A practical evaluation of five dose-volume histogram reduction algorithms

AAPM Task Group Report 267: A joint AAPM GEC-ESTRO report on biophysical models and tools for the planning and evaluation of brachytherapy

Brachytherapy utilizes a multitude of radioactive sources and treatment techniques that often exhibit widely different spatial and temporal dose delivery patterns. Biophysical models, capable of modeling the key interacting effects of dose delivery patterns with the underlying cellular processes of the irradiated tissues, can be a potentially useful tool for elucidating the radiobiological effects of complex brachytherapy dose delivery patterns and for comparing their relative clinical effectiveness. While the biophysical models have been used largely in research settings by experts, it has also been used increasingly by clinical medical physicists over the last two decades. A good understanding of the potentials and limitations of the biophysical models and their intended use is critically important in the widespread use of these models. To facilitate meaningful and consistent use of biophysical models in brachytherapy, Task Group 267 (TG-267) was formed jointly with the American Association of Physics in Medicine (AAPM) and The Groupe Européen de Curiethérapie and the European Society for Radiotherapy & Oncology (GEC-ESTRO) to review the existing biophysical models, model parameters, and their use in selected brachytherapy modalities and to develop practice guidelines for clinical medical physicists regarding the selection, use, and interpretation of biophysical models. The report provides an overview of the clinical background and the rationale for the development of biophysical models in radiation oncology and, particularly, in brachytherapy; a summary of the results of literature review of the existing biophysical models that have been used in brachytherapy; a focused discussion of the applications of relevant biophysical models for five selected brachytherapy modalities; and the task group recommendations on the use, reporting, and implementation of biophysical models for brachytherapy treatment planning and evaluation. The report concludes with discussions on the challenges and opportunities in using biophysical models for brachytherapy and with an outlook for future developments.

Dosimetric predictors and Lyman normal tissue complication probability model of hematological toxicity in cervical cancer patients with treated with pelvic irradiation

PURPOSE

To identify dosimetric parameters associated with acute hematological toxicity (HT) and identify the corresponding normal tissue complication probability (NTCP) model in cervical cancer patients receiving helical tomotherapy (Tomo) or fixed-field intensity-modulated radiation therapy (ff-IMRT) in combination with chemotherapy, that is, concurrent chemoradiotherapy (CCRT) using the Lyman-Kutcher-Burman normal tissue complication probability (LKB-NTCP) model.

METHODS

Data were collected from 232 cervical cancer patients who received Tomo or ff-IMRT from 2015 to 2018. The pelvic bone marrow (PBM) (including the ilium, pubes, ischia, acetabula, proximal femora, and lumbosacral spine) was contoured from the superior boundary (usually the lumbar 5 vertebra) of the planning target volume (PTV) to the proximal end of the femoral head (the lower edge of the ischial tubercle). The parameters of the LKB model predicting ≥grade 2 hematological toxicity (Radiation Therapy Oncology Group [RTOG] grading criteria) (TD50 (1), m, and n) were determined using maximum likelihood analyses. Univariate and multivariate logistic regression analyses were used to identify correlations between dose-volume parameters and the clinical factors of HT.

RESULTS

In total, 212 (91.37%) patients experienced ≥grade 2 hematological toxicity. The fitted normal tissue complication probability model parameters were TD50 (1) = 38.90 Gy (95%CI, [36.94, 40.96]), m = 0.13 (95%CI [0.12, 0.16]), and n = 0.04 (95%CI [0.02, 0.05]). Per the univariate analysis, the NTCP (the use of LKB-NTCP with the set of model parameters found, p = 0.023), maximal PBM dose (p = 0.01), mean PBM dose (p = 0.021), radiation dose (p = 0.001), and V16-53 (p < 0. 05) were associated with ≥grade 2 HT. The NTCP (the use of LKB-NTCP with the set of model parameters found, p = 0.023; AUC = 0.87), V16, V17, and V18 ≥ 79.65%, 75.68%, and 72.65%, respectively (p < 0.01, AUC = 0.66∼0.68), V35 and V36 ≥ 30.35% and 28.56%, respectively (p < 0.05; AUC = 0.71), and V47 ≥ 13.43% (p = 0.045; AUC = 0.80) were significant predictors of ≥grade 2 hematological toxicity from the multivariate logistic regression analysis.

CONCLUSIONS

The volume of the PBM of patients treated with concurrent chemoradiotherapy and subjected to both low-dose (V16-18 ) and high-dose (V35,36 and V47 ) irradiation was associated with hematological toxicity, depending on the fractional volumes receiving the variable degree of dosage. The NTCP were stronger predictors of toxicity than V16-18 , V35, 36 , and V47 . Hence, avoiding radiation hot spots on the PBM could reduce the incidence of severe HT.

