Dataset Information

Real-time computed tomography fluoroscopy-guided solitary lung tumor model in a rabbit.

ABSTRACT: Preclinical studies of lung cancer require suitable large-animal models to allow evaluation and development of surgical and interventional techniques. We assessed the feasibility and safety of a novel rabbit lung cancer model of solitary tumors, in which real-time computed tomography fluoroscopy is used to guide inoculation of VX2 carcinoma single-cell suspensions. Thirty-eight rabbits were divided into four groups according to the volume of the VX2 tissue or cell suspension, the volume of lipiodol, the volume of Matrigel, and the injection needle size. The mixtures were percutaneously injected into rabbit lungs under real-time computed tomography fluoroscopy guidance. Two weeks later, VX2 lung carcinomas were confirmed via positron emission tomography/computed tomography, necropsy, and histology. Real-time computed tomography fluoroscopy allowed the precise inoculation of the tumor cell suspensions containing lipiodol, while the use of Matrigel and a small needle prevented leakage of the suspensions into the lung parenchyma. Solitary lung tumors were successfully established in rabbits (n = 22) inoculated with single-cell suspensions (150 ?L), lipiodol (150 ?L), and Matrigel (150 ?L) using a 26-gauge needle. This combination was determined to be optimal. Pneumothorax was observed in only two of the 38 rabbits (5.3%), both of which survived to the end of the study without any intervention. Real-time computed tomography fluoroscopy-guided inoculation of VX2 single-cell suspensions with lipiodol and Matrigel using a small needle is an easy and safe method to establish solitary lung tumors in rabbits.

SUBMITTER: Choi BH

PROVIDER: S-EPMC5469482 | biostudies-other | 2017

REPOSITORIES: biostudies-other

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Real-time computed tomography fluoroscopy-guided solitary lung tumor model in a rabbit.

Choi Byeong Hyeon BH Young Hwan Seok HS Quan Yu Hua YH Rho Ji Yun JY Eo Jae Seon JS Han Kook Nam KN Choi Young Ho YH Kim Hyun Koo HK

PloS one 20170613 6

Preclinical studies of lung cancer require suitable large-animal models to allow evaluation and development of surgical and interventional techniques. We assessed the feasibility and safety of a novel rabbit lung cancer model of solitary tumors, in which real-time computed tomography fluoroscopy is used to guide inoculation of VX2 carcinoma single-cell suspensions. Thirty-eight rabbits were divided into four groups according to the volume of the VX2 tissue or cell suspension, the volume of lipio ...[more]

PMID: 28609443

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Project description:BackgroundIt has been thought a larger bore biopsy needle may yield a better sample for molecular testing, but this could potentially expose the patient to higher pneumothorax rates. This study aims to determine if a larger bore biopsy system results in more complications.MethodsA total of 193 patients who underwent computed tomography (CT)-guided lung biopsy in a single tertiary center from 2013-2021 were evaluated retrospectively. Patients were divided into two groups, patients who underwent lung biopsy using the 17/18-gauge (18G) biopsy system and the 19/20-gauge (20G) biopsy system. Data recorded included biopsy needle gauge, nodule location and size, plug use, positioning, the length of the intraparenchymal tract, number of biopsy passes, pneumothorax, chest tube insertion, and admission.ResultsThe mean age was 64.1±12.4 years. The median diameter of the lung nodules was 1.95 cm, and the median depth of the intraparenchymal needle tract was 2.7 cm. Pneumothorax was identified during the procedure by CT fluoroscopy or on post-procedural chest X-ray (CXR). The overall rate of pneumothorax among all patients was 35.2%, and 10.9% of the study population (i.e., 30.1% of patients with pneumothorax) required chest tube insertion. The rate of pneumothorax or chest tube insertion was not significantly different between patients who underwent lung biopsy using 17/18G or 19/20G biopsy system. Patients who developed pneumothorax were older, with smaller-sized pulmonary nodules and longer length of the intraparenchymal tract. The pathologic sensitivity of the 18G gun was higher than that of the 20G gun (93% sensitivity, 100% specificity vs. 79.5% sensitivity, 100% specificity). In the multivariate logistic regression fitted model, the length of the intraparenchymal tract was the only factor predictive of post-procedural pneumothorax and chest tube insertion. An intraparenchymal needle tract length of greater than 2 cm was identified to have the best threshold to predict pneumothorax [sensitivity: 73.5%; false positive rate: 57.6%; area under the curve: 66.27%].ConclusionsFindings suggest similar rates of pneumothorax and chest tube insertion using small 19/20G vs. 17/18G biopsy systems. The 18G system was more sensitive compared to the 20G system in determining pathologic results. Increasing length of lung parenchyma needle tract and smaller lung nodules appear to be risk factors for pneumothorax. Physicians should plan on intraparenchymal tracts that are less than 2 cm to decrease the chance of pneumothorax.

