated, and correlations between mechanical liver properties and metabolic functions were found. This study demonstrates improvements in the quality of maps of biophysical parameters for both clinical and preclinical studies, making an important contribution to the clinical translation of multifrequency MRE as a non-invasive imaging modality for abdominal organs and pathologies.Die Magnetresonanzelastographie (MRE) ist eine nichtinvasive Bildgebungsmethode zur Quantifizierung mechanischer Gewebeeigenschaften in vivo bei der Diagnose von Leberfibrose. Limitationen bestehen aufgrund örtlicher Bildauflösung, Bewegungsempfindlichkeit und Insensitivität zu metabolischen Funktionen. Aufgrund technischer Verbesserung in der Bildaufnahme und der Bildauswertung wurde daher anhand von drei Studien zur abdominellen MRE die Bildqualität mechanischer Karten zur Charakterisierung von Lebertumoren verbessert, atmungsinduzierte Organbewegungen korrigiert und die MRE an klinischen PET/MRT implementiert, um an Kleintieren die mechanischen Lebereigenschaften mit metabolischen Funktionen zu korrelieren. Mittels multifrequenter MRE, neuartiger Aktoren und tomoelastographischer Auswertung wurden hochaufgelöste Karten der Steifigkeit (Scherwellengeschwindigkeit in m/s), Wellenpenetration (Wellenpenetrationsrate in m/s) und Fluidität (Phase des komplexen Schermoduls in rad) generiert. Die erste Studie charakterisierte die Steifigkeit und Fluidität von insgesamt 141 Lebertumoren an 70 Patienten. Eine zweite Studie analysierte die Bewegung und den Einfluss auf die Steifigkeit abdomineller Organe mittels unterschiedlicher Aufnahmeparadigmen und Bildregistrierung in 12 Probanden. In einer dritten Studie wurde der Zusammenhang von Lebersteifigkeit und Wellenpenetration zu zentralen metabolischen Leberfunktionen an 19 Kaninchen untersucht. Maligne Lebertumoren können durch erhöhte Steifigkeit und Fluidität (Steifigkeit AUC: 0.88 und Fluidität AUC: 0.95) gut von gutartigen Tumoren (Steifigkeit AUC: 0.85 und Fluidität AUC: 0.86) unterschieden werden. In der zweiten Studie wurden trotz verschiedener Aufnahmeparadigmen und Unterschiede in Untersuchungsdauer, Organbewegung und Bildqualität keine signifikanten Unterschiede in der Organsteifigkeit festgestellt. Die Bildregistrierung verbesserte die Bildschärfe, sodass kein signifikanter Unterschied zwischen freier Atmung und Atempause messbar war. Kaninchenlebern zeigten heterogene Steifigkeiten, sodass eine Zweiteilung in niedrige und hohe Steifigkeit (>1.6 m/s) signifikante Unterschiede in zentralen metabolischen Funktionen zeigte. Steifigkeit und Fluidität, die mittels der Mehrfrequenz-MRE gemessen werden, stellen vielversprechende quantitative Biomarker für die Diagnose maligner Lebertumoren dar. Abdominelle MRE in freier Atmung mit Bildregistrierung ist der beste Kompromiss aus schneller Untersuchungsdauer und guter Bildqualität. Die Anwendbarkeit an Kleintieren in einem klinischen MRT wurde gezeigt, inklusive Korrelationen zwischen mechanischen Lebereigenschaften und metabolischen Funktionen. Diese Arbeit konnte somit die Bildqualität mechanischer Karten sowohl für klinische als auch präklinische Untersuchungen verbessern und damit einen wichtigen Beitrag zur Translation der Multifrequenz-MRE als klinisch angewandte nichtinvasive Bildgebungsmethode abdomineller Organe und Pathologien leisten

Imaging Sensors and Applications

In past decades, various sensor technologies have been used in all areas of our lives, thus improving our quality of life. In particular, imaging sensors have been widely applied in the development of various imaging approaches such as optical imaging, ultrasound imaging, X-ray imaging, and nuclear imaging, and contributed to achieve high sensitivity, miniaturization, and real-time imaging. These advanced image sensing technologies play an important role not only in the medical field but also in the industrial field. This Special Issue covers broad topics on imaging sensors and applications. The scope range of imaging sensors can be extended to novel imaging sensors and diverse imaging systems, including hardware and software advancements. Additionally, biomedical and nondestructive sensing applications are welcome

