MRI intensity inhomogeneity correction by combining intensity and spatial information

We propose a novel fully automated method for retrospective correction of intensity inhomogeneity, which is an undesired phenomenon in many automatic image analysis tasks, especially if quantitative analysis is the final goal. Besides most commonly used intensity features, additional spatial image features are incorporated to improve inhomogeneity correction and to make it more dynamic, so that local intensity variations can be corrected more efficiently. The proposed method is a four-step iterative procedure in which a non-parametric inhomogeneity correction is conducted. First, the probability distribution of image intensities and corresponding second derivatives is obtained. Second, intensity correction forces, condensing the probability distribution along the intensity feature, are computed for each voxel. Third, the inhomogeneity correction field is estimated by regularization of all voxel forces, and fourth, the corresponding partial inhomogeneity correction is performed. The degree of inhomogeneity correction dynamics is determined by the size of regularization kernel. The method was qualitatively and quantitatively evaluated on simulated and real MR brain images. The obtained results show that the proposed method does not corrupt inhomogeneity-free images and successfully corrects intensity inhomogeneity artefacts even if these are more dynamic.     

3D–2D registration in endovascular image-guided surgery: evaluation of state-of-the-art methods on cerebral angiograms

Purpose

Image guidance for minimally invasive surgery is based on spatial co-registration and fusion of 3D pre-interventional images and treatment plans with the 2D live intra-interventional images. The spatial co-registration or 3D–2D registration is the key enabling technology; however, the performance of state-of-the-art automated methods is rather unclear as they have not been assessed under the same test conditions. Herein we perform a quantitative and comparative evaluation of ten state-of-the-art methods for 3D–2D registration on a public dataset of clinical angiograms.

Methods

Image database consisted of 3D and 2D angiograms of 25 patients undergoing treatment for cerebral aneurysms or arteriovenous malformations. On each of the datasets, highly accurate “gold-standard” registrations of 3D and 2D images were established based on patient-attached fiducial markers. The database was used to rigorously evaluate ten state-of-the-art 3D–2D registration methods, namely two intensity-, two gradient-, three feature-based and three hybrid methods, both for registration of 3D pre-interventional image to monoplane or biplane 2D images.

Results

Intensity-based methods were most accurate in all tests (0.3 mm). One of the hybrid methods was most robust with 98.75% of successful registrations (SR) and capture range of 18 mm for registrations of 3D to biplane 2D angiograms. In general, registration accuracy was similar whether registration of 3D image was performed onto mono- or biplanar 2D images; however, the SR was substantially lower in case of 3D to monoplane 2D registration. Two feature-based and two hybrid methods had clinically feasible execution times in the order of a second.

Conclusions

Performance of methods seems to fall below expectations in terms of robustness in case of registration of 3D to monoplane 2D images, while translation into clinical image guidance systems seems readily feasible for methods that perform registration of the 3D pre-interventional image onto biplanar intra-interventional 2D images.

     

Rare complication of breast cancer irradiation: postirradiation osteosarcoma

Radiation-induced osteosarcoma is a rare complication of radiation therapy for breast cancer. The authors present a 60-year-old patient in whom osteosarcoma of the chest wall developed 5 years after modified radical mastectomy and radiation therapy for breast cancer. One year after resection of the chest osteosarcoma, metastasis to the contralateral axillary lymph nodes developed and these were removed. Radiation-induced osteosarcoma is difficult to treat and has a poor prognosis, thus early diagnosis is necessary for optimal treatment.     

Role of olfactory cues in the radial maze performance of rats

Contribution of the smell of food and odor trails to the performance of rats in a 12-arm radial maze was assessed in 12 rats. Choice accuracy was increased rather than decreased by omission of bait (Experiment 1). Maze arms entered during the first 6 choices in the 12-arm radial maze were randomly re-entered during the subsequent 6 choices in a parallel maze assembled from the same maze segments (Experiment 2). Error incidence increased from 1.33 to 1.94 per trial but remained below chance (3.0) when after 6 choices in radial maze A the rat completed the trial in an identical and similarly located maze B (Experiment 3). It is concluded that odor cues alone do not guide the animal's choice, but that they contribute to the complex sensory information essential for correct performance.     

