Multiple myeloma and other plasma cell disorders infiltrate the bone marrow in different patterns. While some patients show a homogeneous distribution of the clonal plasma cells others present with focal accumulations, commonly called focal lesions. Novel imaging techniques can provide information on these infiltration patterns and, due to their low invasiveness, can be performed repeatedly and therefore be used for monitoring. Conventional magnetic resonance imaging (MRI) has a high sensitivity for bone marrow assessment but cannot safely differentiate between active and inactive lesions. Therefore, positron emission tomography, especially combined with computed tomography (PET/CT), has been more widely used, at least for the monitoring of treatment response. Comparative, but mostly retrospective studies, have shown that functional MRI techniques, namely diffusion-weighted imaging (DWI), which assesses the movement of water molecules, can evaluate tissue cellularity with high sensitivity, which challenges the dominance of PET/CT in treatment response assessment. This review will discuss the benefits and challenges of DWI and compare it to other available imaging techniques used in patients with monoclonal plasma cell disorders

Over the last few years, diffusion-weighted imaging (DWI) has become increasingly relevant in the diagnostic assessment of peritoneal carcinomatosis. The aim of this study was to investigate the benefits of high-b DWI (c-DWI) compared to standard DWI in patients with peritoneal carcinomatosis. A cohort of 40 patients with peritoneal carcinomatosis were included in this retrospective study. DWI was performed with b-values of 50, 400, and 800 or 1000 s/mm2 on a 1.5-T magnetic resonance imaging (MRI) scanner. C-DWI was calculated using a mono-exponential model with high b-values of 1000, 2000, 3000, 4000, and 5000 s/mm2. All c-DWI images with high b-values were compared in terms of volume, detectability of peritoneal lesions, and image quality with the DWI sequence acquired with a b-value of 800 or 1000 s/mm2 by two readers. In the group with a b-value of 800 s/mm2, there was no statistically significant difference in terms of lesion volume. In the second group with a b-value of 1000 s/mm2, peritoneal carcinomatosis lesions were statistically significantly larger than in the c-DWI with a- high b-value of 2000 s/mm2 (median 7 cm3, range 1–26 cm3vs. median 6 cm3, range 1–83 cm3, p < 0.05). In both groups, there was a marked decrease in the detectability of peritoneal lesions starting at b = 2000 s/mm2. In addition, image quality decreased noticeably from c-DWI at b = 3000 s/mm2. In both groups, all images with high b-values at b = 4000 s/mm2 and 5000 s/mm2 were not diagnostically valuable due to poor image quality. The c-DWI technique offers good diagnostic performance without additional scanning time. High c-DWI b-values up to b = 1000 s/mm2 provide comparable detectability of peritoneal carcinomatosis compared to standard DWI. Higher b-values over 1500 s/mm2 result in lower image quality, which might lead to misdiagnosis.

This work explores if combining information from multiple Magnetic Resonance Imaging (MRI) modalities provides improved interpretation of brain biological architecture as each MR modality can reveal different characteristics of underlying anatomical structures. Structural MRI provides a means for high-resolution quantitative study of brain morphometry. Diffusion-weighted MR imaging (DWI) allows for low-resolution modeling of diffusivity properties of water molecules. Structural and diffusion-weighted MRI modalities are commonly used for monitoring the biological architecture of the brain in normal development or neurodegenerative disease processes. Structural MRI provides an overall map of brain tissue organization that is useful for identifying distinct anatomical boundaries that define gross organization of the brain. DWI models provide a reflection of the micro-structure of white matter (WM), thereby providing insightful information for measuring localized tissue properties or for generating maps of brain connectivity. Multispectral information from different structural MR modalities can lead to better delineation of anatomical boundaries, but careful considerations should be taken to deal with increased partial volume effects (PVE) when input modalities are provided in different spatial resolutions. Interpretation of diffusion-weighted MRI is strongly limited by its relatively low spatial resolution. PVE's are an inherent consequence of the limited spatial resolution in low-resolution images like DWI. This work develops novel methods to enhance tissue classification by addressing challenges of partial volume effects encountered from multi-modal data that are provided in different spatial resolutions. Additionally, this project addresses PVE in low-resolution DWI scans by introducing a novel super-resolution reconstruction approach that uses prior information from multi-modal structural MR images provided in higher spatial resolution. The major contributions of this work include: 1) Enhancing multi-modal tissue classification by addressing increased PVE when multispectral information come from different spatial resolutions. A novel method was introduced to find pure spatial samples that are not affected by partial volume composition. Once detecting pure samples, we can safely integrate multi-modal information in training/initialization of the classifier for an enhanced segmentation quality. Our method operates in physical spatial domain and is not limited by the constraints of voxel lattice spaces of different input modalities. 2) Enhancing the spatial resolution of DWI scans by introducing a novel method for super-resolution reconstruction of diffusion-weighted imaging data using high biological-resolution information provided by structural MRI data such that the voxel values at tissue boundaries of the reconstructed DWI image will be in agreement with the actual anatomical definitions of morphological data. We used 2D phantom data and 3D simulated multi-modal MR scans for quantitative evaluation of introduced tissue classification approach. The phantom study result demonstrates that the segmentation error rate is reduced when training samples were selected only from the pure samples. Quantitative results using Dice index from 3D simulated MR scans proves that the multi-modal segmentation quality with low-resolution second modality can approach the accuracy of high-resolution multi-modal segmentation when pure samples are incorporated in the training of classifier. We used high-resolution DWI from Human Connectome Project (HCP) as a gold standard for super-resolution reconstruction evaluation to measure the effectiveness of our method to recover high-resolution extrapolations from low-resolution DWI data using three evaluation approaches consisting of brain tractography, rotationally invariant scalars and tensor properties. Our validation demonstrates a significant improvement in the performance of developed approach in providing accurate assessment of brain connectivity and recovering the high-resolution rotationally invariant scalars (RIS) and tensor property measurements when our approach was compared with two common methods in the literature. The novel methods of this work provide important improvements in tools that assist with improving interpretation of brain biological architecture. We demonstrate an increased sensitivity for volumetric and diffusion measures commonly used in clinical trials to advance our understanding of both normal development and disease induced degeneration. The improved sensitivity may lead to a substantial decrease in the necessary sample size required to demonstrate statistical significance and thereby may reduce the cost of future studies or may allow more clinical and observational trials to be performed in parallel.

