Heterogeneous Distribution of Tumor Blood Supply Affects the Response to Chemotherapy in Patients with Head and Neck Cancer

Galmarini, Felipe C.; Galmarini, Carlos M.; Sarchi, María Inés; Abulafia, J; Galmarini, Darío

doi:10.1038/sj.mn.7300126

Cited by 25 publications

(28 citation statements)

References 17 publications

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“…13, 16 Similarly, the effectiveness of chemotherapy delivery to the tumor critically depends on adequate tumor perfusion. 9, 10 DCE-MRI, characterizes microvascular structure and function, 32, 33 indirectly assesses perfusion and oxygenation status, 20, 34, 35 correlates with microvessel density 20 and with direct oxygen measurements 22 in cervical cancer.…”

Section: Discussionmentioning

confidence: 99%

“…Reliable clinically practical and non-invasive methods to effectively evaluate the heterogeneous therapy response in solid tumors have been elusive in clinical practice. Perfusion, reflecting the effectiveness of delivery of chemotherapy, 9, 10 and oxygenation for radiation therapy (RT), 11, 12 can be highly variable within each solid tumor. Essential information on this heterogeneity of perfusion 13 during treatment, has not been incorporated into the treatment strategy despite its known profound impact on therapy outcome in cervical cancer.…”

Section: Introductionmentioning

confidence: 99%

“…Essential information on this heterogeneity of perfusion 13 during treatment, has not been incorporated into the treatment strategy despite its known profound impact on therapy outcome in cervical cancer. 9, 10, 13-18 Furthermore, accuracy of tumor volume measurement, as a early response indicator during treatment, has also been limited because of the irregular tumor shapes and subtlety of early volume regression 19 .…”

Section: Introductionmentioning

confidence: 99%

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Ultra‐early predictive assay for treatment failure using functional magnetic resonance imaging and clinical prognostic parameters in cervical cancer

Mayr

Yuh

Jajoura

et al. 2010

Cancer

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BACKGROUND We prospectively evaluated MRI-parameters quantifying heterogeneous perfusion pattern and residual tumor volume early during treatment in cervical cancer, and compared their predictive power for primary tumor recurrence and cancer death with the standard clinical prognostic factors (CPFs). A novel approach of augmenting the predictive power of CPFs with MRI-parameters was assessed. MATERIALS AND METHODS Sixty-two cervical cancer patients underwent dynamic contrast-enhanced (DCE) MRI before and during early radiation/chemotherapy (2-2.5 weeks into treatment). Heterogeneous tumor perfusion was analyzed by signal intensity (SI) of each tumor voxel. Poorly-perfused tumor regions were quantitated as lower 10th percentile of SI (SI(10%)). DCE-MRI and three-dimensional (3D) tumor volumetry MRI-parameters were assessed as predictors of recurrence and cancer death (median follow-up, 4.1 years). Their discriminating capacity was compared with CPFs (stage, lymphnode status, histology) using sensitivity/specificity and Cox regression analysis. RESULTS SI(10%) and 3D-volume 2-2.5 weeks into therapy independently predicted recurrence (HR=2.6 [1.0-6.5], P=.04; HR=1.9 [1.1-3.5], P=.03, respectively) and death (HR=1.9 [1.0--3.5], P=.03; HR=1.9 [1.2-2.9], P=.01), and were superior to CPFs. The addition of MRI-parameters to CPFs increased sensitivity and specificity of CPFs from 71% and 51% to 100% and 71% for predicting recurrence; and from 79% and 54% to 93% and 60% for predicting death. CONCLUSIONS MRI-parameters reflecting heterogeneous tumor perfusion and subtle tumor volume change early during radiation/chemotherapy are independent and better predictors of tumor recurrence and death than CPFs. Combination of CPFs and MRI-parameters further improves early prediction of treatment failure and may enable a window of opportunity to alter treatment strategy.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Ultra‐early predictive assay for treatment failure using functional magnetic resonance imaging and clinical prognostic parameters in cervical cancer

Mayr

Yuh

Jajoura

et al. 2010

Cancer

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“…DCE MRI indirectly reflects tumor perfusion status and the effectiveness in the delivery of chemotherapeutic drugs (9–11) and oxygen (hypoxia) (12) to the tumor cells. Therefore the DCE-based perfusion biomarkers may provide important information related to the early responsiveness or resistance to an ongoing treatment, which critically influence the ultimate treatment outcomes: local recurrence (LR) vs. control (LC) and death of disease (DOD) vs. disease-specific- survival (DSS) (13–16).…”

Section: Introductionmentioning

confidence: 99%

Validation of optimal DCE-MRI perfusion threshold to classify at-risk tumor imaging voxels in heterogeneous cervical cancer for outcome prediction

