The Gene Kim Lab is focused on understanding the tumor microenvironment through magnetic resonance imaging (MRI), and developing efficient non-invasive imaging tools for reliable prediction and assessment of treatment response in cancer. Treating aggressive cancer remains challenging. It is often unclear whether the lack of an effective response is due to a failure to deliver therapeutics, or an ineffectiveness of therapeutics to kill cancer cells. It is therefore necessary to assess both blood flow and cell death to elucidate the underlying mechanism, and to optimize the treatments. The overarching goal of our research is to understand the link between MRI measures and tumor microstructural and functional properties. Understanding these properties can be beneficial to the development of new diagnostic and therapeutic approaches.
To unravel the complexity of cancer, the lab has been working on several MRI studies with a focus on (i) tumor vascularity, (ii) cellular properties, and (iii) the association of adipose tissue with cancer development and treatment.
Associated Lab Members
Dr. Gene Kim is a professor of biomedical engineering in radiology at Weill Cornell Medicine. He received his Ph.D. in biomedical engineering from the University of Southern California and completed his postdoctoral fellowship in cancer imaging at the University of Pennsylvania. His research focuses on the development of quantitative dynamic contrast-enhanced and diffusion magnetic resonance imaging methods for early detection of cancer and assessment of treatment response, particularly in breast cancer and head and neck cancer. Dr. Kim’s laboratory has been funded by grants from the National Institutes of Health.
Ayesha Das received her Bachelor in Psychology from New York University. During her undergraduate training, she worked in the laboratory of Dr. Wendy Suzuki in the Center for Neuroscience on the physiological changes in sedentary, middle-aged adults who underwent a three-month exercise intervention. She received a Dean’s Undergraduate Research Fund grant to further investigate changes in electroencephalograms (EEG) and behavior in response to exercise intervention. She also worked in the laboratory of Dr. Keith Woerpel in the Department of Chemistry on synthesizing a diastereoselective cyclic acetal and received another Dean’s Undergraduate Research Fund grant to pursue this synthesis. In the Gene Kim lab, Ayesha is interested in synthesizing multimodal contrast agents in order to improve the reproducibility and confidence of the arterial input function as measured through dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI).
Dr. Jin Zhang is an instructor in the radiology department of Weill Cornell Medicine (WCM). Before joining WCM, he was an associate research scientist at the New York University Langone Medical Center. He has focused on dynamic contrast enhanced (DCE)-magnetic resonance imaging (MRI) research for a decade. He specializes in skills related to DCE-MRI using mouse models, including tumor implantation, animal handling, DCE-MRI scanning, image reconstruction, pharmacokinetic model analysis, data processing, and visualization. One contribution: the development of active contrast encoding (ACE)-MRI, which measures multiple parameters in a shortened DCE-MRI scan time and eliminates the need for image registration in traditional DCE-MRI. His research interests are focused on shortening clinical scan time and improving image quality and resolution. With collaborators, he developed another innovative technique for DCE-MRI, 3D ultra-short echo time with golden-angle radial sparse parallel MRI (3D-UTE-GRASP), which extended the GRASP technique from volumetric coverage to 3D isotropic high-resolution coverage in DCE-MRI. These techniques can be directly implemented to clinical scans, greatly improving DCE-MRI quantitative analysis, and benefitting the diagnosis and treatment of various cancers.
Eddy Solomon’s research combines diverse aspects of magnetic resonance imaging (MRI), including pulse sequence programming, advanced image reconstruction, and pre-clinical and clinical patient studies. He received his Ph.D. from the department of chemical physics at the Weizmann Institute of Science, where he developed novel MR methods, based on spatiotemporal encoding (SPEN) principles. He is now a Weill Cornell Medicine faculty instructor of chemical physics in the radiology department. He works on head and neck cancer using diffusion and dynamic contrast-enhanced (DCE) approaches. His aim is to advance body magnetic resonance imaging (MRI) methods in humans, to improve both basic knowledge and patient care.
Jonghyun Bae received his bachelor’s degree in electrical and computer engineering from Rutgers University and his master’s degree in electrical engineering from New York University (NYU) Tandon School of Engineering. He is currently pursuing his Ph.D. in biomedical imaging and technology at Vilcek Institute of Biomedical Graduate study (NYU School of Medicine). His research focuses on detecting subtle blood-brain barrier (BBB) disruptions in Alzheimer’s disease and aging using dynamic contrast-enhanced (DCE) magnetic resonance imaging. Jonghyun has also been interested in developing deep learning-based tools to aid the DCE analysis tailored to detect the subtle changes in BBB.
Karl Kiser received his bachelor’s degree in biophysics from Pitzer College, a Claremont College. During his undergraduate studies, Karl developed his interest in medical imaging while working under Dr. Adam Landsberg, investigating network properties of the human brain connectome from diffusion tensor imaging and fiber tractography. In the Gene Kim Lab, Karl’s focus is on developing methods for characterizing the tissue microenvironment of cancer, particularly cellular water exchange, through the kinetic modeling of dynamic contrast-enhanced magnetic resonance imaging.
