Dynamic contrast-enhanced breast MRI features correlate with invasive breast cancer angiogenesis

Xiao, Jennifer; Rahbar, Habib; Hippe, Daniel S.; Rendi, Mara H.; Parker, Elizabeth; Shekar, Neal; Hirano, Michael; Cheung, Kevin; Partridge, Savannah C.

doi:10.1038/s41523-021-00247-3

Cited by 44 publications

(30 citation statements)

References 58 publications

(25 reference statements)

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“…Breast cancer has many clinically approved mAb-based therapies, including trastuzumab, pertuzumab, margetuximab-cmkb, ado-trastuzumab emtansine, fam-trastuzumab deruxtecan-nxki, and sacituzumab govitecan. Serendipitously, DCE-MRI is often used in patients with breast cancer to evaluate tumor development and facilitate treatment planning [ 47 , 48 , 49 ]. Comparable to the method used by Lu et al, patients eligible for tumor resection through surgery that also undergo DCE-MRI can be administered mAb prior to surgery.…”

Section: Discussionmentioning

confidence: 99%

Dynamic Contrast-Enhanced Magnetic Resonance Imaging for the Prediction of Monoclonal Antibody Tumor Disposition

Bordeau

Polli

Schweser

et al. 2022

IJMS

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The prediction of monoclonal antibody (mAb) disposition within solid tumors for individual patients is difficult due to inter-patient variability in tumor physiology. Improved a priori prediction of mAb pharmacokinetics in tumors may facilitate the development of patient-specific dosing protocols and facilitate improved selection of patients for treatment with anti-cancer mAb. Here, we report the use of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), with tumor penetration of the contrast agent gadobutrol used as a surrogate, to improve physiologically based pharmacokinetic model (PBPK) predictions of cetuximab pharmacokinetics in epidermal growth factor receptor (EGFR) positive xenografts. In the initial investigations, mice bearing Panc-1, NCI-N87, and LS174T xenografts underwent DCE-MRI imaging with the contrast agent gadobutrol, followed by intravenous dosing of an 125Iodine-labeled, non-binding mAb (8C2). Tumor concentrations of 8C2 were determined following the euthanasia of mice (3 h–6 days after 8C2 dosing). Potential predictor relationships between DCE-MRI kinetic parameters and 8C2 PBPK parameters were evaluated through covariate modeling. The addition of the DCE-MRI parameter Ktrans alone or Ktrans in combination with the DCE-MRI parameter Vp on the PBPK parameters for tumor blood flow (QTU) and tumor vasculature permeability (σTUV) led to the most significant improvement in the characterization of 8C2 pharmacokinetics in individual tumors. To test the utility of the DCE-MRI covariates on a priori prediction of the disposition of mAb with high-affinity tumor binding, a second group of tumor-bearing mice underwent DCE-MRI imaging with gadobutrol, followed by the administration of 125Iodine-labeled cetuximab (a high-affinity anti-EGFR mAb). The MRI-PBPK covariate relationships, which were established with the untargeted antibody 8C2, were implemented into the PBPK model with considerations for EGFR expression and cetuximab-EGFR interaction to predict the disposition of cetuximab in individual tumors (a priori). The incorporation of the Ktrans MRI parameter as a covariate on the PBPK parameters QTU and σTUV decreased the PBPK model prediction error for cetuximab tumor pharmacokinetics from 223.71 to 65.02%. DCE-MRI may be a useful clinical tool in improving the prediction of antibody pharmacokinetics in solid tumors. Further studies are warranted to evaluate the utility of the DCE-MRI approach to additional mAbs and additional drug modalities.

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Section: Discussionmentioning

confidence: 99%

Dynamic Contrast-Enhanced Magnetic Resonance Imaging for the Prediction of Monoclonal Antibody Tumor Disposition

Bordeau

Polli

Schweser

et al. 2022

IJMS

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“…Radiomic features could also reflect the angiogenesis status and microvascular density in bladder urothelial carcinoma and in clear-cell renal-cell carcinoma [ 42 , 43 ]. Radiomic parameters also predict microvascular density and angiogenesis in breast cancer [ 44 , 45 , 46 ]. In the study by Dooman Arefan and collaborators, a set of radiomic features identified the heterogeneity of tumor microenvironment cells, with an abundance of fibroblasts and the presence of endothelial and immune cells [ 44 ].…”

