Dr. Cristian T. Badea is a Professor in the Department of Radiology and faculty in the Departments of Biomedical Engineering and Medical Physics. His research focuses on pre-clinical imaging. Dr. Badea has research interests in the physics and biomedical applications of computed tomography (CT), micro-CT, tomosynthesis, and image reconstruction algorithms.
Professor in Radiology
School of Medicine
Associate Professor of Biomedical Engineering
Pratt School of Engineering
Member of the Duke Cancer Institute
Duke Cancer Institute
School of Medicine
University of Patras (Greece)
Tumor perfusion in small animals with tomographic digital subtraction angiography
National Institutes of Health
MRI-Based Deep Learning Segmentation and Radiomics of Sarcoma in Mice.
Small-animal imaging is an essential tool that provides noninvasive, longitudinal insight into novel cancer therapies. However, considerable variability in image analysis techniques can lead to inconsistent results. We have developed quantitative imaging for application in the preclinical arm of a coclinical trial by using a genetically engineered mouse model of soft tissue sarcoma. Magnetic resonance imaging (MRI) images were acquired 1 day before and 1 week after radiation therapy. After the second MRI, the primary tumor was surgically removed by amputating the tumor-bearing hind limb, and mice were followed for up to 6 months. An automatic analysis pipeline was used for multicontrast MRI data using a convolutional neural network for tumor segmentation followed by radiomics analysis. We then calculated radiomics features for the tumor, the peritumoral area, and the 2 combined. The first radiomics analysis focused on features most indicative of radiation therapy effects; the second radiomics analysis looked for features that might predict primary tumor recurrence. The segmentation results indicated that Dice scores were similar when using multicontrast versus single T2-weighted data (0.863 vs 0.861). One week post RT, larger tumor volumes were measured, and radiomics analysis showed greater heterogeneity. In the tumor and peritumoral area, radiomics features were predictive of primary tumor recurrence (AUC: 0.79). We have created an image processing pipeline for high-throughput, reduced-bias segmentation of multiparametric tumor MRI data and radiomics analysis, to better our understanding of preclinical imaging and the insights it provides when studying new cancer therapies.
Holbrook, M. D., et al. “MRI-Based Deep Learning Segmentation and Radiomics of Sarcoma in Mice.” Tomography, vol. 6, no. 1, Mar. 2020, pp. 23–33. Pubmed, doi:10.18383/j.tom.2019.00021.
The impact of respiratory gating on improving volume measurement of murine lung tumors in micro-CT imaging.
Small animal imaging has become essential in evaluating new cancer therapies as they are translated from the preclinical to clinical domain. However, preclinical imaging faces unique challenges that emphasize the gap between mouse and man. One example is the difference in breathing patterns and breath-holding ability, which can dramatically affect tumor burden assessment in lung tissue. As part of a co-clinical trial studying immunotherapy and radiotherapy in sarcomas, we are using micro-CT of the lungs to detect and measure metastases as a metric of disease progression. To effectively utilize metastatic disease detection as a metric of progression, we have addressed the impact of respiratory gating during micro-CT acquisition on improving lung tumor detection and volume quantitation. Accuracy and precision of lung tumor measurements with and without respiratory gating were studied by performing experiments with in vivo images, simulations, and a pocket phantom. When performing test-retest studies in vivo, the variance in volume calculations was 5.9% in gated images and 15.8% in non-gated images, compared to 2.9% in post-mortem images. Sensitivity of detection was examined in images with simulated tumors, demonstrating that reliable sensitivity (true positive rate (TPR) ≥ 90%) was achievable down to 1.0 mm3 lesions with respiratory gating, but was limited to ≥ 8.0 mm3 in non-gated images. Finally, a clinically-inspired "pocket phantom" was used during in vivo mouse scanning to aid in refining and assessing the gating protocols. Application of respiratory gating techniques reduced variance of repeated volume measurements and significantly improved the accuracy of tumor volume quantitation in vivo.
Blocker, S. J., et al. “The impact of respiratory gating on improving volume measurement of murine lung tumors in micro-CT imaging.” Plos One, vol. 15, no. 2, 2020, p. e0225019. Pubmed, doi:10.1371/journal.pone.0225019.
Photon-counting cine-cardiac CT in the mouse.
The maturation of photon-counting detector (PCD) technology promises to enhance routine CT imaging applications with high-fidelity spectral information. In this paper, we demonstrate the power of this synergy and our complementary reconstruction techniques, performing 4D, cardiac PCD-CT data acquisition and reconstruction in a mouse model of atherosclerosis, including calcified plaque. Specifically, in vivo cardiac micro-CT scans were performed in four ApoE knockout mice, following their development of calcified plaques. The scans were performed with a prototype PCD (DECTRIS, Ltd.) with 4 energy thresholds. Projections were sampled every 10 ms with a 10 ms exposure, allowing the reconstruction of 10 cardiac phases at each of 4 energies (40 total 3D volumes per mouse scan). Reconstruction was performed iteratively using the split Bregman method with constraints on spectral rank and spatio-temporal gradient sparsity. The reconstructed images represent the first in vivo, 4D PCD-CT data in a mouse model of atherosclerosis. Robust regularization during iterative reconstruction yields high-fidelity results: an 8-fold reduction in noise standard deviation for the highest energy threshold (relative to unregularized algebraic reconstruction), while absolute spectral bias measurements remain below 13 Hounsfield units across all energy thresholds and scans. Qualitatively, image domain material decomposition results show clear separation of iodinated contrast and soft tissue from calcified plaque in the in vivo data. Quantitatively, spatial, spectral, and temporal fidelity are verified through a water phantom scan and a realistic MOBY phantom simulation experiment: spatial resolution is robustly preserved by iterative reconstruction (10% MTF: 2.8-3.0 lp/mm), left-ventricle, cardiac functional metrics can be measured from iodine map segmentations with ~1% error, and small calcifications (615 μm) can be detected during slow moving phases of the cardiac cycle. Given these preliminary results, we believe that PCD technology will enhance dynamic CT imaging applications with high-fidelity spectral and material information.
