Dose-volume histograms

A plot of a cumulative dose-volume frequency distribution, commonly known as a dose-volume histogram (DVH), graphically summarizes the simulated radiation distribution within a volume of interest of a patient which would result from a proposed radiation treatment plan. DVHs show promise as tools for comparing rival treatment plans for a specific patient by clearly presenting the uniformity of dose in the target volume and any hot spots in adjacent normal organs or tissues. However, because of the loss of positional information in the volume(s) under consideration, it should not be the sole criterion for plan evaluation. DVHs can also be used as input data to estimate tumor control probability (TCP) and normal tissue complication probability (NTCP). The sensitivity of TCP and NTCP calculations to small changes in the DVH shape points to the need for an accurate method for computing DVHs. We present a discussion of the methodology for generating and plotting the DVHs, some caveats, limitations on their use and the general experience of four hospitals using DVHs.     

Influence of rectal volume changes during radiotherapy for prostate cancer: a predictive model for mild-to-moderate late rectal toxicity

PURPOSE: To assess the rectal volume changes during radiotherapy for prostate cancer, to estimate an average rectal dose distribution profile during treatment, and to correlate these parameters with mild-to-moderate late rectal toxicity. MATERIALS AND METHODS: Nine patients with localized prostate cancer underwent virtual CT simulation using a six-field conformal 18-MV photon technique. During treatment, patients underwent weekly pelvic CT scans under simulation conditions. Dosimetries were run with each CT data set using the same beam parameters as in the initial treatment plan. The influence of weekly rectal volume changes on the dose-volume histogram (DVH) profiles was studied. A polynomial function correlating the initial rectal volume with the mean percentage of change in the rectal volume during treatment was used to define a correction factor for rectal DVHs. The model was validated using data from 100 patients treated with 74 Gy according to the same technique. Areas under the curve of the initial rectal DVHs were correlated with toxicity (Radiation Therapy Oncology Group Grade 0 vs. 1-2, Student's t test), with or without the use of the above correction factor. RESULTS: A trend for enlargement of the rectal volume during treatment was observed for most patients in the study with small rectal volumes (<75 cm(3)) at simulation, resulting in an increase in the integral rectal dose by a factor ranging from 1.3 to 2.1. Corrected, but not uncorrected, rectal DVH profiles were strongly predictive of Grade 0 vs. 1-2 late rectal morbidity. CONCLUSIONS: Correcting the area under the curve of the rectal DVH at simulation by a factor that takes into account the projected volume changes during treatment correlates significantly with the probability of mild-to-moderate late rectal toxicity (Grade 1-2). This reliable predictor for mild-to-moderate late rectal morbidity may also be a practical tool for treatment planning.     

Normal tissue complication probabilities: dependence on choice of biological model and dose-volume histogram reduction scheme

PURPOSE: To evaluate the impact of dose-volume histogram (DVH) reduction schemes and models of normal tissue complication probability (NTCP) on ranking of radiation treatment plans. METHODS AND MATERIALS: Data for liver complications in humans and for spinal cord in rats were used to derive input parameters of four different NTCP models. DVH reduction was performed using two schemes: "effective volume" and "preferred Lyman". DVHs for competing treatment plans were derived from a sample DVH by varying dose uniformity in a high dose region so that the obtained cumulative DVHs intersected. Treatment plans were ranked according to the calculated NTCP values. RESULTS: Whenever the preferred Lyman scheme was used to reduce the DVH, competing plans were indistinguishable as long as the mean dose was constant. The effective volume DVH reduction scheme did allow us to distinguish between these competing treatment plans. However, plan ranking depended on the radiobiological model used and its input parameters. CONCLUSIONS: Dose escalation will be a significant part of radiation treatment planning using new technologies, such as 3-D conformal radiotherapy and tomotherapy. Such dose escalation will depend on how the dose distributions in organs at risk are interpreted in terms of expected complication probabilities. The present study indicates considerable variability in predicted NTCP values because of the methods used for DVH reduction and radiobiological models and their input parameters. Animal studies and collection of standardized clinical data are needed to ascertain the effects of non-uniform dose distributions and to test the validity of the models currently in use.     