No description available.

Objective: Chronic recurrent multifocal osteomyelitis/ chronic non-bacterial osteomyelitis (CRMO/CNO) is a rare auto-inflammatory disease and typically manifests in terms of musculoskeletal pain. Because of a high frequency of musculoskeletal disorders in children/ adolescents, it can be quite challenging to distinguish CRMO/ CNO from nonspecific musculosketetal pain or from malignancies. The purpose of this study was to evaluate the visibility of CRMO lesions in a whole-body diffusion-weighted imaging (WB-DWI) technique and its potential clinical value to better characterize MR-visible lesions. Materials and methods: Whole-body imaging at 3T was performed in 16 patients (average: 13 years) with confirmed CRMO. The protocol included 2D Short Tau Inversion Recovery (STIR) imaging in coronal and axial orientation as well as diffusion-weighted imaging in axial orientation. Visibility of lesions in DWI and STIR was evaluated by two readers in consensus. The apparent diffusion coefficient (ADC) was measured for every lesion and corresponding reference locations. Results: A total of 33 lesions (on average 2 per patient) visible in STIR and DWI images (b = 800 s/mm2 and ADC maps) were included, predominantly located in the long bones. With a mean value of 1283 mm2/s in lesions, the ADC was significantly higher than in corresponding reference regions (782 mm2/s). By calculating the ratio (lesion to reference), 82% of all lesions showed a relative signal increase of 10% or higher and 76% (25 lesions) showed a signal increase of more than 15%. The median relative signal increase was 69%. Conclusion: This study shows that WB-DWI can be reliably performed in children at 3T and predominantly, the ADC values were substantially elevated in CRMO lesions. WB-DWI in conjunction with clinical data is seen as a promising technique to distinguish benign inflammatory processes (in terms of increased ADC values) from particular malignancies.

Prostatectomy, surgical resection of the whole prostate is a common treatment for high- risk prostate cancer. Common side effects include long-time urinary and or erectile dysfunction due to damage inflicted to periprostatic nerves. The aim of this study was to identify an optimal magnetic resonance diffusion tensor imaging protocol for visualization and quantification of these nerves, as pre-surgery visualization may help nerve-sparing surgery. Both scanner filter, parameters for accelerated scan techniques, diffusion-related acquisition parameters and post- processing tractography parameters were investigated. Seven healthy volunteers were scanned with a state-of-art 3 T MRI scanner with varying protocol parameters. Diffusion data were processed and analysed using Matlab and Explore DTI. The resulting protocol recommendation included a normalized scanner filter, a parallel imaging acceleration factor of 2, partial Fourier sampling of 6/8, a right-left phase encoding direction, a b-value of 600 s/mm2, monopolar gradient polarity with applied eddy current correction, four acquisitions of 12 diffusion- sensitizing gradient directions, and a reverse phase encoding approach for correction of geometrical image distortions induced by static field inhomogeneity. For post-processing tractography, the recommended parameters were a lower limit for fractional anisotropy of 0.05, a minimum tract length of 3 centimetres and a maximum turning angle between voxels of 60 degrees. The limited parameter range that was tested and the low number of volunteers can be regarded as limitations to this study. Future work should address these issues. Furthermore, feasibility of periprostatic nerve tracking with the optimized protocol should be tested in a patient study.