Stenosing processes due to endotracheal intubation and tracheostomy in children

In 1976–1978 there were 15 children hospitalized in the Children's ORL Clinics in Prague and treated for larynx trauma caused by long-term endotracheal intubation. Tracheostomy was performed in all cases, the changes in the larynx were mostly treated in a conservative manner. In one instance we used laryngofissura; however, further dilatations had be carried out. With a single exception, all the patients have been healed successfully. Plastic operations were performed to make decannulation easier.     

Angioimmunoblastic lymphadenopathy with dysproteinemia following doxycycline administration

Angioimmunoblastic lymphadenopathy with dysproteinemia (AILD) is a primary lymphoproliferative T-cell disorder, currently classified as a peripheral T-cell non-Hodgkin's lymphoma. AILD is characterized by generalized lymphadenopathy, hepatosplenomegaly, immunological abnormalities, polyclonal hypergammaglobulinemia and anemia. We report a case of AILD in an 80-year-old male who presented with a generalized pruritic maculopapular eruption and fever following doxycycline administration. The maculopapular rash progressed to formation of confluent nodules, plaques and finally erythroderma with lymphadenopathy and hepatosplenomegaly. Blood analysis revealed an elevated erythrocyte sedimentation rate and polyclonal hypergammaglobulinemia. Lymph node biopsy showed almost complete effacement of the nodal architecture with diffuse proliferation of small vessels forming an arborizing network, surrounded by atypical lymphocytes, usually CD3+ CD4+ and occasionally CD3+ CD8+. There were also larger cells (immunoblastic shape) that displayed CD20 positively, some scattered plasma cells, and eosinophils. Histology of a cutaneous lesion showed spongiosis and infiltration of the epidermis by atypical lymphocytes with large hyperchromatic nuclei, perivascular dermal lymphocytic infiltrate (CD3+) mixed with plasma cells and occasional large immunoblasts (CD20+). During hospitalization the patient developed hemolytic anemia (Coombs positive) and lung metastases. The prognosis of AILD is generally poor, with a median survival of less than 20 months. Our patient died two and a half months after the diagnosis was made due to sepsis caused by Staphylococcus aureus isolated in hemoculture.     

Validation of White-Matter Lesion Change Detection Methods on a Novel Publicly Available MRI Image Database

Changes of white-matter lesions (WMLs) are good predictors of the progression of neurodegenerative diseases like multiple sclerosis (MS). Based on longitudinal magnetic resonance (MR) imaging the changes can be monitored, while the need for their accurate and reliable quantification led to the development of several automated MR image analysis methods. However, an objective comparison of the methods is difficult, because publicly unavailable validation datasets with ground truth and different sets of performance metrics were used. In this study, we acquired longitudinal MR datasets of 20 MS patients, in which brain regions were extracted, spatially aligned and intensity normalized. Two expert raters then delineated and jointly revised the WML changes on subtracted baseline and follow-up MR images to obtain ground truth WML segmentations. The main contribution of this paper is an objective, quantitative and systematic evaluation of two unsupervised and one supervised intensity based change detection method on the publicly available datasets with ground truth segmentations, using common pre- and post-processing steps and common evaluation metrics. Besides, different combinations of the two main steps of the studied change detection methods, i.e. dissimilarity map construction and its segmentation, were tested to identify the best performing combination.     

Determination of axial vertebral rotation in MR images: comparison of four manual and a computerized method

Axial vertebral rotation (AVR) of 14 normal and 14 scoliotic vertebrae from magnetic resonance (MR) images was determined by three observers using four manual methods and a computerized method, which were based on the evaluation of vertebral symmetry in two dimensions (2D) and in three dimensions (3D). The method of Aaro and Dahlborn proved to be the manual method with the highest intra-observer (1.7° SD) and inter-observer (1.2° SD) reliabilities, and was also most in agreement with the computerized method (1.3° SD, 1.0° MAD). The computerized method yielded higher intra-observer (1.3° SD) and inter-observer (1.4° SD) reliabilities than the manual methods, indicating it to be an efficient alternative for repeatable and reliable AVR measurements.