Cancer Imaging Research

The Henry Ford Cancer Institute’s cancer imaging research program brings together expertise in clinical and basic research imaging. Clinical imaging is the use of proven imaging methods or localized areas of interest to treat a person’s condition. Basic research imaging also uses imaging, but for the purposes of developing innovations in how we will treat patients into the future.

Doctors can treat only the tumors that they can see. Radiologists (doctors who specialize in diagnosing disease using many different types of imaging) help detect cancer. This imaging can then be used to help surgeons, medical oncologists (doctors who specialize in treating cancer with many types of therapies) and radiation oncologists (doctors who specialize in treating disease with targeted radiation therapy) to devise effective treatment plans.

Doctors use imaging for all cancer types to visualize tumors and nearby organs at risk and to better target cancer. Our researchers work to improve the identification, diagnosis and treatment of tumors.

Our cancer imaging investigators belong to the Department of Radiology, the Department of Radiation Oncology and the Department of Neurology. They collaborate with our other cancer research programs.

Our cancer imaging research

Our work investigates new ways to use computed tomography (CT) and magnetic resonance (MR) imaging in cancer care. CT imaging uses specialized X-rays to created detailed images, or scans, of the organs, bones and blood vessels. MR imaging uses magnetic pulses and radio waves to create images of the body’s interior, especially soft-tissue structure.

Some of our newest cancer imaging research projects include:

  • Neuromagnetic resonance: We’re actively researching treatment response with stroke and brain malignancies. Find out more about brain tumor research.
  • Functional imaging in MR: Investigators are studying how to take images of areas where more tumors tend to develop or that have high tumor concentration. We’re using a combination of radiation and imaging to deliver higher doses of radiation to very specific areas.
  • Expertise in deformable image registration: Our experts are mapping each pixel -- very tiny parts of an image -- from one type of image to another to understand how to correlate (register, or align) images. In 2015, the group completed a five-year grant from the National Institutes of Health (NIH), and our researchers are well-recognized experts.
  • Accurate integration of MRI into treatment planning: We are researching several areas of integrating MR imaging into radiation treatment planning to use the most accurate imaging possible:
    • How to quantify, evaluate and correct distortions that can reduce the geometric accuracy of MR images. These distortions may be specific to patients or they may happen with a certain machine.
    • How to develop and validate a synthetic CT derived from MR data. This synthetic or “mimicked” CT takes advantage of MRI's superior soft-tissue contrast without introducing additional image registration uncertainties into the planning process, thereby improving treatment accuracy. Eventually, we hope that radiation oncologists will be able to use synthetic CT in lieu of conventional CT scans for radiation therapy treatment planning, which will reduce the number of procedures and health care costs.
  • Adding MRI into treatment planning for prostate cancer: A clinical trial compares treatment plans using CT-only or MR/CT-combined imaging. The five-year longitudinal study includes patient-reported quality of life, including bladder and urinary issues and sexual health. Learn more about our clinical trials.

Other cancer imaging research

We have several other cancer imaging research projects underway, including:

  • Developing guidelines to assist physicians in recommending, performing and interpreting the results of various types of imaging adult and pediatric patients
  • Using advanced tumor perfusion imaging techniques (a type of imaging that helps identify whether tumors, often brain tumors, have progressed), which can help doctors differentiate the effects of treatment from effects caused by recurrent or progressive tumors
  • Using MR and CT data, patient charts, histopathology and genomic data to identify surrogate imaging biomarkers that correlate with gene expression
  • Differentiating glioma (brain tumor) tissue from radiation injury
  • Examining cell-mediated gene therapy using stem cells to deliver suicide genes, or genes that can attract drugs that are lethal to tumors, to the sites of glioma and breast cancer in animal models
  • Determining how tumor vascular permeability changes following therapy targeting growth receptors using contrast agents and nanoparticles
  • Characterizing different stem cell populations collected from cord blood and bone marrow
  • Using molecular imaging facilities (optical imaging) to track the migration and accumulation of genetically modified cells to sites of interest
  • Tracking the migration and accumulation of nanoprobes to specific targets in brain tumors, via optical imaging
  • Developing ways to characterize cerebrovascular (brain/blood vessel) imaging parameters such as blood flow and volume to serve as indicators for therapeutic response
  • Developing specialized MRI sequences and post-processing software to detect cancer and treatment response
  • Developing novel imaging and contrast agents
  • Studying tumor progression and early responses to chemotherapies in preclinical models of breast and brain tumors, using MRI

Spotlight: studying MR-only planning for radiation therapy

To more precisely localize cancer in the brain, abdomen or pelvis, most radiation oncologists use magnetic resource imaging together with computed tomography (CT) scans to accurately devise patient-specific radiation treatment plans. However, using both imaging modalities can introduce additional uncertainties due to differences in anatomy between the scans. Meanwhile, having two imaging sessions increases costs and patient time.

