Individualization of dose prescription based on normal-tissue dose-volume and radiosensitivity data

Risk adaptive planning with biology-based constraints may lead to higher tumor control probability in tumors of the canine brain: A planning study

BACKGROUND

Classical radiation protocols are guided by physical dose delivered homogeneously over the target. Protocols are chosen to keep normal tissue complication probability (NTCP) at an acceptable level. Organs at risk (OAR) adjacent to the target volume could lead to underdosage of the tumor and a decrease of tumor control probability (TCP). The intent of our study was to explore a biology-based dose escalation: by keeping NTCP for OAR constant, radiation dose was to be maximized, allowing to result in heterogeneous dose distributions.

METHODS

We used computed tomography datasets of 25 dogs with brain tumors, previously treated with 10x4 Gy (40 Gy to PTV D50). We generated 3 plans for each patient: A) original treatment plan with homogeneous dose distribution, B) heterogeneous dose distribution with strict adherence to the same NTCPs as in A), and C) heterogeneous dose distribution with adherence to NTCP <5%. For plan comparison, TCPs and TCP equivalent doses (homogenous target dose which results in the same TCP) were calculated. To enable the use of the generalized equivalent uniform dose (gEUD) metric of the tumor target in plan optimization, the calculated TCP values were used to obtain the volume effect parameter a.

RESULTS

As intended, NTCPs for all OARs did not differ from plan A) to B). In plan C), however, NTCPs were significantly higher for brain (mean 2.5% (SD±1.9, 95%CI: 1.7,3.3), p<0.001), optic chiasm (mean 2.0% (SD±2.2, 95%CI: 1.0,2.8), p=0.010) compared to plan A), but no significant increase was found for the brainstem. For 24 of 25 of the evaluated patients, the heterogenous plans B) and C) led to an increase in target dose and projected increase in TCP compared to the homogenous plan A). Furthermore, the distribution of the projected individual TCP values as a function of the dose was found to be in good agreement with the population TCP model.

CONCLUSION

Our study is a first step towards risk-adaptive radiation dose optimization. This strategy utilizes a biologic objective function based on TCP and NTCP instead of an objective function based on physical dose constraints.

Biological modeling in thermoradiotherapy: present status and ongoing developments toward routine clinical use

Biological modeling for anti-cancer treatments using mathematical models can be very supportive in gaining more insight into dynamic processes responsible for cellular response to treatment, and predicting, evaluating and optimizing therapeutic effects of treatment. This review presents an overview of the current status of biological modeling for hyperthermia in combination with radiotherapy (thermoradiotherapy). Various distinct models have been proposed in the literature, with varying complexity; initially aiming to model the effect of hyperthermia alone, and later on to predict the effect of the combined thermoradiotherapy treatment. Most commonly used models are based on an extension of the linear-quadratic (LQ)-model enabling an easy translation to radiotherapy where the LQ model is widely used. Basic predictions of cell survival have further progressed toward 3 D equivalent dose predictions, i.e., the radiation dose that would be needed without hyperthermia to achieve the same biological effect as the combined thermoradiotherapy treatment. This approach, with the use of temperature-dependent model parameters, allows theoretical evaluation of the effectiveness of different treatment strategies in individual patients, as well as in patient cohorts. This review discusses the significant progress that has been made in biological modeling for hyperthermia combined with radiotherapy. In the future, when adequate temperature-dependent LQ-parameters will be available for a large number of tumor sites and normal tissues, biological modeling can be expected to be of great clinical importance to further optimize combined treatments, optimize clinical protocols and guide further clinical studies.

Prediction of the Acute or Late Radiation Toxicity Effects in Radiotherapy Patients Using Ex Vivo Induced Biodosimetric Markers: A Review