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第18227号 / 工博第3819号 / 新制||工||1585(附属図書館) / 31085 / 京都大学大学院工学研究科電気工学専攻 / (主査)教授 小林 哲生, 教授 引原 隆士, 教授 小山田 耕二 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

Diffusion-weighted imaging (DWI) has rapidly become an essential tool for the detection of malignant liver lesions. The aim of this study was to investigate the usefulness of high b-value computed DWI (c-DWI) in comparison to standard DWI in patients with hepatic metastases. In total, 92 patients with histopathologic confirmed primary tumors with hepatic metastasis were retrospectively analyzed by two readers. DWI was obtained with b-values of 50, 400 and 800 or 1000 s/mm2 on a 1.5 T magnetic resonance imaging (MRI) scanner. C-DWI was calculated with a monoexponential model with high b-values of 1000, 2000, 3000, 4000 and 5000 s/mm2. All c-DWI images with high b-values were compared to the acquired DWI sequence at a b-value of 800 or 1000 s/mm2 in terms of volume, lesion detectability and image quality. In the group of a b-value of 800 from a b-value of 2000 s/mm2, hepatic lesion sizes were significantly smaller than on acquired DWI (metastases lesion sizes b = 800 vs. b 2000 s/mm2: mean 25 cm3 (range 10–60 cm3) vs. mean 17.5 cm3 (range 5–35 cm3), p < 0.01). In the second group at a high b-value of 1500 s/mm2, liver metastases were larger than on c-DWI at higher b-values (b = 1500 vs. b 2000 s/mm2, mean 10 cm3 (range 4–24 cm3) vs. mean 9 cm3 (range 5–19 cm3), p < 0.01). In both groups, there was a clear reduction in lesion detectability at b = 2000 s/mm2, with hepatic metastases being less visible compared to c-DWI images at b = 1500 s/mm2 in at least 80% of all patients. Image quality dropped significantly starting from c-DWI at b = 3000 s/mm2. In both groups, almost all high b-values images at b = 4000 s/mm2 and 5000 s/mm2 were not diagnostic due to poor image quality. High c-DWI b-values up to b = 1500 s/mm2 offer comparable detectability for hepatic metastases compared to standard DWI. Higher b-value images over 2000 s/mm2 lead to a noticeable reduction in imaging quality, which could hamper diagnosis.

No description available.

Introduction : Les analyses de connectivité cérébrale dans les trois troubles majeurs d'hypersomnolence centrale, la narcolepsie de type I (NT1), de type II (NT2) et de l’hypersomnie idiopathique (HI) sont rares dans la littérature. Les études de connectivité structurelle indiquent comment les réseaux de fibres de matière blanche sont organisés et affectés dans le cas de patients atteints de troubles du système nerveux central. L’objectif principal de cette étude est d’observer si la connectivité structurelle est affectée dans la NT1, NT2 et l’HI comparativement à des sujets sains. Une diminution dans les mesures de connectivité globale dans les troubles d’hypersomnolence centrale et leur association à la sévérité des symptômes comme la somnolence sont supposées. Méthodes : Des sujets sains (HC, n=8) et des patients diagnostiqués avec soit l’HI (n=14), la NT1 (n=15) ou la NT2 (n=14) ont suivi une séance d'IRM avec l’imagerie pondérée en diffusion. Les mesures d’intégration (efficacité globale) et de ségrégation (efficacité locale et transitivité), l’index de petit monde, et le degré nodal ont été utilisés. Les variables cliniques d’inertie de sommeil, la somnolence, la dépression, l’anxiété, la sévérité d’hypersomnolence et la durée symptomatique ont été évaluées. Résultats et conclusion : Seul le groupe HI a démontré une efficacité globale significativement plus élevée que le groupe HC, qui pourrait être expliquée par une augmentation de la transmission GABAergique. Le groupe NT2 a démontré une association entre l’efficacité globale et les scores au ESS et HSI. Aucune autre différence significative n’a été démontrée pour les autres mesures globales ni pour les mesures régionales entre les groupes. / Introduction: Structural connectivity studies comparing all three central primary hypersomnolence disorder types, i.e., narcolepsy type I (NT1), type II (NT2) and idiopathic hypersomnia (IH) have been scarce. Differences in structural connectivity may indicate how circuits in the brain are affected in hypersomnolence disorders compared to healthy controls. The main goal of this study is to assess if differences exist between NT1, NT2 and IH patients compared to controls using structural imaging analyses. A decrease in global connectivity measures in all three central hypersomnolence disorders compared to healthy controls and an association to symptom severity like sleepiness is hypothesized. Methods: Patients diagnosed with either NT1 (n=15), NT2 (n=13) or IH (n=14), as well as healthy participants (HC, n=8) were recruited and underwent a DWI session. Data were preprocessed and analyzed using a model based on constrained spherical deconvolution with multi-shell and multi-tissue parameters. Integration (global efficiency) and segregation measures, small-world index and nodal degree were used to evaluate structural connectivity. Clinical variables of sleep inertia, sleepiness, hypersomnia severity, depression, anxiety, and disease duration were evaluated. Results and conclusion: Only IH patients showed a significantly higher global efficiency than HC. An increase in GABAergic transmission is a potential mechanism, but how it relates to IH symptoms is unclear. Global efficiency was also demonstrated to be associated with ESS and HSI scores in the NT2 group. There were no differences between groups for any of the other global or local measures.