Repeatability and variation of region-of-interest methods using quantitative diffusion tensor MR imaging of the brain

Background Diffusion tensor imaging (DTI) is increasingly used in various diseases as a clinical tool for assessing the integrity of the brain’s white matter. Reduced fractional anisotropy (FA) and an increased apparent diffusion coefficient (ADC) are nonspecific findings in most pathological processes affecting the brain’s parenchyma. At present, there is no gold standard for validating diffusion measures, which are dependent on the scanning protocols, methods of the softwares and observers. Therefore, the normal variation and repeatability effects on commonly-derived measures should be carefully examined. Methods Thirty healthy volunteers (mean age 37.8 years, SD 11.4) underwent DTI of the brain with 3T MRI. Region-of-interest (ROI) -based measurements were calculated at eleven anatomical locations in the pyramidal tracts, corpus callosum and frontobasal area. Two ROI-based methods, the circular method (CM) and the freehand method (FM), were compared. Both methods were also compared by performing measurements on a DTI phantom. The intra- and inter-observer variability (coefficient of variation, or CV%) and repeatability (intra-class correlation coefficient, or ICC) were assessed for FA and ADC values obtained using both ROI methods. Results The mean FA values for all of the regions were 0.663 with the CM and 0.621 with the FM. For both methods, the FA was highest in the splenium of the corpus callosum. The mean ADC value was 0.727 ×10-3 mm2/s with the CM and 0.747 ×10-3 mm2/s with the FM, and both methods found the ADC to be lowest in the corona radiata. The CV percentages of the derived measures were < 13% with the CM and < 10% with the FM. In most of the regions, the ICCs were excellent or moderate for both methods. With the CM, the highest ICC for FA was in the posterior limb of the internal capsule (0.90), and with the FM, it was in the corona radiata (0.86). For ADC, the highest ICC was found in the genu of the corpus callosum (0.93) with the CM and in the uncinate fasciculus (0.92) with FM. Conclusions With both ROI-based methods variability was low and repeatability was moderate. The circular method gave higher repeatability, but variation was slightly lower using the freehand method. The circular method can be recommended for the posterior limb of the internal capsule and splenium of the corpus callosum, and the freehand method for the corona radiata.BioMed Central open acces

ДИАГНОСТИЧЕСКИЕ КРИТЕРИИ ПОРОГОВЫХ ЗНАЧЕНИЙ ФРАКЦИОННОЙ АНИЗОТРОПИИ В ОЦЕНКЕ РИСКА КОГНИТИВНЫХ НАРУШЕНИЙ У ПАЦИЕНТОВ С ДИСЦИРКУЛЯТОРНОЙ ПАТОЛОГИЕЙ ГОЛОВНОГО МОЗГА

As a consequence of the cerebral tracts’ damages, encephalopathy comes with cognitive disorders. Diffusion-tensor MRI is a cerebral tracts’ integrity quantitative measurement method. The main purpose of the study was to develop criteria of cerebral tracts integrity using DT-MRI to predict vascular dementia, to find threshold CFA level in liable tracts to measure dementia risk. DT-MR results were compared with neuropsychological tests of subjects with diagnosed encephalopathy. Identified statistically significant (р&lt;0,005) FA decrease in three regions for those subjects with cognitive impairment: front sections of corona radiata, inferior longitudinal fasciculi and anterior horn of internal capsule. Threshold FA level calculated for these 3 region of interests, they can be predictors of the risk of cognitive disorders for subjects with diagnosed encephalopathy.У пациентов с дисциркуляторной энцефалопатией (ДЭ) отмечаются частые проявления расстройств когнитивной сферы, что является следствием органического поражения головного мозга. Методика диффузионно-тензорной магнитно-резонансной томографии (ДТ-МРТ) позволяет производить количественную оценку целостности проводящих путей. Цель исследования: разработать прогностические критерии изменений белого вещества головного мозга при ДЭ, выявить пороговые значения фракционной анизотропии, способные стать предикторами когнитивных нарушений (КН). Произведено сопоставление результатов ДТ-МРТ с данными нейропсихологического тестирования у пациентов с ДЭ. У пациентов с КН отмечалось статистически достоверное (р&lt;0,005) снижение коэффициента фракционной анизотропии (КФА) в трактах передних отделов лучистого венца (лобные доли), в нижнем продольном пучке (височные доли) и в переднем бедре внутренней капсулы. Рассчитаны пороговые значения КФА в данных областях, являющиеся предикторами КН, что дает возможность определить вероятность риска их развития у пациентов с ДЭ. Количественный анализ изменений в структурах мозга, отвечающих за когнитивную функцию, является актуальным для прогнозирования вероятности наступления у пациентов сосудистой деменции

