My research investigates minimally invasive screening methods for early detection of cancer. As a postdoctoral researcher, I design experiments and develop mathematical models to relate the cancer blood-based biomarkers to tumor growth states. My research also touches on targeted cancer therapy using microRNA for cancer. Prior to my affiliation with Stanford, I was a graduate student at the Illinois Institute of Technology (IIT) and my research contributions mainly focused on the biodistribution of cancer drugs, drug-target biomolecules, and targeted imaging agents in living subjects. I am interested in quantitative molecular imaging and kinetic modeling of imaging agents.

Honors & Awards

  • Student Travel Stipend, World Molecular Imaging Congress (2017)
  • Industry Selected Poster Award, World Molecular Imaging Congress (2018)

Professional Education

  • Doctor of Philosophy, Illinois Institute Of Technology (2018)
  • Bachelor of Science, Sharif University of Technology (2013)

Stanford Advisors

All Publications

  • Prediction of optimal contrast times post-imaging agent administration to inform personalized fluorescence-guided surgery. Journal of biomedical optics Sadeghipour, N., Rangnekar, A., Folaron, M., Strawbridge, R., Samkoe, K., Davis, S., Tichauer, K. 2020; 25 (11)


    SIGNIFICANCE: Fluorescence guidance in cancer surgery (FGS) using molecular-targeted contrast agents is accelerating, yet the influence of individual patients' physiology on the optimal time to perform surgery post-agent-injection is not fully understood.AIM: Develop a mathematical framework and analytical expressions to estimate patient-specific time-to-maximum contrast after imaging agent administration for single- and paired-agent (coadministration of targeted and control agents) protocols.APPROACH: The framework was validated in mouse subcutaneous xenograft studies for three classes of imaging agents: peptide, antibody mimetic, and antibody. Analytical expressions estimating time-to-maximum-tumor-discrimination potential were evaluated over a range of parameters using the validated framework for human cancer parameters.RESULTS: Correlations were observed between simulations and matched experiments and metrics of tumor discrimination potential (p<0.05). Based on human cancer physiology, times-to-maximum contrast for peptide and antibody mimetic agents were <200min, >15h for antibodies, on average. The analytical estimates of time-to-maximum tumor discrimination performance exhibited errors of <10% on average, whereas patient-to-patient variance is expected to be greater than 100%.CONCLUSION: We demonstrated that analytical estimates of time-to-maximum contrast in FGS carried out patient-to-patient can outperform the population average time-to-maximum contrast used currently in clinical trials. Such estimates can be made with preoperative DCE-MRI (or similar) and knowledge of the targeted agent's binding affinity.

    View details for DOI 10.1117/1.JBO.25.11.116005

    View details for PubMedID 33200596

  • Highly sensitive eight-channel light sensing system for biomedical applications. Photochemical & photobiological sciences : Official journal of the European Photochemistry Association and the European Society for Photobiology Kim, S. B., Hori, S. S., Sadeghipour, N., Sukumar, U. K., Fujii, R., Massoud, T. F., Paulmurugan, R. 2020


    We demonstrate the potential of an eight-channel light sensing platform system, named Black Box I (BBI), for rapid and highly sensitive measurement of low-level light using a nonradioactive optical readout. We developed, normalized, and characterized the photon sensitivities of the eight channels of the BBI using placental alkaline phosphatase (PLAP) as a model imaging reporter. We found that the BBI system had a statistically strong linear correlation with the reference IVIS Lumina II system. When we applied normalization constants, we were able to optimize the photomultiplier tubes (PMT) of all eight channels of the BBI (up to r2 = 0.998). We investigated the biomedical utilities of BBI by: (i) determining alkaline phosphatase activities in mouse plasma samples as a diagnostic secretory biomarker of cancer, and (ii) diagnosing cancer metastases in the organs of mice bearing triple negative breast cancer. We provide an important new addition to low-cost biomedical instruments intended for pre-clinical diagnostic imaging with high sensitivity, high sample throughput, portability, and rapid on-site analysis of low-level light.

    View details for DOI 10.1039/d0pp00017e

    View details for PubMedID 32159572

  • A paired-agent fluorescent molecular imaging strategy for quantifying antibody drug target engagement in in vivo window chamber xenograft models Nalbant, E., Rounds, C., Sadeghipour, N., Meng, B., Folaron, M. R., Haldar, C., Strawbridge, R. R., Samkoe, K. S., Davis, S. C., Tichauer, K. M., Chan, K. F., Evans, C. L. SPIE-INT SOC OPTICAL ENGINEERING. 2020

    View details for DOI 10.1117/12.2545182

    View details for Web of Science ID 000547324400007

  • Noninvasive quantification of target availability during therapy using paired-agent fluorescence tomography THERANOSTICS Meng, B., Folaron, M. R., Strawbridge, R. R., Sadeghipour, N., Samkoe, K. S., Tichauer, K., Davis, S. C. 2020; 10 (24): 11230–43


