[en] Purpose: To determine, in 3-D, the difference between prostate delineation in MRI or CT for radiotherapy treatment planning. Patients and Methods: Eighteen patients with localized prostate cancer were scanned by means of CT and axial, coronal, and (in seven cases) sagittal MRI. The MRI scans were matched in 3-D on the planning CT using chamfer matching. Three observers outlined the prostate (i.e. no seminal vesicles) in all scans. No observer had knowledge of the contours outlined by the other observers. The volumes were measured and, to quantify differences related to the scan modality, the observer encompassing volume (i.e. the smallest volume encompassing all the volumes outlined by one observer in all scans for that patient) and the observer common volume (i.e. the largest volume common to all the volumes outlined by one observer in all scans for that patient) were determined. Likewise, the observer variation was calculated by determining the scan encompassing and common volume. The spatial difference between CT and MRI and the interobserver variation in a scan were quantified three-dimensionally, by the difference and variation in the distance between the center of gravity and the edge of the delineated prostate in each direction phi and θ (polar coordinates). Results: Inter-scan variation: CT volumes were larger than the axial MRI volumes in 52 out of 54 outlined volumes. The average ratio between these volumes was 1.4, significantly different from 1 (p<0.005). Only small differences were observed between the volumes of the various MRI scans although the coronal MRI was smallest. A large ratio (compared to 1.4) was found between observer encompassing and observer common volume (2.3, 2.5 and 2.6 for each observer), mostly due to variation in location of the MRI volumes. Furthermore, CT derived volumes never entirely encompassed the MRI volumes (Fig. 1). The average distance between CT and axial MRI is shown in Fig. 1, the CT derived contours extended on average 7.5 mm. (SD: 2 mm.) further from the center than the axial MRI at the base of the seminal vesicles (Fig. 1). The apex was located 6.5 mm. (SD: 3 mm.) more superior than on CT. Similar maps could be obtained for the other MRI scans. Inter-observer variation: The average ratio between the volume derived by one observer for a particular scan and patient and the average volume were 0.95, 0.97 and 1.08 (SD: 0.1). The ratio between scan encompassing and common volume was 1.5 and similar for all imaging modalities and directions (SD: 0.2-0.4). From a similar map, as presented in Fig. 1, it could be concluded that the spatial inter-observer variation for CT and axial MRI was similar in both scans and located mainly at the base of the seminal vesicles (max. SD in this area: 2.6 mm.). At the apex the inter-observer variation was less, SD: 2.1 mm. Conclusions: CT derived prostate volumes are larger than MRI derived volumes; this difference is mainly located at the apex and at the base of the seminal vesicles. The inter-observer variation is similar in all directions and both imaging modalities. The inter-scan variation is larger than the inter-observer variation, consequently the prostate GTV is more dependent on the scan modality than on the observer

[en] Purpose: To evaluate the ability of MRI during intracavitary brachytherapy to visualize the tumor extension in relationship to the intracavitary applicator and to compare the actual dose distribution in the Gross Tumor Volume (GTV) as identified on the MRI with the prescribed dose in 'Manchester' point A. Methods and Materials: In 7 patients with cervical cancer stage Ib (n = 2) and IIb (n = 5), both CT and MRI were performed during intracavitary brachytherapy, using a CT-MRI compatible gynaecological applicator. The GTV was drawn on the MRI and subsequently matched in 3-D with the CT-scan using chamfer matching. Isodose distributions were calculated and displayed on the CT-scan. Dose-volume histograms of GTVs as identified on the MRI were obtained and compared with the prescribed dose in point A. Results: Although delineation of the macroscopic tumor on the MRI was possible in all 7 patients, the tumor was better visible in the 2 patients who had brachytherapy after 10 Gy external radiation than in the 5 patients who had brachytherapy after 46 Gy. The GTV varied from 8 cm³ to 44 cm³ with a mean of 22 cm³. In all 7 cases the 'treated volume' (volume encompassed by the reference isodose surface) was considerably larger than the GTV ranging from 95 cm³ to 122 cm³ with a mean of 101 cm³. However, only in 3 patients the reference isodose surface fully covered the GTV. The minimum tumor dose in these patients was 100%, 131% and 136% of the reference dose in point A. In the other 4 patients the percentage of the GTV receiving a dose equal to or higher than the reference dose was 58%, 91%, 98% and 98%. The minimum dose in the GTV in these patients was 44%, 49%, 85% and 91% of the prescribed dose respectively. Conclusion: Using a CT-MRI compatible applicator artefact-free MR images can be obtained during intracavitary brachytherapy allowing good visualization of the tumor. In many patients there is a large discrepancy between the prescribed dose in point A and the actual dose in the GTV as identified on MRI. On average the 'treated volume' is about 5 times as large as the GTV. Work to further evaluate MRI as a tool to optimize and individualize the treatment is ongoing

