Maximum-Intensity Volumes for Fast Contouring of Lung Tumors Including Respiratory Motion in 4DCT Planning

Smart contours: deep learning-driven internal gross tumor volume delineation in non-small cell lung cancer using 4D CT maximum and average intensity projections

BACKGROUND

Delineating the internal gross tumor volume (IGTV) is crucial for the treatment of non-small cell lung cancer (NSCLC). Deep learning (DL) enables the automation of this process; however, current studies focus mainly on multiple phases of four-dimensional (4D) computed tomography (CT), which leads to indirect results. This study proposed a DL-based method for automatic IGTV delineation using maximum and average intensity projections (MIP and AIP, respectively) from 4D CT.

METHODS

We retrospectively enrolled 124 patients with NSCLC and divided them into training (70%, n = 87) and validation (30%, n = 37) cohorts. Four-dimensional CT images were acquired, and the corresponding MIP and AIP images were generated. The IGTVs were contoured on 4D CT and used as the ground truth (GT). The MIP or AIP images, along with the corresponding IGTVs (IGTVMIP-manu and IGTVAIP-manu, respectively), were fed into the DL models for training and validation. We assessed the performance of three segmentation models-U-net, attention U-net, and V-net-using the Dice similarity coefficient (DSC) and the 95th percentile of the Hausdorff distance (HD95) as the primary metrics.

RESULTS

The attention U-net model trained on AIP images presented a mean DSC of 0.871 ± 0.048 and mean HD95 of 2.958 ± 2.266 mm, whereas the model trained on MIP images achieved a mean DSC of 0.852 ± 0.053 and mean HD95 of 3.209 ± 2.136 mm. Among the models, attention U-net and U-net achieved similar results, considerably surpassing V-net.

CONCLUSIONS

DL models can automate IGTV delineation using MIP and AIP images, streamline contouring, and enhance the accuracy and consistency of lung cancer radiotherapy planning to improve patient outcomes.

Cardiac motion and its dosimetric impact during radioablation for refractory ventricular tachycardia

INTRODUCTION

Cardiac radioablation (CR) is a noninvasive treatment option for patients with refractory ventricular tachycardia (VT) during which high doses of radiation, typically 25 Gy, are delivered to myocardial scar. In this study, we investigate motion from cardiac cycle and evaluate the dosimetric impact in a cohort of patients treated with CR.

METHODS

This retrospective study included eight patients treated at our institution who had respiratory-correlated and ECG-gated 4DCT scans acquired within 2 weeks of CR. Deformable image registration was applied between maximum systole (SYS) and diastole (DIAS) CTs to assess cardiac motion. The average respiratory-correlated CT (AVG_resp ) was deformably registered to the average cardiac (AVG_cardiac ), SYS, and DIAS CTs, and contours were propagated using the deformation vector fields (DVFs). Finally, the original treatment plan was recalculated on the deformed AVG_resp CT for dosimetric assessment.

RESULTS

Motion magnitudes were measured as the mean (SD) value over the DVFs within each structure. Displacement during the cardiac cycle for all chambers was 1.4 (0.9) mm medially/laterally (ML), 1.6 (1.0) mm anteriorly/posteriorly (AP), and 3.0 (2.8) mm superiorly/inferiorly (SI). Displacement for the 12 distinct clinical target volumes (CTVs) was 1.7 (1.5) mm ML, 2.4 (1.1) mm AP, and 2.1 (1.5) SI. Displacements between the AVG_resp and AVG_cardiac scans were 4.2 (2.0) mm SI and 5.8 (1.4) mm total. Dose recalculations showed that cardiac motion may impact dosimetry, with dose to 95% of the CTV dropping from 27.0 (1.3) Gy on the AVG_resp to 20.5 (7.1) Gy as estimated on the AVG_cardiac .

CONCLUSIONS

Cardiac CTV motion in this patient cohort is on average below 3 mm, location-dependent, and when not accounted for in treatment planning may impact target coverage. Further study is needed to assess the impact of cardiac motion on clinical outcomes.

