Perfusion parameters as potential imaging biomarkers for the early prediction of radiotherapy response in a rat tumor model

The Role of Dynamic Contrast-Enhanced Magnetic Resonance Imaging in Predicting Treatment Response for Cervical Cancer Treated with Concurrent Chemoradiotherapy

Purpose

To evaluate the role of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in predicting early treatment response.

Materials and Methods

Patients with locally advanced cervical cancer (LACC) treated with concurrent chemoradiotherapy (CCRT) were enrolled. Pelvic DCE-MRI scans were performed before RT (pre-RT), in the middle of RT (mid-RT), and at the end of RT (post-RT), separately. Parameters (ie, K^trans, K_ep, and V_e) were measured. Pre-, mid-, and post-RT K^trans were denoted as K^trans-preTx, K^trans-midTx, and K^trans-postTx, respectively. And the same denoting rule also went for K_ep and V_e. Difference for the same parameter such as K^trans measured between two consecutive time points was calculated as second K^trans value minus first K^trans value. The differences in K^trans between pre-RT and post-RT, between pre-RT and mid-RT, and between mid-RT and post-RT were denoted as ΔK^trans-post-preTx, ΔK^trans-mid-preTx, and ΔK^trans-post-midTx, respectively, and the same denoting rule was also applied to K_ep and V_e.

Results

A total of 57 patients were enrolled. After the treatment, 31 patients had complete response (CR group). The remaining 26 patients had partial response (NCR group). Significant differences were found in K^trans-postTx, K_ep-postTx, V_e-midTx, ΔK^trans-post-preTx, ΔK^trans-post-midTx, ΔK_ep-post-preTx, ΔK_ep-mid-preTx and ΔK_ep-post-midTx between the two groups. Receiver operating characteristic (ROC) analysis for their performances in predicting treatment response showed an area under curve (AUC) of 0.656-0.849, sensitivity of 61.3-93.5%, specificity of 46.1-73.1%, and maximal Youden Index of 36.5-66.6. Among those parameters, K_ep-postTx was the best, and its AUC, sensitivity, specificity, maximal Youden Index, and cutoff value were 0.849, 87.1%, 73.1%, 60.2, and 0.341, respectively. These combined parameters showed an AUC of 0.952, with sensitivity of 87.1%, specificity of 96.1%, and maximal Youden Index of 83.2.

Conclusion

DCE-MRI parameters can predict early treatment outcome. Among those parameters, K_ep-postTx is the best predictor. The combination of multi-parameters can increase the predictive potency.

Dynamic contrast-enhanced MRI histogram parameters predict progression-free survival in patients with advanced esophageal squamous carcinoma receiving concurrent chemoradiotherapy

BACKGROUND

There is increased interest in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for predicting the outcomes of patients with advanced esophageal cancer.

PURPOSE

To explore whether DCE-MRI histogram parameters can predict 12-month progression-free survival (PFS) in patients with advanced esophageal squamous carcinoma receiving concurrent chemoradiation therapy (CRT).

MATERIAL AND METHODS

This retrospective study enrolled 134 patients with advanced esophageal squamous carcinoma who were receiving CRT. The pre-CRT DCE-MRI histogram parameters (median, mean, SD, skewness, kurtosis, and 10th and 90th percentiles) of K^trans, K_ep, and V_e were collected. PFS analyses were performed using the Kaplan-Meier method and log-rank tests to compute the survival curves. The significant prognostic predictors among the data characteristics and DCE-MRI parameters were determined using multivariate Cox proportional hazards regression analyses.

RESULTS

There were 65 good responders (PFS ≥ 12 months) and 69 poor responders (PFS < 12 months). The median and mean values of K^trans were higher, and the kurtosis value of K^trans was lower in good responders. The median, mean, and 10th and 90th percentile values of K^trans were higher, and the kurtosis values of K^trans and V_e were lower in good responders. The PFS of patients aged ≥60 years, a CR effect, or a 10th percentile value of K^trans ≥0.13 was increased (P < 0.001, <0.001, and 0.014, respectively).

CONCLUSION

DCE-MRI histogram parameters can be used to evaluate the response to CRT in patients with advanced esophageal squamous carcinoma. The 10th percentile value of K^trans has significant prognostic value for 12-month PFS.

Virtual monoenergetic reconstructions of dynamic DECT acquisitions for calculation of perfusion maps of blood flow: Quantitative comparison to conventional, dynamic 80 kVp CT perfusion

PURPOSE

Investigation of potential improvements in dynamic CT perfusion measurements by exploitation of improved visualization of contrast agent in virtual monoenergetic reconstructions of images acquired with dual-energy computed tomography (DECT).