[en] Aim: This communication reviews the planning strategies and dose statistics of nine IMRT plans generated for a complex head and neck case. Patient and method: An ethmoid sinus cancer case was sent as an IMRT planning task to all participants of the ESTRO course on 'IMRT and Other Conformal Techniques in Practice', held in Amsterdam in June 2001. Results: Nine IMRT plans were generated for the case, the majority of the plans generated with commercial planning systems. The number of beam incidences ranged between four and eleven, while five of the nine beam setups were coplanar. The planning target volume dose homogeneity was inversely correlated with the degree of sparing of the surrounding organs at risk. Conclusion: IMRT strategies for complex head and neck cases, such as ethmoid sinus cancer, can be striklingly different in various aspects, such as beam setup, total number of segments, PTV dose coverage and dose statistics for organs at risks. (orig.)

[en] The objective of this study was to evaluate the impact of matched CT and MRI information on target delineation in radiotherapy planning for head and neck tumors. MRI images of eight patients with head and neck cancer in supine position, not necessarily obtained in radiotherapy treatment position were matched to the CT scans made in radiotherapy position using automatic three-dimensional chamfer-matching of bony structures. Four independent observers delineated the Gross Tumor Volume (GTV) in CT scans and axial and sagittal MR scans. The GTV's were compared, overlapping volumes and non-overlapping volumes between the different datasets and observers were determined. In all patients a good match of CT and MRI information was accomplished in the head region. The combined information provided a better visualisation of the GTV, oedema and normal tissues compared with CT or MRI alone. Determination of overlapping and non-overlapping volumes proved to be a valuable tool to measure uncertainties in the determination of the GTV. CT-MRI matching in patients with head and neck tumors is feasible and makes a more accurate irradiation with higher tumor doses and less normal tissue complications possible. Remaining uncertainties in the determination of the GTV can be quantified using the combined information of MRI and CT

[en] Despite immobilization of head and neck (H and N) cancer patients, considerable posture changes occur over the course of radiotherapy (RT). To account for the posture changes, we previously implemented a multiple regions of interest (mROIs) registration system tailored to the H and N region for image-guided RT correction strategies. This paper is focused on the automatic segmentation of the ROIs in the H and N region. We developed a fast and robust automatic detection system suitable for an online image-guided application and quantified its performance. The system was developed to segment nine high contrast structures from the planning CT including cervical vertebrae, mandible, hyoid, manubrium of sternum, larynx and occipital bone. It generates nine 3D rectangular-shaped ROIs and informs the user in case of ambiguities. Two observers evaluated the robustness of the segmentation on 188 H and N cancer patients. Bland–Altman analysis was applied to a sub-group of 50 patients to compare the registration results using only the automatically generated ROIs and those manually set by two independent experts. Finally the time performance and workload were evaluated. Automatic detection of individual anatomical ROIs had a success rate of 97%/53% with/without user notifications respectively. Following the notifications, for 38% of the patients one or more structures were manually adjusted. The processing time was on average 5 s. The limits of agreement between the local registrations of manually and automatically set ROIs was comprised between ±1.4 mm, except for the manubrium of sternum (−1.71 mm and 1.67 mm), and were similar to the limits agreement between the two experts. The workload to place the nine ROIs was reduced from 141 s (±20 s) by the manual procedure to 59 s (±17 s) using the automatic method. An efficient detection system to segment multiple ROIs was developed for Cone-Beam CT image-guided applications in the H and N region and is clinically implemented in our department. (paper)