Imaging characteristics of H3 K27M histone-mutant diffuse midline glioma in teenagers and adults

Background: To assess anatomical and quantitative diffusion-weighted MR imaging features in a recently classified lethal neoplasm, H3 K27M histone-mutant diffuse midline glioma [World Health Organization (WHO) IV]. / Methods: Fifteen untreated gliomas in teenagers and adults (median age 19, range, 14–64) with confirmed H3 K27M histone-mutant genotype were analysed at a national referral centre. Morphological characteristics including tumour epicentre(s), T2/FLAIR and Gadolinium enhancement patterns, calcification, haemorrhage and cyst formation were recorded. Multiple apparent diffusion coefficient (ADCmin, ADCmean) regions of interest were sited in solid tumour and normal appearing white matter (ADCNAWM) using post-processing software (Olea Sphere v2.3, Olea Medical). ADC histogram data (2nd, 5th, 10th percentile, median, mean, kurtosis, skewness) were calculated from volumetric tumour segmentations and tested against the regions of interest (ROI) data (Wilcoxon signed rank test). / Results: The median interval from imaging to tissue diagnosis was 9 (range, 0–74) days. The structural MR imaging findings varied between individuals and within tumours, often featuring signal heterogeneity on all MR sequences. All gliomas demonstrated contact with the brain midline, and 67% exhibited rim-enhancing necrosis. The mean ROI ADCmin value was 0.84 (±0.15 standard deviation, SD) ×10−3 mm2/s. In the largest tumour cross-section (excluding necrosis), an average ADCmean value of 1.12 (±0.25)×10−3 mm2/s was observed. The mean ADCmin/NAWM ratio was 1.097 (±0.149), and the mean ADCmean/NAWM ratio measured 1.466 (±0.299). With the exception of the 2nd centile, no statistical difference was observed between the regional and histogram derived ADC results. / Conclusions: H3 K27M-mutant gliomas demonstrate variable morphology and diffusivity, commonly featuring moderately low ADC values in solid tumour. Regional ADC measurements appeared representative of volumetric histogram data in this study

Investigating brain connectivity heritability in a twin study using diffusion imaging data

Heritability of brain anatomical connectivity has been studied with diffusion-weighted imaging (DWI) mainly by modeling each voxel's diffusion pattern as a tensor (e.g., to compute fractional anisotropy), but this method cannot accurately represent the many crossing connections present in the brain. We hypothesized that different brain networks (i.e., their component fibers) might have different heritability and we investigated brain connectivity using High Angular Resolution Diffusion Imaging (HARDI) in a cohort of twins comprising 328 subjects that included 70 pairs of monozygotic and 91 pairs of dizygotic twins. Water diffusion was modeled in each voxel with a Fiber Orientation Distribution (FOD) function to study heritability for multiple fiber orientations in each voxel. Precision was estimated in a test-retest experiment on a sub-cohort of 39 subjects. This was taken into account when computing heritability of FOD peaks using an ACE model on the monozygotic and dizygotic twins. Our results confirmed the overall heritability of the major white matter tracts but also identified differences in heritability between connectivity networks. Inter-hemispheric connections tended to be more heritable than intra-hemispheric and cortico-spinal connections. The highly heritable tracts were found to connect particular cortical regions, such as medial frontal cortices, postcentral, paracentral gyri, and the right hippocampus

Quantitative Diffusion Tensor Image Analysis: A Clinical Approach to Central Nervous System Injuries

