MRI and image quantitation for drug assessment - Growth effects of anabolic steroids and precursors

MRI and image quantitation play an expanding role in modern drug research, because MRI offers high resolution and non-invasive ability, and provides excellent soft tissue contrast. Moreover, with development of effective image segmentation and analysis methods, in-vivo and serial tissue growth measurements could be assessed. In the study, MR image acquisition and analysis protocol were established and validated for investigating the effects of anabolic steroids and precursors on muscle growth and body composition in a guinea pig model. Semi-automatic and interactive segmentation methods were developed to accurately label the tissue of interest for tissue volume estimation. In addition, a longitudinal tissue area outlining procedure was proposed for study of tissue geometric features in relation to tissue growth. Finally, a fully automatic data retrieval and analysis scheme was implemented to facilitate the overall huge amount of image quantitation, statistical analysis, as well as study group comparisons. As a result, highly significant differences in muscle and organ growth were detected between intact and castrated guinea pigs using the selected anabolic steroids, indicating the viability of employing such protocol to assess other anabolic steroids. Furthermore, the anabolic potential of selected steroid precursors and their effects on muscle growth, in comparison with that in respective positive control groups of castrated guinea pigs, were evaluated with the proposed protocol. © 2005 IEEE.published_or_final_versio

Imaging of temporomandibular joint: Approach by direct volume rendering

Materials and Methods: We have studied the temporom-andibular joint anatomy, directly on the living, from 3D images obtained by medical imaging Computed Tomography and Nuclear Magnetic Resonance acquisition, and subsequent re-engineering techniques 3D Surface Rendering and Volume Rendering. Data were analysed with the goal of being able to isolate, identify and distinguish the anatomical structures of the joint, and get the largest possible number of information utilizing software for post-processing work.Results: It was possible to reproduce anatomy of the skeletal structures, as well as through acquisitions of Magnetic Resonance Imaging; it was also possible to visualize the vascular, muscular, ligamentous and tendinous components of the articular complex, and also the capsule and the fibrous cartilaginous disc. We managed the Surface Rendering and Volume Rendering, not only to obtain three-dimensional images for colour and for resolution comparable to the usual anatomical preparations, but also a considerable number of anatomical, minuter details, zooming, rotating and cutting the same images with linking, graduating the colour, transparency and opacity from time to time.Conclusion: These results are encouraging to stimulate further studies in other anatomical districts.Background: The purpose of this study was to conduct a morphological analysis of the temporomandibular joint, a highly specialized synovial joint that permits movement and function of the mandible

An interactive three dimensional approach to anatomical description—the jaw musculature of the Australian laughing kookaburra (Dacelo novaeguineae)

The investigation of form-function relationships requires a detailed understanding of anatomical systems. Here we document the 3-dimensional morphology of the cranial musculoskeletal anatomy in the Australian Laughing Kookaburra Dacelo novaeguineae, with a focus upon the geometry and attachments of the jaw muscles in this species. The head of a deceased specimen was CT scanned, and an accurate 3D representation of the skull and jaw muscles was generated through manual segmentation of the CT scan images, and augmented by dissection of the specimen. We identified 14 major jaw muscles: 6 in the temporal group (M. adductor mandibulae and M. pseudotemporalis), 7 in the pterygoid group (M. pterygoideus dorsalis and M. pterygoideus ventralis), and the single jaw abductor M. depressor mandibulae. Previous descriptions of avian jaw musculature are hindered by limited visual representation and inconsistency in the nomenclature. To address these issues, we: (1) present the 3D model produced from the segmentation process as a digital, fully interactive model in the form of an embedded 3D image, which can be viewed from any angle, and within which major components can be set as opaque, transparent, or hidden, allowing the anatomy to be visualised as required to provide a detailed understanding of the jaw anatomy; (2) provide a summary of the nomenclature used throughout the avian jaw muscle literature. The approach presented here provides considerable advantages for the documentation and communication of detailed anatomical structures in a wide range of taxa

MRI and image quantitation for assessment of the growth effects of anabolic steroid precursors in a guinea pig model