At Henry Ford, we’re working to understand the circumstances in which MR-only imaging for use in radiation treatment planning is safe and effective. Our advances include:

  • Use of MR imaging in radiation therapy: In 2013, Henry Ford acquired one of the nation’s first radiation oncology-dedicated MRI simulation (MR-SIM) scanners. MR-SIM is different from other MRI units in radiology because it has special equipment that allows us to image patients in the position in which they are being treated. We also can use special sequences that help us pinpoint lesions for treatment. The MR-SIM resides at West Bloomfield Hospital and is used to image our radiation therapy patients and to support ongoing research.
  • Development of MR-only radiation therapy: Historically, most radiation therapy includes both CT and MR scans. We’ve received a prestigious grant from the NIH to create a patient model using only MRI data.
  • American Association of Physicists in Medicine task report: Carri Glide-Hurst, Ph.D., is a co-chair with six other national experts on a task group report on how to safely and effectively implement MR-SIM for radiation oncology. The group is developing guidelines on image quality, safety checks and workflow to effectively and accurately apply MR-only technology in a clinical radiation oncology environment.
  • Real-time patient MR imaging: We will be one of the first in the U.S. to offer our patients onboard MRI imaging combined with linear accelerator-based external beam radiation therapy to help radiation oncologists guide and track tumors with respect to the radiation therapy beam. This advance will allow radiation oncologists to visualize anatomy much better and optimize each patient’s treatment plan on a daily basis.
  • NIH grant: Beginning July 1, 2016, we received an NIH R01 grant to study pelvic and brain tumors. This grant will work to translate MR-only radiation for widespread use, with an academic/industry partnership between academics and clinicians at Henry Ford and scientists at Philips.
  • Offline study: We conduct research outside the therapeutic radiation oncology environment. The patients we study simultaneously receive a therapeutically approved imaging protocol.
  • Development of in-house tools: We’re developing our own software tools for MR-only radiation therapy planning. We’re working with Philips, the expert in MRI scanning, to evaluate those tools. The process includes:
    1. MRI landmarks: MRI imaging can be prone to distortion, which risks mismapping of anatomic landmarks. We’re developing a correction algorithm to identify landmarks to map the MRI back to the appropriate location.
    2. Freeware toolkit: Our MRI landmark toolkit will include acquisition and correction approaches including MRI platforms and field strengths (1-tesla, 3-tesla and 5-tesla). Once we validate the toolkit, we’ll make it available via freeware to labs that want to understand and quantify their own magnet.
    3. Clinical approval: Once a toolkit appears to be working, we will create a formal clinical sequence and submit it for FDA approval. This process led to the MR-only sequence for studying prostate cancers.

Benefits of MR-only cancer imaging

The ability to use MR technology alone offers numerous potential benefits for imaging cancer tumors. We’re exploring opportunities to improve treatment based on these advantages.

  • Excellent soft-tissue contrast: MR imaging does a good job of revealing tumors and lesions in soft tissue. As a result, MR is better suited than CT for certain kinds of tumors in the brain, abdomen and pelvis.
  • Consistent, timely imaging: When hospitals take imaging using both a CT and an MR scan, people may be positioned slightly differently for each image. Even a difference of millimeters can affect the success of radiation therapy. In our research, we mimic the radiation oncology treatment setup. As a result, patients who participate in our research have the most up-to-date MRI scans and anatomy before beginning their radiation treatment.
  • Minimal radiation exposure: There are no radiation risks in MRI compared to X-ray-based approaches like CT.
  • Single imaging scan: Traditionally, patients receive both a CT and a MR scan. When we perfect MR-only scanning, patients will be able to save time, have lower costs, have greater accuracy and receive less radiation.

