CIDI-lung-seg: a single-click annotation tool for automatic delineation of lungs from CT scans.

Accurate and fast extraction of lung volumes from computed tomography (CT) scans remains in a great demand in the clinical environment because the available methods fail to provide a generic solution due to wide anatomical variations of lungs and existence of pathologies. Manual annotation, current gold standard, is time consuming and often subject to human bias. On the other hand, current state-of-the-art fully automated lung segmentation methods fail to make their way into the clinical practice due to their inability to efficiently incorporate human input for handling misclassifications and praxis. This paper presents a lung annotation tool for CT images that is interactive, efficient, and robust. The proposed annotation tool produces an "as accurate as possible" initial annotation based on the fuzzy-connectedness image segmentation, followed by efficient manual fixation of the initial extraction if deemed necessary by the practitioner. To provide maximum flexibility to the users, our annotation tool is supported in three major operating systems (Windows, Linux, and the Mac OS X). The quantitative results comparing our free software with commercially available lung segmentation tools show higher degree of consistency and precision of our software with a considerable potential to enhance the performance of routine clinical tasks.

Consistency and efficiency of CT analysis of metastatic disease: semiautomated lesion management application within a PACS.

OBJECTIVE: The purpose of this study was to evaluate the success, consistency, and efficiency of a semiautomated lesion management application within a PACS in the analysis of metastatic lesions in serial CT examinations of cancer patients. MATERIALS AND METHODS: Two observers using baseline and follow-up CT data independently reviewed 93 target lesions (17 lung, five liver, 71 lymph node) in 50 patients with either metastatic bladder or prostate cancer. The observers measured the longest axis (or short axis for lymph nodes) of each lesion and made Response Evaluation Criteria in Solid Tumors (RECIST) determinations using manual and lesion management application methods. The times required for examination review, RECIST calculations, and data input were recorded. The Wilcoxon signed rank test was used to assess time differences, and Bland-Altman analysis was used to assess interobserver agreement within the manual and lesion management application methods. Percentage success rates were also reported. RESULTS: With the lesion management application, most lung and liver lesions were semiautomatically segmented. Comparison of the lesion management application and manual methods for all lesions showed a median time saving of 45% for observer 1 (p<0.05) and 28% for observer 2 (p=0.05) on follow-up scans versus 28% for observer 1 (p<0.05) and 9% for observer 2 (p=0.087) on baseline scans. Variability of measurements showed mean percentage change differences of only 8.9% for the lesion management application versus 26.4% for manual measurements. CONCLUSION: With the lesion management application method, most lung and liver lesions were successfully segmented semiautomatically; the results were more consistent between observers; and assessment of tumor size was faster than with the manual method.

Automated registration, segmentation, and measurement of metastatic melanoma tumors in serial CT scans.

OBJECTIVES: Our goal was to evaluate a new software capability that integrates registration, segmentation and tumor measurement across serial exams within a picture archiving communication system (PACS) to expedite tumor measurement. MATERIALS AND METHODS: Patients treated under institutional review board-approved protocols for metastatic melanoma were retrospectively reviewed. Of the 19 included patients, five were male, the median age was 43.2, and all received treatment using an adoptive cell therapy. Seventy-one lung, liver, and subcutaneous tumors were manually measured using RECIST (Response Evaluation Criteria In Solid Tumors) criteria before therapy (baseline computed tomography [CT]) and within 3 months after therapy (follow-up CT). We performed semiautomated registration, segmentation, and RECIST measurements at both time points within PACS (Carestream Health, Rochester, NY). We compared manual and software-generated RECIST measurements using Bland-Altman plots. RESULTS: The median manually measured RECIST diameter for all baseline tumors was 2.1 (1.0-6.2) cm. The refined registration function identified 70/71 (98.6%) tumors on the follow-up CT. On the baseline CT, all 21 liver, 27/32 (84%) lung, and 10/18 (55%) subcutaneous tumors completed segmentation. On the follow-up CT, 19/21 (90%) liver, 21/27 (78%) lung, and 8/10 (80%) subcutaneous tumors completed segmentation. The Bland-Altman plot demonstrated a 95% confidence interval of ±0.7 cm when comparing the software-generated and manual RECIST measurements. CONCLUSIONS: The PACS software performed semiautomated baseline tumor measurements and fully automated follow-up tumor measurements in a majority of lung, liver, and subcutaneous tumors. In our patients, semiautomated metastatic tumor measurement did not obviate the need for physician oversight due to disease and treatment-related factors.

A voxel-based lesion study on facial emotion recognition after penetrating brain injury.