Since the introduction of magnetic resonance imaging (MRI), the full extent of its possibilities has been extensively studied. Diffusion weighted imaging is a specific MRI protocol that enables the quantitative study of water diffusion in tissue. More recently, diffusion imaging has been extended to diffusion tensor imaging (DTI), which can extract detailed information of tissue microstructure. Overall, the most popular clinical application of DTI is the assessment of human brain white matter (WM). DTI can reveal changes in the brain WM microstructure that are not visible by other means of medical imaging. This microstructural resolution allows DTI to be used for the detection of several neuropathologies affecting the brain’s neural network, such as traumatic brain injuries and various types of neurodegenerative disorders.Mild traumatic brain injury (mTBI) can be defined as a traumatically induced brain function disruption which, in most cases, is not detectable by conventional medical imaging. mTBIs are grievous ailments due to high occurrence and a lack of distinct quantitative diagnostic tools and biomarkers. This signifies that the diagnosis of mTBI is based on subjective clinical measures. Extensive research has been carried out in order to find a clear correlation between DTI derived quantitative metrics and the post-mTBI brain WM. No uniform evidence of absolute conditions of pathology or association with post-injury prognosis has yet been found. However, many previous studies report different correlations between DTI metrics and postinjury brain WM. Unfortunately, the observed changes vary between studies, and final conclusions on the effects of mTBI on brain WM have yet to be made. One source of variation is the incoherency of the analysis methods used in the assessment of mTBI patients. Additionally, the heterogeneity of the studied patient cohorts hinders the chances of drawing a generalisable clinical conclusion.Our work aims to overcome the issues in quantitative mTBI analysis methods by introducing a simple yet robust automated analysis method for human brain WM analysis. Our research began by applying a novel third-party group level analysis method, tract-based spatial statistics (TBSS), to an mTBI patient sample. We tested the whole sample and several subgroups for abnormal WM, but the results were negative. It was also noted during the study that TBSS would not be a suitable tool for clinical mTBI diagnostic purposes as the method is not fully modifiable for the assessment of individual patients and involves an excessive amount of complex image data manipulation. An additional study of traumatic spinal cord injury (SCI) patients was successfully performed applying TBSS. We found widespread neurodegenerative changes in the post-SCI cerebral WM, but also signs of possible neuroplasticity. The results further confirmed the method’s applicability to neuropathologic conditions with homogeneous effects on the brain WM microstructure.Based on our findings, we began to create an automated analysis method using a region of interest (ROI) approach. We utilised human brain atlas-based ROIs in the analysis, which were automatically registered to the analysed subjects. The procedure ensures that the subjects’ images are not heavily processed. This in turn minimises the bias caused by image manipulation. The patients were compared against a normal population DTI reference value model created from our control subjects. The preliminary normal population DTI model created for the purpose was a successful quantitative model of DTI reference values. The normal population model could be used in a variety of clinical applications if a large enough number of control subjects were introduced to the model. The normal model would be especially useful in support of mTBI diagnosis methods.In summary, this thesis has three conclusions. First, we found no DTI measurable associations between WM integrity and acute mTBI when applying TBSS. Second, we found extensive WM changes in the post-SCI brain, which imply an ongoing neuroplastic process in addition to the initial SCI-induced changes. These cerebral WM changes were far more extensive than previously reported. Third, an automated quantitative DTI brain analysis method with prospective clinical applications was introduced. The sensitivity and specificity of the automated method is at an acceptable level when used in conjunction with our preliminary control population set. For clinical applicability, the method requires minor refinements to its usability. More importantly, the normal population model needs to be updated to clinical standards by increasing its statistical power. A large enough normal population data pool could be achieved through an MRI data collection scheme resembling that of a biobank data collection method. In addition, machine learning could be applied in future to create better statistical models for the analysis with more accurate model predicted DTI scalar values.Jo magneettikuvantamisen (MK) alkuajoista lähtien kyseinen kuvantamismodaliteetti on herättänyt runsasta mielenkiintoa sen laajojen mahdollisuuksien ansiosta. MK:ta käytetään laajalti sekä rutinoidusti potilastutkimuksissa että