Get involved with cancer imaging research

You can participate in our cancer imaging research work, whether you are a researcher or a patient.

  • Find a clinical trial: At Henry Ford, we offer hundreds of clinical trials so you can benefit from new techniques before they’re widely available. Learn more about clinical trials.
  • Become a Henry Ford researcher: We often accept researchers to assist in cancer imaging research. Join our research team.
  • Support cancer imaging research: Henry Ford’s Cancer Research Advisory Group (CRAG) provides funding and resources to assist our researchers in their work. Learn how you can support cancer research.

Our researchers

Our cancer imaging researchers include investigators and clinical practitioners -- research specialists as well as doctors and radiologists who work directly with patients. Below, you can learn more about our current researchers. You also can read more about how to join our research team.

Cancer imaging research leaders

Cancer imaging scientific members

Cancer imaging clinical members

Publications in cancer imaging research

We share our work regularly with the medical research community through publication in scientific journals. Search the publications below for topics that interest you.

Publications by Henry Ford cancer imaging researchers

AfzAli M, Ghaffari A, Fatemizadeh E and Soltanian-Zadeh H. Medical image registration using sparse coding of image patches. Computers in biology and medicine. 2016; 73:56-70.

Al Feghali KA, Kolozsvary A, Lapanowski K, Isrow D, Brown SL and Kim JH. A novel mechanism of radiosensitization by metformin. International journal of radiation oncology, biology, physics. 2016; 96(2s):E574.

Bagher-Ebadian H, Schwalb J, Mahmoudi F, Air E, Shokri S, Nazem-Zadeh M, Spanaki-Varelas M, Wasade V and Soltanian-Zadeh H. Localized quantitative analysis of positron emission tomography (PET) for temporal lobe epilepsy lateralization and surgical intervention. J Nucl Med. 2016; 57.

Bagher-Ebadian H, Siddiqui F, Liu C, Movsas B and Chetty IJ. Prediction of response to radiation therapy treatment of head and neck cancers using an artificial neural network developed from cone beam computed tomography image textural information. International journal of radiation oncology, biology, physics. 2016; 96(2s):S98.

Baumer TG, Chan D, Mende V, Dischler J, Zauel R, van Holsbeeck M, Siegal DS, Divine G, Moutzouros V and Bey MJ. Effects of rotator cuff pathology and physical therapy on in vivo shoulder motion and clinical outcomes in patients with a symptomatic full-thickness rotator cuff tear. Orthopaedic journal of sports medicine. 2016; 4(9).

Brennan JR, Wagley N, Kovelman I, Bowyer SM, Richard AE and Lajiness-O'Neill R. Magnetoencephalography shows atypical sensitivity to linguistic sound sequences in autism spectrum disorder. Neuroreport. 2016; 27(13):982-986.

Brown SL, Elmghirbi R, Nagaraja T, Keenan KA, Lapanowski K, Panda S, Inder P, Cabral G, Liu L, Kim JH, Movsas B, Chetty IJ, Ewing JR and Parry R. Toward a noninvasive measurement of cancer stem cells and tumor aggressiveness. International journal of radiation oncology, biology, physics. 2016; 96(2s):E592.

Chetvertkov MA, Siddiqui F, Kim J, Chetty I, Kumarasiri A, Liu C and Gordon JJ. Use of regularized principal component analysis to model anatomical changes during head and neck radiation therapy for treatment adaptation and response assessment. Med Phys. 2016; 43(10):5307-5319.

Dehkordi AN, Kamali-Asl A, Ewing JR and Bagher-Ebadian H. An adaptive model for direct estimation of extravascular-extracellular space in dynamic contrast-enhanced magnetic resonance imaging studies. International journal of radiation oncology, biology, physics. 2016; 96(2s):E644.

Elmghirbi R, Nagaraja TN, Brown SL, Panda S, Aryal MP, Keenan KA, Bagher-Ebadian H, Cabral G and Ewing JR. Acute temporal changes of mri-tracked tumor vascular parameters after combined anti-angiogenic and radiation treatments in a rat glioma model: Identifying signatures of synergism. Radiation research. 2016.

Glide-Hurst C, Price R, Kim JP, Zheng W and Chetty IJ. Validation of synthetic CTs for MR-only planning of brain cancer. Radiother Oncol. 2016; 119:S870.

