Dataset Information

Spatial Characterization of Tumor Perfusion Properties from 3D DCE-US Perfusion Maps are Early Predictors of Cancer Treatment Response.

ABSTRACT: There is a need for noninvasive repeatable biomarkers to detect early cancer treatment response and spare non-responders unnecessary morbidities and costs. Here, we introduce three-dimensional (3D) dynamic contrast enhanced ultrasound (DCE-US) perfusion map characterization as inexpensive, bedside and longitudinal indicator of tumor perfusion for prediction of vascular changes and therapy response. More specifically, we developed computational tools to generate perfusion maps in 3D of tumor blood flow, and identified repeatable quantitative features to use in machine-learning models to capture subtle multi-parametric perfusion properties, including heterogeneity. Models were developed and trained in mice data and tested in a separate mouse cohort, as well as early validation clinical data consisting of patients receiving therapy for liver metastases. Models had excellent (ROC-AUC?>?0.9) prediction of response in pre-clinical data, as well as proof-of-concept clinical data. Significant correlations with histological assessments of tumor vasculature were noted (Spearman R?>?0.70) in pre-clinical data. Our approach can identify responders based on early perfusion changes, using perfusion properties correlated to gold-standard vascular properties.

SUBMITTER: El Kaffas A

PROVIDER: S-EPMC7181711 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Spatial Characterization of Tumor Perfusion Properties from 3D DCE-US Perfusion Maps are Early Predictors of Cancer Treatment Response.

El Kaffas Ahmed A Hoogi Assaf A Zhou Jianhua J Durot Isabelle I Wang Huaijun H Rosenberg Jarrett J Tseng Albert A Sagreiya Hersh H Akhbardeh Alireza A Rubin Daniel L DL Kamaya Aya A Hristov Dimitre D Willmann Jürgen K JK

Scientific reports 20200424 1

There is a need for noninvasive repeatable biomarkers to detect early cancer treatment response and spare non-responders unnecessary morbidities and costs. Here, we introduce three-dimensional (3D) dynamic contrast enhanced ultrasound (DCE-US) perfusion map characterization as inexpensive, bedside and longitudinal indicator of tumor perfusion for prediction of vascular changes and therapy response. More specifically, we developed computational tools to generate perfusion maps in 3D of tumor bloo ...[more]

PMID: 32332790

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Project description:PurposeNeoadjuvant radiotherapy (NeoRT) improves tumor local control and facilitates tumor resection in many cancers. Some clinical studies demonstrated that both timing of surgery and RT schedule influence tumor dissemination, and subsequently patient overall survival. Previously, we developed a pre-clinical model demonstrating the impact of NeoRT schedule and timing of surgery on metastatic spreading. We report on the impact of NeoRT on tumor microenvironment by MRI.MethodsAccording to our NeoRT model, MDA-MB 231 cells were implanted in the flank of SCID mice. Tumors were locally irradiated (PXI X-Rad SmART) with 2x5Gy and then surgically removed at different time points after RT. Diffusion-weighted (DW) and Dynamic contrast enhancement (DCE) MRI images were acquired before RT and every 2 days between RT and surgery. IntraVoxel Incoherent Motion (IVIM) analysis was used to obtain information on intravascular diffusion, related to perfusion (F: perfusion factor) and subsequently tumor vessels perfusion. For DCE-MRI, we performed semi-quantitative analyses.ResultsWith this experimental model, a significant and transient increase of the perfusion factor F [50% of the basal value (n=16, p<0.005)] was observed on day 6 after irradiation as well as a significant increase of the WashinSlope with DCE-MRI at day 6 (n=13, p<0.05). Using immunohistochemistry, a significant increase of perfused vessels was highlighted, corresponding to the increase of perfusion in MRI at this same time point. Moreover, Tumor surgical resection during this peak of vascularization results in an increase of metastasis burden (n=10, p<0.05).ConclusionSignificant differences in perfusion-related parameters (F and WashinSlope) were observed on day 6 in a neoadjuvant radiotherapy model using SCID mice. These modifications are correlated with an increase of perfused vessels in histological analysis and also with an increase of metastasis spreading after the surgical procedure. This experimental observation could potentially result in a way to personalize treatment, by modulating the time of surgery guided on MRI functional data, especially tumor perfusion.