A search for effective methods for the assessment of patients' individual response to radiation is one of the important tasks of clinical radiobiology. This review summarizes available data on the use of ex vivo cytogenetic markers, typically used for biodosimetry, for the prediction of individual clinical radiosensitivity (normal tissue toxicity, NTT) in cells of cancer patients undergoing therapeutic irradiation. In approximately 50% of the relevant reports, selected for the analysis in peer-reviewed international journals, the average ex vivo induced yield of these biodosimetric markers was higher in patients with severe reactions than in patients with a lower grade of NTT. Also, a significant correlation was sometimes found between the biodosimetric marker yield and the severity of acute or late NTT reactions at an individual level, but this observation was not unequivocally proven. A similar controversy of published results was found regarding the attempts to apply G2- and γH2AX foci assays for NTT prediction. A correlation between ex vivo cytogenetic biomarker yields and NTT occurred most frequently when chromosome aberrations (not micronuclei) were measured in lymphocytes (not fibroblasts) irradiated to relatively high doses (4-6 Gy, not 2 Gy) in patients with various grades of late (not early) radiotherapy (RT) morbidity. The limitations of existing approaches are discussed, and recommendations on the improvement of the ex vivo cytogenetic testing for NTT prediction are provided. However, the efficiency of these methods still needs to be validated in properly organized clinical trials involving large and verified patient cohorts.

Uncomplicated and Cancer-Free Control Probability (UCFCP): A new integral approach to treatment plan optimization in photon radiation therapy

PURPOSE

Biological treatment plan evaluation does not currently consider second cancer induction from peripheral doses associated to photon radiotherapy. The aim is to propose a methodology to characterize the therapeutic window by means of an integral radiobiological approach, which considers not only Tumour Control Probability (TCP) and Normal Tissue Complication Probability (NTCP) but also Secondary Cancer Probability (SCP).

METHODS

Uncomplicated and Cancer-Free Control Probability (UCFCP) function has been proposed assuming a statistically uncorrelated response for tumour and normal tissues. The Poisson's and Lyman's models were chosen for TCP and NTCP calculations, respectively. SCP was modelled as the summation of risks associated to photon and neutron irradiation of radiosensitive organs. For the medium (>4Gy) and low dose regions, mechanistic and linear secondary cancer risks models were used, respectively. Two conformal and intensity-modulated prostate plans at 15MV (same prescription dose) were selected to illustrate the UCFCP features.

RESULTS

UCFCP exhibits a bell-shaped behaviour with its maximum inside the therapeutic window. SCP values were not different for the plans analysed (∼2.4%) and agreed with published epidemiological results. Therefore, main differences in UCFCP came from differences in rectal NTCP (18% vs 9% for 3D-CRT and IMRT, respectively). According to UCFCP values, the evaluated IMRT plan ranked first.

CONCLUSIONS

The level of SCP was found to be similar to that of NTCP complications which reinforces the importance of considering second cancer risks as part of the possible late sequelae due to treatment. Previous concerns about the effect of peripheral radiation, especially neutrons, in the induction of secondary cancers can be evaluated by quantifying the UCFCP.

Mechanistic modelling of radiotherapy-induced lung toxicity

OBJECTIVE

This work explores the biological basis of a mechanistic model of radiation-induced lung damage; uniquely, the model makes a connection between the cellular radiobiology involved in lung irradiation and the full three-dimensional distribution of radiation dose.

METHODS

Local tissue damage and loss of global organ function, in terms of radiation pneumonitis (RP), were modelled as different levels of radiation injury. Parameters relating to the former could be derived from the local dose-response function, and the latter from the volume effect of the organ. The literature was consulted to derive information on a threshold dose and volume-effect mechanisms.

RESULTS

Simulations of local tissue damage supported the alveolus as a functional subunit (FSU) which can be regenerated from a single surviving stem cell. A moderate interpatient variation in stem cell radiosensitivity (15%) resulted in a great variation in tissue response between 8 and 20 Gy. The threshold of FSU inactivation within a critical functioning volume leading to RP was found to be approximately 47% and the degree of health status variation (influencing the volume effect) in a population was estimated at 25%.

CONCLUSION

This work has shown that it is possible to make sense of the way the lung responds to radiation by modelling RP mechanistically, from cell death to tissue damage to loss of organ function.

ADVANCES IN KNOWLEDGE

Simulations were able to provide parameter values, currently not available in the literature, related to the response of the lung to irradiation.

