Target Definition in Prostate, Head, and Neck

Fully automated organ segmentation in male pelvic CT images

Accurate segmentation of prostate and surrounding organs at risk is important for prostate cancer radiotherapy treatment planning. We present a fully automated workflow for male pelvic CT image segmentation using deep learning. The architecture consists of a 2D organ volume localization network followed by a 3D segmentation network for volumetric segmentation of prostate, bladder, rectum, and femoral heads. We used a multi-channel 2D U-Net followed by a 3D U-Net with encoding arm modified with aggregated residual networks, known as ResNeXt. The models were trained and tested on a pelvic CT image dataset comprising 136 patients. Test results show that 3D U-Net based segmentation achieves mean (±SD) Dice coefficient values of 90 (±2.0)%, 96 (±3.0)%, 95 (±1.3)%, 95 (±1.5)%, and 84 (±3.7)% for prostate, left femoral head, right femoral head, bladder, and rectum, respectively, using the proposed fully automated segmentation method.

Assessment of the Impact of Deformable Registration of Diagnostic MRI to Planning CT on GTV Delineation for Radiotherapy for Oropharyngeal Carcinoma in Routine Clinical Practice

Background: Aim of study was to assess impact of deformable registration of diagnostic MRI to planning CT upon gross tumour volume (GTV) delineation of oropharyngeal carcinoma in routine practice. Methods: 22 consecutive patients with oropharyngeal squamous cell carcinoma treated with definitive (chemo)radiotherapy between 2015 and 2016, for whom primary GTV delineation had been performed by a single radiation oncologist using deformable registration of diagnostic MRI to planning CT, were identified. Separate GTVs were delineated as part of routine clinical practice (all diagnostic imaging available side-by-side for each delineation) using: CT (GTV_CT), MRI (GTV_MR), and CT and MRI (GTV_CTMR). Volumetric and positional metric analyses were undertaken using contour comparison metrics (Dice conformity index, centre of gravity distance, mean distance to conformity). Results: Median GTV volumes were 13.7 cm³ (range 3.5–41.7), 15.9 cm³ (range 1.6–38.3), 19.9 cm³ (range 5.5–44.5) for GTV_CT, GTV_MR and GTV_CTMR respectively. There was no significant difference in GTV_CT and GTV_MR volumes; GTV_CTMR was found to be significantly larger than both GTV_MR and GTV_CT. Based on positional metrics, GTV_CT and GTV_MR were the least similar (mean Dice similarity coefficient (DSC) 0.71, 0.84, 0.82 for GTV_CT–GTV_MR, GTV_CTMR–GTV_CT and GTV_CTMR–GTV_MR respectively). Conclusions: These data suggest a complementary role of MRI to CT to reduce the risk of geographical misses, although they highlight the potential for larger target volumes and hence toxicity.

Comparative study of algorithms for synthetic CT generation from MRI: Consequences for MRI-guided radiation planning in the pelvic region

PURPOSE

Magnetic resonance imaging (MRI)-guided radiation therapy (RT) treatment planning is limited by the fact that the electron density distribution required for dose calculation is not readily provided by MR imaging. We compare a selection of novel synthetic CT generation algorithms recently reported in the literature, including segmentation-based, atlas-based and machine learning techniques, using the same cohort of patients and quantitative evaluation metrics.

METHODS

Six MRI-guided synthetic CT generation algorithms were evaluated: one segmentation technique into a single tissue class (water-only), four atlas-based techniques, namely, median value of atlas images (ALMedian), atlas-based local weighted voting (ALWV), bone enhanced atlas-based local weighted voting (ALWV-Bone), iterative atlas-based local weighted voting (ALWV-Iter), and a machine learning technique using deep convolution neural network (DCNN).

RESULTS

Organ auto-contouring from MR images was evaluated for bladder, rectum, bones, and body boundary. Overall, DCNN exhibited higher segmentation accuracy resulting in Dice indices (DSC) of 0.93 ± 0.17, 0.90 ± 0.04, and 0.93 ± 0.02 for bladder, rectum, and bones, respectively. On the other hand, ALMedian showed the lowest accuracy with DSC of 0.82 ± 0.20, 0.81 ± 0.08, and 0.88 ± 0.04, respectively. DCNN reached the best performance in terms of accurate derivation of synthetic CT values within each organ, with a mean absolute error within the body contour of 32.7 ± 7.9 HU, followed by the advanced atlas-based methods (ALWV: 40.5 ± 8.2 HU, ALWV-Iter: 42.4 ± 8.1 HU, ALWV-Bone: 44.0 ± 8.9 HU). ALMedian led to the highest error (52.1 ± 11.1 HU). Considering the dosimetric evaluation results, ALWV-Iter, ALWV, DCNN and ALWV-Bone led to similar mean dose estimation within each organ at risk and target volume with less than 1% dose discrepancy. However, the two-dimensional gamma analysis demonstrated higher pass rates for ALWV-Bone, DCNN, ALMedian and ALWV-Iter at 1%/1 mm criterion with 94.99 ± 5.15%, 94.59 ± 5.65%, 93.68 ± 5.53% and 93.10 ± 5.99% success, respectively, while ALWV and water-only resulted in 86.91 ± 13.50% and 80.77 ± 12.10%, respectively.

CONCLUSIONS

Overall, machine learning and advanced atlas-based methods exhibited promising performance by achieving reliable organ segmentation and synthetic CT generation. DCNN appears to have slightly better performance by achieving accurate automated organ segmentation and relatively small dosimetric errors (followed closely by advanced atlas-based methods, which in some cases achieved similar performance). However, the DCNN approach showed higher vulnerability to anatomical variation, where a greater number of outliers was observed with this method. Considering the dosimetric results obtained from the evaluated methods, the challenge of electron density estimation from MR images can be resolved with a clinically tolerable error.

Using synthetic CT for partial brain radiation therapy: Impact on image guidance

PURPOSE

Recent advancements in synthetic computed tomography (synCT) from magnetic resonance (MR) imaging data have made MRI-only treatment planning feasible in the brain, although synCT performance for image guided radiation therapy (IGRT) is not well understood. This work compares geometric equivalence of digitally reconstructed radiographs (DRRs) from CTs and synCTs for brain cancer patients and quantifies performance for partial brain IGRT.

METHODS AND MATERIALS

Ten brain cancer patients (12 lesions, 7 postsurgical) underwent MR-SIM and CT-SIM. SynCTs were generated by combining ultra-short echo time, T1, T2, and fluid attenuation inversion recovery datasets using voxel-based weighted summation. SynCT and CT DRRs were compared using patient-specific thresholding and assessed via overlap index, Dice similarity coefficient, and Jaccard index. Planar IGRT images for 22 fractions were evaluated to quantify differences between CT-generated DRRs and synCT-generated DRRs in 6 quadrants. Previously validated software was implemented to perform 2-dimensional (2D)-2D rigid registrations using normalized mutual information. Absolute (planar image/DRR registration) and relative (differences between synCT and CT DRR registrations) shifts were calculated for each axis and 3-dimensional vector difference. A total of 1490 rigid registrations were assessed.

RESULTS

DRR agreements in anteroposterior and lateral views for overlap index, Dice similarity coefficient, and Jaccard index were >0.95. Normalized mutual information results were equivalent in 75% of quadrants. Rotational registration results were negligible (<0.07°). Statistically significant differences between CT and synCT registrations were observed in 9/18 matched quadrants/axes (P < .05). The population average absolute shifts were 0.77 ± 0.58 and 0.76 ± 0.59 mm for CT and synCT, respectively, for all axes/quadrants. Three-dimensional vectors were <2 mm in 77.7 ± 10.8% and 76.5 ± 7.2% of CT and synCT registrations, respectively. SynCT DRRs were sensitive in postsurgical cases (vector displacements >2 mm in affected quadrants).

CONCLUSIONS

DRR synCT geometry was robust. Although statistically significant differences were observed between CT and synCT registrations, results were not clinically significant. Future work will address synCT generation in postsurgical settings.

Verification of HE-based CTV in laryngeal and hypopharyngeal cancer using pan-cytokeratin

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Currently clinical CTV margins lack evidence and need (histopathological) validation.