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Project description:Rationale: Hepatocellular carcinoma (HCC) is a highly heterogeneous and malignant disease with the complex immune microenvironment, which ultimately influence clinic outcomes of patients. However, the spatial expression patterns of diverse immune cells among tumor microenvironment remain to be further deciphered. Methods: Spatial transcriptomics sequencing (ST) was implemented on two portions of HCC specimens. Differentially expressed genes, cell cycle phases, epithelial-mesenchymal features, pseudo-time and immune infiltration analysis were applied to demonstrate the intratumor heterogeneity and define the specific immune-related regions, and the results were further validated by a second analysis on another ST study. In vitro and in vivo experiments were conducted to confirm the functional mechanisms of key molecules such as CCL15, CCL19 and CCL21. Clinical tissue samples were used to assess their potential prognostic and therapeutic values. Results: Totally, 7553 spots were categorized into 15 subsets by hierarchical clustering, and malignant subsets with intratumor heterogeneity phenotypes were identified. Spatial heterogeneity from distinct sectors highlights specific chemokines: CCL15 is remarkable in the core region of the carcinoma sector and facilitates the immunosuppressive microenvironment by recruiting and polarizing M2-like macrophages in vitro and in vivo; High expression of CCL15 and CD163 respectively predicts poor prognosis of HCC patients, and the combined application of them has better predictive value. CCL19 and CCL21, sharing similar spatial expression patterns, are highly-correlated and prominent in the immune infiltration enrichment and recruit CD3+ T cells and CD20+ B cells to inhibit the growth of HCC, indicating a good prognosis of HCC patients. Conclusions: Taken together, our studies preliminarily reveal intratumor heterogeneity of HCC based on ST techniques and unravel the previously unexplored spatial expression patterns in the immune microenvironment. We also highlight the clinical significance and spatial discrepancy of key molecules, providing novel insight for further developing therapeutic strategies in HCC.

Project description:PurposeTo develop a disposable point-of-care portable perfusion phantom (DP4) and validate its clinical utility in a multi-institutional setting for quantitative dynamic contrast-enhanced magnetic resonance imaging (qDCE-MRI).MethodsThe DP4 phantom was designed for single-use and imaged concurrently with a human subject so that the phantom data can be utilized as the reference to detect errors in qDCE-MRI measurement of human tissues. The change of contrast-agent concentration in the phantom was measured using liquid chromatography-mass spectrometry. The repeatability of the contrast enhancement curve (CEC) was assessed with five phantoms in a single MRI scanner. Five healthy human subjects were recruited to evaluate the reproducibility of qDCE-MRI measurements. Each subject was imaged concurrently with the DP4 phantom at two institutes using three 3T MRI scanners from three different vendors. Pharmacokinetic (PK) parameters in the regions of liver, spleen, pancreas, and paravertebral muscle were calculated based on the Tofts model (TM), extended Tofts model (ETM), and shutter speed model (SSM). The reproducibility of each PK parameter over three measurements was evaluated with the intraclass correlation coefficient (ICC) and compared before and after DP4-based error correction.ResultsThe contrast-agent concentration in the DP4 phantom was linearly increased over 10 min (0.17 mM/min, measurement accuracy: 96%) after injecting gadoteridol (100 mM) at a constant rate (0.24 ml/s, 4 ml). The repeatability of the CEC within the phantom was 0.997 when assessed by the ICC. The reproducibility of the volume transfer constant, Ktrans , was the highest of the PK parameters regardless of the PK models. The ICCs of Ktrans in the TM, ETM, and SSM before DP4-based error correction were 0.34, 0.39, and 0.72, respectively, while those increased to 0.93, 0.98, and 0.86, respectively, after correction.ConclusionsThe DP4 phantom is reliable, portable, and capable of significantly improving the reproducibility of qDCE-MRI measurements.

Dataset Information

Spatial Characterization of Tumor Perfusion Properties from 3D DCE-US Perfusion Maps are Early Predictors of Cancer Treatment Response.

Publications

Spatial Characterization of Tumor Perfusion Properties from 3D DCE-US Perfusion Maps are Early Predictors of Cancer Treatment Response.

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