Medical // 05.04.2022 // DECTRIS

Tumor Imaging With a Novel Spectral Micro-CT

A 10-minute read

Radiomics is a rapidly growing field in diagnostic radiology, wherein images are data mined to define phenotypic characteristics of tumors by extracting quantitative image features such as intensity, shape, size, morphology, and texture. Spectral information obtained using photon-counting detectors (PCD) can improve radiomic analysis based on computed tomography (CT). PCD-CT can generate images with less noise, higher resolution, and improved contrast-to-noise ratio when compared to conventional CT based on energy integrating detectors. Recently, researchers from Duke University have developed PCD-based micro-CT prototypes for quantitative preclinical cancer imaging and for testing novel nanoparticle (NP) contrast agents. On the occasion of their latest publication , we sat down with the group leader, Dr. Cristian Badea, for a short interview.

DECTRIS: Where does your fascination for photon-counting detector technology come from and why did you choose to use it for pre-clinical imaging applications?

Dr. Cristian Badea, leader of the Quantitative Imaging and Analysis Lab at Duke University: Preclinical research is essential in developing and optimizing novel therapeutic approaches. For the last two decades, our lab at Duke University has been engaged in developing X-ray based preclinical imaging. At the time when no commercial or academic micro-CT imaging systems were capable of performing dynamic cardiac CT in the mouse, at Duke our group designed and built a unique micro-CT system that was used to produce the first in vivo cine CT imaging of the murine heart. Following that achievement, we have built next a second-generation dual source/detector micro-CT designed faster dynamic imaging but also capable of spectral characterizations via dual energy. Dual energy micro-CT was applied in imaging myocardial infarction, classification of atherosclerotic plaque composition, and the classification of tumor aggressiveness in lung cancer, and therapy response in primary sarcoma tumors. We were the first to demonstrate dual energy micro-CT imaging using dual nanoparticles (gold and iodine) to image two important vascular biomarkers in tumors—the microvascular blood volume and vascular permeability. However, our dual source micro-CT system used two energy integrating detectors with limited spectral separations. To further improve our spectral and temporal CT imaging we have switched to photon counting detectors and in fact, even implemented a hybrid dual source micro-CT system which uses both a photon counting detector made by DECTRIS and an energy integrating detector.

Setup of the dual-source hybrid micro-CT system. Holbrook, M., D.P. Clark, and C.T. Badea, Dual source hybrid spectral micro-CT using an energy-integrating and a photon-counting detector. Physics in Medicine & Biology, 65, 205012, 2020.

DECTRIS: What clinical problem could you demonstrate to solve with Photon Counting detector technology in your recently published study in the journal Tomography?

Cristian: The purpose of this study was to investigate if radiomic analysis based on preclinical photon counting CT with nanoparticle contrast-enhancement can differentiate tumors based on lymphocyte burden.

The immune response to neoplastic disease involves infiltration by lymphocytes (including T cells and B cells). T cells and B cells are the major cellular components of the adaptive immune response, and they play an important role in cancer progression and response to certain therapeutics, particularly to immunotherapy. Assessment of tumor lymphocytes is usually performed by histopathology and may provide important prognostic information in tumors. However, implementation as a routine clinical biomarker has not yet been achieved. Radiomics provides an innovative approach for identifying and developing quantitative cancer imaging biomarkers that are otherwise not possible when based on conventional imaging-based metrics. Spectral information obtained using photon-counting detectors can improve radiomic analysis based on CT. Although our study was performed at preclinical level using mice,  it will open a window for clinical translation of radiomics on photon counting CT to better differentiate tumors.

Maximum Intensity Projections (MIPs) of the decomposition maps for Rag2−/− and Rag2+/− mouse demonstrate intratumoral nanoparticle accumulation and iodine enhancement as well as the overall quality of the decomposition results. Each pixel in these images represents the maximum voxel value across a projection through a given number of slices. In this case, we have chosen 20 coronal slices to capture the tumor vasculature. We show the Iodine (I), Photoelectric Effect (PE), and Compton Scattering (CS) maps.

DECTRIS: What is needed to bring your methods and imaging protocols into the clinic?

Cristian: The clinical adoption of photon counting technology is still at the very beginnings.  Apart from our preclinical (our in house developed) photon counting micro-CT system, at Duke we are one of the few sites with access to a clinical photon counting CT (Siemens NAEOTOM Alpha). The access to both systems will enable us to perform co-clinical research. By performing scans on both clinical and preclinical photon counting CT systems, we can bridge the translational gap for both imaging algorithms and potentially for the testing of new contrast agents including nanoparticles that show promise in the field of cancer or cardiac theranostics. Moreover, our work will enable new and powerful integrative approaches in co-clinical cancer research where photon counting CT will provide essential imaging data.

Tumor imaging with a novel spectral micro-CT, Quantitative Imaging and Analysis Lab, Duke Radiology.

About Dr. Cristian Badea

Dr. Cristian Badea obtained his PhD at the University of Patras, Greece, in 2001. Shortly later, he joined the Duke University. Cristian is a professor of radiology and he is a head of lab for Quantitative Imaging and Analysis. His research is primarily focused on developing novel imaging systems, reconstruction algorithms and analysis methods, based on X-rays: computed tomography (CT), micro-CT, micro-DSA, tomosynthesis, and fluorescence tomography. His particular interest is extending CT imaging to functional and even molecular imaging capabilities.

About Quantitative Imaging and Analysis Lab at the Duke University

Led by Dr. Cristian Badea, this laboratory is focused on development, optimization and application of novel CT and MRI quantitative imaging at both preclinical and clinical levels. The group counts fifteen members of different backgrounds: radiology, computer science, engineering, and physics. This successful combination of expertise has resulted in various projects and many publications . Apart from research, the laboratory is also offering a service of micro-CT scanning.

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