Purpose CT ventilation imaging (CTVI) is being used to achieve functional avoidance lung cancer radiation therapy in three clinical trials (NCT02528942, NCT02308709, NCT02843568). To address the need for common CTVI validation tools, we have built the Ventilation And Medical Pulmonary Image Registration Evaluation (VAMPIRE) Dataset, and present the results of the first VAMPIRE Challenge to compare relative ventilation distributions between different CTVI algorithms and other established ventilation imaging modalities. Methods The VAMPIRE Dataset includes 50 pairs of 4DCT scans and corresponding clinical or experimental ventilation scans, referred to as reference ventilation images (RefVIs). The dataset includes 25 humans imaged with Galligas 4DPET/CT, 21 humans imaged with DTPA‐SPECT, and 4 sheep imaged with Xenon‐CT. For the VAMPIRE Challenge, 16 subjects were allocated to a training group (with RefVI provided) and 34 subjects were allocated to a validation group (with RefVI blinded). Seven research groups downloaded the Challenge dataset and uploaded CTVIs based on deformable image registration (DIR) between the 4DCT inhale/exhale phases. Participants used DIR methods broadly classified into B‐splines, Free‐form, Diffeomorphisms, or Biomechanical modeling, with CT ventilation metrics based on the DIR evaluation of volume change, Hounsfield Unit change, or various hybrid approaches. All CTVIs were evaluated against the corresponding RefVI using the voxel‐wise Spearman coefficient rS, and Dice similarity coefficients evaluated for low function lung (DSClow) and high function lung (DSChigh). Results A total of 37 unique combinations of DIR method and CT ventilation metric were either submitted by participants directly or derived from participant‐submitted DIR motion fields using the in‐house software, VESPIR. The rS and DSC results reveal a high degree of inter‐algorithm and intersubject variability among the validation subjects, with algorithm rankings changing by up to ten positions depending on the choice of evaluation metric. The algorithm with the highest overall cross‐modality correlations used a biomechanical model‐based DIR with a hybrid ventilation metric, achieving a median (range) of 0.49 (0.27–0.73) for rS, 0.52 (0.36–0.67) for DSClow, and 0.45 (0.28–0.62) for DSChigh. All other algorithms exhibited at least one negative rS value, and/or one DSC value less than 0.5. Conclusions The VAMPIRE Challenge results demonstrate that the cross‐modality correlation between CTVIs and the RefVIs varies not only with the choice of CTVI algorithm but also with the choice of RefVI modality, imaging subject, and the evaluation metric used to compare relative ventilation distributions. This variability may arise from the fact that each of the different CTVI algorithms and RefVI modalities provides a distinct physiologic measurement. Ultimately this variability, coupled with the lack of a “gold standard,” highlights the ongoing importance of further validation studies before CTVI can be widely translated from academic ce...

Pulmonary fissure detection in computed tomography (CT) is a critical component for automatic lobar segmentation. The majority of fissure detection methods use feature descriptors that are hand-crafted, low-level, and have local spatial extent. The design of such feature detectors is typically targeted towards normal fissure anatomy, yielding low sensitivity to weak and abnormal fissures that are common in clinical datasets. Furthermore, local features commonly suffer from low specificity, as the complex textures in the lung can be indistinguishable from the fissure when global context is not considered. We propose a supervised discriminative learning framework for simultaneous feature extraction and classification. The proposed framework, called FissureNet, is a coarse-to-fine cascade of two convolutional neural networks. The coarse-to-fine strategy alleviates the challenges associated with training a network to segment a thin structure that represents a small fraction of the image voxels. FissureNet was evaluated on a cohort of 3706 subjects with inspiration and expiration 3DCT scans from the COPDGene clinical trial and a cohort of 20 subjects with 4DCT scans from a lung cancer clinical trial. On both datasets, FissureNet showed superior performance compared to a deep learning approach using the U-Net architecture and a Hessian-based fissure detection method in terms of area under the precisionrecall curve (PR-AUC). The overall PR-AUC for FissureNet, UNet, and Hessian on the COPDGene (lung cancer) dataset was 0.980 (0.966), 0.963 (0.937), and 0.158 (0.182), respectively. On a subset of 30 COPDGene scans, FissureNet was compared to a recently proposed advanced fissure detection method called derivative of sticks (DoS) and showed superior performance with a PR-AUC of 0.991 compared to 0.668 for DoS.

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Caucasians with prevalence estimates of 2 to 8 cases per The prevalence of homozygous hereditary hemochro-1,000 population. [4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21] Approximately 70% of affected persons matosis (HHC) is estimated at 1:250 in Caucasian adults.possess HLA-A3 alloantigen. 5,[22][23][24][25][26][27][28] Simon et al. hypothesize Little is known about ethnic subpopulations that might that the genetic mutation leading to iron overload originally be at increased risk for this disease. HLA data have sugoccurred in the Celtic peoples and that the HLA marker for gested a Celtic origin for HHC. Screening for HHC was HHC might constitute a genetic tracer of the migratory patoffered to all employees of the Massachusetts Polaroid tern of these peoples. 29 More recently, a non-HLA-linked Corporation. Participants with a transferrin saturation form of iron overload has been described in South African of ú55% or ú45% and an elevated serum ferritin concenblacks. 30 tration on two screenings were referred for liver biopsy.Most studies have dealt with populations from ethnically The diagnosis of HHC was based on histological criteria, homogeneous areas (Table 1). [9][10][11][12][13][14][15][16][17][18][19][20][21]31 Detailed comparisons of quantitative hepatic iron determination, hepatic iron inethnic and racial backgrounds have not been reported. The dex, and the phlebotomy requirement for iron depletion.current study examines the prevalence of HHC in a healthy Participants completed a questionnaire regarding their working population of heterogeneous ethnic and racial backethnic background. Two thousand two hundred ninetyground. We sought to identify ethnic and racial subpopulafour employees were screened, and 5 cases of HHC were tions that might be at high risk for inheriting this disease. tion of HHC with Celtic background (P Å .012). The esti-Polaroid study of prostate-specific antigen values in male employees mated cost of screening per patient identified was over age 50 years, and an additional 1,331 nonduplicate serum sam-$18,041. Polaroid Corporation has a high representation ples were collected through a corporation-wide informational and of employees of British-Irish ancestry. Our data suggest promotional campaign offering free screening for HHC. This included that they are at high risk for developing HHC. A signifi-a telephone hotline outlining the signs and symptoms of HHC and cant association of HHC with Celtic ancestry was found the benefits of early detection. Demographic data for the total Polarin this subpopulation, supporting the concept of a Celtic oid population were made available for comparison ( HLA-A and -B phenotyping of T-lymphocytes was performed on TS, transferrin saturation; HII, hepatic iron index; SF, serum ferritin.probands in anticipation of family screening. 43,44 From the 1 Division of Gastroenterology, Faulkner Hospital, Tufts University School of Medicine, Boston, MA; 2 Medical Department, Polaroid Corporation, Cambridge, MA;Protocol. The initial sc...