edistyksellisissä tutkimuksissa. Diffuusiopainotteisella kuvantamisella voidaan arvioida kudoksen mikroskooppista rakennetta veden diffuusiota mittaamalla. Myöhemmässä vaiheessa diffuusiokuvauksen rinnalle saapui tarkempi tapa määrittää kudoksen rakennetta: diffuusiotensorikuvantaminen (DTI). DTI:n avulla voidaan tutkia aivojen hienorakennetta sekä mikroskooppisia rakenteenmuutoksia, joita ei voida havaita muilla kuvantamismenetelmillä. DTI on mahdollistanut useiden neuropatologisten sairauksien kvantifioinnin lääketieteellisen kuvantamisen avulla, ja varsinkin hermoston rappeumasairauksia voidaan evaluoida DTI:llä.Lievä aivovamma on ulkoisen voiman aiheuttama aivotoiminnan häiriö tai rakenteellinen vaurio, jota usein ei pystytä havaitsemaan kuvantamisen avulla. Suuren ilmaantuvuutensa, yhteisöllisten kustannusten sekä haastavan diagnostiikan takia lievien aivovammojen ennaltaehkäisy on tärkeää. Lievien aivovammojen diagnostiikka perustuu kliinisen arviointiin, jota perinteiset kuvantamistutkimukset (tietokonetomografia ja MK) täydentävät. Perinteisten aivokuvantamistutkimusten ollessa useimmiten löydöksettömiä vammamuutosten suhteen, diagnostiikka jää virhealttiin kliinisen arvioinnin varaan. Objektiivisille diagnostisille menetelmille olisi huutava tarve. DTI-menetelmää on tutkittu pitkään mahdollisena objektiivisena diagnostisena työkaluna. Paljon tutkimusta on tehty DTI skalaarien ja lievien aivovammojen välisen yhteyden löytämiseksi. Nykyisten tutkimustulosten valossa ei voida vielä todeta yksiselitteisen DTI indikaattorin olemassaoloa. DTI:llä nähtävien aivojen valkean aineen muutoksien on kuitenkin tutkimuksissa todettu olevan kytköksissä lievien aivovammojen patologiaan. Valitettavasti tutkimustulokset ovat osittain ristiriitaisia, joten lopullista johtopäätöstä ei vielä voida kirjallisuuden perusteella tehdä. Ristiriitaisten tulosten mahdollinen selitys tosin lienee huomattavasti vaihtelevat tutkimukselliset metodit sekä aineistot.Tutkimuksellamme pyrimme yhtenäistämään aivojen kvantitatiivisen kuvaanalyysin menetelmiä tuomalla kehittelemämme automatisoidun menetelmän kliiniseen ympäristöön. Analyysimme on tehty mahdollisimman yksinkertaiseksi, jotta menetelmä olisi läpinäkyvä, toistettava ja käytäntöön implementoitava. Tutkimuksemme alussa sovelsimme hiljattain julkaistua analyysimenetelmää, Tractbased spatial statisticsia (TBSS) potilaisiin, joilla on todettu lievä aivovamma. Vertasimme aivovammapotilaita verrokkeihin eri tutkimusasetelmissa, mutta emme löytäneet eroa ryhmien välillä. Negatiivisten tulosten valossa päädyimme johtopäätökseen, että TBSS ei ole sopiva menetelmä lievien aivovammojen analyysiin. Vertasimme seuraavaksi selkäydinvammapotilaiden aivojen valkeaa ainetta verrokkien valkeaan aineeseen hyödyntäen muutamaa eri tutkimusasetelmaa. Tutkimuksemme paljasti laaja-alaisia degeneratiivisia sekä mahdollisia aivojen muuntautumiskykyä indikoivia muutoksia selkärankavammapotilaiden aivoissa. Tulokset myös varmistivat TBSS:n soveltuvuuden kollektiivisia valkean aineen muutoksia aiheuttavien neurodegeneratiivisten sairauksien analyysiin.Saatujen kliinisten tulosten perusteella lähdimme kehittämään uutta analyysimenetelmää, joka olisi sovellettavissa lievien aivovammojen lisäksi myös muihin erityyppisiin neurologisiin sairauksiin. Päädyimme mielenkiintoalueisiin (region of interest, ROI) perustuvaan analyysiin, jota voidaan käyttää yksittäisten potilaiden analyysiin. ROI:na käytämme valmiita rakenteellisia aivokartastoja, joiden ROIt rekisteröidään lineaarisesti sekä epälineaarisesti kohteiden DTI kuviin. Tämä lähtökohtaisesti auttaa vähentämään kuvankäsittelyn aiheuttamaa virhettä kvantitatiivisiin arvoihin, sillä kuvattua dataa ei käsitellä. Potilaiden DTI-kuvien kvantitatiivisia arvoja vertaillaan verrokkiaineiston avulla luotuun referenssiarvomalliin. Muodostimme alustavan normaalipopulaatioon perustuvan DTI mallin verrokkidatamme avulla, ja testasimme mallin herkkyyttä ja tarkkuutta, jotka molemmat olivat tyydyttävällä tasolla. Jatkossa riittävän isolla verrokkiaineistolla voitaisiin luoda tarkempi malli normaalipopulaatiosta, jolla voitaisiin mallintaa aivojen DTI-arvoja iän funktiona. Eritoten tämä olisi hyödyllistä lievien aivovammojen tunnistamisessa.Väitöskirjan yhteenveto voidaan jakaa kolmeen johtopäätökseen. Ensiksi; emme löytäneet TBSS:n avulla eroja lievän aivovamman saaneiden potilaiden ja verrokkiaineistomme valkean aineen mikrorakenteessa. Toiseksi; löytämämme poikkeamat selkäydinvammapotilaiden aivojen valkeassa aineessa ovat huomattavasti laajemmat kuin on aiemmin raportoitu. Laaja-alaiset muutokset viittasivat vamman jälkeen esiintyvän neuroplastisiteetin jatkuvan vielä pitkään akuutin trauman jälkeen. Kolmanneksi; esittelemämme automatisoitu DTIanalyysimenetelmä on monikäyttöinen työkalu, jonka kliinistä käyttökelpoisuutta voidaan parantaa lisäämällä verrokkiaineiston kokoa sekä parantelemalla yleistä käytettävyyttä. Riittävän verrokkiaineiston keruu voitaisiin taata esimerkiksi biopankkityylisellä DTI-datankeruujärjestelmällä. Lisäksi tarkempaa tilastollista mallia varten voitaisiin soveltaa tekoälyä koneoppimisen muodossa, jolloin myös DTI skalaarien ennustearvot tarkentuisivat verrokkiaineiston kasvamisen myötä