A method to visualize the uncertainty of the prediction of radiobiological models

A method for quantitative visualization of the uncertainty in the predicted tumor control probability (TCP) and normal tissue complication probability (NTCP) in radiotherapy has been developed. Uncertainties of TCP and NTCP due to inter-individual variation of the underlying radiosensitivity parameters was simulated by sampling the prescribed dose from a uniform distribution and the radiosensitivity-parameters from a Gaussian distribution. The result is visualized as a scatter-plot superimposed to the population-based dose response curves using the prescribed dose as the common dosimetric variable. In addition, probability histograms are derived quantifying the probability of specific TCP- or NTCP-values for individual patients from the underlying population. The method is exemplified with a pleural mesothelioma case with the lung as organ at risk. A prescribed dose of 54 Gy together with radiosensitivity variations of 6% (tumor) and 10% (normal tissue) results in a TCP of 85% (range 68-94%, 90% confidence interval, CI) and an NTCP of 4% (range 3-6%, 90% CI), respectively. Increasing the radiosensitivity variation of the tumor to 15% and reducing the lung tolerance dose by 25% results in values of 84% (range 51-97%, 90% CI) for TCP and 9% (range 6-12%, 90% CI) for NTCP. Increasing the dose to 60 Gy leads to TCP- and NTCP-values of 93% (range 69-100%, 90% CI) and 12% (range 8-17%, 90% CI), respectively. The new method visualizes the uncertainty of TCP- and NTCP-values and hence of the therapeutic window. This can help the clinician to assess the treatment plan for the individual patient.

(Radio)biological optimization of external-beam radiotherapy

“Biological optimization” (BIOP) means planning treatments using (radio)biological criteria and models, that is, tumour control probability and normal-tissue complication probability. Four different levels of BIOP are identified: Level I is “isotoxic” individualization of prescription dose D_presc at fixed fraction number. D_presc is varied to keep the NTCP of the organ at risk constant. Significant improvements in local control are expected for non-small-cell lung tumours. Level II involves the determination of an individualized isotoxic combination of D_presc and fractionation scheme. This approach is appropriate for “parallel” OARs (lung, parotids). Examples are given using our BioSuite software. Hypofractionated SABR for early-stage NSCLC is effectively Level-II BIOP. Level-III BIOP uses radiobiological functions as part of the inverse planning of IMRT, for example, maximizing TCP whilst not exceeding a given NTCP. This results in non-uniform target doses. The NTCP model parameters (reflecting tissue “architecture”) drive the optimizer to emphasize different regions of the DVH, for example, penalising high doses for quasi-serial OARs such as rectum. Level-IV BIOP adds functional imaging information, for example, hypoxia or clonogen location, to Level III; examples are given of our prostate “dose painting” protocol, BioProp. The limitations of and uncertainties inherent in the radiobiological models are emphasized.

Radiobiologically guided optimisation of the prescription dose and fractionation scheme in radiotherapy using BioSuite

OBJECTIVE

Radiobiological models provide a means of evaluating treatment plans. Keeping in mind their inherent limitations, they can also be used prospectively to design new treatment strategies which maximise therapeutic ratio. We propose here a new method to customise fractionation and prescription dose.

METHODS

To illustrate our new approach, two non-small cell lung cancer treatment plans and one prostate plan from our archive are analysed using the in-house software tool BioSuite. BioSuite computes normal tissue complication probability and tumour control probability using various radiobiological models and can suggest radiobiologically optimal prescription doses and fractionation schemes with limited toxicity.

RESULTS

Dose-response curves present varied aspects depending on the nature of each case. The optimisation process suggests doses and fractionation schemes differing from the original ones. Patterns of optimisation depend on the degree of conformality, the behaviour of the normal tissue (i.e. "serial" or "parallel"), the volume of the tumour and the parameters of clonogen proliferation.

CONCLUSION

Individualising the prescription dose and number of fractions with the help of BioSuite results in improved therapeutic ratios as evaluated by radiobiological models.

Dose-painting IMRT optimization using biological parameters

PURPOSE

Our work on dose-painting based on the possible risk characteristics for local recurrence in tumor subvolumes and the optimization of treatment plans using biological objective functions that are region-specific are reviewed.

MATERIALS AND METHODS

A series of intensity modulated dose-painting techniques are compared to their corresponding intensity modulated plans in which the entire PTV is treated to a single dose level, delivering the same equivalent uniform dose (EUD) to the entire PTV. Iso-TCP and iso-NTCP maps are introduced as a tool to aid the planner in the evaluation of the resulting non-uniform dose distributions. Iso-TCP and iso-NTCP maps are akin to iso-dose maps in 3D conformal radiotherapy. The impact of the currently limited diagnostic accuracy of functional imaging on a series of dose-painting techniques is also discussed.

