Interobserver variability in the delineation of the primary lung cancer and lymph nodes on different four-dimensional computed tomography reconstructions

Dosimetric comparison of free-breathing versus respiratory motion-managed radiotherapy via four-dimensional computed tomography-based volumetric-modulated arctherapy for lung cancer

PURPOSE

The aim of this study is to use respiratory motion-managed radiotherapy (RT) to reduce side effects and to compare dosimetric factors with free-breathing planning in patients with lung cancer.

MATERIALS AND METHODS

Simulation images were obtained in 10 respiratory phases with free breathing using four-dimensional computed tomography (4D-CT) scanner. Planning target volume (PTV) was created with 5mm margins in each direction of the internal target volume delineated using the maximum intensity projection. A volumetric arc treatment (VMAT) plan was created so that the prescribed dose would cover 98% of the PTV. Target volumes for the free-breathing VMAT plan were created according to ICRU Reports 62 and the same prescribed dose was used.

RESULTS

Patients were evaluated during January 2020. Median 63Gy (59.4-64) RT was administered. Median PTV volumes were 173.53 and 494.50cm3 (P=0.008) and dose covering 95% of PTV volume was 62.97 and 60.51Gy (P=0.13) in 4D-CT based and free-breathing VMAT plans, respectively. The mean and V50 heart dose was 6.03Gy (vs. 10.36Gy, P=0.043) and 8.2% (vs. 33.9%, P=0.007), and significantly lower in 4D-CT based VMAT plans and there was also found a non-significant reduction for other risky organ doses.

CONCLUSION

Ten patients treated with respiratory motion-managed RT with 4D-CT based VMAT technique. It was observed that PTV did not increase, the target was covered with 95% accuracy, and with statistical significance in heart doses, all risky organ doses were found to be less.

An approach to generate synthetic 4DCT datasets to benchmark Mid-Position implementations

PURPOSE

The Mid-Position image is constructed from 4DCT data using Deformable Image Registration and can be used as planning CT with reduced PTV volumes. 4DCT datasets currently-available for testing do not provide the corresponding Mid-P images of the datasets. This work describes an approach to generate human-like synthetic 4DCT datasets with the associated Mid-P images that can be used as reference in the validation of Mid-P implementations.

METHODS

Twenty synthetic 4DCT datasets with the associated reference Mid-P images were generated from twenty clinical 4DCT datasets. Per clinical dataset, an anchor phase was registered to the remaining nine phases to obtain nine Deformable Vector Fields (DVFs). These DVFs were used to warp the anchor phase in order to generate the synthetic 4DCT dataset and the corresponding reference Mid-P image. Similarly, a reference 4D tumor mask dataset and its corresponding Mid-P tumor mask were generated. The generated synthetic datasets and masks were used to compare and benchmark the outcomes of three independent Mid-P implementations using a set of experiments.

RESULTS

The Mid-P images constructed by the three implementations showed high similarity scores when compared to the reference Mid-P images except for one noisy dataset. The biggest difference in the estimated motion amplitudes (-2.6 mm) was noticed in the Superior-Inferior direction. The statistical analysis showed no significant differences among the three implementations for all experiments.

CONCLUSION

The described approach and the proposed experiments provide an independent method that can be used in the validation of any Mid-P implementation being developed.

Assessing Interobserver Variability in the Delineation of Structures in Radiation Oncology: A Systematic Review

PURPOSE

The delineation of target volumes and organs at risk is the main source of uncertainty in radiation therapy. Numerous interobserver variability (IOV) studies have been conducted, often with unclear methodology and nonstandardized reporting. We aimed to identify the parameters chosen in conducting delineation IOV studies and assess their performances and limits.

METHODS AND MATERIALS

We conducted a systematic literature review to highlight major points of heterogeneity and missing data in IOV studies published between 2018 and 2021. For the main used metrics, we did in silico analyses to assess their limits in specific clinical situations.

RESULTS

All disease sites were represented in the 66 studies examined. Organs at risk were studied independently of tumor site in 29% of reviewed IOV studies. In 65% of studies, statistical analyses were performed. No gold standard (GS; ie, reference) was defined in 36% of studies. A single expert was considered as the GS in 21% of studies, without testing intraobserver variability. All studies reported both absolute and relative indices, including the Dice similarity coefficient (DSC) in 68% and the Hausdorff distance (HD) in 42%. Limitations were shown in silico for small structures when using the DSC and dependence on irregular shapes when using the HD. Variations in DSC values were large between studies, and their thresholds were inconsistent. Most studies (51%) included 1 to 10 cases. The median number of observers or experts was 7 (range, 2-35). The intraclass correlation coefficient was reported in only 9% of cases. Investigating the feasibility of studying IOV in delineation, a minimum of 8 observers with 3 cases, or 11 observers with 2 cases, was required to demonstrate moderate reproducibility.