Respiratory motion management for external radiotherapy treatment

We present the update of the recommendations of the French society of oncological radiotherapy on respiratory motion management for external radiotherapy treatment. Since twenty years and the report 62 of ICRU, motion management during the course of radiotherapy treatment has become an increasingly significant concern, particularly with the development of hypofractionated treatments under stereotactic conditions, using reduced safety margins. This article related orders of motion amplitudes for different organs as well as the definition of the margins in radiotherapy. An updated review of the various movement management strategies is presented as well as main technological solutions enabling them to be implemented: when acquiring anatomical data, during planning and when carrying out treatment. Finally, the management of these moving targets, such as it can be carried out in radiotherapy departments, will be detailed for a few concrete examples of localizations (abdominal, thoracic and hepatic).

A comparative study of the normal oesophageal wall thickness based on 3-dimensional, 4-dimensional, and cone beam computed tomography

BACKGROUND

The study aimed to compare normal oesophageal wall thickness based on 3-dimensional computed tomography (3DCT), 4-dimensional computed tomography (4DCT) and cone beam computed tomography (CBCT).

METHODS

Contrast-enhanced 3DCT, 4DCT, and CBCT scans were acquired from 50 patients with lung cancer or metastatic lung cancer. The outer oesophageal wall was manually contoured on each 3DCT, the maximum intensity projection of 4DCT (4DCTMIP) the end expiration phase of 4DCT (4DCT50) (the end expiration phase of 4DCT) and the CBCT data sets. The average wall thicknesses were measured (defined as R3DCT, R50, RMIP, and RCBCT).

RESULTS

Whether for thoracic or for intra-abdominal segments, there were no significant differences between R3DCT and R50, but significant differences between R3DCT and RMIP, R3DCT and RCBCT. For upper and middle oesophagus, RCBCT were larger than RMIP. There was no significant difference between upper and middle segments on 3DCT, 4DCT, and CBCT. Intra-abdominal oesophageal wall thickness was greater than that of thoracic oesophagus. There were no differences between upper and lower, and middle and lower oesophagus on CBCT.

CONCLUSION

Our findings indicate normal oesophageal wall thickness differed along the length of oesophagus whatever it was delineated on 3DCT, 4DCT (4DCT50 and 4DCTMIP) or CBCT. It is reasonable to use uniform criterion to identify normal esophageal wall thickness when delineating gross tumor volume on 3DCT and 4DCT50, the same is true of delineating internal gross tumor volume on 4DCTMIP or CBCT images for lower and intra-abdominal oesophagus. But, in spite of using contrast-enhanced scanning, relatively blurred boundary on the CBCT images is noteworthy, especially for upper and middle thoracic esophagus.

Four-dimensional Plan Optimization for the Treatment of Lung Tumors Using Pencil-beam Scanning Proton Radiotherapy

Purpose 

This study aimed to evaluate the effectiveness of four-dimensional (4D) robust optimization for proton pencil-beam scanning (PBS) treatment of lung tumors.

Patients and methods 

In seven patients with lung cancer, proton beam therapy was planned using 4D robust optimization over 4D computed tomography (CT) data sets. The gross target volume (GTV) was contoured based on individual breathing phases, and a 5-mm expansion was used to generate the clinical target volume (CTV) for each phase. The 4D optimization was conducted directly on the 4D CT data set. The robust optimization settings included a CT Hounsfield unit (HU) uncertainty of 4% and a setup uncertainty of 5 mm to obtain the CTV. Additional target dose objectives such as those for the internal target volume (ITV) as well as the organ-at-risk (OAR) dose requirements were placed on the average CT. For comparison, three-dimensional (3D) robust optimization was also performed on the average CT. An additional verification 4D CT was performed to verify plan robustness against inter-fractional variations.

Results 

Target coverages were generally higher for 4D optimized plans. The difference was most pronounced for ITV V70Gy when evaluating individual breathing phases. The 4D optimized plans were shown to be able to maintain the ITV coverage at full prescription, while 3D optimized plans could not. More importantly, this difference in ITV V70Gy between the 4D and 3D optimized plans was also consistently observed when evaluating the verification 4D CT, indicating that the 4D optimized plans were more robust against inter-fractional variations. Less difference was seen between the 4D and 3D optimized plans in the lungs criteria: V5Gy and V20Gy.