Principal component analysis-based pattern analysis of dose-volume histograms and influence on rectal toxicity

PURPOSE: The variability of dose-volume histogram (DVH) shapes in a patient population can be quantified using principal component analysis (PCA). We applied this to rectal DVHs of prostate cancer patients and investigated the correlation of the PCA parameters with late bleeding. METHODS AND MATERIALS: PCA was applied to the rectal wall DVHs of 262 patients, who had been treated with a four-field box, conformal adaptive radiotherapy technique. The correlated changes in the DVH pattern were revealed as "eigenmodes," which were ordered by their importance to represent data set variability. Each DVH is uniquely characterized by its principal components (PCs). The correlation of the first three PCs and chronic rectal bleeding of Grade 2 or greater was investigated with uni- and multivariate logistic regression analyses. RESULTS: Rectal wall DVHs in four-field conformal RT can primarily be represented by the first two or three PCs, which describe approximately 94% or 96% of the DVH shape variability, respectively. The first eigenmode models the total irradiated rectal volume; thus, PC1 correlates to the mean dose. Mode 2 describes the interpatient differences of the relative rectal volume in the two- or four-field overlap region. Mode 3 reveals correlations of volumes with intermediate doses ( approximately 40-45 Gy) and volumes with doses >70 Gy; thus, PC3 is associated with the maximal dose. According to univariate logistic regression analysis, only PC2 correlated significantly with toxicity. However, multivariate logistic regression analysis with the first two or three PCs revealed an increased probability of bleeding for DVHs with more than one large PC. CONCLUSIONS: PCA can reveal the correlation structure of DVHs for a patient population as imposed by the treatment technique and provide information about its relationship to toxicity. It proves useful for augmenting normal tissue complication probability modeling approaches.     

早期非小细胞肺癌立体定向放疗肺剂量预测研究

目的 研究基于机器学习算法的早期非小细胞肺癌立体定向放疗肺剂量预测方法和应用于计划质量控制的可行性。方法 利用机器学习算法实现剂量预测。首先,建立专家计划库,提取计划库中的几何特征信息、照射野角度和剂量体积直方图(DVH)参数,在几何及照射野特征和DVH之间建立相关模型;其次,提取专家库外10例患者的几何和照射野特征信息,利用模型预测可实现的DVH值,并将其与实际计划结果比较。结果 10例患者肺平均剂量和V20外部验证的均方根误差分别为91.95 cGy和3.12%。对肺受量高于预测剂量的2例计划进行修改,修改后肺剂量均有所降低。结论 对非小细胞肺癌患者制定立体定向放疗计划前,可根据相关数学模型提前预测肺DVH曲线作为计划评估标准,从而保证治疗计划的质量。     

早期非小细胞肺癌立体定向放疗肺剂量预测研究

目的 研究基于机器学习算法的早期非小细胞肺癌立体定向放疗肺剂量预测方法和应用于计划质量控制的可行性。方法 利用机器学习算法实现剂量预测。首先,建立专家计划库,提取计划库中的几何特征信息、照射野角度和剂量体积直方图(DVH)参数,在几何及照射野特征和DVH之间建立相关模型;其次,提取专家库外10例患者的几何和照射野特征信息,利用模型预测可实现的DVH值,并将其与实际计划结果比较。结果 10例患者肺平均剂量和V20外部验证的均方根误差分别为91.95 cGy和3.12%。对肺受量高于预测剂量的2例计划进行修改,修改后肺剂量均有所降低。结论 对非小细胞肺癌患者制定立体定向放疗计划前,可根据相关数学模型提前预测肺DVH曲线作为计划评估标准,从而保证治疗计划的质量。     

鼻咽癌IMRT计划腮腺剂量预测模型建立与验证

目的 运用医学数据分析方法,建立鼻咽癌IMRT计划腮腺剂量预测模型并评估其准确性。方法 从鼻咽癌治疗数据库中选取50例相同射野角度的IMRT计划,获取腮腺DVH。自编软件计算腮腺中每个体素点到靶区边缘距离,统计并生成DTH。对DVH和DTH 数据进行主成分分析,并以DVH主成分为因变量,以DTH主成分、腮腺体积和靶区体积为自变量进行多元非线性回归,构建DVH预测模型。选取另外10例鼻咽癌IMRT患者,利用模型对腮腺剂量进行预测,并与原有IMRT计划设计的DVH进行比较以验证预测模型的可靠性和准确性。结果 DTH和DVH数据97%以上信息可以通过2、3个主成分进行表示。构建的腮腺DVH模型平均拟合误差为(0±3.5)%。10例验证病例显示腮腺预测DVH曲线形状与原TPS计划结果高度一致,平均偏差(-0.7±4.4)%,模型预测的准确性高达95%。结论 该模型能有效预测鼻咽癌IMRT计划腮腺剂量分布,可作为评估和验证治疗计划腮腺受量的质量保证工具。     