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Tumor outline on HE and pan-cytokeratin staining are comparable for laryngeal cancer.

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HE-based delineations can be used for histopathology based CTV-margin definition.

Background

For accurate target definition, we determined margins for the clinical target volume (CTV) for laryngeal and hypopharyngeal cancer in computed tomography (CT, 4.3 mm), magnetic resonance imaging (MR, 6.1 mm) and fluorodeoxyglucose (FDG)-positron emission tomography (PET, 5.2 mm). Previously, we used Hematoxylin-eosin (HE) stained whole-mount sections of total laryngectomy specimens as gold standard to define CTV margins. In the present study, we verified the HE-based tumor delineation with staining for pan-cytokeratin, specific for squamous cell carcinoma.

Methods

Twenty-seven patients with a T3/T4 laryngeal hypopharyngeal tumor were included. From each patient, a total laryngectomy specimen was obtained. Four subsequent 3-mm thick slices containing tumor were selected of which 4-µm thick whole-mount sections were obtained and stained with HE and for pan-cytokeratin CK-AE1/3. Tumors were microscopically delineated on both sections by an experienced head-and-neck pathologist. Tumor delineations were compared using the conformity index (CI) and the distance between both contours.

Results

The CI between HE-based and CK-AE1/3-based tumor delineations was 0.87. The maximum and 95th percentile (p95) extent of the HE-based tumor delineations from the CK-AE1/3-based tumor delineations were 1.7 mm and 0.7 mm, respectively. The maximum and p95 extent of the CK-AE1/3-based tumor delineations from the HE-based tumor delineations was 1.9 mm and 0.8 mm, respectively.

Conclusions

Histopathological assessment of tumor outline on standard HE-stained sections is comparable to microscopic tumor extent based on squamous cell specific pan-cytokeratin staining. Therefore, CTV margins based on HE based tumor contour will be adequate.

Effect of region extraction and assigned mass-density values on the accuracy of dose calculation with magnetic resonance-based volumetric arc therapy planning

This study aimed to verify the validity of generating treatment plans for volumetric arc therapy (VMAT) for prostate cancer using magnetic resonance (MR) imaging with a dose calculation algorithm in Acuros XB (Eclipse version 13.6; Varian Medical Systems, Palo Alto, CA, USA) based on deterministically solving the linear Boltzmann transport equations. Four different classes were applied to prostate MR images: MR_W (all water equivalent); MR_W+B (water and bone); MR_S+B (soft tissue and bone); and MR_S+B+G (soft tissue, bone, and rectal gas). Each of these regions was assigned a mass density for calculating doses. The assigned mass-density values were then altered in three ways. Using initial planning and optimization parameters, MR-based VMAT plans were generated and compared with corresponding forward-calculated computed tomography-based plans for doses to the target volumes and organs at risk using dose-volume histograms and γ analyses. In the MR_W plans, the mean doses for TVs were overestimated by approximately 1.3%. The MR_W+B plans revealed reduced differences within 0.5%. Further segmentation (MR_S+B) did not result in substantial improvement. Dose deviations affected by the changes in the mass densities assigned to soft tissue were as small as approximately 1.0%, whereas larger deviations were revealed in bone and rectal gas, especially those with > 5% error. Assignment of accurate mass-density values acquired from MR images is needed for MR-based radiation treatment planning. Multiple MR sequences should be acquired for segmentation and mass-density conversion purposes. Segmented MR-based VMAT planning is feasible with a density assignment method using Acuros XB.

Metal artefact reduction for accurate tumour delineation in radiotherapy

BACKGROUND AND PURPOSE

Two techniques for metal artefact reduction for computed tomography were studied in order to identify their impact on tumour delineation in radiotherapy.

MATERIALS AND METHODS

Using specially designed phantoms containing metal implants (dental, spine and hip) as well as patient images, we investigated the impact of two methods for metal artefact reduction on (A) the size and severity of metal artefacts and the accuracy of Hounsfield Unit (HU) representation, (B) the visual impact of metal artefacts on image quality and (C) delineation accuracy. A metal artefact reduction algorithm (MAR) and two types of dual energy virtual monochromatic (DECT VM) reconstructions were used separately and in combination to identify the optimal technique for each implant site.

RESULTS

The artefact area and severity was reduced (by 48-76% and 58-79%, MAR and DECT VM respectively) and accurate Hounsfield-value representation was increased by 22-82%. For each energy, the observers preferred MAR over non-MAR reconstructions (p < 0.01 for dental and hip cases, p < 0.05 for the spine case). In addition, DECT VM was preferred for spine implants (p < 0.01). In all cases, techniques that improved target delineation significantly (p < 0.05) were identified.

CONCLUSIONS

DECT VM and MAR techniques improve delineation accuracy and the optimal of reconstruction technique depends on the type of metal implant.

MRI-only treatment planning: benefits and challenges

Over the past decade, the application of magnetic resonance imaging (MRI) has increased, and there is growing evidence to suggest that improvements in the accuracy of target delineation in MRI-guided radiation therapy may improve clinical outcomes in a variety of cancer types. However, some considerations should be recognized including patient motion during image acquisition and geometric accuracy of images. Moreover, MR-compatible immobilization devices need to be used when acquiring images in the treatment position while minimizing patient motion during the scan time. Finally, synthetic CT images (i.e. electron density maps) and digitally reconstructed radiograph images should be generated from MRI images for dose calculation and image guidance prior to treatment. A short review of the concepts and techniques that have been developed for implementation of MRI-only workflows in radiation therapy is provided in this document.

Automatic segmentation software in locally advanced rectal cancer: READY (REsearch program in Auto Delineation sYstem)-RECTAL 02: prospective study

To validate autocontouring software (AS) in a clinical practice including a two steps delineation quality assurance (QA) procedure.

The existing delineation agreement among experts for rectal cancer and the overlap and time criteria that have to be verified to allow the use of AS were defined.

Median Dice Similarity Coefficient (MDSC), Mean slicewise Hausdorff Distances (MSHD) and Total-Time saving (TT) were analyzed.

Two expert Radiation Oncologists reviewed CT-scans of 44 patients and agreed the reference-CTV: the first 14 consecutive cases were used to populate the software Atlas and 30 were used as Test.

Each expert performed a manual (group A) and an automatic delineation (group B) of 15 Test patients.

The delineations were compared with the reference contours.

The overlap between the manual and automatic delineations with MDSC and MSHD and the TT were analyzed.

Three acceptance criteria were set: MDSC ≥ 0.75, MSHD ≤1mm and TT sparing ≥ 50%.

At least 2 criteria had to be met, one of which had to be TT saving, to validate the system.

The MDSC was 0.75, MSHD 2.00 mm and the TT saving 55.5% between group A and group B. MDSC among experts was 0.84.

Autosegmentation systems in rectal cancer partially met acceptability criteria with the present version.

Delineation of the primary tumour Clinical Target Volumes (CTV-P) in laryngeal, hypopharyngeal, oropharyngeal and oral cavity squamous cell carcinoma: AIRO, CACA, DAHANCA, EORTC, GEORCC, GORTEC, HKNPCSG, HNCIG, IAG-KHT, LPRHHT, NCIC CTG, NCRI, NRG Oncology, PHNS, SBRT, SOMERA, SRO, SSHNO, TROG consensus guidelines

PURPOSE

Few studies have reported large inter-observer variations in target volume selection and delineation in patients treated with radiotherapy for head and neck squamous cell carcinoma. Consensus guidelines have been published for the neck nodes (see Grégoire et al., 2003, 2014), but such recommendations are lacking for primary tumour delineation. For the latter, two main schools of thoughts are prevailing, one based on geometric expansion of the Gross Tumour Volume (GTV) as promoted by DAHANCA, and the other one based on anatomical expansion of the GTV using compartmentalization of head and neck anatomy.

METHOD

For each anatomic location within the larynx, hypopharynx, oropharynx and oral cavity, and for each T-stage, the DAHANCA proposal has been comprehensively reviewed and edited to include anatomic knowledge into the geometric Clinical Target Volume (CTV) delineation concept. A first proposal was put forward by the leading authors of this publication (VG and CG) and discussed with opinion leaders in head and neck radiation oncology from Europe, Asia, Australia/New Zealand, North America and South America to reach a worldwide consensus.

