Optimum parameters in a model for tumour control probability, including interpatient heterogeneity: evaluation of the log-normal distribution

Modeling of the resensitization effect on carbon-ion radiotherapy for stage I non-small cell lung cancer

Objective. To investigate the effect of redistribution and reoxygenation on the 3-year tumor control probability (TCP) of patients with stage I non-small cell lung cancer (NSCLC) treated with carbon-ion radiotherapy.Approach. A meta-analysis of published clinical data of 233 NSCLC patients treated by carbon-ion radiotherapy under 18-, 9-, 4-, and single-fraction schedules was conducted. The linear-quadratic (LQ)-based cell-survival model incorporating the radiobiological 5Rs, radiosensitivity, repopulation, repair, redistribution, and reoxygenation, was developed to reproduce the clinical TCP data. Redistribution and reoxygenation were regarded together as a single phenomenon and termed 'resensitization' in the model. The optimum interval time between fractions was investigated for each fraction schedule using the determined model parameters.Main results.The clinical TCP data for 18-, 9-, and 4-fraction schedules were reasonably reproduced by the model without the resensitization effect, whereas its incorporation was essential to reproduce the TCP data for all fraction schedules including the single fraction. The curative dose for the single-fraction schedule was estimated to be 49.0 Gy (RBE), which corresponds to the clinically adopted dose prescription of 50.0 Gy (RBE). For 18-, 9-, and 4-fraction schedules, a 2-to-3-day interval is required to maximize the resensitization effect during the time interval. In contrast, the single-fraction schedule cannot benefit from the resensitization effect, and the shorter treatment time is preferable to reduce the effect of sub-lethal damage repair during the treatment.Significance.The LQ-based cell-survival model incorporating the radiobiological 5Rs was developed and used to evaluate the effect of the resensitization on clinical results of NSCLC patients treated with hypo-fractionated carbon-ion radiotherapy. The incorporation of the resensitization into the cell-survival model improves the reproducibility to the clinical TCP data. A shorter treatment time is preferable in the single-fraction schedule, while a 2-to-3-day interval between fractions is preferable in the multi-fraction schedules for effective treatments.

Towards optimal heterogeneous prostate radiotherapy dose prescriptions based on patient-specific or population-based biological features

BACKGROUND

Escalation of prescribed dose in prostate cancer (PCa) radiotherapy enables improvement in tumor control at the expense of increased toxicity. Opportunities for reduction of treatment toxicity may emerge if more efficient dose escalation can be achieved by redistributing the prescribed dose distribution according to the known heterogeneous, spatially-varying characteristics of the disease.

PURPOSE

To examine the potential benefits, limitations and characteristics of heterogeneous boost dose redistribution in PCa radiotherapy based on patient-specific and population-based spatial maps of tumor biological features.

METHOD

High-resolution prostate histology images, from a cohort of 63 patients, annotated with tumor location and grade, provided patient-specific "maps" and a population-based "atlas" of cell density and tumor probability. Dose prescriptions were derived for each patient based on a heterogeneous redistribution of the boost dose to the intraprostatic lesions, with the prescription maximizing patient tumor control probability (TCP). The impact on TCP was assessed under scenarios where the distribution of population-based biological data was ignored, partially included, or fully included in prescription generation. Heterogeneous dose prescriptions were generated for three combinations of maps and atlas, and for conventional fractionation (CF), extreme hypo-fractionation (EH), moderate hypo-fractionation (MH), and whole Pelvic RT + SBRT Boost (WPRT + SBRT). The predicted efficacy of the heterogeneous prescriptions was compared with equivalent homogeneous dose prescriptions.

RESULTS

TCPs for heterogeneous dose prescriptions were generally higher than those for homogeneous dose prescriptions. TCP escalation by heterogeneous dose prescription was the largest for CF. When only using population-based atlas data, the generated heterogeneous dose prescriptions of 55 to 58 patients (out of 63) had a higher TCP than for the corresponding homogeneous dose prescriptions. The TCPs of the heterogeneous dose prescriptions generated with the population-based atlas and tumor probability maps did not differ significantly from those using patient-specific biological information. The generated heterogeneous dose prescriptions achieved significantly higher TCP than homogeneous dose prescriptions in the posterior section of the prostate.

CONCLUSION

Heterogeneous dose prescriptions generated via biologically-optimized dose redistribution can produce higher TCP than the homogeneous dose prescriptions for the majority of the patients in the studied cohort. For scenarios where patient-specific biological information was unavailable or partially available, the generated heterogeneous dose prescriptions can still achieve TCP improvement relative to homogeneous dose prescriptions.