    Immuno-oncological treatment strategies that target abnormal receptor profiles of tumors are an increasingly important feature of cancer therapy. Yet, assessing receptor availability (RA) and drug-target engagement, important determinants of therapeutic efficacy, is challenging with current imaging strategies, largely due to the complex nonspecific uptake behavior of imaging agents in tumors. Herein, we evaluate whether a quantitative noninvasive imaging approach designed to compensate for nonspecific uptake, MRI-coupled paired-agent fluorescence tomography (MRI-PAFT), is capable of rapidly assessing the availability of epidermal growth factor receptor (EGFR) in response to one dose of anti-EGFR antibody therapy in orthotopic brain tumor models. Methods: Mice bearing orthotopic brain tumor xenografts with relatively high EGFR expression (U251) (N=10) or undetectable human EGFR (9L) (N=9) were considered in this study. For each tumor type, mice were either treated with one dose of cetuximab, or remained untreated. All animals were scanned using MRI-PAFT, which commenced immediately after paired-agent administration, and values of RA were recovered using a model-based approach, which uses the entire dynamic sequence of agent uptake, as well as a simplified "snapshot" approach which requires uptake measurements at only two time points. Recovered values of RA were evaluated between groups and techniques. Hematoxylin & eosin (H&E) and immunohistochemical (IHC) staining was performed on tumor specimens from every animal to confirm tumor presence and EGFR status. Results: In animals bearing EGFR(+) tumors, a significant difference in RA values between treated and untreated animals was observed (RA = 0.24 ± 0.15 and 0.61 ± 0.18, respectively, p=0.027), with an area under the curve - receiver operating characteristic (AUC-ROC) value of 0.92. We did not observe a statistically significant difference in RA values between treated and untreated animals bearing EGFR(-) tumors (RA = 0.18 ± 0.19 and 0.27 ± 0.21, respectively; p = 0.89; AUC-ROC = 0.55), nor did we observe a difference between treated EGFR(+) tumors compared to treated and untreated EGFR(-) tumors. Notably, the snapshot paired-agent strategy quantified drug-receptor engagement within just 30 minutes of agent administration. Examination of the targeted agent alone showed no capacity to distinguish tumors either by treatment or receptor status, even 24h after agent administration. Conclusions: This study demonstrated that a noninvasive imaging strategy enables rapid quantification of receptor availability in response to therapy, a capability that could be leveraged in preclinical drug development, patient stratification, and treatment monitoring.

    View details for DOI 10.7150/thno.45273

    View details for Web of Science ID 000573666500011

    View details for PubMedID 33042280

    View details for PubMedCentralID PMC7532673

  • Design, Synthesis, and Biological Evaluation of Polyaminocarboxylate Ligand-Based Theranostic Conjugates for Antibody-Targeted Cancer Therapy and Near-Infrared Optical Imaging. ChemMedChem Ren, S., Sun, X., Wang, H., Nguyen, T. H., Sadeghipour, N., Xu, X., Kang, C. S., Liu, Y., Xu, H., Wu, N., Chen, Y., Tichauer, K., Minh, D. D., Chong, H. S. 2018; 13 (24): 2606-2617


    We report the design, synthesis, and evaluation of polyaminocarboxylate ligand-based antibody conjugates for potential application in targeted cancer therapy and near-infrared (NIR) fluorescence imaging. We synthesized a new polyaminocarboxylate chelate (CAB-NE3TA) as a potential anticancer agent. CAB-NE3TA displayed potent inhibitory activities against various cancer cell lines. We then designed a multifunctional theranostic platform (CAB-NE3TA-PAN-IR800) constructed on an epidermal growth factor receptor (EGFR)-targeted antibody (panitumumab, PAN) labeled with a NIR fluorescent dye. We also built the first atomistic model of the EGFR-PAN complex and loaded it with the cytotoxic CAB-NE3TA and the NIR dye. The therapeutic (CAB-NE3TA-PAN) and theranostic (CAB-NE3TA-PAN-IR800) conjugates were evaluated using an EGFR-positive A431 (human skin cancer) cell xenograft mouse model. Biodistribution studies using NIR fluorescence imaging demonstrated that the CAB-NE3TA-PAN labeled with the IR800 dye selectively targeted the A431 tumors in mice and resulted in prolonged retention in the tumor tissue and displayed excellent clearance in blood and normal organs. The therapeutic conjugate was capable of significantly inhibiting tumor growth, leading to nearly complete disappearance of tumors in the mice. The results of our pilot in vivo studies support further evaluation of the novel ligand-based therapeutic and theranostic conjugates for targeted iron chelation cancer therapy and imaging applications.