4D Image Analysis and Diagnosis of Kidney Disease Using DCE-MRI Images

Abstract Because of noninvasive nature, medical imaging is easy to perform though it is extravagant. For furnishing superior anatomy and decisiveness, different characteristics have been extrapolated from intake image. Earlier the processing steps like registration, segmentation are separately applied for extraction of sequential proprieties of DCE-MRI images of kidney. For simultaneous registration and segmentation of the kidney, a 4D model is described. In the conscript of kidney abnormal functioning and disease detection, the glomerular filtration rate (GFR) is a significant factor. Dynamic contrast enhancement magnetic resonance imaging (DCE-MRI) is the imaging proficiency, used for calibrating different parameters homologous to suffuse, capillary leakage, and convey rate in tissues of various organs and diseases detection. The described technique&apos;s approach permits us to automatically accomplishing a statistical analysis of various parameters from alive cells. Conclusion of findings is accomplished by average gray level intensity inside the kidney region

Computational methods for the analysis of functional 4D-CT chest images.

Medical imaging is an important emerging technology that has been intensively used in the last few decades for disease diagnosis and monitoring as well as for the assessment of treatment effectiveness. Medical images provide a very large amount of valuable information that is too huge to be exploited by radiologists and physicians. Therefore, the design of computer-aided diagnostic (CAD) system, which can be used as an assistive tool for the medical community, is of a great importance. This dissertation deals with the development of a complete CAD system for lung cancer patients, which remains the leading cause of cancer-related death in the USA. In 2014, there were approximately 224,210 new cases of lung cancer and 159,260 related deaths. The process begins with the detection of lung cancer which is detected through the diagnosis of lung nodules (a manifestation of lung cancer). These nodules are approximately spherical regions of primarily high density tissue that are visible in computed tomography (CT) images of the lung. The treatment of these lung cancer nodules is complex, nearly 70% of lung cancer patients require radiation therapy as part of their treatment. Radiation-induced lung injury is a limiting toxicity that may decrease cure rates and increase morbidity and mortality treatment. By finding ways to accurately detect, at early stage, and hence prevent lung injury, it will have significant positive consequences for lung cancer patients. The ultimate goal of this dissertation is to develop a clinically usable CAD system that can improve the sensitivity and specificity of early detection of radiation-induced lung injury based on the hypotheses that radiated lung tissues may get affected and suffer decrease of their functionality as a side effect of radiation therapy treatment. These hypotheses have been validated by demonstrating that automatic segmentation of the lung regions and registration of consecutive respiratory phases to estimate their elasticity, ventilation, and texture features to provide discriminatory descriptors that can be used for early detection of radiation-induced lung injury. The proposed methodologies will lead to novel indexes for distinguishing normal/healthy and injured lung tissues in clinical decision-making. To achieve this goal, a CAD system for accurate detection of radiation-induced lung injury that requires three basic components has been developed. These components are the lung fields segmentation, lung registration, and features extraction and tissue classification. This dissertation starts with an exploration of the available medical imaging modalities to present the importance of medical imaging in today’s clinical applications. Secondly, the methodologies, challenges, and limitations of recent CAD systems for lung cancer detection are covered. This is followed by introducing an accurate segmentation methodology of the lung parenchyma with the focus of pathological lungs to extract the volume of interest (VOI) to be analyzed for potential existence of lung injuries stemmed from the radiation therapy. After the segmentation of the VOI, a lung registration framework is introduced to perform a crucial and important step that ensures the co-alignment of the intra-patient scans. This step eliminates the effects of orientation differences, motion, breathing, heart beats, and differences in scanning parameters to be able to accurately extract the functionality features for the lung fields. The developed registration framework also helps in the evaluation and gated control of the radiotherapy through the motion estimation analysis before and after the therapy dose. Finally, the radiation-induced lung injury is introduced, which combines the previous two medical image processing and analysis steps with the features estimation and classification step. This framework estimates and combines both texture and functional features. The texture features are modeled using the novel 7th-order Markov Gibbs random field (MGRF) model that has the ability to accurately models the texture of healthy and injured lung tissues through simultaneously accounting for both vertical and horizontal relative dependencies between voxel-wise signals. While the functionality features calculations are based on the calculated deformation fields, obtained from the 4D-CT lung registration, that maps lung voxels between successive CT scans in the respiratory cycle. These functionality features describe the ventilation, the air flow rate, of the lung tissues using the Jacobian of the deformation field and the tissues’ elasticity using the strain components calculated from the gradient of the deformation field. Finally, these features are combined in the classification model to detect the injured parts of the lung at an early stage and enables an earlier intervention