Organ deformation and dose coverage in robotic respiratory-tracking radiotherapy

PURPOSE: Respiratory motion presents a significant challenge in stereotactic body radiosurgery. Respiratory tracking that follows the translational movement of the internal fiducials minimizes the uncertainties in dose delivery. However, the effect of deformation, defined as any changes in the body and organs relative to the center of fiducials, remains unanswered. This study investigated this problem and a possible solution. METHODS AND MATERIALS: Dose delivery using a robotic respiratory-tracking system was studied with clinical data. Each treatment plan was designed with the computed tomography scan in the end-expiration phase. The planned beams were applied to the computed tomography scan in end-inspiration following the shift of the fiducials. The dose coverage was compared with the initial plan, and the uncertainty due to the deformation was estimated. A necessary margin from the clinical target volume to the planning target volume was determined to account for this and other sources of uncertainty. RESULTS: We studied 12 lung and 5 upper abdomen lesions. Our results demonstrated that for lung patients with properly implanted fiducials a 3-mm margin is required to compensate for the deformation and a 5-mm margin is required to compensate for all uncertainties. Our results for the upper abdomen tumors were still preliminary but indicated a similar result, although a larger margin might be required. CONCLUSION: The effect of body deformation was studied. We found that adequate dose coverage for lung tumors can be ensured with proper fiducial placement and a 5-mm planning target volume margin. This approach is more practical and effective than a recent proposal to combine four-dimensional planning with respiratory tracking.     

前列腺癌碳离子治疗直肠剂量体积直方图预测模型

目的 基于日本经验建立局部效应模型(LEM)下前列腺癌碳离子治疗直肠剂量体积直方图(DVH)预测模型,为临床降低直肠不良反应发生率提供参考。方法 收集局限期前列腺癌患者计划CT图像 76例,采用微剂量动力模型(MKM)进行治疗计划;然后,基于与MKM计划相同的射野,采用LEM重新计算生物剂量获得LEM计划,并在LEM计划中提取直肠几何特征及DVH参数。采用线性回归法对其中 61例计划信息进行建模,余 15例计划用于验证。结果 61例患者计划靶体积沿左右方向外扩1cm后与直肠交叠部分体积同直肠体积比值可作为预测直肠DVH的特征参数。15例患者预测DVH同LEM计划DVH的拟合度优(R²=0.964),基于预测DVH进一步预测直肠不良反应与基于LEM计划DVH预测直肠不良反应的结果一致。结论 线性回归方法可建立较为准确的前列腺癌碳离子治疗直肠DVH预测模型,可能为临床降低直肠不良反应发生率提供一定参考,还有待于临床大样本数据进一步验证。     

Accuracy of volume and DVH parameters determined with different brachytherapy treatment planning systems.

PURPOSE: To determine the uncertainties in dose volume histogram (DVH) analysis used in modern brachytherapy treatment planning systems (TPSs). MATERIALS AND METHODS: A phantom with three different volumes was scanned with CT and MRI. An inter-observer analysis was based on contouring performed by 5 persons. The volume of a standard contour set was calculated using seven different TPSs. For five systems a typical brachytherapy dose distribution was used to compare DVH determination. RESULTS: The inter-observer variability (1SD) was 13% for a small cylindrical volume, 5% for a large cylinder and 3% for a conical shape. A standardized volume for a 4mm CT scan contoured on seven different TPS varied by 7%, 2%, and 5% (1SD). Use of smaller slice thickness reduced the variations. A treatment plan with the sources between the large cylindrical shape and the cone showed variations for D(2cc) of 1% and 5% (1SD), respectively. Deviations larger than 10% were observed for a smaller source to cylinder surface distance of 5mm. CONCLUSIONS: Modern TPSs minimize the volumetric and dosimetric calculation uncertainties. These are comparable to inter-observer contouring variations. However, differences in volume result from the methods of calculation in the first and last slice of a contoured structure. For this situation and in case of high dose gradients inside analyzed volumes, high uncertainties were observed. The use of DVH parameters in clinical practice should take into account the method of calculation and the possible uncertainties.     

Comparison of dose length, area, and volume histograms as quantifiers of urethral dose in prostate brachytherapy

Purpose: To determine the magnitude of the differences between urethral dose-volume, dose-area, and dose-length histograms (DVH, DAH, and DLH, respectively, or DgH generically).