RESULTS

Utilizing biological parameters (risk-adaptive optimization) in the generation of dose-painting plans results in an increase in the therapeutic ratio as compared to conventional dose-painting plans in which optimization techniques based on physical dose are employed.

CONCLUSION

Dose-painting employing biological parameters appears to be a promising approach for individualized patient- and disease-specific radiotherapy.

Evaluation of adaptive radiotherapy of bladder cancer by image-based tumour control probability modelling

Clinical implementation of adaptive radiotherapy strategies could benefit from extended tools for plan evaluation and selection. For this purpose we investigated the feasibility of image-based tumour control probability (TCP) modelling using the bladder as example of a tumour site with potential benefit from adaptive strategies.

MATERIAL AND METHODS

Two bladder cancer patients that underwent planning CT and daily cone beam CT (CBCT) imaging during the treatment course were included. The bladder was outlined in every image series. Following a previously published procedure, various adaptive planning target volumes (PTVs) were generated from the inter-fractional bladder variation observed during the first four CBCT sessions. Intensity modulated treatment plans delivering 60 Gy to a given PTV were generated. In addition, simultaneous integrated boost (SIB) plans giving a 10 Gy boost to the tumour were created. Using the daily CBCT images and polynomial warping, the dose in each bladder volume element was tracked fraction by fraction. TCP calculations employing the tracked accumulated dose distributions, together with radiosensitivity parameters estimated from published data on local control of bladder cancer were performed. The dependence of TCP on the simulated clonogenic cell distribution was also explored.

RESULTS

For a uniform clonogenic cell density in the whole bladder, TCP varied between 53% and 58% for the 60 Gy plans, while it was between 51% and 64% for the SIB plans. The lowest values were found when using the smallest PTVs, as they did not geometrically enclose the clinical target volume in all fractions. When increasing the clonogenic cell density in the tumour relative to that in the remaining bladder, the TCP saturated at approximately 75% for the SIB plans.

CONCLUSION

Dose tracking and TCP calculation provided additional information to standard criteria such as geometrical coverage for the selected cases. TCP modelling may be a useful tool in plan evaluation and for selection between multiple plans.

Peripheral leukocyte response to oncological radiotherapy: Expression of heat shock proteins

PURPOSE

To study Heat Shock Proteins (HSP) expression in patients subjected to radiotherapy and their potential use as biomarkers for radiation tolerance. An evaluation is also made of whether irradiated volume is critical to the outcome of normal tissue injury using polymorphonuclear neutrophils as biosensors, and whether HSP antibodies (Ab) may be involved in post-radiotherapy disease.

MATERIAL AND METHODS

Twelve patients receiving the same total dose of radiotherapy, but in three different volumes, and four healthy volunteers used as controls were analysed. hsp27 and 70i mRNA were determined by Reverse Transcription-Polymerase Chain Reaction (RT-PCR) and Southern-blot, HSP by flow cytometry, and HSP-Ab by Enzyme-linked Immnoadsorbent Assay (ELISA). The clinical protocol included radiation related toxicity based on clinical and analytical scales.

RESULTS

Radiotherapy caused hsp downregulation, maximum in patients with the largest irradiated volumes, and a decrease in intracellular HSP content. Patients with greatest intraleukocyte HSP levels before treatment suffered more severe radiation morbidity. Patients with endocrine neoplasms presented the highest HSP-Ab titers.

CONCLUSIONS

Radiotherapy downregulates hsp27 and 70i, which would enhance radiosensitivity. HSP content prior to treatment is suggested as a prognostic biomarker for radiation tolerance, with circulating leukocytes as biosensors. HSP-Ab may be biomarkers of tumor disease, but do not seem to be involved in the morbidity of acute post-radiotherapy disease, which is closely related to the volumes irradiated.

Dose-volume and biological-model based comparison between helical tomotherapy and (inverse-planned) IMAT for prostate tumours

BACKGROUND AND PURPOSE

Helical tomotherapy (HT) and intensity-modulated arc therapy (IMAT) are two arc-based approaches to the delivery of intensity-modulated radiotherapy (IMRT). Through plan comparisons we have investigated the potential of IMAT, both with constant (conventional or IMAT-C) and variable (non-conventional or IMAT-NC, a theoretical exercise) dose-rate, to serve as an alternative to helical tomotherapy.

