Analysis Of Anatomical Changes Research Articles

Forum ophthalmicum – how to take control over accumulation of diagnostic data from macular OCT with benefit for both doctor and patient?

Wet age-related macular degeneration (wet AMD) is a disease which requires regular diagnostic tests such as macular optical coherent tomography which is extremely important both in diagnosis and disease monitoring. With constant aging of the population, we are dealing with an increasing incidence rate of AMD, which makes it even more important to have a tool allowing for quick and precise analysis of anatomical changes in macular region, particularly in the current complicated epidemiological situation when diagnostic time should be used most efficiently to plan the follow-up treatment. Forum® software allows for the precise analysis of many tests performed in a single patient and combining it with treatment effectiveness assessment which substantially accelerates the diagnostics.

Utilizing Deformable Image Registration and Quality Assurance to Automate Analysis of Anatomic Changes After Head and Neck Radiation Therapy

Deformable image registration (DIR) algorithms are clinically utilized in radiation therapy without quality assurance (QA) of the deformation vector fields (DVFs) produced. This study investigated the feasibility of simultaneous automated detection of anatomic changes and DIR-QA for patients who receive head and neck (H&N) radiation therapy. For 10 patients with H&N cancer, three DIR algorithms were used to map initial planning computed tomography (CT) images to posttreatment images and analyze anatomic changes in organs-at-risk (OARs) and gross tumor volumes (GTVs). Automated analysis of anatomic changes was carried out by computing the Jacobian determinant, |J|, of the deformation vector field (DVF) resulting from each of 3 different, commercially available DIRs, which map image intensity between images. |J| is the relative deformation of each mapped voxel, and we focused on the 50% deformation level, i.e., where voxels expand or contract by at least 50% (J50). The Jacobian volume histogram (JVH) for OARs and GTVs described the volume of each structure, which deformed at a specified level. In order to differentiate DVF error from true deformation in QA of the DVFs, we utilized the magnitude of vector curl, |C|, and knowledge of limitations in dense tissue deformation (e.g., in bone we expect J50 = 0). Deformation vector field regions with relatively large |C| and/or large deformation in dense tissue were considered erroneous. Analysis of |J| revealed >50% regression (J50) in up to 48% of GTV volumes (J50 >10% in 3/10 cases) and up to 70% volume of parotid glands (J50>10% in 6/10 cases); however, these relatively large volume changes were not consistent across the three DIR algorithms with differences in J50 up to 7 cm3 of GTV and up to 16 cm3 of parotids. Inconsistent deformations at J50 in up to 5 cm3 of tissue were also detected in the oral cavity (6/10) and larynx (3/10 cases), but not in the esophagus (maximum difference of 0.9 cm3) or spinal cord (maximum difference of 0.9 cm3). For mandible, volumes of large deformation up to 23 cm3 were detected implying DVF errors. Thresholding |C| at 0.8 (80% relative rotation) allowed rapid identification of errors in DVFs. For GTVs, at least 1 DVF per patient could be identified and disregarded due to non-physical, large rotations in each of the 3/10 cases with large differences in J50(>5 cm3 with |C|>0.8). No single algorithm was consistently superior to the others in terms of minimizing large, unrealistic deformations across the ten cases considered. Fully automated detection of anatomic response to radiation therapy is not currently feasible based on the presence of implausible deformations and rotations; however, by incorporating DVF-QA utilizing Jacobian and curl, it may be possible to rule-out DVFs and find realistic, patient-specific anatomic variations.

Building Spatiotemporal Anatomical Models using Joint 4-D Segmentation, Registration, and Subject-Specific Atlas Estimation.

Longitudinal analysis of anatomical changes is a vital component in many personalized-medicine applications for predicting disease onset, determining growth/atrophy patterns, evaluating disease progression, and monitoring recovery. Estimating anatomical changes in longitudinal studies, especially through magnetic resonance (MR) images, is challenging because of temporal variability in shape (e.g. from growth/atrophy) and appearance (e.g. due to imaging parameters and tissue properties affecting intensity contrast, or from scanner calibration). This paper proposes a novel mathematical framework for constructing subject-specific longitudinal anatomical models. The proposed method solves a generalized problem of joint segmentation, registration, and subject-specific atlas building, which involves not just two images, but an entire longitudinal image sequence. The proposed framework describes a novel approach that integrates fundamental principles that underpin methods for image segmentation, image registration, and atlas construction. This paper presents evaluation on simulated longitudinal data and on clinical longitudinal brain MRI data. The results demonstrate that the proposed framework effectively integrates information from 4-D spatiotemporal data to generate spatiotemporal models that allow analysis of anatomical changes over time.

Quantitative analysis of anatomical changes in the cuneate nucleus following forelimb denervation: A stereological morphometric study in adult cats

Quantitative analysis of anatomical changes in the cuneate nucleus following forelimb denervation: A stereological morphometric study in adult cats

Quantitative analysis of anatomical changes in the cuneate nucleus following forelimb denervation: A stereological morphometric study in adult cats

Quantitative analysis of anatomical changes in the cuneate nucleus following forelimb denervation: A stereological morphometric study in adult cats

Quantitative analysis of anatomical changes in the cuneate nucleus following forelimb denervation: a stereological morphometric study in adult cats.

The consequences on the cuneate nucleus of the transection of the major nerves of the forelimb in adult cats were studied quantitatively with stereological procedures on celloidin-embedded material. The cell cluster region of the normal cuneate was 2.93 +/- 0.41 (mean +/- SD) mm3. This volume decreased significantly 4.5 weeks after the injury. The decrease amounted to 11-23%, and persisted until the longest survival studied (36 weeks). Despite this reduction in nuclear volume, there was no significant loss of neurons. The normal cell cluster region contained 48.8 +/- 7.3 (mean +/- SD) x 1000 neurons. Neuronal density showed a significant 16.8% mean increase between 4 weeks and 36 weeks of deafferentation. Perikaryal volume decreased by an average of 15.2%, between 1 and 36 weeks, but since cell bodies make only a small fraction of the total volume, much of the overall volume reduction observed must be attributed to a concomitant reduction of the neuropil. The distribution of cell size suggested that there are two populations of neurons, presumably corresponding to interneurons and projection neurons. This bimodal distribution was maintained after deafferentation, but after 4 weeks it shifted to the left, showing an increase in small cells and a decrease of large cells. These findings demonstrate that peripheral deafferentation causes a substantial and persistent decrease of cytoplasmic mass in the cuneate nucleus, involving both neuropil and neuronal cell bodies, but does not lead to neuron loss, at least up to 36 weeks after injury. These effects suggest that the altered synaptic input and trophic support subsequent to deafferentation leave the cuneate nucleus in a permanently compromised, albeit seemingly stable, state.