Methods and Materials: Six consecutive iodine-125 (¹²⁵I) patients and 6 consecutive palladium-103 (¹⁰³Pd) patients implanted via a modified uniform planning approach were evaluated with day 0 computed tomography (CT)-based dosimetry. The urethra was identified by the presence of a urinary catheter and was hand drawn on the CT images with a mean radius of 3.3 ± 0.7 mm. A 0.1-mm calculation matrix was employed for the urethral volume and surface analysis, and urethral dose points were placed at the centroid of the urethra on each 5-mm CT slice.

Results: Although individual patient DLHs were step-like, due to the sparseness of the data points, the composite urethral DLH, DAH, and DVHs were qualitatively similar. The DAH curve delivered more radiation than the other two curves at all doses greater than 90% of the prescribed minimum peripheral dose (mPD) to the prostate. In addition, the DVH curve was consistently higher than the DLH curve at most points throughout that range. Differences between the DgH curves were analyzed by integrating the difference curves between 0 and 200% of the mPD. The area-length, area-volume, and volume-length difference curves integrated in the ratio of 3:2:1. The differences were most pronounced near the inflection point of the DgH curves with mean A₁₂₅, V₁₂₅, and L₁₂₅ values of 36.6%, 31.4%, and 23.0%, respectively, of the urethra. Quantifiers of urethral hot spots such as D₁₀, defined as the minimal dose delivered to the hottest 10% of the urethra, followed the same ranking: area analysis indicated the highest dose and length analysis, the lowest dose. D₁₀ was 148% and 136% of mPD for area and length evaluations, respectively. Comparing the two isotopes in terms of the amount of urethra receiving a given dose, ¹⁰³Pd implants were significantly cooler than ¹²⁵I implants over most of the range of clinical interest, from 100% to 150% of mPD.

Conclusion: Dose gradients in prostate implants result in the observed ordering of DAH, DVH, and DLH from higher to lower doses. The three histogram approaches remain in close agreement up to 100% of the mPD but diverge at higher doses. Although urethral point doses are the most easily determined, they underestimate the amount of urethra at risk at higher doses compared to dose area analysis. Because dosimetric parameters detailing high-dose regions such as D₁₀ show only slight differences between calculation methods, they are recommended over the corresponding geometric entities G₁₅₀ or G₁₇₅. The differences between the D_gg entities are sufficiently small that they are unlikely to be of clinical significance or to confound analyses attempting to correlate urinary morbidity with urethral dosimetry.     

Dose-Volume Histograms for bladder and rectum

: A careful examination of the foundation upon which the concept of the Dose-Volume Histogram (DVH) is built, and the implications of this set of parameters on the clinical application and interpretation of the DVH concept has not been conducted since the introduction of DVHs as a tool for the quantitative evaluation of treatment plans. The purpose of the work presented herein is to illustrate problems with current methods of implementing and interpreting DVHs when applied to hollow anatomic structures such as the bladder and rectum.

: A typical treatment plan for external beam irradiation of a patient with prostate cancer was chosen to provide a data set from which DVH curves for both the bladder and rectum were calculated. The two organs share the property of being shells with contents that are of no clinical importance. DVHs for both organs were computed using a solid model and using a shell model. Typical treatment plans for prostate cancer were used to generate DVH curves for both models. The Normal Tissue Complication Probability (NTCP) for these organs is discussed in this context.

: For an eight-field conformal treatment plan of the prostate, a bladder DVH curve generated using the shell model is higher than the corresponding curve generated using the solid model. The shell model also has a higher NTCP. A six-field conformal treatment plan slo results in a higher DVH curve for the shell model. A treatment plan consisting of bilateral 120-degree arcs, results in a higher DVH curve for the shell model, as well as a higher NTCP.

: The DVH concept currently used in evaluation of treatment plans is problematic because current practices of defining exactly what constitutes “bladder” and “rectum.” Commonly used methods of tracing the bladder and rectum imply use of a solid structure model for DVHs. In reality, these organs are shells and the critical structure associated with NTCP is obviously and indisputably the shell, as opposed to its contents. Treatment planning algorithms for DVH computation should thus be modified to utilize the shell model for these organs.     

