Segmentation editing improves efficiency while reducing inter-expert variation and maintaining accuracy for normal brain tissues in the presence of space-occupying lesions.

Image segmentation has become a vital and often rate-limiting step in modern radiotherapy treatment planning. In recent years, the pace and scope of algorithm development, and even introduction into the clinic, have far exceeded evaluative studies. In this work we build upon our previous evaluation of a registration driven segmentation algorithm in the context of 8 expert raters and 20 patients who underwent radiotherapy for large space-occupying tumours in the brain. In this work we tested four hypotheses concerning the impact of manual segmentation editing in a randomized single-blinded study. We tested these hypotheses on the normal structures of the brainstem, optic chiasm, eyes and optic nerves using the Dice similarity coefficient, volume, and signed Euclidean distance error to evaluate the impact of editing on inter-rater variance and accuracy. Accuracy analyses relied on two simulated ground truth estimation methods: simultaneous truth and performance level estimation and a novel implementation of probability maps. The experts were presented with automatic, their own, and their peers' segmentations from our previous study to edit. We found, independent of source, editing reduced inter-rater variance while maintaining or improving accuracy and improving efficiency with at least 60% reduction in contouring time. In areas where raters performed poorly contouring from scratch, editing of the automatic segmentations reduced the prevalence of total anatomical miss from approximately 16% to 8% of the total slices contained within the ground truth estimations. These findings suggest that contour editing could be useful for consensus building such as in developing delineation standards, and that both automated methods and even perhaps less sophisticated atlases could improve efficiency, inter-rater variance, and accuracy.

Evaluation of multiple-atlas-based strategies for segmentation of the thyroid gland in head and neck CT images for IMRT.

Segmenting the thyroid gland in head and neck CT images is of vital clinical significance in designing intensity-modulated radiation therapy (IMRT) treatment plans. In this work, we evaluate and compare several multiple-atlas-based methods to segment this structure. Using the most robust method, we generate automatic segmentations for the thyroid gland and study their clinical applicability. The various methods we evaluate range from selecting a single atlas based on one of three similarity measures, to combining the segmentation results obtained with several atlases and weighting their contribution using techniques including a simple majority vote rule, a technique called STAPLE that is widely used in the medical imaging literature, and the similarity between the atlas and the volume to be segmented. We show that the best results are obtained when several atlases are combined and their contributions are weighted with a measure of similarity between each atlas and the volume to be segmented. We also show that with our data set, STAPLE does not always lead to the best results. Automatic segmentations generated by the combination method using the correlation coefficient (CC) between the deformed atlas and the patient volume, which is the most accurate and robust method we evaluated, are presented to a physician as 2D contours and modified to meet clinical requirements. It is shown that about 40% of the contours of the left thyroid and about 42% of the right thyroid can be used directly. An additional 21% on the left and 24% on the right require only minimal modification. The amount and the location of the modifications are qualitatively and quantitatively assessed. We demonstrate that, although challenged by large inter-subject anatomical discrepancy, atlas-based segmentation of the thyroid gland in IMRT CT images is feasible by involving multiple atlases. The results show that a weighted combination of segmentations by atlases using the CC as the similarity measure slightly outperforms standard combination methods, e.g. the majority vote rule and STAPLE, as well as methods selecting a single most similar atlas. The results we have obtained suggest that using our contours as initial contours to be edited has clinical value.

SU-E-T-429: Image-Guided Eye Plaque Brachytherapy Optimization: Implications for Patients at 2-Year Follow-up.

PURPOSE: Episcleral eye plaque brachytherapy has been utilized in the treatment of intra-ocular malignancies, delivering large prescription doses to the apex of the tumor. Advances in dose calculation and image guidance, via calibrated fundus images, enable localization of the tumor and determination of dose to the macula, optic disc, and lens. A two-year post-implant study aims to correlate dosimetry with local tumor control and changes in visual acuity, as well as assess the need for plaque optimization with respect to critical structures. METHODS: A retrospective, two-year follow-up study of 21 patients who have received episcleral eye plaque brachytherapy at our institution was used to correlate dosimetry with clinical outcomes and evaluate the need for eye plaque optimization. BEBIG Plaque Simulator wasused in treatment planning; fundus photographs were registered for tumor localization and the TG43-U1 formulism enabled dose calculation of I-125- loaded COMS plaques. Doses to the apex, macula, and optic disc were correlated to changes in apex height and visual acuity. Selected patients were replanned using optimization strategies to reduce dose to critical structures. RESULTS: A total of seven patients (33%) noted improved eyesight at two years. 11 (52%) patients lost at least two lines of vision at two years. Two patients saw increases in apical height (9%) within two years. Optimized eye plaque plans were able to reduce optic disc and macular doses (average 68Gy and 80Gy, respectively) by 36% and 25% on the average, while maintaining the prescribed dose. CONCLUSION: Image guidance and optimization are important tools that can aid in treatment of intra-ocular malignancies, as these techniques provide physicists with the ability to spare critical structures while delivering the prescription dose, thus increasing the possibility of local control and vision sparing.