Glide-Hurst CK, Miller BM, Kim JP, Siddiqui MS and Movsas B. Potential failure modes for magnetic resonance-only treatment planning in the pelvis. International journal of radiation oncology, biology, physics. 2016; 96(2s):S233-s234.

Griffith B and Jain R. Perfusion imaging in neuro-oncology: Basic techniques and clinical applications. Magnetic resonance imaging clinics of North America. 2016; 24(4):765-779.

Hosseini MP, Nazem-Zadeh MR, Pompili D, Jafari-Khouzani K, Elisevich K and Soltanian-Zadeh H. Comparative performance evaluation of automated segmentation methods of hippocampus from magnetic resonance images of temporal lobe epilepsy patients. Med Phys. 2016; 43(1):538.

Isrow D, Kolozsvary A, Lapanowski K, Brown SL and Kim JH. Metformin's preferential cytotoxic effect on cancer stem/non-stem cell populations is (glucose) dependent and correlated with intracellular levels of reactive oxygen species. International journal of radiation oncology, biology, physics. 2016; 96(2s):E565.

Karki K, Ewing JR, Ali MM. Targeting glioma with a dual mode optical and paramagnetic nanoprobe across the blood-brain tumor barrier. Journal of nanomedicine & nanotechnology. Aug 2016;7(4) PMID: 27695645.

Kim J, Wu Q, Zhao B, Wen N, Ajlouni M, Movsas B and Chetty IJ. To gate or not to gate - dosimetric evaluation comparing Gated vs. ITV-based methodologies in stereotactic ablative body radiotherapy (SABR) treatment of lung cancer. Radiation oncology (London, England). 2016; 11(1):125.

Kim JH, Brown SL and Kolozsvary A. Methods to mitigate injury from radiation exposure by administering cxcr4 antagonist during decisive treatment window. Google Patents. 2016.

Knight R, Nagaraja T, Li L, Jiang Q, Tundo K, Chopp M and Seyfried D. A prospective safety trial of atorvastatin treatment to assess rebleeding after spontaneous intracerebral hemorrhage: A serial MRI investigation. Austin J Cerebrovasc Dis Stroke. 2016; 3(1).

Kupsky D, Wang DD, Eng M, Song T, Pantelic M, Nadig J, Greenbaum A and O'Neill W. TCT-621 Left atrial appendage characteristics evaluated by computed tomography following closure with Watchman device. J Am Coll Cardiol. 2016; 68(18s):B253.

Liu LJ, Brown SL, Ewing JR, Ala BD, Schneider KM, Schlesinger M. Estimation of tumor interstitial fluid pressure (tifp) noninvasively. PloS one. 2016;11(7):e0140892. PMID: 27467886.

MaBouDi H, Shimazaki H, Amari S and Soltanian-Zadeh H. Representation of higher-order statistical structures in natural scenes via spatial phase distributions. Vision research. 2016; 120:61-73.

Maleki-Balajoo S, Hossein-Zadeh GA, Soltanian-Zadeh H and Ekhtiari H. Locally estimated hemodynamic response function and activation detection sensitivity in heroin-cue reactivity study. Basic and clinical neuroscience. 2016; 7(4):299-314.

Mendiratta-Lala M, Park H, Kolicaj N, Mendiratta V and Bassi D. Small intrahepatic peripheral cholangiocarcinomas as mimics of hepatocellular carcinoma in multiphasic CT. Abdominal radiology (New York). 2016.

Nagaraja TN, Keenan KA, Ewing JR and Knight RA. Surrogate MRI signatures for contrast enhanced imaging that predict acute blood-brain barrier damage in ischemia-reperfusion. Stroke. 2016; 47.

Nazem-Zadeh MR, Bowyer SM, Moran JE, Davoodi-Bojd E, Zillgitt A, Weiland BJ, Bagher-Ebadian H, Mahmoudi F, Elisevich K and Soltanian-Zadeh H. MEG Coherence and DTI Connectivity in mTLE. Brain topography. 2016.

Nazem-Zadeh MR, Elisevich K, Air EL, Schwalb JM, Divine G, Kaur M, Wasade VS, Mahmoudi F, Shokri S, Bagher-Ebadian H and Soltanian-Zadeh H. DTI-based response-driven modeling of mTLE laterality. NeuroImage Clinical. 2016; 11:694-706.