Methods to calculate normal tissue complication and tumour control probabilities for fractionated inhomogeneous dose distribution of intensity-modulated radiation therapy

Objectives: This study is designed to present and evaluate radiobiological-based dose–volume histogram (DVH) reduction schemes to calculate normal tissue complication probability (NTCP) and tumour control probability (TCP) for intensity-modulated radiation therapy (IMRT).

Methods: The proposed DVH reduction schemes were derived for 2 Gy per fraction and prescribed dose per fraction for critical organs and tumours, respectively. Sample computed tomography scans were used to generate two IMRT plans to deliver 54 Gy to PTV1 and 24 Gy to PTV2 via sequential IMRT boost (SqIB) and simultaneous integrated IMRT boost (SIB) plans. Differential DVHs were used to calculate effective volumes using published values of related parameters of critical organs and prostate.

Results: NTCP values for bladder were almost zero for both IMRT plans. The plots between k and NTCP for rectum and femurs (k = 0.1–1.0) show higher NTCP for SqIB than that for SIB. The TCP decreases with increasing clonogenic cell density and is higher for SIB than that for SqIB for all clonogenic cell densities. The value of α proposed by Brenner and Hall shows very low radio sensitivity of clonogens of the prostate, which gives very low TCP for conventional doses of 70–80 Gy delivered in 7–8 weeks, even for very low clonogenic cell density in the prostate.

Conclusion: The presented DVH reduction schemes have radiobiological bearing and therefore seem to be effective in calculating fairly accurate NTCP and TCP.

A modelling study of the potential influence of low dose hypersensitivity on radiation treatment planning

BACKGROUND AND PURPOSE

Low dose hyper-radiosensitivity (HRS) has been observed in both normal tissues and tumours. This modelling study explores the possible impact of HRS on radiation treatment planning.

PATIENTS AND METHODS

The interplay between volume-effect and HRS was studied in an idealized comparison of partial versus whole organ irradiation. In the further studies, CT scans of three previously scanned patients were used to estimate normal tissue complication probability (NTCP) for the kidneys after a conformal and a conventional treatment plan with and without consideration of HRS.

RESULTS

Idealized treatment plans were compared as pairs of a conventional and a conformal plan both treating the same target volume to the same dose per fraction. Contour maps of the difference in NTCP between paired plans showed a strong dependence on the magnitude of both the volume effect and the HRS effect. For more clinically realistic treatment plans with NTCP calculated for the kidney, the balance between the sparing due to the LQ effect and the increased sensitivity due to the HRS effect was dependent on both the dose distribution and the fractionation.

CONCLUSIONS

HRS may potentially affect radiotherapy treatment planning and the relative importance of HRS is larger in a tissue or organ with a pronounced volume effect. If HRS is expressed in some normal tissues or organs, this could offset much of the sparing predicted by the LQ formalism. However, in some clinical situations the NTCP calculated with correction for HRS may still be lower than the NTCP calculated from the uncorrected physical doses.

Volumetric Uncertainty in Radiotherapy

The technologies available to identify anatomical structures (including radiotherapy target and normal tissue 'volumes'), and to deliver dose accurately to these volumes, have improved significantly in the past decade. However, the ability of clinicians to identify volumes accurately and consistently in patients still suffers from uncertainties that arise from human error, inadequate training, lack of consensus on the derivation of volumes and inadequate characterisation of the accuracy and specificity of imaging technologies. Inadequate volume definition of a target can result in treatment failure and, consequently, disease progression; excessive volume may also lead to unnecessary patient injury. This is a serious problem in routine clinical care. In the context of large multi-centre clinical trials, uncertainty and inconsistency in tissue-volume reporting will be carried through to the analysis of treatment effect on outcome, which will subsequently influence the treatment of future patients. Strategies need to be set in place to ensure that the abilities and consistency of clinicians in defining volumes are aligned with the ability of new technologies to present volumetric information. This review seeks to define the concept of volumetric uncertainty and propose a conceptual model that has these errors evaluated and responded to separately. Specifically, we will explore the major causes, consequences of, and possible remediation of volumetric uncertainty, from the point of view of a multidisciplinary radiotherapy clinical environment.