Conclusion 

The proton PBS treatment plans optimized directly on the 4D CT were shown to be more robust when compared to those optimized on a regular 3D CT. Robust 4D optimization can improve the target coverage for the proton PBS lung treatments.

Advances in the use of motion management and image guidance in radiation therapy treatment for lung cancer

The development of advanced radiation technologies, including intensity-modulated radiation therapy (IMRT), stereotactic body radiation therapy (SBRT) and proton therapy, has resulted in increasingly conformal radiation treatments. Recent evidence for the importance of minimizing dose to normal critical structures including the heart and lungs has led to incorporation of these advanced treatment modalities into radiation therapy (RT) for non-small cell lung cancer (NSCLC). While such technologies have allowed for improved dose delivery, implementation requires improved target accuracy with treatments, placing increasing importance on evaluating tumor motion at the time of planning and verifying tumor position at the time of treatment. In this review article, we describe issues and updates related both to motion management and image guidance in the treatment of NSCLC.

Optimizing immobilization, margins, and imaging for lung stereotactic body radiation therapy

The simultaneous advancement of technologies for the delivery of precisely targeted radiation therapy and the paradigm shift to substantial hypofractionation have led to significant improvements in the treatment of early stage non-small cell lung cancer (ES-NSCLC). Stereotactic body radiation therapy (SBRT) has become a well-established option for the treatment of ES-NSCLC and is now becoming widely available within the radiation oncology community. Implementation of this technique, however, requires highly accurate target delineation, thorough evaluation of tumor motion, and improved on-board imaging at the time of treatment for patient alignment, each of which is critical for successful tumor control and mitigation of risks to normal tissues. In this article, we review updates and issues related to immobilization and image guidance for SBRT in the treatment of ES-NSCLC.

Motion management strategies and technical issues associated with stereotactic body radiotherapy of thoracic and upper abdominal tumors: A review from NRG oncology

The efficacy of stereotactic body radiotherapy (SBRT) has been well demonstrated. However, it presents unique challenges for accurate planning and delivery especially in the lungs and upper abdomen where respiratory motion can be significantly confounding accurate targeting and avoidance of normal tissues. In this paper, we review the current literature on SBRT for lung and upper abdominal tumors with particular emphasis on addressing respiratory motion and its affects. We provide recommendations on strategies to manage motion for different, patient-specific situations. Some of the recommendations will potentially be adopted to guide clinical trial protocols.

Advances in radiotherapy techniques and delivery for non-small cell lung cancer: benefits of intensity-modulated radiation therapy, proton therapy, and stereotactic body radiation therapy

The 21st century has seen several paradigm shifts in the treatment of non-small cell lung cancer (NSCLC) in early-stage inoperable disease, definitive locally advanced disease, and the postoperative setting. A key driver in improvement of local disease control has been the significant evolution of radiation therapy techniques in the last three decades, allowing for delivery of definitive radiation doses while limiting exposure of normal tissues. For patients with locally-advanced NSCLC, the advent of volumetric imaging techniques has allowed a shift from 2-dimensional approaches to 3-dimensional conformal radiation therapy (3DCRT). The next generation of 3DCRT, intensity-modulated radiation therapy and volumetric-modulated arc therapy (VMAT), have enabled even more conformal radiation delivery. Clinical evidence has shown that this can improve the quality of life for patients undergoing definitive management of lung cancer. In the early-stage setting, conventional fractionation led to poor outcomes. Evaluation of altered dose fractionation with the previously noted technology advances led to advent of stereotactic body radiation therapy (SBRT). This technique has dramatically improved local control and expanded treatment options for inoperable, early-stage patients. The recent development of proton therapy has opened new avenues for improving conformity and the therapeutic ratio. Evolution of newer proton therapy techniques, such as pencil-beam scanning (PBS), could improve tolerability and possibly allow reexamination of dose escalation. These new progresses, along with significant advances in systemic therapies, have improved survival for lung cancer patients across the spectrum of non-metastatic disease. They have also brought to light new challenges and avenues for further research and improvement.

Target volume and artifact evaluation of a new data-driven 4D CT

PURPOSE

Four-dimensional computed tomography (4D CT) is often used to define the internal gross target volume (IGTV) for radiation therapy of lung cancer. Traditionally, this technique requires the use of an external motion surrogate; however, a new image, data-driven 4D CT, has become available. This study aims to describe this data-driven 4D CT and compare target contours created with it to those created using standard 4D CT.