Project description:To describe in detail a dataset consisting of serial four-dimensional computed tomography (4DCT) and 4D cone beam CT (4DCBCT) images acquired during chemoradiotherapy of 20 locally advanced, nonsmall cell lung cancer patients we have collected at our institution and shared publicly with the research community.As part of an NCI-sponsored research study 82 4DCT and 507 4DCBCT images were acquired in a population of 20 locally advanced nonsmall cell lung cancer patients undergoing radiation therapy. All subjects underwent concurrent radiochemotherapy to a total dose of 59.4-70.2 Gy using daily 1.8 or 2 Gy fractions. Audio-visual biofeedback was used to minimize breathing irregularity during all fractions, including acquisition of all 4DCT and 4DCBCT acquisitions in all subjects. Target, organs at risk, and implanted fiducial markers were delineated by a physician in the 4DCT images. Image coordinate system origins between 4DCT and 4DCBCT were manipulated in such a way that the images can be used to simulate initial patient setup in the treatment position. 4DCT images were acquired on a 16-slice helical CT simulator with 10 breathing phases and 3 mm slice thickness during simulation. In 13 of the 20 subjects, 4DCTs were also acquired on the same scanner weekly during therapy. Every day, 4DCBCT images were acquired on a commercial onboard CBCT scanner. An optically tracked external surrogate was synchronized with CBCT acquisition so that each CBCT projection was time stamped with the surrogate respiratory signal through in-house software and hardware tools. Approximately 2500 projections were acquired over a period of 8-10 minutes in half-fan mode with the half bow-tie filter. Using the external surrogate, the CBCT projections were sorted into 10 breathing phases and reconstructed with an in-house FDK reconstruction algorithm. Errors in respiration sorting, reconstruction, and acquisition were carefully identified and corrected.4DCT and 4DCBCT images are available in DICOM format and structures through DICOM-RT RTSTRUCT format. All data are stored in the Cancer Imaging Archive (TCIA, http://www.cancerimagingarchive.net/) as collection 4D-Lung and are publicly available.Due to high temporal frequency sampling, redundant (4DCT and 4DCBCT) data at similar timepoints, oversampled 4DCBCT, and fiducial markers, this dataset can support studies in image-guided and image-guided adaptive radiotherapy, assessment of 4D voxel trajectory variability, and development and validation of new tools for image registration and motion management.

Project description:BackgroundMultimodality positron emission tomography/computed tomography (PET/CT) imaging combines the anatomical information of CT with the functional information of PET. In the diagnosis and treatment of many cancers, such as non-small cell lung cancer (NSCLC), PET/CT imaging allows more accurate delineation of tumor or involved lymph nodes for radiation planning.PurposeIn this paper, we propose a hybrid regional network method of automatically segmenting lung tumors from PET/CT images.MethodsThe hybrid regional network architecture synthesizes the functional and anatomical information from the two image modalities, whereas the mask regional convolutional neural network (R-CNN) and scoring fine-tune the regional location and quality of the output segmentation. This model consists of five major subnetworks, that is, a dual feature representation network (DFRN), a regional proposal network (RPN), a specific tumor-wise R-CNN, a mask-Net, and a score head. Given a PET/CT image as inputs, the DFRN extracts feature maps from the PET and CT images. Then, the RPN and R-CNN work together to localize lung tumors and reduce the image size and feature map size by removing irrelevant regions. The mask-Net is used to segment tumor within a volume-of-interest (VOI) with a score head evaluating the segmentation performed by the mask-Net. Finally, the segmented tumor within the VOI was mapped back to the volumetric coordinate system based on the location information derived via the RPN and R-CNN. We trained, validated, and tested the proposed neural network using 100 PET/CT images of patients with NSCLC. A fivefold cross-validation study was performed. The segmentation was evaluated with two indicators: (1) multiple metrics, including the Dice similarity coefficient, Jacard, 95th percentile Hausdorff distance, mean surface distance (MSD), residual mean square distance, and center-of-mass distance; (2) Bland-Altman analysis and volumetric Pearson correlation analysis.ResultsIn fivefold cross-validation, this method achieved Dice and MSD of 0.84 ± 0.15 and 1.38 ± 2.2 mm, respectively. A new PET/CT can be segmented in 1 s by this model. External validation on The Cancer Imaging Archive dataset (63 PET/CT images) indicates that the proposed model has superior performance compared to other methods.ConclusionThe proposed method shows great promise to automatically delineate NSCLC tumors on PET/CT images, thereby allowing for a more streamlined clinical workflow that is faster and reduces physician effort.

Dataset Information

Real-time computed tomography fluoroscopy-guided solitary lung tumor model in a rabbit.

Publications

Real-time computed tomography fluoroscopy-guided solitary lung tumor model in a rabbit.

Similar Datasets

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