Multiparametric Analysis of Longitudinal Quantitative MRI Data to Identify Distinct Tumor Habitats in Preclinical Models of Breast Cancer
This study identifies physiological tumor habitats from quantitative magnetic resonance imaging (MRI) data and evaluates their alterations in response to therapy. Two models of breast cancer (BT-474 and MDA-MB-231) were imaged longitudinally with diffusion-weighted MRI and dynamic contrast-enhanced...
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MDPI AG
2020-06-01
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| Series: | Cancers |
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| Online Access: | https://www.mdpi.com/2072-6694/12/6/1682 |
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| author | Anum K. Syed Jennifer G. Whisenant Stephanie L. Barnes Anna G. Sorace Thomas E. Yankeelov |
| author_facet | Anum K. Syed Jennifer G. Whisenant Stephanie L. Barnes Anna G. Sorace Thomas E. Yankeelov |
| author_sort | Anum K. Syed |
| collection | DOAJ |
| description | This study identifies physiological tumor habitats from quantitative magnetic resonance imaging (MRI) data and evaluates their alterations in response to therapy. Two models of breast cancer (BT-474 and MDA-MB-231) were imaged longitudinally with diffusion-weighted MRI and dynamic contrast-enhanced MRI to quantify tumor cellularity and vascularity, respectively, during treatment with trastuzumab or albumin-bound paclitaxel. Tumors were stained for anti-CD31, anti-Ki-67, and H&E. Imaging and histology data were clustered to identify tumor habitats and percent tumor volume (MRI) or area (histology) of each habitat was quantified. Histological habitats were correlated with MRI habitats. Clustering of both the MRI and histology data yielded three clusters: high-vascularity high-cellularity (HV-HC), low-vascularity high-cellularity (LV-HC), and low-vascularity low-cellularity (LV-LC). At day 4, BT-474 tumors treated with trastuzumab showed a decrease in LV-HC (<i>p</i> = 0.03) and increase in HV-HC (<i>p</i> = 0.03) percent tumor volume compared to control. MDA-MB-231 tumors treated with low-dose albumin-bound paclitaxel showed a longitudinal decrease in LV-HC percent tumor volume at day 3 (<i>p</i> = 0.01). Positive correlations were found between histological and imaging-derived habitats: HV-HC (BT-474: <i>p</i> = 0.03), LV-HC (MDA-MB-231: <i>p</i> = 0.04), LV-LC (BT-474: <i>p</i> = 0.04; MDA-MB-231: <i>p</i> < 0.01). Physiologically distinct tumor habitats associated with therapeutic response were identified with MRI and histology data in preclinical models of breast cancer. |
| first_indexed | 2024-03-10T18:54:51Z |
| format | Article |
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| institution | Directory Open Access Journal |
| issn | 2072-6694 |
| language | English |
| last_indexed | 2024-03-10T18:54:51Z |
| publishDate | 2020-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Cancers |
| spelling | doaj.art-fd3c3fa8b7ff438cbb77c22e9b4bf0892023-11-20T04:52:44ZengMDPI AGCancers2072-66942020-06-01126168210.3390/cancers12061682Multiparametric Analysis of Longitudinal Quantitative MRI Data to Identify Distinct Tumor Habitats in Preclinical Models of Breast CancerAnum K. Syed0Jennifer G. Whisenant1Stephanie L. Barnes2Anna G. Sorace3Thomas E. Yankeelov4Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX 78712, USADepartment of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USAOden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX 78712, USADepartment of Biomedical Engineering, The University of Alabama at Birmingham, Birmingham, AL 35294, USADepartment of Biomedical Engineering, The University of Texas at Austin, Austin, TX 78712, USAThis study identifies physiological tumor habitats from quantitative magnetic resonance imaging (MRI) data and evaluates their alterations in response to therapy. Two models of breast cancer (BT-474 and MDA-MB-231) were imaged longitudinally with diffusion-weighted MRI and dynamic contrast-enhanced MRI to quantify tumor cellularity and vascularity, respectively, during treatment with trastuzumab or albumin-bound paclitaxel. Tumors were stained for anti-CD31, anti-Ki-67, and H&E. Imaging and histology data were clustered to identify tumor habitats and percent tumor volume (MRI) or area (histology) of each habitat was quantified. Histological habitats were correlated with MRI habitats. Clustering of both the MRI and histology data yielded three clusters: high-vascularity high-cellularity (HV-HC), low-vascularity high-cellularity (LV-HC), and low-vascularity low-cellularity (LV-LC). At day 4, BT-474 tumors treated with trastuzumab showed a decrease in LV-HC (<i>p</i> = 0.03) and increase in HV-HC (<i>p</i> = 0.03) percent tumor volume compared to control. MDA-MB-231 tumors treated with low-dose albumin-bound paclitaxel showed a longitudinal decrease in LV-HC percent tumor volume at day 3 (<i>p</i> = 0.01). Positive correlations were found between histological and imaging-derived habitats: HV-HC (BT-474: <i>p</i> = 0.03), LV-HC (MDA-MB-231: <i>p</i> = 0.04), LV-LC (BT-474: <i>p</i> = 0.04; MDA-MB-231: <i>p</i> < 0.01). Physiologically distinct tumor habitats associated with therapeutic response were identified with MRI and histology data in preclinical models of breast cancer.https://www.mdpi.com/2072-6694/12/6/1682diffusion-weighted MRIdynamic contrast-enhanced MRIimmunohistochemistryhabitat imagingintratumoral heterogeneity |
| spellingShingle | Anum K. Syed Jennifer G. Whisenant Stephanie L. Barnes Anna G. Sorace Thomas E. Yankeelov Multiparametric Analysis of Longitudinal Quantitative MRI Data to Identify Distinct Tumor Habitats in Preclinical Models of Breast Cancer Cancers diffusion-weighted MRI dynamic contrast-enhanced MRI immunohistochemistry habitat imaging intratumoral heterogeneity |
| title | Multiparametric Analysis of Longitudinal Quantitative MRI Data to Identify Distinct Tumor Habitats in Preclinical Models of Breast Cancer |
| title_full | Multiparametric Analysis of Longitudinal Quantitative MRI Data to Identify Distinct Tumor Habitats in Preclinical Models of Breast Cancer |
| title_fullStr | Multiparametric Analysis of Longitudinal Quantitative MRI Data to Identify Distinct Tumor Habitats in Preclinical Models of Breast Cancer |
| title_full_unstemmed | Multiparametric Analysis of Longitudinal Quantitative MRI Data to Identify Distinct Tumor Habitats in Preclinical Models of Breast Cancer |
| title_short | Multiparametric Analysis of Longitudinal Quantitative MRI Data to Identify Distinct Tumor Habitats in Preclinical Models of Breast Cancer |
| title_sort | multiparametric analysis of longitudinal quantitative mri data to identify distinct tumor habitats in preclinical models of breast cancer |
| topic | diffusion-weighted MRI dynamic contrast-enhanced MRI immunohistochemistry habitat imaging intratumoral heterogeneity |
| url | https://www.mdpi.com/2072-6694/12/6/1682 |
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