TEST-RETEST RELIABILITY OF FRACTIONAL ANISOTROPY IN 5-YEAR-OLDS

Diffusion tensor imaging (DTI) has provided great insights to the microstructural features of developing brain and has been shown to be reliable in infants. However, the repeatability of the DTI scalars for older pediatric age groups has not been thoroughly addressed. In this study, DTI scans of 5-year-olds were used to investigate the test-retest reliability of three different measurements with both voxel-wise and region of interest (ROI) analysis. Out of 96 diffusion encoding directions, divided into three parts, 20 unique diffusion encoding directions were chosen per measurement from 48 subjects. Tract based spatial analysis (TBSS) was used to extract fractional anisotropy (FA) values from those images and using the FA values the repeatability of the measurements was assessed by intraclass correlation coefficient (ICC) and standard error of measurement (SEM). Overall, FA values had high repeatability both in voxel-based analysis (ICC>0.73) and ROI analysis (for non-skeletonized ROI type 88% of the ROI labels: ICC>0.75, for skeletonized ROI type 87% of the ROI labels: ICC>0.75). Using a skeleton in the ROI analysis did not contribute to the repeatability and the volume size was found to be a contributing factor for repeatability. Interscanner reliability as well as reliability measured by using different atlases are yet to be investigated in 5-year-old data