Treatment planning of intracranial targets on MRI derived substitute CT data

Background

The use of magnetic resonance imaging (MRI) as a complement to computed tomography (CT) in the target definition procedure for radiotherapy is increasing. To eliminate systematic uncertainties due to image registration, a workflow based entirely on MRI may be preferable. In the present pilot study, we investigate dose calculation accuracy for automatically generated substitute CT (s-CT) images of the head based on MRI. We also produce digitally reconstructed radiographs (DRRs) from s-CT data to evaluate the feasibility of patient positioning based on MR images.

Methods and materials

Five patients were included in the study. The dose calculation was performed on CT, s-CT, s-CT data without inhomogeneity correction and bulk density assigned MRI images. Evaluation of the results was performed using point dose and dose volume histogram (DVH) comparisons, and gamma index evaluation.

Results

The results demonstrate that the s-CT images improve the dose calculation accuracy compared to the method of non-inhomogeneity corrected dose calculations (mean improvement 2.0% points) and that it performs almost identically to the method of bulk density assignment. The s-CT based DRRs appear to be adequate for patient positioning of intra-cranial targets, although further investigation is needed on this subject.

Conclusion

The s-CT method is very fast and yields data that can be used for treatment planning without sacrificing accuracy.     

Inclusion of geometrical uncertainties in radiotherapy treatment planning by means of coverage probability

PURPOSE: Following the ICRU-50 recommendations, geometrical uncertainties in tumor position during radiotherapy treatments are generally included in the treatment planning by adding a margin to the clinical target volume (CTV) to yield the planning target volume (PTV). We have developed a method for automatic calculation of this margin. METHODS AND MATERIALS: Geometrical uncertainties of a specific patient group can normally be characterized by the standard deviation of the distribution of systematic deviations in the patient group (Sigma) and by the average standard deviation of the distribution of random deviations (sigma). The CTV of a patient to be planned can be represented in a 3D matrix in the treatment room coordinate system with voxel values one inside and zero outside the CTV. Convolution of this matrix with the appropriate probability distributions for translations and rotations yields a matrix with coverage probabilities (CPs) which is defined as the probability for each point to be covered by the CTV. The PTV can then be chosen as a volume corresponding to a certain iso-probability level. Separate calculations are performed for systematic and random deviations. Iso-probability volumes are selected in such a way that a high percentage of the CTV volume (on average > 99%) receives a high dose (> 95%). The consequences of systematic deviations on the dose distribution in the CTV can be estimated by calculation of dose histograms of the CP matrix for systematic deviations, resulting in a so-called dose probability histogram (DPH). A DPH represents the average dose volume histogram (DVH) for all systematic deviations in the patient group. The consequences of random deviations can be calculated by convolution of the dose distribution with the probability distributions for random deviations. Using the convolved dose matrix in the DPH calculation yields full information about the influence of geometrical uncertainties on the dose in the CTV. RESULTS: The model is demonstrated to be fast and accurate for a prostate, cervix, and lung cancer case. A CTV-to-PTV margin size which ensures at least 95% dose to (on average) 99% of the CTV, appears to be equal to about 2Sigma + 0.7sigma for three all cases. Because rotational deviations are included, the resulting margins can be anisotropic, as shown for the prostate cancer case. CONCLUSION: A method has been developed for calculation of CTV-to-PTV margins based on the assumption that the CTV should be adequately irradiated with a high probability.     

Reporting and analyzing statistical uncertainties in Monte Carlo-based treatment planning

PURPOSE: To investigate methods of reporting and analyzing statistical uncertainties in doses to targets and normal tissues in Monte Carlo (MC)-based treatment planning. METHODS AND MATERIALS: Methods for quantifying statistical uncertainties in dose, such as uncertainty specification to specific dose points, or to volume-based regions, were analyzed in MC-based treatment planning for 5 lung cancer patients. The effect of statistical uncertainties on target and normal tissue dose indices was evaluated. The concept of uncertainty volume histograms for targets and organs at risk was examined, along with its utility, in conjunction with dose volume histograms, in assessing the acceptability of the statistical precision in dose distributions. The uncertainty evaluation tools were extended to four-dimensional planning for application on multiple instances of the patient geometry. All calculations were performed using the Dose Planning Method MC code. RESULTS: For targets, generalized equivalent uniform doses and mean target doses converged at 150 million simulated histories, corresponding to relative uncertainties of less than 2% in the mean target doses. For the normal lung tissue (a volume-effect organ), mean lung dose and normal tissue complication probability converged at 150 million histories despite the large range in the relative organ uncertainty volume histograms. For "serial" normal tissues such as the spinal cord, large fluctuations exist in point dose relative uncertainties. CONCLUSIONS: The tools presented here provide useful means for evaluating statistical precision in MC-based dose distributions. Tradeoffs between uncertainties in doses to targets, volume-effect organs, and "serial" normal tissues must be considered carefully in determining acceptable levels of statistical precision in MC-computed dose distributions.     