Clinical quantitative coronary artery stenosis and coronary atherosclerosis imaging: a Consensus Statement from the Quantitative Cardiovascular Imaging Study Group

The detection and characterization of coronary artery stenosis and atherosclerosis using imaging tools are key for clinical decision-making in patients with known or suspected coronary artery disease. In this regard, imaging-based quantification can be improved by choosing the most appropriate imaging modality for diagnosis, treatment and procedural planning. In this Consensus Statement, we provide clinical consensus recommendations on the optimal use of different imaging techniques in various patient populations and describe the advances in imaging technology. Clinical consensus recommendations on the appropriateness of each imaging technique for direct coronary artery visualization were derived through a three-step, real-time Delphi process that took place before, during and after the Second International Quantitative Cardiovascular Imaging Meeting in September 2022. According to the Delphi survey answers, CT is the method of choice to rule out obstructive stenosis in patients with an intermediate pre-test probability of coronary artery disease and enables quantitative assessment of coronary plaque with respect to dimensions, composition, location and related risk of future cardiovascular events, whereas MRI facilitates the visualization of coronary plaque and can be used in experienced centres as a radiation-free, second-line option for non-invasive coronary angiography. PET has the greatest potential for quantifying inflammation in coronary plaque but SPECT currently has a limited role in clinical coronary artery stenosis and atherosclerosis imaging. Invasive coronary angiography is the reference standard for stenosis assessment but cannot characterize coronary plaques. Finally, intravascular ultrasonography and optical coherence tomography are the most important invasive imaging modalities for the identification of plaques at high risk of rupture. The recommendations made in this Consensus Statement will help clinicians to choose the most appropriate imaging modality on the basis of the specific clinical scenario, individual patient characteristics and the availability of each imaging modality

Doctor of Philosophy

dissertationImage-based biomechanics, particularly numerical modeling using subject-specific data obtained via imaging, has proven useful for elucidating several biomechanical processes, such as prediction of deformation due to external loads, applicable to both normal function and pathophysiology of various organs. As the field evolves towards applications that stretch the limits of imaging hardware and acquisition time, the information traditionally expected as input for numerical routines often becomes incomplete or ambiguous, and requires specific acquisition and processing strategies to ensure physical accuracy and compatibility with predictive mathematical modeling. These strategies, often derivatives or specializations of traditional mechanics, effectively extend the nominal capability of medical imaging hardware providing subject-specific information coupled with the option of using the results for predictive numerical simulations. This research deals with the development of tools for extracting mechanical measurements from a finite set of imaging data and finite element analysis in the context of constructing structural atlases of the heart, understanding the biomechanics of the venous vasculature, and right ventricular failure. The tools include: (1) application of Hyperelastic Warping image registration to displacement-encoded MRI for reconstructing absolute displacement fields, (2) combination of imaging and a material parameter identification approach to measure morphology, deformation, and mechanical properties of vascular tissue, and (3) extrapolation of diffusion tensor MRI acquired at a single time point for the prediction the structural changes across the cardiac cycle with mechanical simulations. Selected tools were then applied to evaluate structural changes in a reversible animal model for right ventricular failure due to pressure overload

Role of diffusion tensor imaging as an imaging biomarker and theranostic tool in structural imaging of traumatic brain injury

Neuroimaging technology is at a "newborn" stage in the evaluation of TBI. While additional literature are obviously required to decide whether these modalities and progress in knowledge with noninvasive monitors will allow early and consistent recognition of revocable secondary brain damages, the final query is whether these new modalities will help in treatment plans that will absolutely mark result. DTI is an influential instrument for assessing white matter anatomy and related anomalies. DTI was formerly an investigation tool, but is using clinical practice. Accepting the terms and basic ideas of this method can aid in the clinical implementation and interpretation of this blend of structural and physiologic white matter evaluation. In conclusion, although DTI is as a diagnostic tool for severity of TBI and as an outcome predictor, but severe preclinical and clinical validation of each imaging method should be a top importance