METHOD

For 17 patients with pancreatic carcinoma, dynamic dual-source DECT acquisitions were performed at 80kVp/Sn140kVp every 1.5 s over 51 s. Virtual monoenergetic images (VMI) were reconstructed for photon energies between 40 keV and 150 keV (5 keV steps). Using the maximum-slope model, perfusion maps of blood flow were calculated from VMIs and 80kVp images and compared quantitatively with regard to blood flow measured in regions of interest in healthy tissue and carcinoma, standard deviation (SD), and absolute-difference-to-standard-deviation ratio (ADSDR) of measurements.

RESULTS

On average, blood flow calculated from VMIs increased with increasing energy levels from 114.3 ± 37.2 mL/100 mL/min (healthy tissue) and 45.6 ± 25.3 mL/100 mL/min (carcinoma) for 40 keV to 128.6 ± 58.9 mL/100 mL/min (healthy tissue) and 75.5 ± 49.8 mL/100 mL/min (carcinoma) for 150 keV, compared to 114.2 ± 37.4 mL/100 mL/min (healthy tissue) and 46.5 ± 26.6 mL/100 mL/min (carcinoma) for polyenergetic 80kVp. Differences in blood flow between tissue types were significant for all energies. Differences between perfusion maps calculated from VMIs and 80kVp images were not significant below 110 keV. SD and ADSDR were significantly better for perfusion maps calculated from VMIs at energies between 40 keV and 55 keV than for those calculated from 80kVp images. Compared to effective dose of dynamic 80kVp acquisitions (4.6 ± 2.2mSv), dose of dynamic DECT/VMI acquisitions (8.0 ± 3.7mSv) was higher.

CONCLUSIONS

Perfusion maps of blood flow based on low-energy VMIs between 40 keV and 55 keV offer improved robustness and quality of quantitative measurements over those calculated from 80kVp image data (reference standard), albeit at increased patient radiation exposure.

Histogram analysis of DCE-MRI for chemoradiotherapy response evaluation in locally advanced esophageal squamous cell carcinoma

AIMS

The aim of the study was to predict and assess treatment response by histogram analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to patients with locally advanced esophageal squamous cell carcinoma receiving chemoradiotherapy (CRT).

MATERIALS AND METHODS

Seventy-two patients with locally advanced esophageal squamous cell carcinoma who underwent DCE-MRI before and after chemoradiotherapy were enrolled and divided into the complete response (CR) group and the non-CR group based on RECIST. The histogram parameters (10th percentile, 90th percentile, median, mean, standard deviation, skewness, and kurtosis) of pre-CRT and post-CRT were compared using a paired Student's t test in the CR and non-CR groups, respectively. The histogram parameter differences between the CR and the non-CR groups were compared using an unpaired Student's t test. A receiver operating characteristic (ROC) analysis was performed to evaluate the diagnostic performance.

RESULTS

The histogram parameters of K^trans values were observed to have significantly decreased after chemoradiotherapy in the CR group. The CR responders showed significantly higher median, mean, and 10th and 90th percentile of pre-K^trans values than those of the non-CR group. The histogram analysis indicated the decreased heterogeneity in the CR group after CRT. Esophageal cancer with higher pre-K^trans and lower post-K^trans values indicated a good treatment response to CRT. Pre-K^trans-10th showed the best diagnostic performance in predicting the chemoradiotherapy response.

CONCLUSIONS

The histogram parameters of K^trans are useful in the assessment and prediction of the chemoradiotherapy response in patients with advanced esophageal squamous cell carcinoma. DCE-MRI could serve as an adjunctive imaging technique for treatment planning.

Dynamic contrast-enhanced MRI for advanced esophageal cancer response assessment after concurrent chemoradiotherapy

PURPOSE

We aimed to evaluate the treatment response of patients with esophageal cancer after concurrent chemoradiation therapy (CRT) using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).

METHODS

This retrospective study included 59 patients with histologically confirmed esophageal squamous cell carcinoma. The patients underwent DCE-MRI before and 4 weeks after CRT. Patients with complete response were defined as the CR group; partial response, stable disease, and progressive disease patients were defined as the non-CR group. DCE-MRI parameters (Ktrans, Ve, and Kep) were measured and compared between pre- and post-CRT in the CR and non-CR groups, respectively. Pre-CRT and post-CRT parameters were used to calculate the absolute change and the ratio of change. DCE-MRI parameters were compared between the CR and non-CR groups. Receiver operating characteristic (ROC) curves were used to verify diagnostic performance.

RESULTS

Patients with higher T-stage esophageal cancer might present with poorer response. After CRT, the Ktrans and Kep values significantly decreased in the CR group, whereas only Kep value decreased in the non-CR group. The post-Ktrans and post-Kep values were observed to be significantly lower in the CR group than in the non-CR group. The absolute change and ratio of change of both Ktrans and Kep were higher in the CR group than in the non-CR group. Based on ROC analysis, the ratio of change in Ktrans was the best parameter to assess treatment response (AUC= 0.840).

CONCLUSION

DCE-MRI parameters are valuable in predicting and assessing concurrent CRT response for advanced esophageal cancer.

