Temporal Lung Tumor Volume Changes in Small-Cell Lung Cancer Patients Undergoing Chemoradiotherapy

Adaptive radiation therapy (art) for patients with limited-stage small cell lung cancer (LS-SCLC): A dosimetric evaluation

Background

Adaptive radiation therapy (ART) refers to redesigning of radiation therapy (RT) treatment plans with respect to dynamic changes in tumor size and location throughout the treatment course. In this study, we performed a comparative volumetric and dosimetric analysis to investigate the impact of ART for patients with limited-stage small cell lung cancer (LS-SCLC).

Methods

Twenty-four patients with LS-SCLC receiving ART and concomitant chemotherapy were included in the study. ART was performed by replanning of patients based on a mid-treatment computed tomography (CT)-simulation which was routinely scheduled for all patients 20-25 days after the initial CT-simulation. While the first 15 RT fractions were planned using the initial CT-simulation images, the latter 15 RT fractions were planned using the mid-treatment CT-simulation images acquired 20-25 days after the initial CT-simulation. In order to document the impact of ART, target and critical organ dose-volume parameters acquired from this adaptive radiation treatment planning (RTP) were compared with the RTP based solely on the initial CT-simulation to deliver the whole RT dose of 60 Gy.

Results

Statistically significant reduction was detected in gross tumor volume (GTV) and planning target volume (PTV) during the conventionally fractionated RT course along with statistically significant reduction in critical organ doses with incorporation of ART.

Conclusion

One-third of the patients in our study who were otherwise ineligible for curative intent RT due to violation of critical organ dose constraints could be treated with full dose irradiation by use of ART. Our results suggest significant benefit of ART for patients with LS-SCLC.

A method for predictive modeling of tumor regression for lung adaptive radiotherapy

PURPOSE

The purpose of this work is to create a decision support methodology to predict when patients undergoing radiotherapy treatment for locally advanced lung cancer would potentially benefit from adaptive radiotherapy. The proposed methodology seeks to eliminate the manual subjective review by developing an automated statistical learning model to predict when tumor regression would trigger implementation of adaptive radiotherapy based on quantified anatomic changes observed in individual patients on-treatment cone beam computed tomographies (CTs). This proposed process seeks to improve the efficacy and efficiency of both the existing manual and automated adaptive review processes for locally advanced stage III lung cancer.

METHODS

A predictive algorithm was developed as a decision support tool to determine the potential utility of mid-treatment adaptive radiotherapy based on anatomic changes observed on 1158 daily CBCT images across 43 patients. The anatomic changes on each axial slice within specified regions-of-interest were quantified into a single value utilizing imaging similarity criteria comparing the daily CBCT to the initial simulation CT. The range of the quantified metrics for each fraction across all axial slices are reduced to specified quantiles, which are used as the predictive input to train a logistic regression algorithm. A "ground-truth" of the need for adaptive radiotherapy based on tumor regression was evaluated systematically on each of the daily CBCTs and used as the classifier in the logistic regression algorithm. Accuracy of the predictive model was assessed utilizing both a tenfold cross validation and an independent validation dataset, with the sensitivity, specificity, and fractional accuracy compared to the ground-truth.

RESULTS

The sensitivity and specificity for the individual daily fractions ranged from 87.9%-94.3% and 91.9%-98.6% for a probability threshold of 0.2-0.5, respectively. The corresponding average treatment fraction difference between the model predictions and assessed ART "ground-truth" ranged from -2.25 to -0.07 fractions, with the model predictions consistently predicting the potential need for ART earlier in the treatment course. By initially utilizing a lower probability threshold, the higher sensitivity minimizes the chance of false negative by alerting the clinician to review a higher number of questionable cases.

CONCLUSIONS

The proposed methodology accurately predicted the first fraction at which individual patients may benefit from ART based on quantified anatomic changes observed in the on-treatment volumetric imaging. The generalizability of the proposed method has potential to expand to additional modes of adaptive radiotherapy for lung cancer patients with observed underlying anatomic changes.

Recent developments in radiotherapy for small-cell lung cancer: a review by the Oncologic Group for the Study of Lung Cancer (Spanish Radiation Oncology Society)

Small-cell lung cancer (SCLC) accounts for 13% of all lung tumours. The standard treatment in patients with limited-stage disease is radiotherapy combined with chemotherapy. In extensive SCLC, the importance of consolidation thoracic radiotherapy in patients with a good treatment response has become increasingly recognized. In both limited and extensive disease, prophylactic cranial irradiation is recommended in patients who respond to treatment. New therapeutic approaches such as immunotherapy are being increasingly incorporated into the treatment of SCLC, although more slowly than in non-small cell lung cancer (NSCLC). Diverse radiation dose and fractionation schemes, administered in varying combinations with these new drugs, are being investigated. In the present study we review and update the role of radiotherapy in the treatment of SCLC. We also discuss the main clinical trials currently underway in order to identify future trends.