Mechanisms of Melanoma Progression and Treatment Resistance: Role of Cancer Stem-like Cells

Melanoma is the third most common type of skin cancer, characterized by its heterogeneity and propensity to metastasize to distant organs. Melanoma is a heterogeneous tumor, composed of genetically divergent subpopulations, including a small fraction of melanoma-initiating cancer stem-like cells (CSCs) and many non-cancer stem cells (non-CSCs). CSCs are characterized by their unique surface proteins associated with aberrant signaling pathways with a causal or consequential relationship with tumor progression, drug resistance, and recurrence. Melanomas also harbor significant alterations in functional genes (BRAF, CDKN2A, NRAS, TP53, and NF1). Of these, the most common are the BRAF and NRAS oncogenes, with 50% of melanomas demonstrating the BRAF mutation (BRAFV600E). While the successful targeting of BRAFV600E does improve overall survival, the long-term efficacy of available therapeutic options is limited due to adverse side effects and reduced clinical efficacy. Additionally, drug resistance develops rapidly via mechanisms involving fast feedback re-activation of MAPK signaling pathways. This article updates information relevant to the mechanisms of melanoma progression and resistance and particularly the mechanistic role of CSCs in melanoma progression, drug resistance, and recurrence.

Voxel-level biological optimisation of prostate IMRT using patient-specific tumour location and clonogen density derived from mpMRI

AIMS

This study aimed to develop a framework for optimising prostate intensity-modulated radiotherapy (IMRT) based on patient-specific tumour biology, derived from multiparametric MRI (mpMRI). The framework included a probabilistic treatment planning technique in the effort to yield dose distributions with an improved expected treatment outcome compared with uniform-dose planning approaches.

METHODS

IMRT plans were generated for five prostate cancer patients using two inverse planning methods: uniform-dose to the planning target volume and probabilistic biological optimisation for clinical target volume tumour control probability (TCP) maximisation. Patient-specific tumour location and clonogen density information were derived from mpMRI and geometric uncertainties were incorporated in the TCP calculation. Potential reduction in dose to sensitive structures was assessed by comparing dose metrics of uniform-dose plans with biologically-optimised plans of an equivalent level of expected tumour control.

RESULTS

The planning study demonstrated biological optimisation has the potential to reduce expected normal tissue toxicity without sacrificing local control by shaping the dose distribution to the spatial distribution of tumour characteristics. On average, biologically-optimised plans achieved 38.6% (p-value: < 0.01) and 51.2% (p-value: < 0.01) reduction in expected rectum and bladder equivalent uniform dose, respectively, when compared with uniform-dose planning.

CONCLUSIONS

It was concluded that varying the dose distribution within the prostate to take account for each patient's clonogen distribution was feasible. Lower doses to normal structures compared to uniform-dose plans was possible whilst providing robust plans against geometric uncertainties. Further validation in a larger cohort is warranted along with considerations for adaptive therapy and limiting urethral dose.

Radiobiological parameters in a tumour control probability model for prostate cancer LDR brachytherapy

To provide recommendations for the selection of radiobiological parameters for prostate cancer treatment planning. Recommendations were based on validation of the previously published values, parameter estimation and a consideration of their sensitivity within a tumour control probability (TCP) model using clinical outcomes data from low-dose-rate (LDR) brachytherapy. The proposed TCP model incorporated radiosensitivity (α) heterogeneity and a non-uniform distribution of clonogens. The clinical outcomes data included 849 prostate cancer patients treated with LDR brachytherapy at four Australian centres between 1995 and 2012. Phoenix definition of biochemical failure was used. Validation of the published values from four selected literature and parameter estimation was performed with a maximum likelihood estimation method. Each parameter was varied to evaluate the change in calculated TCP to quantify the sensitivity of the model to its radiobiological parameters. Using a previously published parameter set and a total clonogen number of 196 000 provided TCP estimates that best described the patient cohort. Fitting of all parameters with a maximum likelihood estimation was not possible. Variations in prostate TCP ranged from 0.004% to 0.67% per 1% change in each parameter. The largest variation was caused by the log-normal distribution parameters for α (mean, [Formula: see text], and standard deviation, σ _α ). Based on the results using the clinical cohort data, we recommend a previously published dataset is used for future application of the TCP model with inclusion of a patient-specific, non-uniform clonogen density distribution which could be derived from multiparametric imaging. The reduction in uncertainties in these parameters will improve the confidence in using biological models for clinical radiotherapy planning.

Advances in radiotherapy techniques and delivery for non-small cell lung cancer: benefits of intensity-modulated radiation therapy, proton therapy, and stereotactic body radiation therapy

The 21st century has seen several paradigm shifts in the treatment of non-small cell lung cancer (NSCLC) in early-stage inoperable disease, definitive locally advanced disease, and the postoperative setting. A key driver in improvement of local disease control has been the significant evolution of radiation therapy techniques in the last three decades, allowing for delivery of definitive radiation doses while limiting exposure of normal tissues. For patients with locally-advanced NSCLC, the advent of volumetric imaging techniques has allowed a shift from 2-dimensional approaches to 3-dimensional conformal radiation therapy (3DCRT). The next generation of 3DCRT, intensity-modulated radiation therapy and volumetric-modulated arc therapy (VMAT), have enabled even more conformal radiation delivery. Clinical evidence has shown that this can improve the quality of life for patients undergoing definitive management of lung cancer. In the early-stage setting, conventional fractionation led to poor outcomes. Evaluation of altered dose fractionation with the previously noted technology advances led to advent of stereotactic body radiation therapy (SBRT). This technique has dramatically improved local control and expanded treatment options for inoperable, early-stage patients. The recent development of proton therapy has opened new avenues for improving conformity and the therapeutic ratio. Evolution of newer proton therapy techniques, such as pencil-beam scanning (PBS), could improve tolerability and possibly allow reexamination of dose escalation. These new progresses, along with significant advances in systemic therapies, have improved survival for lung cancer patients across the spectrum of non-metastatic disease. They have also brought to light new challenges and avenues for further research and improvement.