[en] In 3-dimensional (3D) conformal radiotherapy of parotid gland tumors, little effort is made to avoid the auditory system or the oral cavity. Damage may occur when the ear is located inside the treatment field. The purpose of this study was to design and evaluate an intensity-modulation radiotherapy (IMRT) class solution, and to compare this technique to a 3D conformal approach with respect to hearing loss. Twenty patients with parotid gland cancer were retrospectively planned with 2 different techniques using the original planning target volume (PTV). First, a conventional technique using a wedged beam pair was applied, yielding a dose distribution conformal to the shape of the PTV. Next, an IMRT technique using a fluence map optimization with predefined constraints was designed. A dose of 66 Gy in the PTV was given at the International Commission on Radiation Units and Measures (ICRU) dose prescription point. Dose-volume histograms of the PTV and organs at risk (OARs), such as auditory system, oral cavity, and spinal cord, were compared. The dose in the OARs was lower in the IMRT plans. The mean volume of the middle ear receiving a dose higher than 50 Gy decreased from 66.5% to 33.4%. The mean dose in the oral cavity decreased from 19.4 Gy to 16.6 Gy. The auditory system can be spared if the distance between the inner ear and the PTV is 0.6 cm or larger, and if the overlap between the middle ear and the PTV is smaller than 10%. The maximum dose in the spinal cord was below 40 Gy in all treatment plans. The mean volume of the PTV receiving less than 95% of the prescribed dose increased in the IMRT plan slightly from 3.3% to 4.3 % (p = 0.01). The mean volume receiving more than 107% increased from 0.9% to 2.5% (p = 0.02). It can be concluded that the auditory system, as well as the oral cavity, can be spared with IMRT, but at the cost of a slightly larger dose inhomogeneity in the PTV. The IMRT technique can therefore, in most cases, be recommended as the treatment of choice for the irradiation of parotid tumors

[en] The Pareto front reflects the optimal trade-offs between conflicting objectives and can be used to quantify the effect of different beam configurations on plan robustness and dose-volume histogram parameters. Therefore, our aim was to develop and implement a method to automatically approach the Pareto front in robust intensity-modulated proton therapy (IMPT) planning. Additionally, clinically relevant Pareto fronts based on different beam configurations will be derived and compared to enable beam configuration selection in cervical cancer proton therapy. A method to iteratively approach the Pareto front by automatically generating robustly optimized IMPT plans was developed. To verify plan quality, IMPT plans were evaluated on robustness by simulating range and position errors and recalculating the dose. For five retrospectively selected cervical cancer patients, this method was applied for IMPT plans with three different beam configurations using two, three and four beams. 3D Pareto fronts were optimized on target coverage (CTV D_9_9_%) and OAR doses (rectum V_3_0_G_y; bladder V_4_0_G_y). Per patient, proportions of non-approved IMPT plans were determined and differences between patient-specific Pareto fronts were quantified in terms of CTV D_9_9_%, rectum V_3_0_G_y and bladder V_4_0_G_y to perform beam configuration selection. Per patient and beam configuration, Pareto fronts were successfully sampled based on 200 IMPT plans of which on average 29% were non-approved plans. In all patients, IMPT plans based on the 2-beam set-up were completely dominated by plans with the 3-beam and 4-beam configuration. Compared to the 3-beam set-up, the 4-beam set-up increased the median CTV D_9_9_% on average by 0.2 Gy and decreased the median rectum V_3_0_G_y and median bladder V_4_0_G_y on average by 3.6% and 1.3%, respectively. This study demonstrates a method to automatically derive Pareto fronts in robust IMPT planning. For all patients, the defined four-beam configuration was found optimal in terms of plan robustness, target coverage and OAR sparing. (paper)

[en] Setup and range uncertainties compromise radiotherapy plan robustness. We introduce a method to evaluate the clinical effect of these uncertainties on the population using tumor control probability (TCP) and normal tissue complication probability (NTCP) models.

Eighteen oropharyngeal cancer patients treated with curative intent were retrospectively included. Both photon (VMAT) and proton (IMPT) plans were created using a planning target volume as planning objective. Plans were recalculated for uncertainty scenarios: two for range over/undershoot (IMPT) or CT-density scaling (VMAT), six for shifts. An average shift scenario () was calculated to assess random errors. Dose differences between nominal and scenarios were translated to TCP (2 models) and NTCP (15 models). A weighted average (W_Avg) of the TCP/NTCP based on Gaussian distribution over the variance scenarios was calculated to assess the clinical effect of systematic errors on the population.

TCP/NTCP uncertainties were larger in IMPT compared to VMAT. Although individual perturbations showed risks of plan deterioration, the scenario did not show a substantial decrease in any of the TCP endpoints suggesting evaluated plans in this cohort were robust for random errors. Evaluation of the W_Avg scenario to assess systematic errors showed in VMAT no substantial decrease in TCP endpoints and in IMPT a limited decrease. In IMPT, the W_Avg scenario had a mean TCP loss of 0%–2% depending on plan type and primary or nodal control. The W_Avg for NTCP endpoints was around 0%, except for mandible necrosis in IMPT (W_Avg: 3%).

The estimated population impact of setup and range uncertainties on TCP/NTCP following VMAT or IMPT of oropharyngeal cancer patients was small for both treatment modalities. The use of TCP/NTCP models allows for clinical interpretation of the population effect and could be considered for incorporation in robust evaluation methods.