Clark, DP; Holbrook, M; Lee, C-L; Badea, CT
Clark, Darin P., et al. “Photon-counting cine-cardiac CT in the mouse.” Plos One, vol. 14, no. 9, 2019, p. e0218417. Pubmed, doi:10.1371/journal.pone.0218417.
Sensitization of Vascular Endothelial Cells to Ionizing Radiation Promotes the Development of Delayed Intestinal Injury in Mice.
Exposure of the gastrointestinal (GI) tract to ionizing radiation can cause acute and delayed injury. However, critical cellular targets that regulate the development of radiation-induced GI injury remain incompletely understood. Here, we investigated the role of vascular endothelial cells in controlling acute and delayed GI injury after total-abdominal irradiation (TAI). To address this, we used genetically engineered mice in which endothelial cells are sensitized to radiation due to the deletion of the tumor suppressor p53. Remarkably, we found that VE-cadherin-Cre; p53FL/FL mice, in which both alleles of p53 are deleted in endothelial cells, were not sensitized to the acute GI radiation syndrome, but these mice were highly susceptible to delayed radiation enteropathy. Histological examination indicated that VE-cadherin-Cre; p53FL/FL mice that developed delayed radiation enteropathy had severe vascular injury in the small intestine, which was manifested by hemorrhage, loss of microvessels and tissue hypoxia. In addition, using dual-energy CT imaging, we showed that VE-cadherin-Cre; p53FL/FL mice had a significant increase in vascular permeability of the small intestine in vivo 28 days after TAI. Together, these findings demonstrate that while sensitization of endothelial cells to radiation does not exacerbate the acute GI radiation syndrome, it is sufficient to promote the development of late radiation enteropathy.
Lee, Chang-Lung, et al. “Sensitization of Vascular Endothelial Cells to Ionizing Radiation Promotes the Development of Delayed Intestinal Injury in Mice.” Radiat Res, vol. 192, no. 3, Sept. 2019, pp. 258–66. Pubmed, doi:10.1667/RR15371.1.
To gate or not to gate: An evaluation of respiratory gating techniques to improve volume measurement of murine lung tumors in micro-CT imaging
© 2019 SPIE. Small animal imaging has become essential in evaluating new cancer therapies as they are translated from the preclinical to clinical domain. However, preclinical imaging is faced with unique challenges that emphasize the gap between mouse and man. One example is the difference in breathing patterns and breath-holding ability, which can dramatically affect tumor burden assessment in lung tissue. Our group is developing quantitative imaging methods for the preclinical arm of a co-clinical trial studying synergy between immunotherapy (anti-PD-1) and radiotherapy in a soft tissue sarcoma model. To mimic imaging performed in patients, primary sarcomas lesions are imaged with micro-MRI, while detection of lung metastases is performed with micro-CT. This study addresses whether respiratory gating during micro-CT acquisition improves lung tumor volume quantitation. Accuracy and precision of lung tumor measurements was determined by performing experiments involving simulations, a pocket phantom and in vivo scans with and without prospective respiratory gating. Sensitivity and precision of segmentation with and without gating was studied using simulated lung tumors. A clinically-inspired "pocket phantom" was used during in vivo mouse scanning to aid in refining and assessing the gating protocols. Finally, we performed a series of in vivo scans on tumor-bearing mice while varying the animal's position (test-retest), and performing the analyses in triplicate to assess the effects of gating. Application of respiratory gating techniques reduced variance of repeated volume measurements and significantly improved the accuracy of tumor volume quantitation in vivo.
Blocker, S. J., et al. “To gate or not to gate: An evaluation of respiratory gating techniques to improve volume measurement of murine lung tumors in micro-CT imaging.” Progress in Biomedical Optics and Imaging Proceedings of Spie, vol. 10953, 2019. Scopus, doi:10.1117/12.2512534.
Progress in Biomedical Optics and Imaging Proceedings of Spie
Angiography, Digital Subtraction
Carcinoma, Non-Small-Cell Lung
Cardiac-Gated Imaging Techniques
Cardiovascular Physiological Phenomena
Cell Line, Tumor
Disease Models, Animal
Equipment Failure Analysis
Equipment and Supplies
Evaluation Studies as Topic
Fluorescent Antibody Technique
Four-Dimensional Computed Tomography
Image Interpretation, Computer-Assisted
Image Processing, Computer-Assisted
Magnetic Resonance Imaging
Mammary Neoplasms, Animal
Mammary Neoplasms, Experimental
Mice, Inbred BALB C
Mice, Inbred C57BL
Platelet Endothelial Cell Adhesion Molecule-1
Product Surveillance, Postmarketing
Proto-Oncogene Proteins p21(ras)
Radiation Injuries, Experimental
Radiographic Image Enhancement
Radiographic Image Interpretation, Computer-Assisted
Rats, Inbred F344
Reproducibility of Results
Respiratory-Gated Imaging Techniques
Reverse Transcriptase Polymerase Chain Reaction
Sensitivity and Specificity
Spectrometry, X-Ray Emission
Tomography Scanners, X-Ray Computed
Tomography, Emission-Computed, Single-Photon
Tomography, X-Ray Computed
Tumor Markers, Biological
Tumor Suppressor Protein p53
Ventricular Function, Left
Whole Body Imaging
X-Ray Intensifying Screens
Professor in Radiology
Bryan Research Building, Room 161F, Durham, NC 27710