RESULTS

This consensus proposes two CTVs for the primary tumour, the so called CTV-P1 and CVT-P2, corresponding to a high and lower tumour burden, and which should be associated with a high and a lower dose prescription, respectively.

CONCLUSION

Implementation of these guidelines in the daily practice of radiation oncology should contribute to reduce treatment variations from clinicians to clinicians, facilitate the conduct of multi-institutional clinical trials, and contribute to improved care of patients with head and neck carcinoma.

Automated, reference-free local error assessment of multimodal deformable image registration for radiotherapy in the head and neck

BACKGROUND

Head and neck MR-CT deformable image registration (DIR) for radiotherapy planning is hindered by the lack of both ground-truth and per-patient accuracy assessment methods. This study assesses novel post-registration reference-free error assessment algorithms, based on local rigid re-registration of native and pseudomodality images.

METHODS

Head and neck MR obtained in and out of the treatment position underwent DIR to planning CT. Block-wise mutual information (b-MI) and pseudomodality mutual information (b-pmMI) algorithms were validated against applied rotations and translations. Inherent registration error detection was compared across 14 patient datasets.

RESULTS

Using radiotherapy position MR-CT DIR, quantitative comparison of applied rotations and translations revealed that errors between 1 and 4 mm were accurately determined by both algorithms. Using diagnostic position MR-CT DIR, translations of up to 5 mm were accurately detected within the gross tumour volume by both methods. In 14 patient datasets, b-MI and b-pmMI detected similar errors with improved stability in regions of low contrast or CT artefact and a 10-fold speedup for b-pmMI.

CONCLUSIONS

b-MI and b-pmMI algorithms have been validated as providing accurate reference-free quantitative assessment of DIR accuracy on a per-patient basis. b-pmMI is faster and more robust in the presence of modality-specific information.

Consequences of introducing geometric GTV to CTV margin expansion in DAHANCA contouring guidelines for head and neck radiotherapy

BACKGROUND AND PURPOSE

Defining margins around the Gross Tumour Volume (GTV) to create a Clinical Target Volume (CTV) for head and neck cancer radiotherapy has traditionally been based on presumed knowledge of anatomical routes of spread. However, using a concentric geometric expansion around the GTV may be more reproducible. The purpose of this study was to analyse the inter-observer consistency of geometric CTV delineation with adaptation for anatomical boundaries versus anatomically defined CTVs.

MATERIAL AND METHODS

Radiation oncologists at four Danish cancer centres delineated high, intermediate and elective dose CTVs (CTV1, CTV2 and CTV3, respectively) in a patient-case template (stage IV squamous cell carcinoma of the oropharynx), first using mainly anatomical margins (original standard) and then using concentric geometric expansion (new standard). Each centre made a dummy-run radiotherapy plan based on the delineated CTVs. The difference between the CTV contours and the radiotherapy plans was evaluated across the centres.

RESULTS

Anatomy-based contours were significantly more heterogenous and showed larger volume differences between centres than geometric margins. Dice similarity coefficient increased by 0.29 and mean surface distance decreased by 4mm for CTV1. Use of consistent CTV volumes resulted in more consistent irradiated volumes between centres.

CONCLUSION

Introduction of geometric margins resulted in more uniform CTV1 and CTV2 delineation. Geometric CTV expansion was easier, left less room for misinterpretation, and resulted in more uniform treatment plans with similar irradiated high and intermediate dose volumes across all centres.

Local Protocol Variations for Image Guided Radiation Therapy in the Multicenter Dutch Hypofractionation (HYPRO) Trial: Impact of Rectal Balloon and MRI Delineation on Anorectal Dose and Gastrointestinal Toxicity Levels

PURPOSE

The phase 3 HYpofractionated irradiation for PROstate cancer (HYPRO) trial randomized patients with intermediate- to high-risk localized prostate cancer to conventionally fractionated (78 Gy in 39 fractions) or hypofractionated (64.6 Gy in 19 fractions) radiation therapy. Differences in techniques and treatment protocols were present between participating centers. This study aimed to compare dose parameters and patient-reported gastrointestinal symptoms between these centers.

METHODS AND MATERIALS

From the trial population, we selected patients (N=572) from 4 treatment centers who received image guided (IG) intensity modulated radiation therapy (IMRT). Center A (n=242) applied planning target volume (PTV) margins of 5 to 6 mm and was considered the reference center. In center B (n=170, 7-mm margins), magnetic resonance imaging (MRI) was integrated in treatment planning. An endorectal balloon (ERB) was applied in center C (n=85, 7-mm margins). Center D (n=75) applied the largest PTV margins of 8 mm. The study protocol provided identical anorectal dose constraints, and local protocols were applied for further treatment optimization. Anorectal dose-surface histograms were compared by applying t tests. Rectal complaints during follow-up (6 months to 4 years) were compared in a generalized linear model, adjusting for age, follow-up, treatment arm, and hormone therapy.

RESULTS

Favorable anorectal dose distributions were found for center B (MRI delineation) and center C (ERB application) as compared with centers A and D. These were associated with significantly lower incidences of patient-reported complaints of rectal incontinence, use of incontinence pads, and rectal discomfort in these centers. Furthermore, lower incidences of increased stool frequency (≥4 per day) and mucous loss were observed for center C.

CONCLUSIONS

Despite comparable IG-IMRT techniques and predefined dose constraints, pronounced differences in dose distributions and toxicity rates were observed. MRI delineation and ERB application were associated with favorable rectal dose parameters and toxicity profiles, whereas a 2- to 3-mm difference in PTV margins did not translate into observed differences. We conclude that choices for treatment optimization of IG-IMRT are important and clinically relevant for patients since these affect symptoms experienced in daily life.

Evaluation of the performance of deformable image registration between planning CT and CBCT images for the pelvic region: comparison between hybrid and intensity-based DIR

This study aimed to evaluate the performance of the hybrid deformable image registration (DIR) method in comparison with intensity-based DIR for pelvic cone-beam computed tomography (CBCT) images, using intensity and anatomical information. Ten prostate cancer patients treated with intensity-modulated radiation therapy (IMRT) were studied. Nine or ten CBCT scans were performed for each patient. First, rigid registration was performed between the planning CT and all CBCT images using gold fiducial markers, and then DIR was performed. The Dice similarity coefficient (DSC) and center of mass (COM) displacement were used to evaluate the quantitative DIR accuracy. The average DSCs for intensity-based DIR for the prostate, rectum, bladder, and seminal vesicles were 0.84 ± 0.05, 0.75 ± 0.05, 0.69 ± 0.07 and 0.65 ± 0.11, respectively, whereas those values for hybrid DIR were 0.98 ± 0.00, 0.97 ± 0.01, 0.98 ± 0.00 and 0.94 ± 0.03, respectively (P < 0.05). The average COM displacements for intensity-based DIR for the prostate, rectum, bladder, and seminal vesicles were 2.0 ± 1.5, 3.7 ± 1.4, 7.8 ± 2.2 and 3.6 ± 1.2 mm, whereas those values for hybrid DIR were 0.1 ± 0.0, 0.3 ± 0.2, 0.2 ± 0.1 and 0.6 ± 0.6 mm, respectively (P < 0.05). These results showed that the DSC for hybrid DIR had a higher DSC value and smaller COM displacement for all structures and all patients, compared with intensity-based DIR. Thus, the accumulative dose based on hybrid DIR might be trusted as a high-precision dose estimation method that takes into account organ movement during treatment radiotherapy.