MRI and image quantitation play an expanding role in modern drug research. With effective image segmentation and analysis methods, in vivo and longitudinal tissue growth can be assessed. The effects of the nandrolone and testosterone steroids on muscle growth have been investigated previously, in which MRI acquisition and analysis protocol were established, and excellent correlations were found between MRI measurement and dissection analyzes. In this study, the MRI protocol was used to evaluate the anabolic potential of 4 steroid precursors. The effects on muscle growth in castrated guinea pigs, in comparison with that of respective positive control steroids were determined.MRI and image quantitation play an expanding role in modern drug research. With effective image segmentation and analysis methods, in vivo and longitudinal tissue growth can be assessed. The effects of the nandrolone and testosterone steroids on muscle growth have been investigated previously, in which MRI acquisition and analysis protocol were established, and excellent correlations were found between MRI measurement and dissection analyzes. In this study, the MRI protocol was used to evaluate the anabolic potential of 4 steroid precursors. The effects on muscle growth in castrated guinea pigs, in comparison with that of respective positive control steroids were determined.published_or_final_versio

Segmentation of Human Muscles of Mastication from Magnetic Resonance Images

Ph.DDOCTOR OF PHILOSOPH

Deep learning-based quantification of temporalis muscle has prognostic value in patients with glioblastoma

Background Glioblastoma is the commonest malignant brain tumour. Sarcopenia is associated with worse cancer survival, but manually quantifying muscle on imaging is time-consuming. We present a deep learning-based system for quantification of temporalis muscle, a surrogate for skeletal muscle mass, and assess its prognostic value in glioblastoma. Methods A neural network for temporalis segmentation was trained with 366 MRI head images from 132 patients from 4 different glioblastoma data sets and used to quantify muscle cross-sectional area (CSA). Association between temporalis CSA and survival was determined in 96 glioblastoma patients from internal and external data sets. Results The model achieved high segmentation accuracy (Dice coefficient 0.893). Median age was 55 and 58 years and 75.6 and 64.7% were males in the in-house and TCGA-GBM data sets, respectively. CSA was an independently significant predictor for survival in both the in-house and TCGA-GBM data sets (HR 0.464, 95% CI 0.218–0.988, p = 0.046; HR 0.466, 95% CI 0.235–0.925, p = 0.029, respectively). Conclusions Temporalis CSA is a prognostic marker in patients with glioblastoma, rapidly and accurately assessable with deep learning. We are the first to show that a head/neck muscle-derived sarcopenia metric generated using deep learning is associated with oncological outcomes and one of the first to show deep learning-based muscle quantification has prognostic value in cancer

Deep Learning vs. Atlas-Based Models for Fast Auto-Segmentation of the Masticatory Muscles on Head and Neck CT Images

BACKGROUND: Impaired function of masticatory muscles will lead to trismus. Routine delineation of these muscles during planning may improve dose tracking and facilitate dose reduction resulting in decreased radiation-related trismus. This study aimed to compare a deep learning model with a commercial atlas-based model for fast auto-segmentation of the masticatory muscles on head and neck computed tomography (CT) images. MATERIAL AND METHODS: Paired masseter (M), temporalis (T), medial and lateral pterygoid (MP, LP) muscles were manually segmented on 56 CT images. CT images were randomly divided into training (n = 27) and validation (n = 29) cohorts. Two methods were used for automatic delineation of masticatory muscles (MMs): Deep learning auto-segmentation (DLAS) and atlas-based auto-segmentation (ABAS). The automatic algorithms were evaluated using Dice similarity coefficient (DSC), recall, precision, Hausdorff distance (HD), HD95, and mean surface distance (MSD). A consolidated score was calculated by normalizing the metrics against interobserver variability and averaging over all patients. Differences in dose (∆Dose) to MMs for DLAS and ABAS segmentations were assessed. A paired t-test was used to compare the geometric and dosimetric difference between DLAS and ABAS methods. RESULTS: DLAS outperformed ABAS in delineating all MMs (p \u3c 0.05). The DLAS mean DSC for M, T, MP, and LP ranged from 0.83 ± 0.03 to 0.89 ± 0.02, the ABAS mean DSC ranged from 0.79 ± 0.05 to 0.85 ± 0.04. The mean value for recall, HD, HD95, MSD also improved with DLAS for auto-segmentation. Interobserver variation revealed the highest variability in DSC and MSD for both T and MP, and the highest scores were achieved for T by both automatic algorithms. With few exceptions, the mean ∆D98%, ∆D95%, ∆D50%, and ∆D2% for all structures were below 10% for DLAS and ABAS and had no detectable statistical difference (P \u3e 0.05). DLAS based contours had dose endpoints more closely matched with that of the manually segmented when compared with ABAS. CONCLUSIONS: DLAS auto-segmentation of masticatory muscles for the head and neck radiotherapy had improved segmentation accuracy compared with ABAS with no qualitative difference in dosimetric endpoints compared to manually segmented contours