Sawwal Qayyum received his bachelor’s degree in biology from Ramapo College of New Jersey. During his undergraduate training, he spent his seminar year looking at embryogenesis-lethal genes in C. elegans using RNA interference (RNAi) and clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 to visualize protein localization via green fluorescent (GFP) recombinant vectors. He previously worked at the New York University Langone Medical Center as a senior animal care technician, attaining there his laboratory animal technologist certification. He spent two years interning at the Preclinical Imaging Core headed by Dr. Wadghiri. There he became familiar with different modalities of optical imaging, magnetic resonance imaging (MRI), and tumor pH probe design. In the Gene Kim lab, Sawwal is studying the effect of metronomic chemotherapy on the tumor vasculature and angiogenesis of orthotopic triple-negative breast cancer (TNBC) and glioma mouse models using dynamic contrast-enhanced (DCE)-MRI.
Imaging tumor vascular properties
Chaotic vascular growth is a hallmark of malignant tumors and an important target for cancer treatment. The primary method that we have been using for the study of tumor vascularity is dynamic contrast enhanced (DCE) MRI (Kim et al., 2007 and 2010). In order to further understand the contrast dynamics inside the tumor with a high precision, the lab has been actively developing fast MRI methods that provide a higher temporal and spatial resolution, including the 3D ultra-short echo time (UTE) golden-angle radial sparse and parallel (GRASP) MRI method (Feng et al., 2014; Zhang et al., 2019).
Among many contrast kinetic parameters that can be measured using DCE-MRI, the Kim lab is particularly interested in the cellular-interstitial water exchange rate. The lab's recent head and neck cancer study found patients with slower transcytolemmal water exchange rates at pre-treatment have significantly prolonged overall survival at five years and beyond (Chawla et al., 2018). The lab showed that the effect of water exchange can be actively encoded in the dynamic data in order to improve the precision of water exchange rate measurement (Zhang and Kim, 2019). In addition, the lab introduced a single comprehensive imaging method, namely active contrast encoding (ACE)-MRI (Zhang et al., 2017), that provides pre-contrast T1 and actual flip angle from the dynamic data and eliminates the need to measure them separately. The goal: bring quantitative DCE-MRI to routine clinical imaging exams for accurate assessment of cancer treatment response, and also to extend its use to other microvascular diseases.
Imaging tumor cellular properties
Another useful approach for the assessment of tumor treatment response is to measure cellular microstructural properties using diffusion MRI (dMRI) (Kim et al., 2009). Conventional dMRI measures such as apparent diffusion coefficient, however, remain non-specific biomarkers. The dMRI technique allows one to represent different biophysical properties of tissue depending on the diffusion weighting strength (q) and diffusion time (t) used for the measurement. The feasibility of measuring cell size using the t-dependency of dMRI was reported earlier with reference to different muscle groups (Kim et al., 2005). Inspired by these results, the lab has focused on investigating quantitative ways to utilize both the q- and t-dependency of dMRI data for assessment of cell viability by measuring cell size, extracellular volume fraction, and cellular compartmental diffusivities. This led the lab to propose the POMACE (pulsed and oscillating gradient MRI for assessment of cell size and extracellular space) framework (Reynaud et al., 2016) as a non-invasive imaging method to measure cellular microstructural properties.
Moreover, the lab has demonstrated that t-dependency of diffusional kurtosis can also be used to measure the cellular-interstitial water exchange rate (Zhang et al., 2021). This innovative approach does not require the use of an exogenous contrast agent to measure the water exchange rate and can provide a non-contrast imaging marker for cellular metabolism. The lab's investigation of quantitative dMRI measures in cancer, including the cellular-interstitial water exchange rate in head and neck cancer patients undergoing radiation therapy, is conducted in collaboration with the National Institutes of Health/National Cancer Institute (NIH/NCI) Quantitative Imaging Network.
Association of adipose tissue with cancer development
It has been increasingly recognized that adipose tissue may not be an “innocent bystander” in cancer development and progression. The lab has been developing fast MR spectroscopic imaging methods to measure fatty acid compositions in breast adipose tissue and investigating how these fatty acids are associated with breast cancer (Freed et al., 2016). After menopause, adipose tissue becomes the principal site of estrogen biosynthesis, and there is ample evidence demonstrating possible links between tissue hormone levels and fatty acid composition. While these hormonal effects are recognized as significant confounding factors in breast MRI, they may also provide a non-invasive means to study the effect of hormones on normal breast tissue and its association with breast cancer development and progression as demonstrated in our previous studies (Amarosa et al., 2013; Clendenen et al., 2013).
The team aims to develop MR spectroscopic imaging methods to measure fatty acid composition in breast adipose tissue and to assess its association with female hormones at the tissue level; the vascular and cellular properties of breast fibroglandular tissue; and cancer development.
Award or Grant: R01CA219964, National Cancer Institute (NCI) (02/01/18 – 01/31/23).
Description: The role of breast fatty acid composition in breast cancer development, in conjunction with breast density and body mass index, has not been fully investigated. The central hypothesis of the Kim lab is that...
Awards or Grants: UG3/UH3CA228699, National Cancer Institute NCI, 5/1/2019 to 4/30/2024
Description: Quantitative diffusion magnetic resonance imaging (dMRI) remains challenging as dMRI data represent different biophysical properties of tissue depending on diffusion weighting strength (q) and diffusion...
Awards or Grants: R01 CA160620, National Cancer Institute (NCI), 2/1/2019-1/31/2024
Description: Assessment of cancer treatment requires an effective non-invasive method of measuring both the vascular and cellular changes induced by therapies. The Kim team’s underlying hypothesis is that a single...