Iterative framework for the joint segmentation and CT synthesis of MR images: application to MRI-only radiotherapy treatment planning

To tackle the problem of magnetic resonance imaging (MRI)-only radiotherapy treatment planning (RTP), we propose a multi-atlas information propagation scheme that jointly segments organs and generates pseudo x-ray computed tomography (CT) data from structural MR images (T1-weighted and T2-weighted). As the performance of the method strongly depends on the quality of the atlas database composed of multiple sets of aligned MR, CT and segmented images, we also propose a robust way of registering atlas MR and CT images, which combines structure-guided registration, and CT and MR image synthesis. We first evaluated the proposed framework in terms of segmentation and CT synthesis accuracy on 15 subjects with prostate cancer. The segmentations obtained with the proposed method were compared using the Dice score coefficient (DSC) to the manual segmentations. Mean DSCs of 0.73, 0.90, 0.77 and 0.90 were obtained for the prostate, bladder, rectum and femur heads, respectively. The mean absolute error (MAE) and the mean error (ME) were computed between the reference CTs (non-rigidly aligned to the MRs) and the pseudo CTs generated with the proposed method. The MAE was on average [Formula: see text] HU and the ME [Formula: see text] HU. We then performed a dosimetric evaluation by re-calculating plans on the pseudo CTs and comparing them to the plans optimised on the reference CTs. We compared the cumulative dose volume histograms (DVH) obtained for the pseudo CTs to the DVH obtained for the reference CTs in the planning target volume (PTV) located in the prostate, and in the organs at risk at different DVH points. We obtained average differences of [Formula: see text] in the PTV for [Formula: see text], and between [Formula: see text] and 0.05% in the PTV, bladder, rectum and femur heads for D mean and [Formula: see text]. Overall, we demonstrate that the proposed framework is able to automatically generate accurate pseudo CT images and segmentations in the pelvic region, potentially bypassing the need for CT scan for accurate RTP.

Contouring and dose calculation in head and neck cancer radiotherapy after reduction of metal artifacts in CT images

BACKGROUND

Delineation accuracy of the gross tumor volume (GTV) in radiotherapy planning for head and neck (H&N) cancer is affected by computed tomography (CT) artifacts from metal implants which obscure identification of tumor as well as organs at risk (OAR). This study investigates the impact of metal artifact reduction (MAR) in H&N patients in terms of delineation consistency and dose calculation precision in radiation treatment planning.

MATERIAL AND METHODS

Tumor and OAR delineations were evaluated in planning CT scans of eleven oropharynx patients with streaking artifacts in the tumor region preceding curative radiotherapy (RT). The GTV-tumor (GTV-T), GTV-node and parotid glands were contoured by four independent observers on standard CT images and MAR images. Dose calculation was evaluated on thirty H&N patients with dental implants near the treated volume. For each patient, the dose derived from the clinical treatment plan using the standard image set was compared with the recalculated dose on the MAR image dataset.

RESULTS

Reduction of metal artifacts resulted in larger volumes of all delineated structures compared to standard reconstruction. The GTV-T and the parotids were on average 22% (p < 0.06) and 7% larger (p = 0.005), respectively, in the MAR image plan compared to the standard image plan. Dice index showed reduced inter-observer variations after reduction of metal artifacts for all structures. The average surface distance between contours of different observers improved using the MAR images for GTV and parotids (p = 0.04 and p = 0.01). The median volume receiving a dose difference larger than ±3% was 2.3 cm³ (range 0-32 cm³).

CONCLUSIONS

Delineation of structures in the head and neck were affected by metal artifacts and volumes were generally larger and more consistent after reduction of metal artifacts, however, only small changes were observed in the dose calculations.

The influence of non-rigid anatomy and patient positioning on endoscopy-CT image registration in the head and neck

PURPOSE

To assess the influence of non-rigid anatomy and differences in patient positioning between CT acquisition and endoscopic examination on endoscopy-CT image registration in the head and neck.

METHODS

Radiotherapy planning CTs and 31-35 daily treatment-room CTs were acquired for nineteen patients. Diagnostic CTs were acquired for thirteen of the patients. The surfaces of the airways were segmented on all scans and triangular meshes were created to render virtual endoscopic images with a calibrated pinhole model of an endoscope. The virtual images were used to take projective measurements throughout the meshes, with reference measurements defined as those taken on the planning CTs and test measurements defined as those taken on the daily or diagnostic CTs. The influence of non-rigid anatomy was quantified by 3D distance errors between reference and test measurements on the daily CTs, and the influence of patient positioning was quantified by 3D distance errors between reference and test measurements on the diagnostic CTs. The daily CT measurements were also used to investigate the influences of camera-to-surface distance, surface angle, and the interval of time between scans.

RESULTS

Average errors in the daily CTs were 0.36 ± 0.61 cm in the nasal cavity, 0.58 ± 0.83 cm in the naso- and oropharynx, and 0.47 ± 0.73 cm in the hypopharynx and larynx. Average errors in the diagnostic CTs in those regions were 0.52 ± 0.69 cm, 0.65 ± 0.84 cm, and 0.69 ± 0.90 cm, respectively. All CTs had errors heavily skewed towards 0, albeit with large outliers. Large camera-to-surface distances were found to increase the errors, but the angle at which the camera viewed the surface had no effect. The errors in the Day 1 and Day 15 CTs were found to be significantly smaller than those in the Day 30 CTs (P < 0.05).

CONCLUSIONS

Inconsistencies of patient positioning have a larger influence than non-rigid anatomy on projective measurement errors. In general, these errors are largest when the camera is in the superior pharynx, where it sees large distances and a lot of muscle motion. The errors are larger when the interval of time between CT acquisitions is longer, which suggests that the interval of time between the CT acquisition and the endoscopic examination should be kept short. The median errors found in this study are comparable to acceptable levels of uncertainty in deformable CT registration. Large errors are possible even when image alignment is very good, indicating that projective measurements must be made carefully to avoid these outliers.

Clinical adequacy assessment of autocontours for prostate IMRT with meaningful endpoints

PURPOSE

To determine if radiation treatment plans created based on autosegmented (AS) regions-of-interest (ROI)s are clinically equivalent to plans created based on manually segmented ROIs, where equivalence is evaluated using probabilistic dosimetric metrics and probabilistic biological endpoints for prostate IMRT.

METHOD AND MATERIALS

Manually drawn contours and autosegmented ROIs were created for 167 CT image sets acquired from 19 prostate patients. Autosegmentation was performed utilizing Pinnacle's Smart Probabilistic Image Contouring Engine. For each CT set, 78 Gy/39 fraction 7-beam IMRT treatment plans with 1 cm CTV-to-PTV margins were created for each of the three contour scenarios; PMD using manually delineated (MD) ROIs, PAS using autosegmented ROIs, and PAM using autosegmented organ-at-risks (OAR)s and the manually drawn target. For each plan, 1000 virtual treatment simulations with different systematic errors for each simulation and a different random error for each fraction were performed. The statistical probability of achieving dose-volume metrics (coverage probability (CP)), expectation values for normal tissue complication probability (NTCP), and tumor control probability (TCP) metrics for all possible cross-evaluation pairs of ROI types and planning scenarios were reported. In evaluation scenarios, the root mean square loss (RMSL) and maximum absolute loss (MAL) of coverage probability of dose-volume objectives, E[TCP], and E[NTCP] were compared with respect to the base plan created and evaluated with manually drawn contours.

RESULTS

Femoral head dose objectives were satisfied in all situations, as well as the maximum dose objectives for all ROIs. Bladder metrics were within the clinical coverage tolerances except D35Gy for the autosegmented plan evaluated with the manual contours. Dosimetric indices for CTV and rectum could be highly compromised when the definition of the ROIs switched from manually delineated to autosegmented. Seventy-two percent of CT image sets satisfied the worst-case CP thresholds for all dosimetric objectives in all scenarios, the percentage dropped to 50% if biological indices were taken into account. Among evaluation scenarios, (MD,PAM ) bore the highest resemblance to (MD,PMD ) where 99% and 88% of cases met all CP thresholds for bladder and rectum, respectively.

CONCLUSIONS

When including daily setup variations in prostate IMRT, the dose-volume metric CP, and biological indices of ROIs were approximately equivalent for the plans created based on manually drawn targets and autosegmented OARs in 88% of cases. The accuracy of autosegmented prostates and rectums are impediment to attain statistically equivalent plans created based on manually drawn ROIs.