Highlights:

– TCP/NTCP models allow for a clinical evaluation of uncertainty scenarios.

– For this cohort, in silico-PTV based IMPT plans and VMAT plans were robust for random setup errors.

– Effect of systematic errors on the population was limited: mean TCP loss was 0%–2%. (paper)

[en] Purpose: The aim of this study is to develop and validate a generic method for automatic bladder segmentation on cone beam computed tomography (CBCT), independent of gender and treatment position (prone or supine), using only pretreatment imaging data. Methods: Data of 20 patients, treated for tumors in the pelvic region with the entire bladder visible on CT and CBCT, were divided into four equally sized groups based on gender and treatment position. The full and empty bladder contour, that can be acquired with pretreatment CT imaging, were used to generate a patient-specific bladder shape model. This model was used to guide the segmentation process on CBCT. To obtain the bladder segmentation, the reference bladder contour was deformed iteratively by maximizing the cross-correlation between directional grey value gradients over the reference and CBCT bladder edge. To overcome incorrect segmentations caused by CBCT image artifacts, automatic adaptations were implemented. Moreover, locally incorrect segmentations could be adapted manually. After each adapted segmentation, the bladder shape model was expanded and new shape patterns were calculated for following segmentations. All available CBCTs were used to validate the segmentation algorithm. The bladder segmentations were validated by comparison with the manual delineations and the segmentation performance was quantified using the Dice similarity coefficient (DSC), surface distance error (SDE) and SD of contour-to-contour distances. Also, bladder volumes obtained by manual delineations and segmentations were compared using a Bland-Altman error analysis. Results: The mean DSC, mean SDE, and mean SD of contour-to-contour distances between segmentations and manual delineations were 0.87, 0.27 cm and 0.22 cm (female, prone), 0.85, 0.28 cm and 0.22 cm (female, supine), 0.89, 0.21 cm and 0.17 cm (male, supine) and 0.88, 0.23 cm and 0.17 cm (male, prone), respectively. Manual local adaptations improved the segmentation results significantly (p < 0.01) based on DSC (6.72%) and SD of contour-to-contour distances (0.08 cm) and decreased the 95% confidence intervals of the bladder volume differences. Moreover, expanding the shape model improved the segmentation results significantly (p < 0.01) based on DSC and SD of contour-to-contour distances. Conclusions: This patient-specific shape model based automatic bladder segmentation method on CBCT is accurate and generic. Our segmentation method only needs two pretreatment imaging data sets as prior knowledge, is independent of patient gender and patient treatment position and has the possibility to manually adapt the segmentation locally

[en] To study radiotherapy-related adverse effects, detailed dose information (3D distribution) is needed for accurate dose-effect modeling. For childhood cancer survivors who underwent radiotherapy in the pre-CT era, only 2D radiographs were acquired, thus 3D dose distributions must be reconstructed from limited information. State-of-the-art methods achieve this by using 3D surrogate anatomies. These can however lack personalization and lead to coarse reconstructions. We present and validate a surrogate-free dose reconstruction method based on Machine Learning (ML). Abdominal planning CTs (n = 142) of recently-treated childhood cancer patients were gathered, their organs at risk were segmented, and 300 artificial Wilms’ tumor plans were sampled automatically. Each artificial plan was automatically emulated on the 142 CTs, resulting in 42,600 3D dose distributions from which dose-volume metrics were derived. Anatomical features were extracted from digitally reconstructed radiographs simulated from the CTs to resemble historical radiographs. Further, patient and radiotherapy plan features typically available from historical treatment records were collected. An evolutionary ML algorithm was then used to link features to dose-volume metrics. Besides 5-fold cross validation, a further evaluation was done on an independent dataset of five CTs each associated with two clinical plans. Cross-validation resulted in mean absolute errors ≤ 0.6 Gy for organs completely inside or outside the field. For organs positioned at the edge of the field, mean absolute errors ≤ 1.7 Gy for $D_{\mathrm{m}\mathrm{e}\mathrm{a}\mathrm{n}}$, ≤ 2.9 Gy for $D_{2\mathrm{c}\mathrm{c}}$, and ≤ 13% for $V_{5\mathrm{G}\mathrm{y}}$ and $V_{10\mathrm{G}\mathrm{y}}$, were obtained, without systematic bias. Similar results were found for the independent dataset. To conclude, we proposed a novel organ dose reconstruction method that uses ML models to predict dose-volume metric values given patient and plan features. Our approach is not only accurate, but also efficient, as the setup of a surrogate is no longer needed. (paper)