    View details for DOI 10.1002/cmdc.201800598

    View details for PubMedID 30403833

    View details for PubMedCentralID PMC6324731

  • Correcting for targeted and control agent signal differences in paired-agent molecular imaging of cancer cell-surface receptors. Journal of biomedical optics Sadeghipour, N., Davis, S. C., Tichauer, K. M. 2018; 23 (6): 1-11


    Paired-agent kinetic modeling protocols provide one means of estimating cancer cell-surface receptors with in vivo molecular imaging. The protocols employ the coadministration of a control imaging agent with one or more targeted imaging agent to account for the nonspecific uptake and retention of the targeted agent. These methods require the targeted and control agent data be converted to equivalent units of concentration, typically requiring specialized equipment and calibration, and/or complex algorithms that raise the barrier to adoption. This work evaluates a kinetic model capable of correcting for targeted and control agent signal differences. This approach was compared with an existing simplified paired-agent model (SPAM), and modified SPAM that accounts for signal differences by early time point normalization of targeted and control signals (SPAMPN). The scaling factor model (SPAMSF) outperformed both SPAM and SPAMPN in terms of accuracy and precision when the scale differences between targeted and imaging agent signals (α) were not equal to 1, and it matched the performance of SPAM for α  =  1. This model could have wide-reaching implications for quantitative cancer receptor imaging using any imaging modalities, or combinations of imaging modalities, capable of concurrent detection of at least two distinct imaging agents (e.g., SPECT, optical, and PET/MR).

    View details for DOI 10.1117/1.JBO.23.6.066004

    View details for PubMedID 29931837

    View details for PubMedCentralID PMC6013418

  • Quantifying cancer cell receptors with paired-agent fluorescent imaging: a novel method to account for tissue optical property effects. Proceedings of SPIE--the International Society for Optical Engineering Sadeghipour, N., Davis, S. C., Tichauer, K. M. 2018; 10497


    Dynamic fluorescence imaging approaches can be used to estimate the concentration of cell surface receptors in vivo. Kinetic models are used to generate the final estimation by taking the targeted imaging agent concentration as a function of time. However, tissue absorption and scattering properties cause the final readout signal to be on a different scale than the real fluorescent agent concentration. In paired-agent imaging approaches, simultaneous injection of a suitable control imaging agent with a targeted one can account for non-specific uptake and retention of the targeted agent. Additionally, the signal from the control agent can be a normalizing factor to correct for tissue optical property differences. In this study, the kinetic model used for paired-agent imaging analysis (i.e., simplified reference tissue model) is modified and tested in simulation and experimental data in a way that accounts for the scaling correction within the kinetic model fit to the data to ultimately extract an estimate of the targeted biomarker concentration.

    View details for DOI 10.1117/12.2290631

    View details for PubMedID 30220772

    View details for PubMedCentralID PMC6136426

  • Generalized paired-agent kinetic model for in vivo quantification of cancer cell-surface receptors under receptor saturation conditions. Physics in medicine and biology Sadeghipour, N., Davis, S. C., Tichauer, K. M. 2017; 62 (2): 394-414


    New precision medicine drugs oftentimes act through binding to specific cell-surface cancer receptors, and thus their efficacy is highly dependent on the availability of those receptors and the receptor concentration per cell. Paired-agent molecular imaging can provide quantitative information on receptor status in vivo, especially in tumor tissue; however, to date, published approaches to paired-agent quantitative imaging require that only 'trace' levels of imaging agent exist compared to receptor concentration. This strict requirement may limit applicability, particularly in drug binding studies, which seek to report on a biological effect in response to saturating receptors with a drug moiety. To extend the regime over which paired-agent imaging may be used, this work presents a generalized simplified reference tissue model (GSRTM) for paired-agent imaging developed to approximate receptor concentration in both non-receptor-saturated and receptor-saturated conditions. Extensive simulation studies show that tumor receptor concentration estimates recovered using the GSRTM are more accurate in receptor-saturation conditions than the standard simple reference tissue model (SRTM) (% error (mean  ±  sd): GSRTM 0  ±  1 and SRTM 50  ±  1) and match the SRTM accuracy in non-saturated conditions (% error (mean  ±  sd): GSRTM 5  ±  5 and SRTM 0  ±  5). To further test the approach, GSRTM-estimated receptor concentration was compared to SRTM-estimated values extracted from tumor xenograft in vivo mouse model data. The GSRTM estimates were observed to deviate from the SRTM in tumors with low receptor saturation (which are likely in a saturated regime). Finally, a general 'rule-of-thumb' algorithm is presented to estimate the expected level of receptor saturation that would be achieved in a given tissue provided dose and pharmacokinetic information about the drug or imaging agent being used, and physiological information about the tissue. These studies suggest that the GSRTM is necessary when receptor saturation exceeds 20% and highlight the potential for GSRTM to accurately measure receptor concentrations under saturation conditions, such as might be required during high dose drug studies, or for imaging applications where high concentrations of imaging agent are required to optimize signal-to-noise conditions. This model can also be applied to PET and SPECT imaging studies that tend to suffer from noisier data, but require one less parameter to fit if images are converted to imaging agent concentration (quantitative PET/SPECT).

    View details for DOI 10.1088/1361-6560/62/2/394

    View details for PubMedID 27997381

    View details for PubMedCentralID PMC5226886