Interobserver delineation uncertainty in involved-node radiation therapy (INRT) for early-stage Hodgkin lymphoma: on behalf of the Radiotherapy Committee of the EORTC lymphoma group

BACKGROUND AND PURPOSE

In early-stage classical Hodgkin lymphoma (HL) the target volume nowadays consists of the volume of the originally involved nodes. Delineation of this volume on a post-chemotherapy CT-scan is challenging. We report on the interobserver variability in target volume definition and its impact on resulting treatment plans.

MATERIALS AND METHODS

Two representative cases were selected (1: male, stage IB, localization: left axilla; 2: female, stage IIB, localizations: mediastinum and bilateral neck). Eight experienced observers individually defined the clinical target volume (CTV) using involved-node radiotherapy (INRT) as defined by the EORTC-GELA guidelines for the H10 trial. A consensus contour was generated and the standard deviation computed. We investigated the overlap between observer and consensus contour [Sørensen-Dice coefficient (DSC)] and the magnitude of gross deviations between the surfaces of the observer and consensus contour (Hausdorff distance). 3D-conformal (3D-CRT) and intensity-modulated radiotherapy (IMRT) plans were calculated for each contour in order to investigate the impact of interobserver variability on each treatment modality. Similar target coverage was enforced for all plans.

RESULTS

The median CTV was 120 cm³ (IQR: 95-173 cm³) for Case 1, and 255 cm³ (IQR: 183-293 cm³) for Case 2. DSC values were generally high (>0.7), and Hausdorff distances were about 30 mm. The SDs between all observer contours, providing an estimate of the systematic error associated with delineation uncertainty, ranged from 1.9 to 3.8 mm (median: 3.2 mm). Variations in mean dose resulting from different observer contours were small and were not higher in IMRT plans than in 3D-CRT plans.

CONCLUSIONS

We observed considerable differences in target volume delineation, but the systematic delineation uncertainty of around 3 mm is comparable to that reported in other tumour sites. This report is a first step towards calculating an evidence-based planning target volume margin for INRT in HL.

A patch-based pseudo-CT approach for MRI-only radiotherapy in the pelvis

PURPOSE

In radiotherapy based only on magnetic resonance imaging (MRI), knowledge about tissue electron densities must be derived from the MRI. This can be achieved by converting the MRI scan to the so-called pseudo-computed tomography (pCT). An obstacle is that the voxel intensities in conventional MRI scans are not uniquely related to electron density. The authors previously demonstrated that a patch-based method could produce accurate pCTs of the brain using conventional T1-weighted MRI scans. The method was driven mainly by local patch similarities and relied on simple affine registrations between an atlas database of the co-registered MRI/CT scan pairs and the MRI scan to be converted. In this study, the authors investigate the applicability of the patch-based approach in the pelvis. This region is challenging for a method based on local similarities due to the greater inter-patient variation. The authors benchmark the method against a baseline pCT strategy where all voxels inside the body contour are assigned a water-equivalent bulk density. Furthermore, the authors implement a parallelized approximate patch search strategy to speed up the pCT generation time to a more clinically relevant level.

METHODS

The data consisted of CT and T1-weighted MRI scans of 10 prostate patients. pCTs were generated using an approximate patch search algorithm in a leave-one-out fashion and compared with the CT using frequently described metrics such as the voxel-wise mean absolute error (MAEvox) and the deviation in water-equivalent path lengths. Furthermore, the dosimetric accuracy was tested for a volumetric modulated arc therapy plan using dose-volume histogram (DVH) point deviations and γ-index analysis.

RESULTS

The patch-based approach had an average MAEvox of 54 HU; median deviations of less than 0.4% in relevant DVH points and a γ-index pass rate of 0.97 using a 1%/1 mm criterion. The patch-based approach showed a significantly better performance than the baseline water pCT in almost all metrics. The approximate patch search strategy was 70x faster than a brute-force search, with an average prediction time of 20.8 min.

CONCLUSIONS

The authors showed that a patch-based method based on affine registrations and T1-weighted MRI could generate accurate pCTs of the pelvis. The main source of differences between pCT and CT was positional changes of air pockets and body outline.

Modality-specific target definition for laryngeal and hypopharyngeal cancer on FDG-PET, CT and MRI

BACKGROUND AND PURPOSE

The goal of this study was to improve target definition by deriving modality-specific margins for clinical target volumes (CTV) for laryngeal and hypopharyngeal cancer on CT, MRI and 18-FDG-PET.

MATERIAL AND METHODS

Twenty-five patients with T3/T4 laryngeal/hypopharyngeal cancer underwent CT, MRI and 18-FDG-PET scans before laryngectomy. HE-sections were obtained from the surgical specimen and tumor was delineated (tumor_HE). The GTVs on CT and MRI were delineated in consensus. PET-based GTVs were automatically segmented. The three-dimensionally reconstructed specimen was registered to the various images. Modality-specific CTV margins were derived and added to the GTVs to achieve adequate tumor coverage. The resulting CTVs were compared with each other, to tumor_HE, and to CTV_CT10 constructed on CT with the clinical margin of 10mm.

RESULTS

CTV margins of 4.3mm (CT), 6.1mm (MRI) and 5.2mm (PET) were needed to achieve adequate tumor coverage. The median volumes of the resulting modality-specific CTVs were 44ml (CT), 48ml (MRI) and 39ml (PET), while the CTV_10mm was 80ml.

CONCLUSION

For laryngohypopharyngeal tumors, 45-52% target volume reduction compared with CTV_10mm is achievable when modality-specific CTV margins are used. PET-based CTVs were significantly smaller compared to CT- and MRI-based CTVs.

Evaluation of a multi-atlas CT synthesis approach for MRI-only radiotherapy treatment planning

BACKGROUND AND PURPOSE

Computed tomography (CT) imaging is the current gold standard for radiotherapy treatment planning (RTP). The establishment of a magnetic resonance imaging (MRI) only RTP workflow requires the generation of a synthetic CT (sCT) for dose calculation. This study evaluates the feasibility of using a multi-atlas sCT synthesis approach (sCTa) for head and neck and prostate patients.

MATERIAL AND METHODS

The multi-atlas method was based on pairs of non-rigidly aligned MR and CT images. The sCTa was obtained by registering the MRI atlases to the patient's MRI and by fusing the mapped atlases according to morphological similarity to the patient. For comparison, a bulk density assignment approach (sCTbda) was also evaluated. The sCTbda was obtained by assigning density values to MRI tissue classes (air, bone and soft-tissue). After evaluating the synthesis accuracy of the sCTs (mean absolute error), sCT-based delineations were geometrically compared to the CT-based delineations. Clinical plans were re-calculated on both sCTs and a dose-volume histogram and a gamma analysis was performed using the CT dose as ground truth.

RESULTS

Results showed that both sCTs were suitable to perform clinical dose calculations with mean dose differences less than 1% for both the planning target volume and the organs at risk. However, only the sCTa provided an accurate and automatic delineation of bone.

CONCLUSIONS

Combining MR delineations with our multi-atlas CT synthesis method could enable MRI-only treatment planning and thus improve the dosimetric and geometric accuracy of the treatment, and reduce the number of imaging procedures.

A review of substitute CT generation for MRI-only radiation therapy

Radiotherapy based on magnetic resonance imaging as the sole modality (MRI-only RT) is an area of growing scientific interest due to the increasing use of MRI for both target and normal tissue delineation and the development of MR based delivery systems. One major issue in MRI-only RT is the assignment of electron densities (ED) to MRI scans for dose calculation and a similar need for attenuation correction can be found for hybrid PET/MR systems. The ED assigned MRI scan is here named a substitute CT (sCT). In this review, we report on a collection of typical performance values for a number of main approaches encountered in the literature for sCT generation as compared to CT. A literature search in the Scopus database resulted in 254 papers which were included in this investigation. A final number of 50 contributions which fulfilled all inclusion criteria were categorized according to applied method, MRI sequence/contrast involved, number of subjects included and anatomical site investigated. The latter included brain, torso, prostate and phantoms. The contributions geometric and/or dosimetric performance metrics were also noted. The majority of studies are carried out on the brain for 5–10 patients with PET/MR applications in mind using a voxel based method. T1 weighted images are most commonly applied. The overall dosimetric agreement is in the order of 0.3–2.5%. A strict gamma criterion of 1% and 1mm has a range of passing rates from 68 to 94% while less strict criteria show pass rates > 98%. The mean absolute error (MAE) is between 80 and 200 HU for the brain and around 40 HU for the prostate. The Dice score for bone is between 0.5 and 0.95. The specificity and sensitivity is reported in the upper 80s% for both quantities and correctly classified voxels average around 84%. The review shows that a variety of promising approaches exist that seem clinical acceptable even with standard clinical MRI sequences. A consistent reference frame for method benchmarking is probably necessary to move the field further towards a widespread clinical implementation.