DTI study of the frontal lobes, hippocampus, amygdala and neurocognitive assessment in patients with bipolar-schizophrenic spectrum disorders

Schizophrenic and bipolar disorders are complex and disabling psychiatric diseases whose recent neurobiological, neuropsychological and genetic findings is in contrast with the traditional categorical approach of psychiatric nosography. The multiple threshold model describes the complex relationship between the shared genetic background and the wide phenotypic expression in the various disorders ascribed to the bipolar schizophrenic spectrum. This model assumes that common genes are involved in a spectrum of disorders ranging from major depression, to bipolar and schizophrenia and that their effect is additive along a continuum of risk: when a certain threshold is exceeded the quantitative difference becomes a qualitative difference that manifests itself as a different disorder (eg. switching from major depression to bipolar disorder to schizo-affective disorder than schizophrenic) (Kelsoe 2003). A field of great interest in neuroscience and psychiatric research is finding evidence of shared clinical features and pathophysiological pathways between these disorders. Genetics, histopathological and MRI in vivo studies have consistently revealed abnormalities in brain neural networks among these disorders. The Diffusion tensor imaging (DTI) is a fundamental brain imaging technique to investigate white matter‘s structural connectivity, despite its relative recently introduction in clinical practice and research. AIM OF THE STUDY: to investigate the DTI measures of WM integrity in specific brain regions and the cognitive performances in a group of patients with the bipolar-schizophrenic spectrum disorders and a group of healthy control subjects. In order to verify or exclude specific diagnosis-related differences, we performed cross-sectional comparisons between the sub group of bipolar patients, schizophrenic patients and healthy controls. METHODS: 64 patients -32 schizophrenic (SZ), 25 bipolars (BP)-, and 31 healthy controls underwent 1,5 T MRI scanning, comprehending DTI acquisitions and volumetric T1 3D with a specifically designed acquisition protocol, at the Neuroradiology Unit of Conegliano Hospital. Then we calculate DTI indices of bilateral frontal lobes, hippocampus and amygdala using ANALYZE 10.0 software, all recruited subjects underwent clinical and standardized, thorough neurocognitive assessment (ENB, Mondini et al; WCST). RESULTS: we found statistically significant alterations of the DTI indicies for the regions of interest (ROIs), that pointed out shared abnormalities among the patients with bipolar schizophrenic-spectrum disorder regarding frontal lobes with respect to healthy control subjects; more interesting, we find a complex pattern of alterations among the hippocampal region and amygdala between the patients and the control group and also comparing the schizophrenic with the bipolar patients. Moreover we found out a significant impairment on the performances during the neurocognitive and neuro psychological assessment across all tests in the patients opposed to healthy controls. We also pointed out some interesting correlations between the scores of the battery test administrated (ENB, Mondini et al; WCST) and the FA and ADC indices for the frontal lobes, as expected from the abundant current literature, but also for the hippocampus and amygdala. This approach could help to the understand some aspects of the complexity of the Bipolar-schizophrenic spectrum disorders CONCLUSION: in this study we highlighted shared tracts among the spectrum disorders such as the common neurocognitive and neuropsychological impairment, the compromised structural integrity of the white matter in the frontal regions and probably, in some degree, even of the right hippocampus, implying that these two disorders may share some common pathophysiological mechanisms, further demonstrating how alterations in the cerebral white matter networks, involving the frontal regions and also subcortical structures, such as the hippocampus and amygdala, contribute to the pathophysiological process of schizophrenia and bipolar disorder. Our findings also bring out differences among the two groups of patients, with the bipolars showing a most prominent alteration of the left amygdala and the schizophrenics a predominant deficit on the right hippocampus and amygdala. In the bipolar-schizophrenic spectrum disorders it might be speculated that the alteration and disruption of white matter connectivity, and their correlation with neurocognitive performances, could be interpreted as a possible “biological marker”. This might help to specifically define the common and the different aspects of these disorders in order to better understand their complex pathophysiological mechanisms, jet to be clearly defined