Newman LA, Stark A, Chitale D, Pepe M, Longton G, Worsham MJ, Nathanson SD, Miller P, Bensenhaver JM, Proctor E, Swain M, Patriotis C and Engstrom PF. Association between benign breast disease in african american and white american women and subsequent triple-negative breast cancer. JAMA oncology. 2016.

Parekh R, Kazimi M, Skorupski S, Fagoaga O, Jafri S and Segovia MC. Intestine transplantation across a positive crossmatch with preformed donor-specific antibodies. Transplantation proceedings. 2016; 48(2):489-491.

Petraszko A, Siegal D, Flynn M, Rao SD, Peterson E and van Holsbeeck M. Erratum to: The advantages of tomosynthesis for evaluating bisphosphonate-related atypical femur fractures compared to radiography. Skeletal radiology. 2016.

Price RG, Kim JP, Zheng W, Chetty IJ and Glide-Hurst C. Image guided radiation therapy using synthetic computed tomography images in brain cancer. International journal of radiation oncology, biology, physics. 2016.

Rao B, Jafri SM, Kazimi M, Mullins K, Raoufi M and Segovia MC. A case report of acute cellular rejection following intestinal transplantation managed with adalimumab. Transplantation proceedings. 2016; 48(2):536-538.

Rao B, Segovia MC, Kazimi M, Parekh R, Raoufi M and Jafri SM. Use of everolimus after multivisceral transplantation: A report of two cases. Transplantation proceedings. 2016; 48(2):485-488.

Rezaeian MR, Hossein-Zadeh GA and Soltanian-Zadeh H. Simultaneous optimization of power and duration of radio-frequency pulse in PARACEST MRI. Magnetic resonance imaging. 2016.

Rheinboldt M, DelProposto Z, Blase J and Hakim B. Acute presentation of lhermitte-duclos disease in adult patient in association with cowden syndrome. Appl Radiol. 2016; 45(8):28-31.

Riaz RM, Myers DT and Williams TR. Multidetector CT imaging of bariatric surgical complications: a pictorial review. Abdominal radiology. 2016; 41(1):174-188.

Samadi S, Soltanian-Zadeh H and Jutten C. Integrated Analysis of EEG and fMRI using sparsity of spatial maps. Brain topography. 2016.

Sever A, Rheinboldt M, Scher C, DelProposto Z and Klochko C. Multimodality imaging of gout: A review of characteristic features with attention to recent developments in imaging diagnosis. Emergency Radiology. 2016; 23(6):573.

Sever A, Rheinboldt M, Scher C, DelProposto Z and Klochko C. Musculoskeletal ultrasound in the diagnosis and management of acute crystalline arthropathy: A growing role in the emergency setting. Emergency Radiology. 2016; 23(6):573.

Shaaban S, Alsulami M, Arbab SA, Ara R, Shankar A, Iskander A, Angara K, Jain M, Bagher-Ebadian H, Achyut BR and Arbab AS. Targeting bone marrow to potentiate the anti-tumor effect of tyrosine kinase inhibitor in preclinical rat model of human glioblastoma. International journal of cancer research. 2016; 12(2):69-81.

Shankar A, Borin TF, Iskander A, Varma NR, Achyut BR, Jain M, Mikkelsen T, Guo AM, Chwang WB, Ewing JR, Bagher-Ebadian H and Arbab AS. Combination of vatalanib and a 20-HETE synthesis inhibitor results in decreased tumor growth in an animal model of human glioma. OncoTargets and therapy. 2016; 9:1205-1219.

Shvarts V, Zoltay G, Bowyer SM, Zillgitt A, Moran JE, Mason RK, Tepley N and Burdette D. Periodic discharges: Insight from magnetoencephalography. Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society. 2016.

Siegal D, Davis L, Scheer M and Walker L. Entrapment neuropathies of the upper extremity nerves. Current Radiology Reports. 2016; 4(12).