Comparison of Safety Margin Generation Concepts in Image Guided Radiotherapy to Account for Daily Head and Neck Pose Variations

Purpose

Intensity modulated radiation therapy (IMRT) of head and neck tumors allows a precise conformation of the high-dose region to clinical target volumes (CTVs) while respecting dose limits to organs a risk (OARs). Accurate patient setup reduces translational and rotational deviations between therapy planning and therapy delivery days. However, uncertainties in the shape of the CTV and OARs due to e.g. small pose variations in the highly deformable anatomy of the head and neck region can still compromise the dose conformation. Routinely applied safety margins around the CTV cause higher dose deposition in adjacent healthy tissue and should be kept as small as possible.

Materials and Methods

In this work we evaluate and compare three approaches for margin generation 1) a clinically used approach with a constant isotropic 3 mm margin, 2) a previously proposed approach adopting a spatial model of the patient and 3) a newly developed approach adopting a biomechanical model of the patient. All approaches are retrospectively evaluated using a large patient cohort of over 500 fraction control CT images with heterogeneous pose changes. Automatic methods for finding landmark positions in the control CT images are combined with a patient specific biomechanical finite element model to evaluate the CTV deformation.

Results

The applied methods for deformation modeling show that the pose changes cause deformations in the target region with a mean motion magnitude of 1.80 mm. We found that the CTV size can be reduced by both variable margin approaches by 15.6% and 13.3% respectively, while maintaining the CTV coverage. With approach 3 an increase of target coverage was obtained.

Conclusion

Variable margins increase target coverage, reduce risk to OARs and improve healthy tissue sparing at the same time.

Atlas-guided generation of pseudo-CT images for MRI-only and hybrid PET-MRI-guided radiotherapy treatment planning

Magnetic resonance imaging (MRI)-guided attenuation correction (AC) of positron emission tomography (PET) data and/or radiation therapy (RT) treatment planning is challenged by the lack of a direct link between MRI voxel intensities and electron density. Therefore, even if this is not a trivial task, a pseudo-computed tomography (CT) image must be predicted from MRI alone. In this work, we propose a two-step (segmentation and fusion) atlas-based algorithm focusing on bone tissue identification to create a pseudo-CT image from conventional MRI sequences and evaluate its performance against the conventional MRI segmentation technique and a recently proposed multi-atlas approach. The clinical studies consisted of pelvic CT, PET and MRI scans of 12 patients with loco-regionally advanced rectal disease. In the first step, bone segmentation of the target image is optimized through local weighted atlas voting. The obtained bone map is then used to assess the quality of deformed atlases to perform voxel-wise weighted atlas fusion. To evaluate the performance of the method, a leave-one-out cross-validation (LOOCV) scheme was devised to find optimal parameters for the model. Geometric evaluation of the produced pseudo-CT images and quantitative analysis of the accuracy of PET AC were performed. Moreover, a dosimetric evaluation of volumetric modulated arc therapy photon treatment plans calculated using the different pseudo-CT images was carried out and compared to those produced using CT images serving as references. The pseudo-CT images produced using the proposed method exhibit bone identification accuracy of 0.89 based on the Dice similarity metric compared to 0.75 achieved by the other atlas-based method. The superior bone extraction resulted in a mean standard uptake value bias of  -1.5  ±  5.0% (mean  ±  SD) in bony structures compared to  -19.9  ±  11.8% and  -8.1  ±  8.2% achieved by MRI segmentation-based (water-only) and atlas-guided AC. Dosimetric evaluation using dose volume histograms and the average difference between minimum/maximum absorbed doses revealed a mean error of less than 1% for the both target volumes and organs at risk. Two-dimensional (2D) gamma analysis of the isocenter dose distributions at 1%/1 mm criterion revealed pass rates of 91.40  ±  7.56%, 96.00  ±  4.11% and 97.67  ±  3.6% for MRI segmentation, atlas-guided and the proposed methods, respectively. The proposed method generates accurate pseudo-CT images from conventional Dixon MRI sequences with improved bone extraction accuracy. The approach is promising for potential use in PET AC and MRI-only or hybrid PET/MRI-guided RT treatment planning.

Functional magnetic resonance imaging techniques and their development for radiation therapy planning and monitoring in the head and neck cancers

Radiation therapy (RT), in particular intensity-modulated radiation therapy (IMRT), is becoming a more important nonsurgical treatment strategy in head and neck cancer (HNC). The further development of IMRT imposes more critical requirements on clinical imaging, and these requirements cannot be fully fulfilled by the existing radiotherapeutic imaging workhorse of X-ray based imaging methods. Magnetic resonance imaging (MRI) has increasingly gained more interests from radiation oncology community and holds great potential for RT applications, mainly due to its non-ionizing radiation nature and superior soft tissue image contrast. Beyond anatomical imaging, MRI provides a variety of functional imaging techniques to investigate the functionality and metabolism of living tissue. The major purpose of this paper is to give a concise and timely review of some advanced functional MRI techniques that may potentially benefit conformal, tailored and adaptive RT in the HNC. The basic principle of each functional MRI technique is briefly introduced and their use in RT of HNC is described. Limitation and future development of these functional MRI techniques for HNC radiotherapeutic applications are discussed. More rigorous studies are warranted to translate the hypotheses into credible evidences in order to establish the role of functional MRI in the clinical practice of head and neck radiation oncology.

The feasibility of atlas-based automatic segmentation of MRI for H&N radiotherapy planning

Atlas‐based autosegmentation is an established tool for segmenting structures for CT‐planned head and neck radiotherapy. MRI is being increasingly integrated into the planning process. The aim of this study is to assess the feasibility of MRI‐based, atlas‐based autosegmentation for organs at risk (OAR) and lymph node levels, and to compare the segmentation accuracy with CT‐based autosegmentation. Fourteen patients with locally advanced head and neck cancer in a prospective imaging study underwent a T1‐weighted MRI and a PET‐CT (with dedicated contrast‐enhanced CT) in an immobilization mask. Organs at risk (orbits, parotids, brainstem, and spinal cord) and the left level II lymph node region were manually delineated on the CT and MRI separately. A ‘leave one out’ approach was used to automatically segment structures onto the remaining images separately for CT and MRI. Contour comparison was performed using multiple positional metrics: Dice index, mean distance to conformity (MDC), sensitivity index (Se Idx), and inclusion index (Incl Idx). Automatic segmentation using MRI of orbits, parotids, brainstem, and lymph node level was acceptable with a DICE coefficient of 0.73−0.91, MDC 2.0−5.1 mm, Se Idx 0.64−0.93, Incl Idx 0.76−0.93. Segmentation of the spinal cord was poor (Dice coefficient 0.37). The process of automatic segmentation was significantly better on MRI compared to CT for orbits, parotid glands, brainstem, and left lymph node level II by multiple positional metrics; spinal cord segmentation based on MRI was inferior compared with CT. Accurate atlas‐based automatic segmentation of OAR and lymph node levels is feasible using T1‐MRI; segmentation of the spinal cord was found to be poor. Comparison with CT‐based automatic segmentation suggests that the process is equally as, or more accurate, using MRI. These results support further translation of MRI‐based segmentation methodology into clinical practice.

PACS number(s): 87.55.de

Uncertainties in target volume delineation in radiotherapy - are they relevant and what can we do about them?