CONCLUSIONS

Implementation of future IOV studies would benefit from a more standardized methodology: clear definitions of the gold standard and metrics and a justification of the tradeoffs made in the choice of the number of observers and number of delineated cases should be provided.

Towards mid-position based Stereotactic Body Radiation Therapy on the MR-linac for central lung tumours

Background and purpose: Central lung tumours can be treated by magnetic resonance (MR)-guided radiotherapy. Complications might be reduced by decreasing the Planning Target Volume (PTV) using mid-position (midP)-based planning instead of Internal Target Volume (ITV)-based planning. In this study, we aimed to verify a method to automatically derive patient-specific PTV margins for midP-based planning, and show dosimetric robustness of midP-based planning for a 1.5T MR-linac.

Materials and methods: Central(n = 12) and peripheral(n = 4) central lung tumour cases who received 8x7.5 Gy were included. A midP-image was reconstructed from ten phases of the 4D-Computed Tomography using deformable image registration. The Gross Tumor Volume (GTV) was delineated on the midP-image and the PTV margin was automatically calculated based on van Herk’s margin recipe, treating the standard deviation of all Deformation Vector Fields, within the GTV, as random error component. Dosimetric robustness of midP-based planning for MR-linac using automatically derived margins was verified by 4D dose-accumulation. MidP-based plans were compared to ITV-based plans. Automatically derived margins were verified with manually derived margins.

Results: The mean D95% target coverage in GTV + 2 mm was 59.9 Gy and 62.0 Gy for midP- and ITV-based central lung plans, respectively. The mean lung dose was significantly lower for midP-based treatment plans (difference:-0.3 Gy; p<0.042). Automatically derived margins agreed within one millimeter with manually derived margins.

Conclusions: This retrospective study indicates that mid-position-based treatment plans for central lung Stereotactic Body Radiation Therapy yield lower OAR doses compared to ITV-based treatment plans on the MR-linac. Patient-specific GTV-to-PTV margins can be derived automatically and result in clinically acceptable target coverage.

Evaluation of Lung Tumor Target Volume in a Large Sample: Target and Clinical Factors Influencing the Volume Derived From Four-Dimensional CT and Cone Beam CT

Background and Purpose

This study aimed to systematically evaluate the influence of target-related and clinical factors on volume differences and the similarity of targets derived from four-dimensional computed tomography (4DCT) and cone beam computed tomography (CBCT) images in lung stereotactic body radiation therapy (SBRT).

Materials and Methods

4DCT and CBCT image data of 210 tumors from 195 patients were analyzed. The internal gross target volume (IGTV) derived from the maximum intensity projection (MIP) of 4DCT (IGTV-MIP) and the IGTV from CBCT (IGTV-CBCT) were compared with the reference IGTV from 10 phases of 4DCT (IGTV-10). The target size, tumor motion, and the similarity between IGTVs were measured. The influence of target-related and clinical factors on the adequacy of IGTVs derived from 4DCT MIP and CBCT images was evaluated.

Results

The mean tumor motion amplitude in the 3D direction was 6.5 ± 5 mm. The mean size ratio of IGTV-CBCT and IGTV-MIP compared to IGTV-10 in all patients was 0.71 ± 0.21 and 0.8 ± 0.14, respectively. Female sex, greater BSA, and larger target size were protective factors, while the Karnofsky Performance Status, body mass index, and motion were risk factors for the similarity between IGTV-MIP and IGTV-10. Older age and larger target size were protective factors, while adhesion to the heart, coexistence with cardiopathy, and tumor motion were risk factors for the similarity between IGTV-CBCT and IGTV-10.

Conclusion

Clinical factors should be considered when using MIP images for defining ITV, and when using CBCT images for verifying treatment targets.