Simmons RM, Ballman KV, Cox C, Carp N, Sabol J, Hwang RF, Attai D, Sabel M, Nathanson D, Kenler A, Gold L, Kaufman C, Han L, Bleznak A, Stanley Smith J, Holmes D, et al. A phase II trial exploring the success of cryoablation therapy in the treatment of invasive breast carcinoma: Results from ACOSOG (Alliance) Z1072. Annals of surgical oncology. 2016.

Snyder KC, Kim J, Reding A, Fraser C, Gordon J, Ajlouni M, Movsas B and Chetty IJ. Development and evaluation of a clinical model for lung cancer patients using stereotactic body radiotherapy (SBRT) within a knowledge-based algorithm for treatment planning. Journal of applied clinical medical physics. 2016; 17(6):6429.

Spain JA, Rheinboldt M and DelProposto Z. Acute biliary inflammation and secondary complications: The gamut of MDCT imaging findings. Emergency Radiology. 2016; 23(6):572-573.

Stone M, Parrish D, Rheinboldt M, DelProposto Z and Doshi P. Beyond trauma: The gamut of acute inflammatory and vascular spinal emergencies. Emergency Radiology. 2016; 23(6):570-571.

Takahashi K, Obeid J, Burmeister CS, Bruno DA, Kazimi MM, Yoshida A, Abouljoud MS and Schnickel GT. Intrahepatic cholangiocarcinoma in the liver explant after liver transplantation: Histological differentiation and prognosis. Annals of transplantation. 2016; 21:208-215.

To DT, Kim JP, Price RG, Chetty IJ and Glide-Hurst CK. Impact of incorporating visual biofeedback in 4D MRI. Journal of applied clinical medical physics. 2016; 17(3):6017.

Vithanarachchi SM, Foley CD, Trimpin S, Ewing JR, Ali MM, Allen MJ. Myelin-targeted, texaphyrin-based multimodal imaging agent for magnetic resonance and optical imaging. Contrast media & molecular imaging. Sep 6 2016 PMID: 27596704.

Wang DD, Eng M, Kupsky D, Myers E, Forbes M, Rahman M, Zaidan M, Parikh S, Wyman J, Pantelic M, Song T, Nadig J, Karabon P, Greenbaum A and O'Neill W. Application of 3-dimensional computed tomographic image guidance to WATCHMAN implantation and impact on early operator learning curve: Single-center experience. JACC Cardiovascular interventions. 2016; 9(22):2329-2340.

Wasade VS, Balki I, Bowyer SM, Gaddam S, Mohammadi-Nejad AR, Nazem-Zadeh MR, Soltanian-Zadeh H, Zillgitt A and Spanaki-Varelas M. Controllable yawning expressed as focal seizures of frontal lobe epilepsy. Epilepsy & behavior case reports. 2016; 6:61-63.

Wen N, Bagher-Ebadian H, Pantelic M, Hearshen D, Elshaikh MA, Chetty IJ and Movsas B. A physiologically nested pharmacokinetic model in dynamic contrast-enhanced magnetic resonance imaging for detection of dominant intraprostatic lesions in patients with prostate cancer. International journal of radiation oncology, biology, physics. 2016; 96(2s):E619.

Wen N, Lu S, Kim J, Qin Y, Huang Y, Zhao B, Liu C and Chetty IJ. Precise film dosimetry for stereotactic radiosurgery and stereotactic body radiotherapy quality assurance using Gafchromic EBT3 films. Radiation oncology (London, England). 2016; 11(1):132.

Yip J, Bruno DA, Burmeister C, Kazimi M, Yoshida A, Abouljoud MS and Schnickel GT. Deep vein thrombosis and pulmonary embolism in liver transplant patients: Risks and prevention. Transplantation direct. 2016; 2(4):e68.

Yoon HJ, Shanker A, Wang Y, Kozminsky M, Jin Q, Palanisamy N, Burness ML, Azizi E, Simeone DM, Wicha MS, Kim J and Nagrath S. Tunable thermal-sensitive polymer-graphene oxide composite for efficient capture and release of viable circulating tumor cells. Advanced materials (Deerfield Beach, Fla). 2016.

Zhang L, Varma NR, Gang ZZ, Ewing JR, Arbab AS, Ali MM. Targeting triple negative breast cancer with a small-sized paramagnetic nanoparticle. Journal of nanomedicine & nanotechnology. Oct 2016;7(5) PMID: 28018751.

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Learn more about cancer research at Henry Ford.