MATERIALS AND METHODS

Six patients with prostate tumours treated by HT with a moderately hypo-fractionated protocol, involving a simultaneous integrated boost, were re-planned as IMAT treatments. A method for IMAT inverse-planning using a commercial module for static IMRT combined with a multi-leaf collimator (MLC) arc-sequencing was developed. IMAT plans were compared to HT plans in terms of dose statistics and radiobiological indices.

RESULTS

Concerning the planning target volume (PTV), the mean doses for all PTVs were similar for HT and IMAT-C plans with minimum dose, target coverage, equivalent uniform dose (EUD) and tumour control probability (TCP) values being generally higher for HT; maximum dose and degree of heterogeneity were instead higher for IMAT-C. In relation to organs at risk, mean doses and normal tissue complication probability (NTCP) values were similar between the two modalities, except for the penile bulb where IMAT was significantly better. Re-normalizing all plans to the same rectal toxicity (NTCP=5%), the HT modality yielded higher TCP than IMAT-C but there was no significant difference between HT and IMAT-NC. The integral dose with HT was higher than that for IMAT.

CONCLUSIONS

with regards to the plan analysis, the HT is superior to IMAT-C in terms of target coverage and dose homogeneity within the PTV. Introducing dose-rate variation during arc-rotation, not deliverable with current linac technology, the simulations result in comparable plan indices between (IMAT-NC) and HT.

Limitations of a TCP model incorporating population heterogeneity

The variation between individuals in their dose-response characteristics complicates attempts to extract estimates of radiobiological parameters (e.g. alpha, beta, etc) from fits to clinical dose-response data. The use of 'population' dose-response models that explicitly account for this variability is necessary to avoid obtaining skewed parameter estimates. In this work, we evaluated an example of a 'population' tumour control probability (TCP) model in terms of its ability to provide reliable parameter estimates. This was accomplished by performing fits of this population model to 'pseudo' data sets, which were generated with Monte Carlo techniques and based on preset values for the various radiobiological parameters. The fitting exercises illustrated considerable correlations between the model parameters. Especially significant was the large correlation observed between the parameter mu=alpha/sigmaalpha used to characterize the level of population heterogeneity in radiosensitivity and the alpha/beta parameter typically used to describe the response to fractionation. The results imply that fits to clinical data may not be able to distinguish between tumours exhibiting a high degree of heterogeneity and a strong beta-mechanism and those containing little heterogeneity and having a weak beta-mechanism. One implication is that basing the design of optimal fractionation regimes on such fitting results may be error-prone. If in vitro assays are to be used to independently determine biologically reasonable ranges for parameter values, an accurate knowledge of the relationship between in vitro and in vivo dose-response characteristics is required.

Radical radiotherapy for prostate cancer

External beam radiotherapy is one of the curative treatment options for localised prostate cancer. This article will describe recent advances in prostate radiotherapy, focussing on the results of randomised trials which have addressed the role of radiation dose escalation and of adjuvant hormone therapy. Current controversies will then be considered, including the merits of radiotherapy in comparison with alternative approaches to early prostate cancer, and the possible role of adjuvant radiation following surgery. Finally, future developments will be described, including hypofractionation and dose individualisation, which have the potential to further improve the outcome of external beam radiotherapy for prostate cancer.

Potential improvements in the therapeutic ratio of prostate cancer irradiation: dose escalation of pathologically identified tumour nodules using intensity modulated radiotherapy