Comparison of rectal dose-wall histogram versus dose-volume histogram for modeling the incidence of late rectal bleeding after radiotherapy

PURPOSE: To compare the fits of normal-tissue complication probability (NTCP) models based on rectal dose-wall histograms (DWHs) vs. dose-volume histograms (DVHs) when the two are used to analyze a common set of late rectal toxicity data. METHODS AND MATERIALS: Data were analyzed from 128 prostate cancer patients treated with 3-dimensional conformal radiotherapy (3D-CRT) at The University of Texas M.D. Anderson Cancer Center (UTMDACC). The DVH for total rectal volume, including contents, was obtained for each patient from the treatment-planning system. A DWH was also computed, using the outer rectal contour plus an autogenerated inner contour that corresponds to an assumed 3-mm rectal wall thickness. The endpoint for analysis was Grade 2 or higher late rectal bleeding within 2 years of treatment; all patients had at least 2 years of follow-up. Four different NTCP models were fitted to the response data by using either the DVH or the DWH to describe the dose distribution to rectum or rectal wall, respectively. The 4 models considered were the Lyman model, the mean dose model, the parallel-architecture model, and a model based on the volume of a organ receiving more than a specified dose (the "cutoff-dose" model). RESULTS: For each of the models, the fit to the late rectal bleeding data was slightly improved when the analysis was based on the rectal DWH instead of on the DVH. In addition, the results of the cutoff dose and parallel architecture models were consistent with one another for the DWH data but not for the DVH data. For the DWH data, both models predict a 50% or higher incidence of Grade 2 or worse late rectal bleeding within 2 years if 80% or more of the rectal wall is exposed to doses greater than 32 Gy. A 50% or higher incidence of rectal bleeding is also predicted if the mean dose to rectal wall exceeds 53.2 Gy. CONCLUSIONS: A consistent, although modest, improvement occurs in the fits of NTCP models to the UTMDACC 2-year late rectal bleeding data when the fit is based on the rectal dose-wall histogram instead of on the dose-volume histogram for entire rectum, including contents.     

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.     

The impact of organ motion on intestine doses and complication probabilities in radiotherapy of bladder cancer.

BACKGROUND AND PURPOSE: The intestine is an organ at risk during irradiation of tumours in the abdomen and pelvis, and it is therefore of interest to predict the risk for complications when planning the treatment. However, this organ displays considerable temporal variations in volume and shape. The aim of this investigation was to investigate the uncertainties caused by organ motion in dose-volume histograms (DVHs) and normal-tissue-complication probabilities (NTCP's). PATIENTS AND METHODS: Between 6 and 8 weekly repeat CT scans were acquired for 10 patients with muscle invading urinary bladder cancer. The intestine was delineated in all scans, and the coordinates of the outlines were transferred to the planning CT using the appropriate transformation. Using the actual treatment plan, the DVHs for each of these 6-8 instances of the intestine as well as the corresponding NTCP estimates were calculated. Also, for each patient, a 3D matrix was created that contained the number of scans where the intestine occupied the voxels represented by the elements of the matrix. From this matrix additional information about the organ movements were extracted. RESULTS: The mean values (across scans for individual patients) for the volume receiving at least 30.8 Gy, V30.8, ranged from 77 to 336 cm3, from 52 to 250 cm3 for V49.5 and from 38 to 243 cm3 for V53.5. The corresponding relative standard deviations were 0.45, 0.45, and 0.51, respectively. The relative standard deviations (over repeat scans for each patient) had ranges 0.065-0.45, 0.10-0.53, and 0.10-0.54 and the mean relative deviations were 0.20, 0.24, and 0.26, approximately half the magnitude of the variation between the mean values for the patients. For 6 out of 10 patients, the volume occupied by the intestine in only one of the CT scans was larger than the volume occupied in all CT scans, thus illustrating the very mobile nature of this organ. CONCLUSIONS: The movements of the small intestine cause large uncertainties in the DVH and calculated NTCP for the individual patient, and the usefulness of dose constraints for this organ may be questioned. Still, the inter-patient variation was larger, and it may be that the DVH can be useful for judging which patients have the greatest risk for radiation injury.