Huang¹,

Yuh²,

Grecula³

et al. 2014

Magnetic Resonance Imaging

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Purpose To classify tumor imaging voxels at-risk for treatment failure within the heterogeneous cervical cancer using DCE MRI and determine optimal voxel’s DCE threshold values at different treatment time points for early prediction of treatment failure. Material and Method DCE-MRI from 102 patients with Stage IB2–IVB cervical cancer was obtained at 3 different treatment time points: before (MRI 1) and during treatment (MRI 2 at 2–2.5 weeks and MRI 3 at 4–5 weeks). For each tumor voxel, the plateau signal intensity (SI) was derived from its time-SI curve from the DCE MRI. The optimal SI thresholds to classify the at-risk tumor voxels was determined by the maximal area under the curve using ROC analysis when varies SI value from 1.0 to 3.0 and correlates with treatment outcome. Results The optimal SI thresholds for MRI 1, 2 and 3 were 2.2, 2.2 and 2.1 for significant differentiation between local recurrence/control, respectively, and 1.8, 2.1 and 2.2 for death/survival, respectively. Conclusion Optimal SI thresholds are clinically validated to quantify at-risk tumor voxels which vary with time. A single universal threshold (SI = 1.9) was identified for all 3 treatment time points and remain significant for the early prediction of treatment failure.

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“…Although the concept of tumor heterogeneity has not been incorporated into the current clinical oncology practice nor the evidence-based cancer treatment paradigm, there is ample evidence that heterogeneous functional/biological properties of tumors profoundly influence treatment outcome (3, 12, 16, 17). With the notion of variable therapy responsiveness at different subregions within the same tumor (3, 16, 17), treatment failure is more critically influenced by at-risk subregions of the tumor, which possess unfavorable functional/biological properties, including poor perfusion and hypoxia (18–20). However, tumor heterogeneity is challenging to characterize and quantify in the clinical setting.…”

Section: Introductionmentioning

confidence: 99%

Characterizing Tumor Heterogeneity With Functional Imaging and Quantifying High-Risk Tumor Volume for Early Prediction of Treatment Outcome: Cervical Cancer as a Model

Mayr¹,

Huang²,

Wang³

et al. 2012

International Journal of Radiation Oncology*Biology*Physics

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Purpose Treatment response in cancer has been monitored by measuring anatomic tumor volume (ATV) at various times without considering the inherent functional tumor heterogeneity known to critically influence ultimate treatment outcome: primary tumor control and survival. This study applied dynamic contrast-enhanced (DCE) functional MRI to characterize tumors’ heterogeneous subregions with low DCE values, at risk for treatment failure, and to quantify the functional risk volume (FRV) for personalized early prediction of treatment outcome. Methods and Materials DCE-MRI was performed in 102 stage IB2–IVA cervical cancer patients to assess tumor perfusion heterogeneity before and during radiation/chemotherapy. FRV represents the total volume of tumor voxels with critically low DCE signal intensity (<2.1 compared with precontrast image, determined by previous receiver operator characteristic analysis). FRVs were correlated with treatment outcome (follow-up: 0.2–9.4, mean 6.8 years) and compared with ATVs (Mann-Whitney, Kaplan-Meier, and multivariate analyses). Results Before and during therapy at 2–2.5 and 4–5 weeks of RT, FRVs >20, >13, and >5 cm3, respectively, significantly predicted unfavorable 6-year primary tumor control (p = 0.003, 7.3 × 10−8, 2.0 × 10−8) and disease-specific survival (p = 1.9 × 10−4, 2.1 × 10−6, 2.5 × 10−7, respectively). The FRVs were superior to the ATVs as early predictors of outcome, and the differentiating power of FRVs increased during treatment. Discussion Our preliminary results suggest that functional tumor heterogeneity can be characterized by DCE-MRI to quantify FRV for predicting ultimate long-term treatment outcome. FRV is a novel functional imaging heterogeneity parameter, superior to ATV, and can be clinically translated for personalized early outcome prediction before or as early as 2–5 weeks into treatment.

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Heterogeneous Distribution of Tumor Blood Supply Affects the Response to Chemotherapy in Patients with Head and Neck Cancer

Cited by 25 publications

References 17 publications

Ultra‐early predictive assay for treatment failure using functional magnetic resonance imaging and clinical prognostic parameters in cervical cancer

Ultra‐early predictive assay for treatment failure using functional magnetic resonance imaging and clinical prognostic parameters in cervical cancer

Validation of optimal DCE-MRI perfusion threshold to classify at-risk tumor imaging voxels in heterogeneous cervical cancer for outcome prediction

Characterizing Tumor Heterogeneity With Functional Imaging and Quantifying High-Risk Tumor Volume for Early Prediction of Treatment Outcome: Cervical Cancer as a Model

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