The potential of intensity modulated radiotherapy (IMRT) to improve the therapeutic ratio in prostate cancer by dose escalation of intraprostatic tumour nodules (IPTNs) was investigated using a simultaneous integrated boost technique. The prostate and organs-at-risk were outlined on CT images from six prostate cancer patients. Positions of IPTNs were transferred onto the CT images from prostate maps derived from sequential large block sections of whole prostatectomy specimens. Inverse planned IMRT dose distributions were created to irradiate the prostate to 70 Gy and all the IPTNs to 90 Gy. A second plan was produced to escalate only the dominant IPTN (DIPTN) to 90 Gy, mimicking current imaging techniques. These plans were compared with homogeneous prostate irradiation to 70 Gy using dose-volume histograms, tumour control probability (TCP) and normal tissue complication probability (NTCP) for the rectum. The mean dose to IPTNs was increased from 69.8 Gy to 89.1 Gy if all the IPTNs were dose escalated (p=0.0003). This corresponded to a mean increase in TCP of 8.7-31.2% depending on the alpha/beta ratio of prostate cancer (p<0.001), and a mean increase in rectal NTCP of 3.0% (p<0.001). If only the DIPTN was dose escalated, the TCP was increased by 6.4-27.5% (p<0.003) and the rectal NTCP was increased by 1.8% (p<0.01). In the dose escalated DIPTN IMRT plans, the highest rectal NTCP was seen in patients with IPTNs in the posterior peripheral zone close to the anterior rectal wall, and the lowest NTCP was seen with IPTNs in the lateral peripheral zone. The ratio of increased TCP to NTCP may represent an improvement in the therapeutic ratio, but was dependent on the position of the IPTN relative to the anterior rectal wall. Improvements in prostate imaging and prostate immobilization are required before clinical implementation would be possible. Clinical trials are required to confirm the clinical benefits of these improved dose distributions.

Uncertainties in model-based outcome predictions for treatment planning

PURPOSE

Model-based treatment-plan-specific outcome predictions (such as normal tissue complication probability [NTCP] or the relative reduction in salivary function) are typically presented without reference to underlying uncertainties. We provide a method to assess the reliability of treatment-plan-specific dose-volume outcome model predictions.

METHODS AND MATERIALS

A practical method is proposed for evaluating model prediction based on the original input data together with bootstrap-based estimates of parameter uncertainties. The general framework is applicable to continuous variable predictions (e.g., prediction of long-term salivary function) and dichotomous variable predictions (e.g., tumor control probability [TCP] or NTCP). Using bootstrap resampling, a histogram of the likelihood of alternative parameter values is generated. For a given patient and treatment plan we generate a histogram of alternative model results by computing the model predicted outcome for each parameter set in the bootstrap list. Residual uncertainty ("noise") is accounted for by adding a random component to the computed outcome values. The residual noise distribution is estimated from the original fit between model predictions and patient data.

RESULTS

The method is demonstrated using a continuous-endpoint model to predict long-term salivary function for head-and-neck cancer patients. Histograms represent the probabilities for the level of posttreatment salivary function based on the input clinical data, the salivary function model, and the three-dimensional dose distribution. For some patients there is significant uncertainty in the prediction of xerostomia, whereas for other patients the predictions are expected to be more reliable. In contrast, TCP and NTCP endpoints are dichotomous, and parameter uncertainties should be folded directly into the estimated probabilities, thereby improving the accuracy of the estimates. Using bootstrap parameter estimates, competing treatment plans can be ranked based on the probability that one plan is superior to another. Thus, reliability of plan ranking could also be assessed.

CONCLUSIONS

A comprehensive framework for incorporating uncertainties into treatment-plan-specific outcome predictions is described. Uncertainty histograms for continuous variable endpoint models provide a straightforward method for visual review of the reliability of outcome predictions for each treatment plan.

Partial irradiation of the heart

Radiation-induced heart disease (RIHD) includes pericarditis, ischemic heart disease, and myocardial infarction and leads in some cases to fatal complications. It has been shown that the increased survival due to radiotherapy could be negated by excess deaths from RIHD in breast cancer radiotherapy for left-sided tumors. Subclinical effects following irradiation have been detected in several studies both of breast cancer and Hodgkin's irradiation. The dose-volume response relationships describing cardiac complications have been studied for pericarditis and cardiac mortality by means of biologic models, including the well-known Lyman-Kutcher-Burman (LKB) model and Källman's relative seriality model. Studies by Martel and coworkers on pericarditis and by Gagliardi and coworkers on cardiac mortality are reviewed. The anatomical and functional definition of the heart represents a key issue in modeling, as it affects strongly the dosimetrical data to be used as input data in the models. Several treatment strategies to decrease heart irradiation, based on models and/or based on dose-distribution evaluations, are reviewed. It is concluded that left-sided breast cancer patients should always be 3-dimensional (3D) dose planned.