A simulation framework for modeling tumor control probability in breast conserving therapy

BACKGROUND AND PURPOSE

Microscopic disease (MSD) left after tumorectomy is a major cause of local recurrence in breast conserving therapy (BCT). However, the effect of microscopic disease and RT dose on tumor control probability (TCP) was seldom studied quantitatively. A simulation framework was therefore constructed to explore the relationship between tumor load, radiation dose and TCP.

MATERIALS AND METHODS

First, we modeled total disease load and microscopic spread with a pathology dataset. Then we estimated the remaining disease load after tumorectomy through surgery simulation. The Webb-Nahum TCP model was extended by clonogenic cell fraction to model the risk of local recurrence. The model parameters were estimated by fitting the simulated results to the observations in two clinical trials.

RESULTS

Higher histopathology grade has a strong correlation with larger MSD cell quantity. On average 12.5% of the MSD cells remained in the patient's breast after surgery but varied considerably among patients (0-100%); illustrating the role of radiotherapy. A small clonogenic cell fraction was optimal in our model (one in every 2.7*10(6)cells). The mean radiosensitivity was estimated at 0.067Gy(-1) with standard deviation of 0.022Gy(-1).

CONCLUSION

A relationship between radiation dose and TCP was established in a newly designed simulation framework with detailed disease load, surgery and radiotherapy models.

Evaluation of the deformation and corresponding dosimetric implications in prostate cancer treatment

The cone-beam computed tomography (CBCT) imaging modality is an integral component of image-guided adaptive radiation therapy (IGART), which uses patient-specific dynamic/temporal information for potential treatment plan modification. In this study, an offline process for the integral component IGART framework has been implemented that consists of deformable image registration (DIR) and its validation, dose reconstruction, dose accumulation and dose verification. This study compares the differences between planned and estimated delivered doses under an IGART framework of five patients undergoing prostate cancer radiation therapy. The dose calculation accuracy on CBCT was verified by measurements made in a Rando pelvic phantom. The accuracy of DIR on patient image sets was evaluated in three ways: landmark matching with fiducial markers, visual image evaluation and unbalanced energy (UE); UE has been previously demonstrated to be a feasible method for the validation of DIR accuracy at a voxel level. The dose calculated on each CBCT image set was reconstructed and accumulated over all fractions to reflect the 'actual dose' delivered to the patient. The deformably accumulated (delivered) plans were then compared to the original (static) plans to evaluate tumor and normal tissue dose discrepancies. The results support the utility of adaptive planning, which can be used to fully elucidate the dosimetric impact based on the simulated delivered dose to achieve the desired tumor control and normal tissue sparing, which may be of particular importance in the context of hypofractionated radiotherapy regimens.

In silico modelling of treatment-induced tumour cell kill: developments and advances

Mathematical and stochastic computer (in silico) models of tumour growth and treatment response of the past and current eras are presented, outlining the aims of the models, model methodology, the key parameters used to describe the tumour system, and treatment modality applied, as well as reported outcomes from simulations. Fractionated radiotherapy, chemotherapy, and combined therapies are reviewed, providing a comprehensive overview of the modelling literature for current modellers and radiobiologists to ignite the interest of other computational scientists and health professionals of the ever evolving and clinically relevant field of tumour modelling.

Time-dependent cell disintegration kinetics in lung tumors after irradiation

We study the time-dependent disintegration kinetics of tumor cells that did not survive radiotherapy treatment. To evaluate the cell disintegration rate after irradiation, we studied the volume changes of solitary lung tumors after stereotactic radiotherapy. The analysis is performed using two approximations: (1) tumor volume is a linear function of the total cell number in the tumor and (2) the cell disintegration rate is governed by the exponential decay with constant risk, which is defined by the initial cell number and a half-life T(1/2). The half-life T(1/2) is determined using the least-squares fit to the clinical data on lung tumor size variation with time after stereotactic radiotherapy. We show that the tumor volume variation after stereotactic radiotherapy of solitary lung tumors can be approximated by an exponential function. A small constant component in the volume variation does not change with time; however, this component may be the residual irregular density due to radiation fibrosis and was, therefore, subtracted from the total volume variation in our computations. Using computerized fitting of the exponent function to the clinical data for selected patients, we have determined that the average half-life T(1/2) of cell disintegration is 28.2 days for squamous cell carcinoma and 72.4 days for adenocarcinoma. This model is needed for simulating the tumor volume variation during radiotherapy, which may be important for time-dependent treatment planning of proton therapy that is sensitive to density variations.