Comparison of manual and automatic segmentation methods for brain structures in the presence of space-occupying lesions: a multi-expert study.

The purpose of this work was to characterize expert variation in segmentation of intracranial structures pertinent to radiation therapy, and to assess a registration-driven atlas-based segmentation algorithm in that context. Eight experts were recruited to segment the brainstem, optic chiasm, optic nerves, and eyes, of 20 patients who underwent therapy for large space-occupying tumors. Performance variability was assessed through three geometric measures: volume, Dice similarity coefficient, and Euclidean distance. In addition, two simulated ground truth segmentations were calculated via the simultaneous truth and performance level estimation algorithm and a novel application of probability maps. The experts and automatic system were found to generate structures of similar volume, though the experts exhibited higher variation with respect to tubular structures. No difference was found between the mean Dice similarity coefficient (DSC) of the automatic and expert delineations as a group at a 5% significance level over all cases and organs. The larger structures of the brainstem and eyes exhibited mean DSC of approximately 0.8-0.9, whereas the tubular chiasm and nerves were lower, approximately 0.4-0.5. Similarly low DSCs have been reported previously without the context of several experts and patient volumes. This study, however, provides evidence that experts are similarly challenged. The average maximum distances (maximum inside, maximum outside) from a simulated ground truth ranged from (-4.3, +5.4) mm for the automatic system to (-3.9, +7.5) mm for the experts considered as a group. Over all the structures in a rank of true positive rates at a 2 mm threshold from the simulated ground truth, the automatic system ranked second of the nine raters. This work underscores the need for large scale studies utilizing statistically robust numbers of patients and experts in evaluating quality of automatic algorithms.

Evidence for metabolic abnormalities in the muscles of patients with fibromyalgia.

Widespread muscle pain, fatigue, and weakness are defining characteristics of patients with fibromyalgia (FM). The aim of this review is to summarize recent investigations of muscle abnormalities in FM, which can be classified as structural, metabolic, or functional in nature. Histologic muscle abnormalities of membranes, mitochondria, and fiber type have been well described at both the light microscopic and ultrastructural levels. These structural abnormalities often correlate with biochemical abnormalities, defective energy production, and the resultant dysfunction of FM muscles. The observed abnormalities in FM muscles are consistent with neurologic findings and disturbances in the hypothalamic-pituitary-adrenal axis. Functional changes in FM muscles are assessed most directly by strength and endurance measurements, but pain and psychologic factors may interfere with accurate assessments. To compensate for diminished effort, the decreased efficiency of the work performance by patients with FM can be verified from P-31 magnetic resonance spectroscopy (MRS) data by calculation of the work/energy-cost ratio for various tasks. In the disease course, muscle abnormalities may be elicited by intrinsic changes within the muscle tissue itself and/or extrinsic neurologic and endocrine factors. The accurate assignment of intrinsic or extrinsic factors has been substantially clarified by a recent surge of experimental findings. Irrespective of the multifaceted causes of muscle dysfunction and pain, an in-depth understanding of the muscle defects may provide ideas for characterization of the underlying pathogenesis and development of new therapeutic approaches for fibromyalgia syndrome.

Muscle abnormalities in juvenile dermatomyositis patients: P-31 magnetic resonance spectroscopy studies.

OBJECTIVE: To characterize metabolic abnormalities in the muscles of children with the juvenile variant of dermatomyositis (JDM) by the use of noninvasive P-31 magnetic resonance spectroscopy (MRS). METHODS: Thirteen patients with JDM (ages 4-16 years) were studied. Biochemical status was evaluated with P-31 MRS by determining the concentrations of the high-energy phosphate compounds, ATP and phosphocreatine (PCr), ratios of inorganic phosphate (Pi) to PCr (Pi:PCr ratio), levels of free cytosolic ADP, and phosphorylation potentials (PPs) during rest, exercise, and recovery. RESULTS: Significant metabolic abnormalities were observed in the thigh muscles of 10 severely affected patients during rest, 2 graded levels of exercise, and recovery. Mean ATP and PCr levels in the muscles of JDM patients were 35-40% below the normal control values (P < 0.003). These data, along with elevated Pi:PCr ratios, higher ADP levels, and abnormal values for PPs, indicated defective oxidative phosphorylation in the mitochondria of diseased JDM muscles. MRS findings were normal in 2 additional patients who had improved with prednisone treatment and in 1 patient who had no muscle weakness (amyopathic variant of JDM). CONCLUSION: JDM patients can be monitored with noninvasive P-31 MRS without sedation. Biochemical defects in energy metabolism are concordant with the weakness and fatigue reported by JDM patients. Quantitative MRS data are useful for evaluating patients and optimizing drug treatment regimens.