Probabilistic target definition and planning in patients with prostate cancer

Intro.Current radiation therapy (RT) planning guidelines handle uncertainties in RT using geometric margins. This approach is simple to use but oversimplifies complex underlying processes and is cumbersome for non-homogeneous dose prescriptions. In this work, we characterize the performance of a novel probabilistic target definition and planning (PTP) approach, which uses voxel-level tumor likelihood information in treatment plan optimization.Methods.We expanded a treatment planning system with probabilistic therapy planning functionality that utilizes non-binary target maps (TM) as voxel-level input to dose plan optimization. Different dose plans were calculated and compared for twelve prostate cancer patients with multiparametric magnetic resonance imaging derived TMs. Dose plans were created using both classical and PTP approaches for uniform and integrated dose boost prescriptions. Dose performance between the different approaches was compared using dose benchmarks on target and organ-at-risk (OAR) volumes.Results.Over all dose metrics, PTP was shown to be comparable to classical planning. For plans of uniform dose prescription, the PTP approach created plans within 1 Gy of the classical planning approach across all dose metrics, with no significant differences (p > 0.2). For plans with the integrated dose boost, PTP plans exhibited higher dose heterogeneity, but still showed target doses comparable to the classical approach, without increasing doses to OAR.Conclusion.In this work we introduce direct incorporation of probabilistic target definition into treatment planning. This treatment planning approach can produce both uniform dose plans and plans with integrated dose boosts that are comparable to ones created using classical dose planning. PTP is a flexible way to optimize external beam radiotherapy, as it is not limited by the use of margins. PTP can produce dose plans equivalent to classical planning, while also allows for greater versatility in dose prescription and direct incorporation of patient target definition uncertainty into treatment planning.

Optimising use of 4D-CT phase information for radiomics analysis in lung cancer patients treated with stereotactic body radiotherapy

Purpose. 4D-CT is routine imaging for lung cancer patients treated with stereotactic body radiotherapy. No studies have investigated optimal 4D phase selection for radiomics. We aim to determine how phase data should be used to identify prognostic biomarkers for distant failure, and test whether stability assessment is required. A phase selection approach will be developed to aid studies with different 4D protocols and account for patient differences. Methods. 186 features were extracted from the tumour and peritumour on all phases for 258 patients. Feature values were selected from phase features using four methods: (A) mean across phases, (B) median across phases, (C) 50% phase, and (D) the most stable phase (closest in value to two neighbours), coined personalised selection. Four levels of stability assessment were also analysed, with inclusion of: (1) all features, (2) stable features across all phases, (3) stable features across phase and neighbour phases, and (4) features averaged over neighbour phases. Clinical-radiomics models were built for twelve combinations of feature type and assessment method. Model performance was assessed by concordance index (c-index) and fraction of new information from radiomic features. Results. The most stable phase spanned the whole range but was most often near exhale. All radiomic signatures provided new information for distant failure prediction. The personalised model had the highest c-index (0.77), and 58% of new information was provided by radiomic features when no stability assessment was performed. Conclusion. The most stable phase varies per-patient and selecting this improves model performance compared to standard methods. We advise the single most stable phase should be determined by minimising feature differences to neighbour phases. Stability assessment over all phases decreases performance by excessively removing features. Instead, averaging of neighbour phases should be used when stability is of concern. The models suggest that higher peritumoural intensity predicts distant failure.

Challenges in the target volume definition of lung cancer radiotherapy

Radiotherapy, with or without systemic treatment has an important role in the management of lung cancer. In order to deliver the treatment accurately, the clinician must precisely outline the gross tumour volume (GTV), mostly on computed tomography (CT) images. However, due to the limited contrast between tumour and non-malignant changes in the lung tissue, it can be difficult to distinguish the tumour boundaries on CT images leading to large interobserver variation and differences in interpretation. Therefore the definition of the GTV has often been described as the weakest link in radiotherapy with its inaccuracy potentially leading to missing the tumour or unnecessarily irradiating normal tissue. In this article, we review the various techniques that can be used to reduce delineation uncertainties in lung cancer.

Automated gross tumor volume contour generation for large-scale analysis of early-stage lung cancer patients planned with 4D-CT

PURPOSE

Patients with early-stage lung cancer undergoing stereotactic ablative radiotherapy receive four-dimensional computed tomography (4D-CT) for treatment planning. Often, an internal gross target volume (iGTV), which approximates the motion envelope of a tumor over the breathing cycle, is delineated without defining a gross tumor volume (GTV). However, the GTV volume and shape are important parameters for prognostic and dose modelling, and there is interest in radiomic features extracted from the GTV and surrounding tissue. We demonstrate and validate a method to generate the GTV from an iGTV contour to aid retrospective analysis on routine data.