Variation in the probability of cardiac complications with radiation technique in early breast cancer

Cardiac damage is recognized to be a potentially serious side effect of breast cancer radiotherapy, the risk of which may be reduced by the choice of appropriate radiotherapy technique. We have previously described variation in physical dose to the heart dependent upon radiotherapy technique. In this paper we report the calculated improvement in normal tissue complication probability (NTCP) (for cardiac damage) achievable by these methods. Cardiac doses were calculated from dose-volume histograms (DVHs) using a "Helax" planning system for 11 patients with left-sided tumours and 5 patients with right-sided tumours. The DVH reduction algorithm of Lyman and Wolbarst [1989] was applied to each DVH to produce a value for the NTCP. For left-sided tumours, mean NTCP with the standard technique was 7.4 +/- 5.6% (range 0.6-17%) and for the optimum technique mean NTCP was 0.3 +/- 0.6% (range 0-2%) (p < 0.003 for the difference between the two techniques): a predicted reduction in late cardiac complications of 23-fold, which is not clearly evident from viewing the DVH raw data.

High-dose-rate brachytherapy may be radiobiologically superior to low-dose rate due to slow repair of late-responding normal tissue cells

BACKGROUND AND PURPOSE

Recent analysis of morbidity for patients treated with the continuous hyperfractionated accelerated radiotherapy (CHART) regimen demonstrates that repair half-times for late-reacting normal tissue cells are of the order of 4-5 h, which is considerably longer than previously believed. This would reduce repair of these tissue cells during a course of low-dose rate (LDR) brachytherapy, but have no effect at high-dose-rate (HDR), where there is no repair during, and full repair between fractions, regardless of repair half-time. The effect this has upon radiobiologic comparison of LDR and HDR is the topic of this paper.

METHODS AND MATERIALS

The linear-quadratic (L-Q) model is used to compare late-effect biologically effective doses (BEDs) of LDR and HDR, for constant BED (tumor). The effects of dose rate (for LDR), fractionation (for HDR), and geometrical sparing of normal tissues are all considered. Repair half-times observed in the CHART study are used to investigate the potential impact of long repair times on the comparison of LDR and HDR.

RESULTS

It is demonstrated that, for a repair half-time of 1.5 h for tumor cells, if the half-time for repair of late-reacting normal tissue cells exceeds about 2.5 h, LDR becomes radiobiologically inferior to HDR. Even with the least HDR-favorable combinations of parameters, HDR at over about 5 Gy/fraction ought to be radiobiologically superior to LDR at 0.5 Gy/h, so long as the time between HDR fractions is long compared to the repair half time. It is also shown that any geometrical sparing of normal tissues will benefit HDR more than LDR.

CONCLUSION

The previously held belief that LDR must be inherently superior radiobiologically to HDR is wrong if the long repair times demonstrated in the recent CHART study are applicable to other late-reacting normal tissues. This could explain why HDR has been so successful in clinical practice, especially for the treatment of cervical cancer, despite previous convictions of radiobiologic inferiority of this modality.

Comparative analysis of dose volume histogram reduction algorithms for normal tissue complication probability calculations

A model for estimating radiotherapy treatment outcome through the probability of damage to normal tissue and the probability of tumour control is a useful tool for treatment plan optimization, dose escalation strategies and other currently used procedures in radiation oncology. Normal tissue complication estimation (NTCP) is here analysed from the point of view of the reliability and internal consistency of the most popular model. Five different dose volume histogram (DVH) reduction algorithms, applied to the Lyman model for NTCP calculation. were analysed and compared. The study was carried out for sets of parameters corresponding to quite different expected dose-response relationships. In particular, we discussed the dependence of the models on the parameters and on the dose bin size in the DVH. The sensitivity of the different reduction schemes to dose inhomogeneities was analysed, using a set of simple DVHs representing typical situations of radiation therapy routine. Significant differences were substantiated between the various reduction methods regarding the sensitivity to the degree of irradiation homogeneity, to the model parameters and to the dose bin size. Structural aspects of the reduction formalism allowed an explanation for these differences. This work shows that DVH reduction for NTCP calculation has still to be considered as a very delicate field and used with extreme care, especially for clinical applications, at least until the actual formulations are tuned against strong clinical data.

