Convexity-constrained and nonnegativity-constrained spherical factorization in diffusion-weighted imaging.

Diffusion-weighted imaging (DWI) facilitates probing neural tissue structure non-invasively by measuring its hindrance to water diffusion. Analysis of DWI is typically based on generative signal models for given tissue geometry and microstructural properties. In this work, we generalize multi-tissue spherical deconvolution to a blind source separation problem under convexity and nonnegativity constraints. This spherical factorization approach decomposes multi-shell DWI data, represented in the basis of spherical harmonics, into tissue-specific orientation distribution functions and corresponding response functions, without assuming the latter as known thus fully unsupervised. In healthy human brain data, the resulting components are associated with white matter fibres, grey matter, and cerebrospinal fluid. The factorization results are on par with state-of-the-art supervised methods, as demonstrated also in Monte-Carlo simulations evaluating accuracy and precision of the estimated response functions and orientation distribution functions of each component. In animal data and in the presence of oedema, the proposed factorization is able to recover unseen tissue structure, solely relying on DWI. As such, our method broadens the applicability of spherical deconvolution techniques to exploratory analysis of tissue structure in data where priors are uncertain or hard to define.

Image-based in vivo assessment of targeting accuracy of stereotactic brain surgery in experimental rodent models.

Stereotactic neurosurgery is used in pre-clinical research of neurological and psychiatric disorders in experimental rat and mouse models to engraft a needle or electrode at a pre-defined location in the brain. However, inaccurate targeting may confound the results of such experiments. In contrast to the clinical practice, inaccurate targeting in rodents remains usually unnoticed until assessed by ex vivo end-point histology. We here propose a workflow for in vivo assessment of stereotactic targeting accuracy in small animal studies based on multi-modal post-operative imaging. The surgical trajectory in each individual animal is reconstructed in 3D from the physical implant imaged in post-operative CT and/or its trace as visible in post-operative MRI. By co-registering post-operative images of individual animals to a common stereotaxic template, targeting accuracy is quantified. Two commonly used neuromodulation regions were used as targets. Target localization errors showed not only variability, but also inaccuracy in targeting. Only about 30% of electrodes were within the subnucleus structure that was targeted and a-specific adverse effects were also noted. Shifting from invasive/subjective 2D histology towards objective in vivo 3D imaging-based assessment of targeting accuracy may benefit a more effective use of the experimental data by excluding off-target cases early in the study.

Multi-phase rotational angiography of the left ventricle to assist ablations: feasibility and accuracy of novel imaging.

AIMS: Interventional left ventricular (LV) procedures integrating static 3D anatomy visualization are subject to mismatch with dynamic catheter movements due to prominent LV motion. We aimed to evaluate the accuracy of a recently developed acquisition and post-processing protocol for low radiation dose LV multi-phase rotational angiography (4DRA) in patients. METHODS AND RESULTS: 4DRA image acquisition of the LV was performed as investigational acquisition in patients undergoing left-sided ablation (11 men; BMI = 24.7 ± 2.5 kg/m²). Iodine contrast was injected in the LA, while pacing from the RA at a cycle length of 700 ms. 4DRA acquisition and reconstruction were possible in all 11 studies. Reconstructed images were post-processed using streak artefact reduction algorithms and an interphase registration-based filtering method, increasing contrast-to-noise ratio by a factor 8.2 ± 2.1. This enabled semi-automatic segmentation, yielding LV models of five equidistant phases per cardiac cycle. For evaluation, off-line 4DRA fluoroscopy registration was performed, and the 4DRA LV contours of the different phases were compared with the contours of five corresponding phases of biplane LV angiography, acquired in identical circumstances. Of the distances between these contours, 95% were <4 mm in both incidences. Effective radiation dose for 4DRA, calculated by patient-specific Monte-Carlo simulation, was 5.1 ± 1.1 mSv. CONCLUSION: Creation of 4DRA LV models in man is feasible at near-physiological heart rate and with clinically acceptable radiation dose. They showed high accuracy with respect to LV angiography in RAO and LAO. The presented technology not only opens perspectives for full cardiac cycle dynamic anatomical guidance during interventional procedures, but also for 3DRA without need for very rapid pacing.

Global tractography of multi-shell diffusion-weighted imaging data using a multi-tissue model.

Diffusion-weighted imaging and tractography provide a unique, non-invasive technique to study the macroscopic structure and connectivity of brain white matter in vivo. Global tractography methods aim at reconstructing the full-brain fiber configuration that best explains the measured data, based on a generative signal model. In this work, we incorporate a multi-shell multi-tissue model based on spherical convolution, into a global tractography framework, which allows to deal with partial volume effects. The required tissue response functions can be estimated from and hence calibrated to the data. The resulting track reconstruction is quantitatively related to the apparent fiber density in the data. In addition, the fiber orientation distribution for white matter and the volume fractions of gray matter and cerebrospinal fluid are produced as ancillary results. Validation results on simulated data demonstrate that this data-driven approach improves over state-of-the-art streamline and global tracking methods, particularly in the valid connection rate. Results in human brain data correspond to known white matter anatomy and show improved modeling of partial voluming. This work is an important step toward detecting and quantifying white matter changes and connectivity in healthy subjects and patients.

Closed-chest animal model of chronic coronary artery stenosis. Assessment with magnetic resonance imaging.