METHOD

It is possible to reconstruct the geometry of a tumor with knowledge of tumor motion and the motion envelope formed during respiration. To demonstrate this, the tumor motion path was estimated with local rigid registration, and the iGTV positioned incrementally at stations along the reverse path. It is shown that the tumor volume is the largest set common to the intersection of the iGTV at these positions, hence can be derived. This was implemented for 521 lung lesions on 4D-CT. Eleven patients with a GTV delineation performed by a radiation oncologist on a reference phase (50%) were used for validation. The generated GTV was compared to that delineated by the expert using distance-to-agreement (DTA), volume, and distance between centres of mass. An overall success rate was determined by detecting registration inaccuracy and performing a quality check on the routine iGTV. For successfully generated contours, GTV volume was compared to iGTV volume in a prognostic model for overall survival.

RESULTS

For the validation dataset, DTA mean (0.79 - 1.55 mm) and standard deviation (0.68 - 1.51 mm) were comparable to expected observer variation. Difference in volume was < 5 cm³ , and average difference in position was 1.21 mm. Deviations in shape and position were mainly caused by observer differences in iGTV and GTV interpretation as opposed to algorithm performance. For the complete dataset, an acceptable contour was generated for 94% of patients using statistical and visual assessment to detect failures. Generated GTV volumes improved prognostic model performance over iGTV volumes.

CONCLUSION

A method to generate a GTV from an iGTV and 4D-CT dataset was developed. This method facilitates data analysis of patients with early-stage lung cancer treated in the routine setting, that is, data mining, prognostic modeling, and radiomics. Generation failure detection removes the need for visual assessment of all contours, reducing a time-consuming aspect of big-data analysis. Favorable prognostic performance of generated GTV volumes over iGTV ones demonstrates opportunities to use this methodology for future study.

Investigation of inter-fraction target motion variations in the context of pencil beam scanned proton therapy in non-small cell lung cancer patients

Purpose

For locally advanced‐stage non‐small cell lung cancer (NSCLC), inter‐fraction target motion variations during the whole time span of a fractionated treatment course are assessed in a large and representative patient cohort. The primary objective is to develop a suitable motion monitoring strategy for pencil beam scanning proton therapy (PBS‐PT) treatments of NSCLC patients during free breathing.

Methods

Weekly 4D computed tomography (4DCT; 41 patients) and daily 4D cone beam computed tomography (4DCBCT; 10 of 41 patients) scans were analyzed for a fully fractionated treatment course. Gross tumor volumes (GTVs) were contoured and the 3D displacement vectors of the centroid positions were compared for all scans. Furthermore, motion amplitude variations in different lung segments were statistically analyzed. The dosimetric impact of target motion variations and target motion assessment was investigated in exemplary patient cases.

Results

The median observed centroid motion was 3.4 mm (range: 0.2–12.4 mm) with an average variation of 2.2 mm (range: 0.1–8.8 mm). Ten of 32 patients (31.3%) with an initial motion <5 mm increased beyond a 5‐mm motion amplitude during the treatment course. Motion observed in the 4DCBCT scans deviated on average 1.5 mm (range: 0.0–6.0 mm) from the motion observed in the 4DCTs. Larger motion variations for one example patient compromised treatment plan robustness while no dosimetric influence was seen due to motion assessment biases in another example case.

Conclusions

Target motion variations were investigated during the course of radiotherapy for NSCLC patients. Patients with initial GTV motion amplitudes of < 2 mm can be assumed to be stable in motion during the treatment course. For treatments of NSCLC patients who exhibit motion amplitudes of > 2 mm, 4DCBCT should be considered for motion monitoring due to substantial motion variations observed.

Mid-position treatment strategy for locally advanced lung cancer: a dosimetric study

OBJECTIVE

The internal target volume (ITV) strategy generates larger planning target volumes (PTVs) in locally advanced non-small cell lung cancer (LA-NSCLC) than the Mid-position (Mid-p) strategy. We investigated the benefit of the Mid-p strategy regarding PTV reduction and dose to the organs at risk (OARs).

METHODS

44 patients with LA-NSCLC were included in a randomized clinical study to compare ITV and Mid-p strategies. GTV were delineated by a physician on maximum intensity projection images and on Mid-p images from four-dimensional CTs. CTVs were obtained by adding 6 mm uniform margin for microscopic extension. CTV to PTV margins were calculated using the van Herk's recipe for setup and delineation errors. For the Mid-p strategy, the mean target motion amplitude was added as a random error. For both strategies, three-dimensional conformal plans delivering 60-66 Gy to PTV were performed. PTVs, dose-volume parameters for OARs (lung, esophagus, heart, spinal cord) were reported and compared.