Treatment plan comparison using equivalent uniform biologically effective dose (EUBED)

With the continuing improvement in computer speed, dose distributions can be calculated quickly with confidence. However, the resulting biological effect is known with much less certainty, despite its critical importance when assessing treatment plans. To assess plans accurately, biologically based methods of ranking plans are necessary. Many authors have suggested the use of dose volume histograms with reduction schemes and Niemierko has recently introduced another method based on the cell kill occurring in the tumour. This study presents an investigation into this value and suggests a use in prescribing dose. Equivalent uniform dose (EUD) can obviously be used for assessing treatment plans, although in its current form it is not adequate for assessing normal tissues; however, it can also be used to adjust the prescription dose ensuring all plans deliver the same EUD to the tumour. Once this is performed, plans can more easily be assessed on the effects to the normal tissues. In calculating the EUD another concept is introduced--the equivalent uniform biologically effective dose (EUBED). This value considers the distribution of dose and dose per fraction when comparing plans. Reduced dose per fraction at the edge of the target volume will exacerbate the effect of reduced dose on cell kill. Two methods are suggested for calculating the necessary prescription dose: one using an iterative method and one using the gradient of the EUBED function. A comparison was made for a series of stereotactic cases using different collimator sizes. Interestingly, using this method, although the maximum doses were different, the dose volume histograms (DVHs) for the brainstem were similar in all cases.

Evaluation of two dose-volume histogram reduction models for the prediction of radiation pneumonitis

PURPOSE

To evaluate the similarities between the mean lung dose and two dose-volume histogram (DVH) reduction techniques of 3D dose distributions of the lung.

PATIENTS AND METHODS

DVHs of the lungs were calculated from 3D dose distributions of patients treated for malignant lymphoma (44), breast cancer (42) and lung cancer (20). With a DVH reduction technique, a DVH is summarized by the equivalent uniform dose (EUD), a quantity which is directly related to the normal tissue complication probability (NTCP). Two DVH reduction techniques were used. The first was based on an empirical model proposed by Kutcher et al. (Kutcher, G.J., Burman, C., Brewster, M.S., Goitein, M. and Mohan, R. Histogram reduction method for calculating complication probabilities for three-dimensional treatment planning evaluations. Int. J. Radiat. Oncol. Biol. Phys. 21: 137-146, 1991), which needs a volume exponent n. Several values for n were tested. The second technique was based on a radiobiological model, the parallel functional subunit model developed by Niemierko et al. (Niemierko, A. and Goitein, M. Modeling of normal tissue response to radiation: the critical volume model. Int. J. Radiat. Oncol. Biol. Phys. 25: 135-145, 1993) and Jackson et al. (Jackson, A., Kutcher, G.J. and Yorke, E.D. Probability of radiation-induced complications for normal tissues with parallel architecture subject to non-uniform irradiation. Med. Phys. 20: 613-625, 1993), for which a local dose-effect relation needed to be specified. This relation was obtained from an analysis of perfusion and ventilation SPECT data.

RESULTS

It can be shown analytically that the two DVH reduction techniques are identical, if the local dose-effect relation obeys a power-law relationship in the clinical dose range. Local dose-effect relations based on perfusion and ventilation SPECT data can indeed be fitted with a power-law relationship in the range 0-80 Gy, from which values of n = 0.8-0.9 were deduced. These correspond to the commonly used value of n = 0.87 for lung tissue and yielded EUDn=0.87 values which were almost identical to the mean lung doses. For other n values, for which no experimental data are present, differences exist between EUD and mean dose values. Six patients with malignant lymphoma (6/44) and none of the breast cancer patients (0/42) developed radiation pneumonitis. These cases occurred only at high values for the mean lung dose.

CONCLUSION

The two DVH reduction techniques are identical for lung and are very similar to mean dose calculations. The two techniques are also relatively similar for other model parameter values.

Selection of coplanar or noncoplanar beams using three-dimensional optimization based on maximum beam separation and minimized nontarget irradiation

PURPOSE

The design of an appropriate set of multiple fixed fields to achieve a steep dose gradient at the tumor edge, with minimal normal tissue exposure, is a very difficult problem, since a virtually infinite number of possible beam orientations exists. In practice we have selected beams in an iterative and often time-consuming process. This work proposes an optimization method, based on geometric and dose elements, to effectively arrive at a set of beam orientations.

METHODS AND MATERIALS

Beams are selected by minimizing a goal function including an angle function (beam separation for steep dose gradient at target edge) and a length function (related to normal tissue dose volume histogram). The relative importance of these two factors may be adjusted depending on the clinic situation. The model is flexible and can include case specific practical anatomic and physical considerations.

RESULTS

In extremely simple situations, the goal function yields results consistent with well-known analytical solutions. When applied to more complex clinical situations, it provides clinically reasonable solutions similar to those empirically developed by the clinician. The optimization process takes approximately 25 min on a UNIX workstation.

CONCLUSION

The optimization scheme provides a practical means for rapidly designing multiple field coplanar or noncoplanar treatments. It overcomes limitations in human three-dimensional visualization such as trying to visualize beam directions and keeping track of the hinge angle between beams while accounting for anatomic/machine constraints. In practice, it has been used as a starting point for physicians to make modifications, based on their clinical judgment.