Association of Topoisomerase II (TOP2A) and Dual-Specificity Phosphatase 6 (DUSP6) Single Nucleotide Polymorphisms with Radiation Treatment Response and Prognosis of Lung Cancer in Han Chinese

Background

Mutations of DNA topoisomerase II (TOP2A) are associated with chemotherapy resistance, whereas dual-specificity phosphatase 6 (DUSP6) negatively regulates members of the mitogen-activated protein (MAP) kinase superfamily to control cell proliferation. This study assessed TOP2A and DUSP6 single nucleotide polymorphisms (SNPs) in non-small cell lung cancer (NSCLC) patients for association with chemoradiotherapy responses and prognosis.

Material/Methods

A total of 140 Chinese patients with histologically confirmed NSCLC were enrolled and subjected to genotyping of TOP2A rs471692 and DUSP6 rs2279574 using Taqman PCR. An independent sample t test was used to analyze differences in tumor regression after radiotherapy versus SNP risk factors. Kaplan-Meier curves analyzed overall survival, followed by the log-rank test and Cox proportional hazard models.

Results

There were no significant associations of TOP2A rs471692 and DUSP6 rs2279574 polymorphisms or clinicopathological variables with response to chemoradiotherapy (p>0.05). Comparing overall survival of 87 patients with stage I–III NSCLC treated with radiotherapy or chemoradiotherapy to clinicopathological variables, the data showed that tumor regression, weight loss, clinical stage, and cigarette smoking were independent prognostic predictors (p=0.009, 0.043, 0.004, and 0.025, respectively). Tumor regression rate >0.34 was associated with patent survival versus tumor regression rate ≤0.34 (p=0.007).

Conclusions

TOP2A rs471692 and DUSP6 rs2279574 SNPs were not associated with chemoradiotherapy response, whereas tumor regression, weight loss, clinical stage, and cigarette smoking were independent prognostic predictors for these Chinese patients with NSCLC.

Tumour volume changes assessed with high-quality KVCT in lung cancer patients undergoing concurrent chemoradiotherapy

OBJECTIVE

We evaluated tumour volume changes in patients with lung cancer undergoing concurrent chemoradiotherapy using image-guided radiotherapy (RT).

METHODS

The kilovoltage image was obtained using CT on rail at every five fractions. The gross tumour volumes (GTVs), including the primary tumour and lymph nodes (LNs), were contoured to analyse the time and degree of tumour regression.

RESULTS

46 patients [32, non-small-cell lung cancer (NSCLC), and 14, small-cell lung cancer (SCLC)] were included in this study. In total, 281 CT scans and 82 sites of GTVs were evaluated. Significant volume changes occurred in both the NSCLC and SCLC groups (p < 0.001 and 0.002), and the average GTV change compared with baseline was 49.85 ± 3.65 [standard error (SE)]% and 65.95 ± 4.60 (SE)% for the NSCLC and SCLC groups, respectively. A significant difference in the degree of volume reduction between the primary tumour and LNs was observed in only the NSCLC group (p < 0.0001) but not in the SCLC group (p = 0.735). The greatest volume regression compared with the volume before the five fractions occurred between the 15 and 20 fractions in the NSCLC group and between the 5 and 10 fractions in the SCLC group.

CONCLUSION

Both primary tumour and LNs were well defined using CT on rail. Significant volume changes occurred during RT, and there was a difference in volume reduction between the NSCLC and SCLC groups, regarding the degree and timing of the tumour reduction in the primary tumour and LNs.

ADVANCES IN KNOWLEDGE

NSCLC and SCLC groups showed differences in the degree and timing of volume reduction. The primary tumour and LNs in NSCLC regressed differently.

Inter-tester reproducibility of tumour change in small cell lung cancer patients undergoing chemoradiotherapy

BACKGROUND

Tumour volume change during delivery of chemoradiotherapy is observed in small cell lung cancer (SCLC) patients. In this study, we have compared tumour volume and anatomical changes, e.g. atelectasis or pleural effusions determined by three different methods.

METHOD

A total of 37 SCLC patients undergoing thoracic radiotherapy during 2010-2011 were included. The patients were treated based on a daily three-dimensional (3D) cone beam computed tomography (CBCT) bony anatomy registration. The CBCT scans were retrospectively reviewed visually by a radiation therapist (Visual-RTT) in order to register tumour volume changes. Furthermore, the tumour volume changes were obtained by either deformable image registration (DIR) or delineation by a radiation oncologist (RO). Kappa (κ) statistics and paired t-tests were used for evaluation of the inter-tester agreement.

RESULTS

The tumour volume change between the Visual-RTT, the DIR and the RO assessments obtained 84-97% agreement (κ = 0.68-0.95). Furthermore, there was no statistically significant difference between the tumour change assessment of the RO (mean 13.6 ml) and the DIR (mean 14.5 ml), p = 0.59. Tumour shrinkage was observed in 15 (41%) patients and anatomical changes in seven (19%) patients.

CONCLUSION

The inter-tester reproducibility of tumour volume change between the three methods is excellent. Visual-RTT on-line inspection may be used to determine tumour shrinkage and anatomical changes as atelectasis or pleural effusions during the radiotherapy course by use of daily CBCT scans.