To evaluate the consequences of chronic non-occlusive coronary artery (CA) stenosis on myocardial function, perfusion and viability, we developed a closed-chest, closed-pericardium pig model, using magnetic resonance imaging (MRI) as quantitative imaging tool. Pigs underwent a percutaneous copper-coated stent implantation in the left circumflex CA (n = 19) or sham operation (n = 5). To evaluate the occurrence of myocardial infarction, cardiac troponin I (cTnI) levels were repetitively measured. At week 6, CA stenosis severity was quantified with angiography and cine, first-pass and contrast-enhanced MRI were performed to evaluate cardiac function, perfusion and viability. In the stenting group, cTnI values significantly increased at day 3 and day 5 (P = 0.01), and normalized at day 12. At angiography, 13/19 stented pigs had a stenosis >75%. Mean degree of CA stenosis was 91 +/- 4%, range 83-98%. At contrast-enhanced MRI, mean infarct size was 7 +/- 6%, range 0.7-18.4%. Five of the 6 pigs with stenosis <75% had no infarction. Stented pigs showed significantly higher Left-ventricular volumes and normalized mass (P < 0.05), and lower ejection fraction (P = 0.03) than the sham pigs. Both wall thickening and myocardial perfusion were significantly lower in animals with at least one segment >50% infarct (23 +/- 8%; 0.05 +/- 0.01 a.u./s) and animals with only <50% infarct segments (29% +/- 12%; 0.07 +/- 0.02 a.u./s), than sham pigs (52 +/- 6%; 0.10 +/- 0.03 a.u./s) (P < 0.001; P < 0.05). This minimally-invasive animal model of chronic, non-occlusive CA stenosis, presenting a mixture of perfusion and functional impairment and a variable degree of myocardial necrosis, can be used as substitute to study chronic myocardial hypoperfusion.

Bone quality assessment based on cone beam computed tomography imaging.

OBJECTIVES: The aim of this in vitro study was to investigate the accuracy of fractal analysis and morphometry for bone quality assessment as measured with dual energy X-ray absorptiometry (DXA). MATERIAL AND METHODS: Nineteen mandibular bone samples were used for the creation of artificial bone lesions (n=5) or decalcification (n=12) to simulate osteoporosis; two samples were used as controls. Cone beam computed tomography (CBCT) and DXA scans were made before and after processing the samples. The image data obtained from the CBCT scans were used to calculate the mean fractal dimension (FD), bone area and density (morphometric analysis) of the samples. Bone mineral density (BMD) was obtained from the DXA scans and set as a reference value for bone quality. The correlation between BMD and FD and between BMD and morphometric results were calculated. RESULTS: A significant correlation between FD and BMD (rho=+0.71 to +0.75; P<0.05) was observed. Bone area and BMD of the specimens (rho=+0.69 to +0.85; P<0.05) were also significantly related, in contrast to the density analysis, for which no significant correlation to BMD was found. CONCLUSIONS: The results of this study suggest that fractal analysis and bone area measurement have potential to evaluate bone quality on CBCT images, while density measurement does not seem to be valid.

Minimal shape and intensity cost path segmentation.

A new generic model-based segmentation algorithm is presented, which can be trained from examples akin to the active shape model (ASM) approach in order to acquire knowledge about the shape to be segmented and about the gray-level appearance of the object in the image. Whereas ASM alternates between shape and intensity information during search, the proposed approach optimizes for shape and intensity characteristics simultaneously. Local gray-level appearance information at the landmark points extracted from feature images is used to automatically detect a number of plausible candidate locations for each landmark. The shape information is described by multiple landmark-specific statistical models that capture local dependencies between adjacent landmarks on the shape. The shape and intensity models are combined in a single cost function that is optimized noniteratively using dynamic programming, without the need for initialization. The algorithm was validated for segmentation of anatomical structures in chest and hand radiographs. In each experiment, the presented method had a significant higher performance when compared to the ASM schemes. As the method is highly effective, optimally suited for pathological cases and easy to implement, it is highly useful for many medical image segmentation tasks.

Assessment of bone segmentation quality of cone-beam CT versus multislice spiral CT: a pilot study.

OBJECTIVES: The objective of this study was to quantitatively assess the quality of jawbone models generated from cone beam computed tomography (CBCT) by comparison with similar models obtained from multislice spiral computed tomography (MSCT). MATERIAL AND METHODS: Three case studies were performed involving images of anthropomorphic head phantoms and real patients acquired with 3 CBCT (NewTom 9000 DVT, Accuitomo 3D, and i-CAT) and 2 MSCT scanners (Somatom VolumeZoom and Lightspeed). Bone was segmented from the CBCT and MSCT images using global thresholding. CBCT vs MSCT segmentation differences were assessed by comparing bone thickness measurements at anatomically corresponding sites, identified automatically by CBCT to MSCT image registration. RESULTS: There was a statistically significant difference between the MSCT and CBCT segmented bone thicknesses, varying from 0.05 +/- 0.47 mm (i-CAT) up to 1.2 +/- 1.00 mm (3D Accuitomo, posterior maxilla). CONCLUSIONS: An automated, reproducible, and observer-independent method has been developed to assess the quality of CBCT bone models using MSCT as a clinically established method of reference. Our validation method is generally applicable in cases where no geometric ground-truth is available.