Background

Modern radiotherapy techniques enable delivery of high doses to the target volume without escalating dose to organs at risk, offering the possibility of better local control while preserving good quality of life. Uncertainties in target volume delineation have been demonstrated for most tumour sites, and various studies indicate that inconsistencies in target volume delineation may be larger than errors in all other steps of the treatment planning and delivery process. The aim of this paper is to summarize the degree of delineation uncertainties for different tumour sites reported in the literature and review the effect of strategies to minimize them.

Conclusions

Our review confirmed that interobserver variability in target volume contouring represents the largest uncertainty in the process for most tumour sites, potentially resulting in a systematic error in dose delivery, which could influence local control in individual patients. For most tumour sites the optimal combination of imaging modalities for target delineation still needs to be determined. Strict use of delineation guidelines and protocols is advisable both in every day clinical practice and in clinical studies to diminish interobserver variability. Continuing medical education of radiation oncologists cannot be overemphasized, intensive formal training on interpretation of sectional imaging should be included in the program for radiation oncology residents.

Deformable image registration and interobserver variation in contour propagation for radiation therapy planning

Deformable image registration (DIR) and interobserver variation inevitably introduce uncertainty into the treatment planning process. The purpose of the current work was to measure deformable image registration (DIR) errors and interobserver variability for regions of interest (ROIs) in the head and neck and pelvic regions. Measured uncertainties were combined to examine planning margin adequacy for contours propagated for adaptive therapy and to assess the trade‐off of DIR and interobserver uncertainty in atlas‐based automatic segmentation. Two experienced dosimetrists retrospectively contoured brainstem, spinal cord, anterior oral cavity, larynx, right and left parotids, optic nerves, and eyes on the planning CT (CT1) and attenuation‐correction CT of diagnostic PET/CT (CT2) for 30 patients who received radiation therapy for head and neck cancer. Two senior radiation oncology residents retrospectively contoured prostate, bladder, and rectum on the postseed‐implant CT (CT1) and planning CT (CT2) for 20 patients who received radiation therapy for prostate cancer. Interobserver variation was measured by calculating mean Hausdorff distances between the two observers' contours. CT2 was deformably registered to CT1 via commercially available multipass B‐spline DIR. CT2 contours were propagated and compared with CT1 contours via mean Hausdorff distances. These values were summed in quadrature with interobserver variation for margin analysis and compared with interobserver variation for statistical significance using two‐tailed t‐tests for independent samples (α=0.05). Combined uncertainty ranged from 1.5‐5.8 mm for head and neck structures and 3.1‐3.7 mm for pelvic structures. Conventional 5 mm margins may not be adequate to cover this additional uncertainty. DIR uncertainty was significantly less than interobserver variation for four head and neck and one pelvic ROI. DIR uncertainty was not significantly different than interobserver variation for four head and neck and one pelvic ROI. DIR uncertainty was significantly greater than interobserver variation for two head and neck and one pelvic ROI. The introduction of DIR errors may offset any reduction in interobserver variation by using atlas‐based automatic segmentation.

PACS number(s): 87.57.nj, 87.55.D‐

Multimodality imaging with CT, MR and FDG-PET for radiotherapy target volume delineation in oropharyngeal squamous cell carcinoma

Background

This study aimed to quantify the variation in oropharyngeal squamous cell carcinoma gross tumour volume (GTV) delineation between CT, MR and FDG PET-CT imaging.

Methods

A prospective, single centre, pilot study was undertaken where 11 patients with locally advanced oropharyngeal cancers (2 tonsil, 9 base of tongue primaries) underwent pre-treatment, contrast enhanced, FDG PET-CT and MR imaging, all performed in a radiotherapy treatment mask. CT, MR and CT-MR GTVs were contoured by 5 clinicians (2 radiologists and 3 radiation oncologists). A semi-automated segmentation algorithm was used to contour PET GTVs. Volume and positional analyses were undertaken, accounting for inter-observer variation, using linear mixed effects models and contour comparison metrics respectively.

Results

Significant differences in mean GTV volume were found between CT (11.9 cm³) and CT-MR (14.1 cm³), p < 0.006, CT-MR and PET (9.5 cm³), p < 0.0009, and MR (12.7 cm³) and PET, p < 0.016. Substantial differences in GTV position were found between all modalities with the exception of CT-MR and MR GTVs. A mean of 64 %, 74 % and 77 % of the PET GTVs were included within the CT, MR and CT-MR GTVs respectively. A mean of 57 % of the MR GTVs were included within the CT GTV; conversely a mean of 63 % of the CT GTVs were included within the MR GTV. CT inter-observer variability was found to be significantly higher in terms of position and/or volume than both MR and CT-MR (p < 0.05). Significant differences in GTV volume were found between GTV volumes delineated by radiologists (9.7 cm³) and oncologists (14.6 cm³) for all modalities (p = 0.001).

Conclusions

The use of different imaging modalities produced significantly different GTVs, with no single imaging technique encompassing all potential GTV regions. The use of MR reduced inter-observer variability. These data suggest delineation based on multimodality imaging has the potential to improve accuracy of GTV definition.

Trial registration

ISRCTN Registry: ISRCTN34165059. Registered 2nd February 2015.

Ultrasound versus Cone-beam CT image-guided radiotherapy for prostate and post-prostatectomy pretreatment localization

PURPOSE

To evaluate the accuracy of an intra-modality trans-abdominal ultrasound (TA-US) device against soft-tissue based Cone-Beam Computed tomography (CBCT) registration for prostate and post-prostatectomy pre-treatment positioning.

METHODS

The differences between CBCT and US shifts were calculated on 25 prostate cancer patients (cohort A) and 11 post-prostatectomy patients (cohort B), resulting in 284 and 106 paired shifts for cohorts A and B, respectively. As a second step, a corrective method was applied to the US registration results to decrease the systematic shifts observed between TA-US and CBCT results. This method consisted of subtracting the mean difference obtained between US and CBCT registration results during the first 3 sessions from the US registration results of the subsequent sessions. Inter-operator registration variability (IOV) was also investigated for both modalities.

RESULTS

After initial review, about 20% of the US images were excluded because of insufficient quality. The average differences between US and CBCT were: 2.8 ± 4.1 mm, -0.9 ± 4.2 mm, 0.4 ± 3.4 mm for cohort A and 1.3 ± 5.0 mm, -2.3 ± 4.6 mm, 0.5 ± 2.9 mm for cohort B, in the anterior-posterior (AP), superior-inferior (SI) and lateral (LR) directions, respectively. After applying the corrective method, only the differences in the AP direction remained significant (p < 0.05). The IOV values were between 0.6-2.0 mm and 2.1-3.5 mm for the CBCT and TA-US modalities, respectively.

CONCLUSIONS

Based on the obtained results and on the image quality, the TA-US imaging modality is not safely interchangeable with CBCT for pre-treatment repositioning. Treatment margins adaptation based on the correction of the systematic shifts should be considered.

Advances in Radiotherapy for Head and Neck Cancer

Over the last few decades, significant improvements have been made in the radiotherapy (RT) treatment of head and neck malignancies. The progressive introduction of intensity-modulated RT and the use of multimodality imaging for target volume and organs at risk delineation, together with the use of altered fractionation regimens and concomitant administration of chemotherapy or targeted agents, have accompanied efficacy improvements in RT. Altogether, such improvements have translated into improvement in locoregional control and overall survival probability, with a decrease in the long-term adverse effects of RT and an improvement in quality of life. Further progress in the treatment of head and neck malignancies may come from a better integration of molecular imaging to identify tumor subvolumes that may require additional radiation doses (ie, dose painting) and from treatment adaptation tracing changes in patient anatomy during treatment. Proton therapy generates even more exquisite dose distribution in some patients, thus potentially further improving patient outcomes. However, the clinical benefit of these approaches, although promising, for patients with head and neck cancer need to be demonstrated in prospective randomized studies. In this context, our article will review some of these advances, with special emphasis on target volume and organ-at-risk delineation, use of molecular imaging for tumor delineation, dose painting for dose escalation, dose adaptation throughout treatment, and potential benefit of proton therapy.