RESULTS

With the Mid-p strategy, the median of volume reduction was 23.5 cm3 (p = 0.012) and 8.8 cm3 (p = 0.0083) for PTVT and PTVN respectively; the median mean lung dose reduction was 0.51 Gy (p = 0.0057). For 37.1% of the patients, delineation errors led to smaller PTV with the ITV strategy than with the Mid-p strategy.

CONCLUSION

PTV and mean lung dose were significantly reduced using the Mid-p strategy. Delineation uncertainty can unfavorably impact the advantage.

ADVANCES IN KNOWLEDGE

To the best of our knowledge, this is the first dosimetric comparison study between ITV and Mid-p strategies for LA-NSCLC.

Impact of Peer Review in Reducing Uncertainty in the Definition of the Lung Target Volume Among Trainee Oncologists

AIMS

To evaluate the impact of peer review and contouring workshops on reducing uncertainty in target volume delineation for lung cancer radiotherapy.

MATERIALS AND METHODS

Data from two lung cancer target volume delineation courses were analysed. In total, 22 trainees in clinical oncology working across different UK centres attended these courses with priori experience in lung cancer radiotherapy. The courses were made up of short presentations and contouring practice sessions. The participants were divided into two groups and asked to first individually delineate (IND) and then individually peer review (IPR) the contours of another participant. The contours were discussed with an expert panel consisting of two consultant clinical oncologists and a consultant radiologist. Contours were analysed quantitatively by measuring the volume and local distance standard deviation (localSD) from the reference expert consensus contour and qualitatively through visual analysis. Feedback from the participants was obtained using a questionnaire.

RESULTS

All participants applied minor editing to the contours during IPR, leading to a non-statistically significant reduction in the mean delineated volume (IND = 140.92 cm3, IPR = 125.26 cm3, P = 0.211). The overall interobserver variation was similar, with a localSD of 0.33 cm and 0.38 cm for the IND and IPR, respectively (P = 0.848). Six participants (29%) carried out correct major changes by either including tumour or excluding healthy tissue. One participant (5%) carried out an incorrect edit by excluding parts of the tumour, while another observer failed to identify a major contour error. The participants' level of confidence in target volume delineation increased following the course and identified the discussions with the radiologist and colleagues as the most important highlights of the course.

CONCLUSION

IPR could improve target volume delineation quality among trainee oncologists by identifying most major contour errors. However, errors were also introduced after IPR, suggesting the need to further discuss major changes with a multidisciplinary team.

An evaluation of the mid-ventilation method for the planning of stereotactic lung plans

BACKGROUND AND PURPOSE

Stereotactic ablative body radiotherapy for lung plans requires 4DCT. Most radiotherapy centres use this to determine an internal target volume (ITV), despite studies suggesting that planning on a mid-ventilation (Mid-V) phase can reduce target volumes. The purpose of this study is two-fold: to determine whether the Mid-V approach provides adequate coverage and to discuss methods to enable the Mid-V approach to be applied more widely.

METHOD

4D scans of 79 patients were outlined on every phase. The mid-V phase was identified. Margins were determined from the range of motion, and plans generated with a 55 Gy prescription. A grid-based method was used to get the probability of tumour coverage in the presence of systematic and random uncertainties, with and without blurring for breathing motion.

RESULTS

For the Mid-V plans with the margins calculated from the van-Herk formula, after blurring doses for breathing, the coverage (dose covering 95% of the CTV 95% of the time) was greater than for plans with isotropic 5 mm margins uncorrected for breathing (58.2 Gy v 57.3 Gy). Similar results were obtained for a linear margin chosen as 0.15 of the breathing range. Deformable contour propagation in a commercial outlining system (ProSoma) identified the same mid-V phase in the majority of cases.

CONCLUSION

Our results confirm that a mid-V approach can be used to reduce the PTV size, with no loss of tumour coverage. We propose the use of a simplified margin formula equal to the margin ignoring breathing plus 0.15 of the range of motion.

[Image-guided radiotherapy in lung cancer]

Image-guided radiotherapy takes place at every step of the treatment in lung cancer, from treatment planning, with fusion imaging, to daily in-room repositioning. Managing tumoral and surrounding thoracic structures motion has been allowed since the routine use of 4D computed tomography (4DCT). The integration of respiratory motion has been made with "passive" techniques based on reconstruction images from 4DCT planning, or "active" techniques adapted to the patient's breathing. Daily repositioning is based on regular images, weekly or daily, low (kV) or high (MV) energy. MRI and functional imaging also play an important part in lung cancer radiation and open the way for adaptative radiotherapy.