Section: Liver Premetastatic Niche Formation In Crc Patientsmentioning

confidence: 99%

“…Reasonably, the different phases of metastatic niche formation (each one represented by a puzzle piece in the figure) could be detected by radiogenomics approaches in the near future. The references included in the figure show related manuscript with information about tumor cell extravasation [ 34 , 35 ], neoangiogenesis [ 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 ], immunosurveillance evasion [ 44 , 47 , 48 , 49 , 50 , 51 , 52 , 53 ] and tumor growth [ 41 ] that could be theoretically translated to metastatic niche detection. Created with BioRender.com.…”

Section: Figurementioning

confidence: 99%

Radiogenomics: Hunting Down Liver Metastasis in Colorectal Cancer Patients

Pinta

Castillo

Collado

et al. 2021

Cancers

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Radiomics is a developing new discipline that analyzes conventional medical images to extract quantifiable data that can be mined for new biomarkers that show the biology of pathological processes at microscopic levels. These data can be converted into image-based signatures to improve diagnostic, prognostic and predictive accuracy in cancer patients. The combination of radiomics and molecular data, called radiogenomics, has clear implications for cancer patients’ management. Though some studies have focused on radiogenomics signatures in hepatocellular carcinoma patients, only a few have examined colorectal cancer metastatic lesions in the liver. Moreover, the need to differentiate between liver lesions is fundamental for accurate diagnosis and treatment. In this review, we summarize the knowledge gained from radiomics and radiogenomics studies in hepatic metastatic colorectal cancer patients and their use in early diagnosis, response assessment and treatment decisions. We also investigate their value as possible prognostic biomarkers. In addition, the great potential of image mining to provide a comprehensive view of liver niche formation is examined thoroughly. Finally, new challenges and current limitations for the early detection of the liver premetastatic niche, based on radiomics and radiogenomics, are also discussed.

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“…DCE-MRI utilizes timed pre-and post-contrast imaging; consequently, the semi-quantitative dynamics of contrast uptake and intensity (initial peak enhancements, delayed phasewashout) are routinely used for radiologic evaluation of DCE-MRI (18). DCE-MRI has proven to be highly sensitive and has revolutionized early detection of breast cancers, particularly in women who are at increased risk for breast cancer (19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30)(31). Consequently, breast DCE-MRI has become standard of care and made it possible to obtain a high-resolution image of breast cancers and their associated vasculature.…”

Section: Breast Dce-mrimentioning

confidence: 99%

“…DCE-MRI is standard-of-care for high-risk cancer screening and surgical staging and is not readily replaced. Furthermore, DCE-MRI time-sequence imaging data provides an opportunity to perform kinetic and pharmacokinetic modeling; this modeling holds promise to better characterize tumors (28,30,39,40), monitor treatment effects (25,31,41), and plan radiation and surgical interventions (29,(42)(43)(44). Given the importance of DCE-MRI imaging, recent efforts have focused on detecting blood vessels in DCE-MRI images.…”

Section: Importance and Limitations Of Mri-based Vessel Detection In Breast Tissue And Cancermentioning

confidence: 99%

Vascularity and Dynamic Contrast-Enhanced Breast Magnetic Resonance Imaging

et al. 2021

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Angiogenesis is a key step in the initiation and progression of an invasive breast cancer. High microvessel density by morphological characterization predicts metastasis and poor survival in women with invasive breast cancers. However, morphologic characterization is subject to variability and only can evaluate a limited portion of an invasive breast cancer. Consequently, breast Magnetic Resonance Imaging (MRI) is currently being evaluated to assess vascularity. Recently, through the new field of radiomics, dynamic contrast enhanced (DCE)-MRI is being used to evaluate vascular density, vascular morphology, and detection of aggressive breast cancer biology. While DCE-MRI is a highly sensitive tool, there are specific features that limit computational evaluation of blood vessels. These include (1) DCE-MRI evaluates gadolinium contrast and does not directly evaluate biology, (2) the resolution of DCE-MRI is insufficient for imaging small blood vessels, and (3) DCE-MRI images are very difficult to co-register. Here we review computational approaches for detection and analysis of blood vessels in DCE-MRI images and present some of the strategies we have developed for co-registry of DCE-MRI images and early detection of vascularization.

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Dynamic contrast-enhanced breast MRI features correlate with invasive breast cancer angiogenesis

Cited by 44 publications

References 58 publications

Dynamic Contrast-Enhanced Magnetic Resonance Imaging for the Prediction of Monoclonal Antibody Tumor Disposition

Dynamic Contrast-Enhanced Magnetic Resonance Imaging for the Prediction of Monoclonal Antibody Tumor Disposition

Radiogenomics: Hunting Down Liver Metastasis in Colorectal Cancer Patients

Vascularity and Dynamic Contrast-Enhanced Breast Magnetic Resonance Imaging

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