Cone beam computed tomography guided treatment delivery and planning verification for magnetic resonance imaging only radiotherapy of the brain

BACKGROUND

Radiotherapy based on MRI only (MRI-only RT) shows a promising potential for the brain. Much research focuses on creating a pseudo computed tomography (pCT) from MRI for treatment planning while little attention is often paid to the treatment delivery. Here, we investigate if cone beam CT (CBCT) can be used for MRI-only image-guided radiotherapy (IGRT) and for verifying the correctness of the corresponding pCT.

MATERIAL AND METHODS

Six patients receiving palliative cranial RT were included in the study. Each patient had three-dimensional (3D) T1W MRI, a CBCT and a CT for reference. Further, a pCT was generated using a patch-based approach. MRI, pCT and CT were placed in the same frame of reference, matched to CBCT and the differences noted. Paired pCT-CT and pCT-CBCT data were created in bins of 10 HU and the absolute difference calculated. The data were converted to relative electron densities (RED) using the CT or a CBCT calibration curve. The latter was either based on a CBCT phantom (phan) or a paired CT-CBCT population (pop) of the five other patients.

RESULTS

Non-significant (NS) differences in the pooled CT-CBCT, MRI-CBCT and pCT-CBCT transformations were noted. The largest deviations from the CT-CBCT reference were < 1 mm and 1°. The average median absolute error (MeAE) in HU was 184 ± 34 and 299 ± 34 on average for pCT-CT and pCT-CBCT, respectively, and was significantly different (p < 0.01) in each patient. The average MeAE in RED was 0.108 ± 0.025, 0.104 ± 0.011 and 0.099 ± 0.017 for pCT-CT, pCT-CBCT phan (p < 0.01 on 2 patients) and pCT-CBCT pop (NS), respectively.

CONCLUSIONS

CBCT can be used for patient setup with either MRI or pCT as reference. The correctness of pCT can be verified from CBCT using a population-based calibration curve in the treatment geometry.

Benchmarking of a treatment planning system for spot scanning proton therapy: comparison and analysis of robustness to setup errors of photon IMRT and proton SFUD treatment plans of base of skull meningioma

PURPOSE

Base of skull meningioma can be treated with both intensity modulated radiation therapy (IMRT) and spot scanned proton therapy (PT). One of the main benefits of PT is better sparing of organs at risk, but due to the physical and dosimetric characteristics of protons, spot scanned PT can be more sensitive to the uncertainties encountered in the treatment process compared with photon treatment. Therefore, robustness analysis should be part of a comprehensive comparison between these two treatment methods in order to quantify and understand the sensitivity of the treatment techniques to uncertainties. The aim of this work was to benchmark a spot scanning treatment planning system for planning of base of skull meningioma and to compare the created plans and analyze their robustness to setup errors against the IMRT technique.

METHODS

Plans were produced for three base of skull meningioma cases: IMRT planned with a commercial TPS [Monaco (Elekta AB, Sweden)]; single field uniform dose (SFUD) spot scanning PT produced with an in-house TPS (PSI-plan); and SFUD spot scanning PT plan created with a commercial TPS [XiO (Elekta AB, Sweden)]. A tool for evaluating robustness to random setup errors was created and, for each plan, both a dosimetric evaluation and a robustness analysis to setup errors were performed.

RESULTS

It was possible to create clinically acceptable treatment plans for spot scanning proton therapy of meningioma with a commercially available TPS. However, since each treatment planning system uses different methods, this comparison showed different dosimetric results as well as different sensitivities to setup uncertainties. The results confirmed the necessity of an analysis tool for assessing plan robustness to provide a fair comparison of photon and proton plans.

CONCLUSIONS

Robustness analysis is a critical part of plan evaluation when comparing IMRT plans with spot scanned proton therapy plans.

Contouring variability of human- and deformable-generated contours in radiotherapy for prostate cancer

This study was designed to evaluate contouring variability of human-and deformable-generated contours on planning CT (PCT) and CBCT for ten patients with low-or intermediate-risk prostate cancer. For each patient in this study, five radiation oncologists contoured the prostate, bladder, and rectum, on one PCT dataset and five CBCT datasets. Consensus contours were generated using the STAPLE method in the CERR software package. Observer contours were compared to consensus contour, and contour metrics (Dice coefficient, Hausdorff distance, Contour Distance, Center-of-Mass [COM] Deviation) were calculated. In addition, the first day CBCT was registered to subsequent CBCT fractions (CBCTn: CBCT2-CBCT5) via B-spline Deformable Image Registration (DIR). Contours were transferred from CBCT1 to CBCTn via the deformation field, and contour metrics were calculated through comparison with consensus contours generated from human contour set. The average contour metrics for prostate contours on PCT and CBCT were as follows: Dice coefficient-0.892 (PCT), 0.872 (CBCT-Human), 0.824 (CBCT-Deformed); Hausdorff distance-4.75 mm (PCT), 5.22 mm (CBCT-Human), 5.94 mm (CBCT-Deformed); Contour Distance (overall contour)-1.41 mm (PCT), 1.66 mm (CBCT-Human), 2.30 mm (CBCT-Deformed); COM Deviation-2.01 mm (PCT), 2.78 mm (CBCT-Human), 3.45 mm (CBCT-Deformed). For human contours on PCT and CBCT, the difference in average Dice coefficient between PCT and CBCT (approx. 2%) and Hausdorff distance (approx. 0.5 mm) was small compared to the variation between observers for each patient (standard deviation in Dice coefficient of 5% and Hausdorff distance of 2.0 mm). However, additional contouring variation was found for the deformable-generated contours (approximately 5.0% decrease in Dice coefficient and 0.7 mm increase in Hausdorff distance relative to human-generated contours on CBCT). Though deformable contours provide a reasonable starting point for contouring on CBCT, we conclude that contours generated with B-Spline DIR require physician review and editing if they are to be used in the clinic.

Quantitative Imaging in Radiation Oncology: An Emerging Science and Clinical Service

Radiation oncology has long required quantitative imaging approaches for the safe and effective delivery of radiation therapy. The past 10 years has seen a remarkable expansion in the variety of novel imaging signals and analyses that are starting to contribute to the prescription and design of the radiation treatment plan. These include a rapid increase in the use of magnetic resonance imaging, development of contrast-enhanced imaging techniques, integration of fluorinated deoxyglucose-positron emission tomography, evaluation of hypoxia imaging techniques, and numerous others. These are reviewed with an effort to highlight challenges related to quantification and reproducibility. In addition, several of the emerging applications of these imaging approaches are also highlighted. Finally, the growing community of support for establishing quantitative imaging approaches as we move toward clinical evaluation is summarized and the need for a clinical service in support of the clinical science and delivery of care is proposed.

Estimation of patient setup uncertainty using BrainLAB Exatrac X-Ray 6D system in image-guided radiotherapy

The purpose of this study was to evaluate setup uncertainties for brain sites with ExacTrac X‐Ray 6D system and to provide optimal margin guidelines. Fifteen patients with brain tumor were included in this study. Two X‐ray images with ExacTrac X‐Ray 6D system were used to verify patient position and tumor target localization before each treatment. The 6D fusion software first generates various sets of DRRs with position variations in both three translational and three rotational directions (six degrees of freedom) for the CT images. Setup variations (translation and rotation) after correction were recorded and corrected before treatment. The 3D deviations are expressed as mean±standard deviation. The random error (Σ(σi)), systematic error (μi), and group systematic error (M(μi)) for the different X‐ray were calculated using the definitions of van Herk.⁽¹⁾ Mean setup errors were calculated from X‐ray images acquired after all fractions. There is moderate patient‐to‐patient variation in the vertical direction and small variations in systematic errors and magnitudes of random errors are smaller. The global systematic errors were measured to be less than 2.0 mm in each direction. Random component of all patients are smaller ranging from 0.1–0.3 mm small. The safety margin (SM) to the lateral, is 0.5 mm and 2.6 mm for van Herk⁽¹⁾ and Stroom et al.,⁽²⁾ respectively, craniocaudal axis is 1.5 mm and 3.4 mm, respectively, and with respect to the antero–posterior axis, 2.3 mm and 3.9 mm. Daily X‐ray imaging is essential to compare and assess the accuracy of treatment delivery to different anatomical locations.

PACS number: 87.55.D