Morphological characteristics of masticatory muscles in Wistar rats (Rattus norvegicus albinus) by computed microtomography

Orientador: Alexandre Rodrigues FreireDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Odontologia de PiracicabaResumo: Esta dissertação de mestrado teve como objetivo estuda a morfologia dos músculos da mastigação de ratos da linhagem Wistar. Esta linhagem de roedores é amplamente utilizada como modelo experimental para estudos direcionados ao entendimento dos efeitos das diferentes condições oclusais, de normalidade e patológicas, nos tecidos periodontais de suporte. Ao longo dos anos, foram obtidos dados importantes relacionados à tais efeitos, porém há uma lacuna de conhecimento relacionados à esses dados devido a falta de estudos direcionados ao entendimento da dinâmica mastigatória destes animais. O estudo da anatomia dos músculos mastigatórios, neste caso, torna-se base essencial para entender tal dinâmica. Foi relizado um estudo em que se utilizou 10 ratos machos adultos, da linhagem Wistar, que foram eutanaziados aos 2 meses de idade. As cabeças dos animais foram removidas e dissecadas para exposição dos músculos da mastigação: masseter, temporal, pterigoideos e zigomaticomandibular. Após fixação em formol tamponado, as peças foram lavadas em água destilada e mergulhadas em uma solução de diiodo iodeto de potássio (I2KI) durante 1 mês. Foram realizadas microtomografias em alta resolução das cabeças, das quais foram obtidas imagens sequenciais que foram transferidas ao software Materialise Mimics v18 para segmentação das imagens. Na segmentação foi utilizada a densidade da estrutura muscular, aumentada pela ação da solução de iodo, para isolar cada músculo e construir uma superfície 3D. A partir da superfície 3D foi realizada a descrição anatômica caracterizando forma, direção das fibras, origem e inserção muscular. Assim, foi possível caracterizar anatomicamente os músculos da mastigação que irá contribuir para estudos futuros envolvendo a dinâmica muscularAbstract: This master degree dissertation aimed to study the morphology of masticatory muscles of Wistar rats. This rodent lineage is widely used as an experimental model for studies aimed at understanding the effects of different occlusal conditions, both normal and pathological, on the periodontal tissues. Over the years, important data related to these effects have been obtained, but there is a knowledge gap related to these data due to the lack of studies aimed at understanding the masticatory dynamics in these animals. The anatomical study of the masticatory muscles, in this case, becomes an essential basis for understanding such dynamics. A study was conducted in which 10 adult male Wistar rats were euthanized at 2 months of age. The heads of the animals were removed and dissected for exposure to the chewing muscles: masseter, temporallis, pterygoid and zygomaticcomandibularis. After fixation in buffered formaldehyde solution, the pieces were washed in distilled water and immersed in iodine solution (I2KI) during 1 month. High resolution microCT of the heads were obtained, which sequential images were obtained and transferred to the Materialise Mimics v18 software for image segmentation. In the segmentation, the density of the muscular structure, increased by the action of the iodine solution, was used to isolate each muscle and construct a 3D surfaces. From the 3D surfaces, the anatomical description was carried out, characterizing shape, fiber directions and muscular insertions. Thus, it was possible to anatomically characterize masticatory muscles that will contribute to future studies involving muscle dynamicsMestradoAnatomiaMestra em Biologia Buco-Dental33003033001P3CAPE

Temporal muscle thickness is an independent prognostic marker in melanoma patients with newly diagnosed brain metastases.

OBJECTIVES: The purpose of this study was to evaluate the prognostic relevance of temporal muscle thickness (TMT) in melanoma patients with newly diagnosed brain metastases. METHODS: TMT was retrospectively assessed in 146 melanoma patients with newly diagnosed brain metastases on cranial magnetic resonance images. Chart review was used to retrieve clinical parameters, including disease-specific graded prognostic assessment (DS-GPA) and survival times. RESULTS: Patients with a TMT > median showed a statistically significant increase in survival time (13 months) compared to patients with a TMT < median (5 months; p < 0.001; log rank test). A Cox regression model revealed that the risk of death was increased by 27.9% with every millimeter reduction in TMT. In the multivariate analysis, TMT (HR 0.724; 95% 0.642-0.816; < 0.001) and DS-GPA (HR 1.214; 95% CI 1.023-1.439; p = 0.026) showed a statistically significant correlation with overall survival. CONCLUSION: TMT is an independent predictor of survival in melanoma patients with brain metastases. This parameter may aid in patient selection for clinical trials or to the choice of different treatment options based on the determination of frail patient populations