Evaluation of Multislice Spiral Computed Tomography Perfusion Imaging for the Efficacy of Preoperative Concurrent Chemoradiotherapy in Middle-aged and Elderly Patients with Locally Advanced Gastric Cancer

Background

This study aimed to investigate the predictive value of multislice spiral computed tomography (MSCT) perfusion imaging for the efficacy of preoperative concurrent chemoradiotherapy (CCRT) in middle-aged and elderly patients with locally advanced gastric cancer (LAGC).

Material/Methods

One-hundred twenty-six middle-aged and elderly patients with LAGC were selected. MSCT was performed before and after CCRT to obtain perfusion parameters: blood flow volume (BF), blood volume (BV), mean transit time (MTT), and permeability surface (PS). After CCRT, according to Response Evaluation Criteria in Solid Tumors (RECIST), patients were categorized into the effective group and the ineffective group. Overall survival rate was measured by Kaplan-Meier analysis. ROC curve was applied to evaluate the predictive value of perfusion parameters. Multiple logistic regression analysis was applied to analyze the association of perfusion parameters with the efficacy of preoperative treatment.

Results

Tumor volume reduction rates of the effective and ineffective groups were 59.23±8.53% and 10.41±3.36%. BF, BV, and PS values in the effective group were significantly decreased after CCRT. ROC curves indicated high sensitivities and specificities of BF value (79.00%, 73.44%), BV value (71.00%, 75.00%), and PS value (82.30%, 90.63%). The incidence rate of weakness and anorexia in the effective group was much higher than that in the ineffective group. Patients with low BF, BV, and PS values (less their optimal cutoff values) had longer survival times than these with high BF, BV, and PS values.

Conclusions

MSCT might have predictive values for the efficacy of preoperative CCRT in the treatment of LAGC.

An application study of low-dose computed tomography perfusion imaging (LDCTPI) in breast cancer and breast fibroadenoma

PURPOSE

To explore the characteristics of breast cancer and breast fibroadenoma using low-dose computed tomography perfusion imaging (LDCTPI) including specific perfusion parameter values, and seek the potential clinical applications in cancer prognosis assessment.

MATERIALS AND METHODS

Fifty patients including 30 diagnosed with breast cancer and 20 with breast fibroadenoma, as well as 15 control subjects with normal breasts were studied prospectively using LDCTPI examinations. The acquired volumetric imaging data were used for calculation, mapping and analysis by using a body tumor perfusion protocol in the CT perfusion software to measure 4 parameters: blood flow (BF), blood volume (BV), mean transit time (MTT), and the permeability surface (PS) area product. Statistical data analysis was then performed to distinguish the difference of the 4 parameter values among normal control, breast cancer and breast fibroadenoma cases.

RESULTS

The mean perfusion values of 15 normal controls were as follows: BF, 20.03±4.08 mL/100 g/min; BV, 4.53±0.95 mL/100 g; MTT, 5.90±0.82 s; and PS, 9.25±1.18 mL/100 g/min. The mean perfusion values of 30 cancer patients were as follows: BF, 56.67±6.59 mL/100 g/min; BV, 5.82±0.68 mL/100 g; MTT, 6.01±0.82 s; and PS, 24.95±5.05 mL/100 g/min. The mean perfusion values of 20 patients with breast fibroadenoma were as follows: BF, 46.24±6.65 mL/100 g/min; BV, 5.07±0.73 mL/100 g; MTT, 7.51±0.62 s; and PS, 16.73±6.48 mL/100 g/min. Comparing the 3 groups, differences were all statistically significant for BF, BV, MTT and PS values (p < 0.05, respectively); The BF, BV, PS values were highest in group of cancer patients, while the MTT value was highest in group of patients diagnosed with breast fibroadenoma.

CONCLUSION

Breast CT perfusion imaging is a promising functional imaging technology in breast cancer diagnosis, which can provide valuable quantitative imaging markers to assist evaluation of breast tumors.

Radiomics and its emerging role in lung cancer research, imaging biomarkers and clinical management: State of the art

With the development of functional imaging modalities we now have the ability to study the microenvironment of lung cancer and its genomic instability. Radiomics is defined as the use of automated or semi-automated post-processing and analysis of large amounts of quantitative imaging features that can be derived from medical images. The automated generation of these analytical features helps to quantify a number of variables in the imaging assessment of lung malignancy. These imaging features include: tumor spatial complexity, elucidation of the tumor genomic heterogeneity and composition, subregional identification in terms of tumor viability or aggressiveness, and response to chemotherapy and/or radiation. Therefore, a radiomic approach can help to reveal unique information about tumor behavior. Currently available radiomic features can be divided into four major classes: (a) morphological, (b) statistical, (c) regional, and (d) model-based. Each category yields quantitative parameters that reflect specific aspects of a tumor. The major challenge is to integrate radiomic data with clinical, pathological, and genomic information to decode the different types of tissue biology. There are many currently available radiomic studies on lung cancer for which there is a need to summarize the current state of the art.