The ability to read emotions in the face of another person is an important social skill that can be impaired in subjects with traumatic brain injury (TBI). To determine the brain regions that modulate facial emotion recognition, we conducted a whole-brain analysis using a well-validated facial emotion recognition task and voxel-based lesion symptom mapping (VLSM) in a large sample of patients with focal penetrating TBIs (pTBIs). Our results revealed that individuals with pTBI performed significantly worse than normal controls in recognizing unpleasant emotions. VLSM mapping results showed that impairment in facial emotion recognition was due to damage in a bilateral fronto-temporo-limbic network, including medial prefrontal cortex (PFC), anterior cingulate cortex, left insula and temporal areas. Beside those common areas, damage to the bilateral and anterior regions of PFC led to impairment in recognizing unpleasant emotions, whereas bilateral posterior PFC and left temporal areas led to impairment in recognizing pleasant emotions. Our findings add empirical evidence that the ability to read pleasant and unpleasant emotions in other people's faces is a complex process involving not only a common network that includes bilateral fronto-temporo-limbic lobes, but also other regions depending on emotional valence.

Molecular imaging of pediatric brain tumors: comparison of tumor metabolism using ¹8F-FDG-PET and MRSI.

Magnetic resonance spectroscopic imaging (MRSI) and (18)F-fluorodeoxyglucose positron emission tomography (FDG-PET) are non-invasive imaging techniques routinely used to evaluate tumor malignancy in adults with brain tumors. We compared the metabolic activity of pediatric brain tumors using FDG-PET and MRSI. Children (n = 37) diagnosed with a primary brain tumor underwent FDG-PET and MRSI within two weeks of each other. Tumor metabolism was classified as inactive, active or highly active using the maximum choline:N-acetyl-asparate (Cho:NAA) on MRSI and the highest tumor uptake on FDG-PET. A voxel-wise comparison was used to evaluate the area with the greatest abnormal metabolism. Agreement between methods was assessed using the percent agreement and the kappa statistic (κ). Pediatric brain tumors were metabolically heterogeneous on FDG-PET and MRSI studies. Active tumor metabolism was observed more frequently using MRSI compared to FDG-PET, and agreement in tumor classification was weak (κ = 0.16, p = 0.12), with 42 % agreement (95 % CI = 25-61 %). Voxel-wise comparison for identifying the area of greatest metabolic activity showed overlap in the majority (62 %) of studies, though exact agreement between techniques was low (29.4 %, 95 % CI = 15.1-47.5 %). These results indicate that FDG-PET and MRSI detect similar but not always identical regions of tumor activity, and there is little agreement in the degree of tumor metabolic activity between the two techniques.

Single-trial fMRI shows contralesional activity linked to overt naming errors in chronic aphasic patients.

We used fMRI to investigate the roles played by perilesional and contralesional cortical regions during language production in stroke patients with chronic aphasia. We applied comprehensive psycholinguistic analyses based on well-established models of lexical access to overt picture-naming responses, which were evaluated using a single trial design that permitted distinction between correct and incorrect responses on a trial-by-trial basis. Although both correct and incorrect naming responses were associated with left-sided perilesional activation, incorrect responses were selectively associated with robust right-sided contralesional activity. Most notably, incorrect responses elicited overactivation in the right inferior frontal gyrus that was not observed in the contrasts for patients' correct responses or for responses of age-matched control subjects. Errors were produced at slightly later onsets than accurate responses and comprised predominantly semantic paraphasias and omissions. Both types of errors were induced by pictures with greater numbers of alternative names, and omissions were also induced by pictures with late acquired names. These two factors, number of alternative names per picture and age of acquisition, were positively correlated with activation in left and right inferior frontal gyri in patients as well as control subjects. These results support the hypothesis that some right frontal activation may normally be associated with increasing naming difficulty, but in patients with aphasia, right frontal overactivation may reflect ineffective effort when left hemisphere perilesional resources are insufficient. They also suggest that contralesional areas continue to play a role--dysfunctional rather than compensatory--in chronic aphasic patients who have experienced a significant degree of recovery.

Conventional magnetic resonance imaging features in patients with tropical spastic paraparesis.

Conventional brain and spinal cord magnetic resonance images were performed in 21 patients with human T-cell lymphotropic virus (HTLV)-1 associated myelopathy/tropical spastic paraparesis, to assess the role of conventional magnetic resonance imaging (MRI) in the disease diagnosis. These patients had no other central nervous system conditions or related risk factors at the time of tropical spastic paraparesis diagnosis. Eleven (52.4%) patients showed nonspecific brain abnormalities on T2-weighted images. The majority (77.2%) of brain abnormalities were located in the deep white matter. A transient contrast-enhancing lesion was identified in the brain of only one patient. In the brain of another patient, 9.0% of the T2-hyperintense lesion load was hypointense on the correspondent T1-weighted images. No differences in terms of demographic, biological, or clinical variables were present between patients with abnormal brain images and those with normal brain magnetic resonance images. Spinal cord T2-weighted images were abnormal in three (14.3%) patients. In one of these three patients, a diffuse but transient edema was found along the entire tract of the spinal cord. White matter lesions were present in the central nervous system of 60% of the cases in this study. However, no correlations between magnetic resonance imaging and clinical findings, and no specificity of lesions were observed. Hence, conventional magnetic resonance imaging is a sensitive but not highly specific tool for diagnosis of tropical spastic paraparesis.