METHODS AND MATERIALS

Cine CT data of 35 patients undergoing stereotactic body radiation therapy were collected and sorted into phases using standard and data-driven 4D CT. IGTV contours were drawn using a semiautomated method on maximum intensity projection images of both 4D CT methods. Errors resulting from reproducibility of the method were characterized. A comparison of phase image artifacts was made using a normalized cross-correlation method that assigned a score from +1 (data-driven "better") to -1 (standard "better").

RESULTS

The volume difference between the data-driven and standard IGTVs was not significant (data driven was 2.1 ± 1.0% smaller, P = .08). The Dice similarity coefficient showed good similarity between the contours (0.949 ± 0.006). The mean surface separation was 0.4 ± 0.1 mm and the Hausdorff distance was 3.1 ± 0.4 mm. An average artifact score of +0.37 indicated that the data-driven method had significantly fewer and/or less severe artifacts than the standard method (P = 1.5 × 10^-5 for difference from 0).

CONCLUSIONS

On average, the difference between IGTVs derived from data-driven and standard 4D CT was not clinically relevant or statistically significant, suggesting data-driven 4D CT can be used in place of standard 4D CT without adjustments to IGTVs. The relatively large differences in some patients were usually attributed to limitations in automatic contouring or differences in artifacts. Artifact reduction and setup simplicity suggest a clinical advantage to data-driven 4D CT.

Evaluation of 4D CT acquisition methods designed to reduce artifacts

Four-dimensional computed tomography (4D CT) is used to account for respiratory motion in radiation treatment planning, but artifacts resulting from the acquisition and postprocessing limit its accuracy. We investigated the efficacy of three experimental 4D CT acquisition methods to reduce artifacts in a prospective institutional review board approved study. Eighteen thoracic patients scheduled to undergo radiation therapy received standard clinical 4D CT scans followed by each of the alternative 4D CT acquisitions: 1) data oversampling, 2) beam gating with breathing irregularities, and 3) rescanning the clinical acquisition acquired during irregular breathing. Relative values of a validated correlation-based artifact metric (CM) determined the best acquisition method per patient. Each 4D CT was processed by an extended phase sorting approach that optimizes the quantitative artifact metric (CM sorting). The clinical acquisitions were also postprocessed by phase sorting for artifact comparison of our current clinical implementation with the experimental methods. The oversampling acquisition achieved the lowest artifact presence among all acquisitions, achieving a 27% reduction from the current clinical 4D CT implementation (95% confidence interval = 34-20). The rescan method presented a significantly higher artifact presence from the clinical acquisition (37%; p < 0.002), the gating acquisition (26%; p < 0.005), and the oversampling acquisition (31%; p < 0.001), while the data lacked evidence of a significant difference between the clinical, gating, and oversampling methods. The oversampling acquisition reduced artifact presence from the current clinical 4D CT implementation to the largest degree and provided the simplest and most reproducible implementation. The rescan acquisition increased artifact presence significantly, compared to all acquisitions, and suffered from combination of data from independent scans over which large internal anatomic shifts occurred.

Intensity-Modulated Radiotherapy versus 3-Dimensional Conformal Radiotherapy Strategies for Locally Advanced Non-Small-Cell Lung Cancer

Chemoradiotherapy is the current standard of care in patients with advanced inoperable stage IIIA or IIIB non-small cell lung cancer (NSCLC). Three-dimensional radiotherapy (3DCRT) has been a trusted method for a long time and has well-known drawbacks, most of which could be improved by Intensity Modulated Radiotherapy (IMRT). IMRT is not currently the standard treatment of locally advanced NSCLC, but almost all patients could benefit to a degree in organ at risk sparing, dose coverage conformality, or dose escalation. The most critical step for a radiation oncology department is to strictly evaluate its own technical and physical capabilities to determine the ability of IMRT to deliver an optimal treatment plan. This includes calculating the internal tumor motion (ideally 4DCT or equivalent techniques), treatment planning software with an up-to-date heterogeneity correction algorithm, and daily image guidance. It is crucial to optimise and individualise the therapeutic ratio for each patient during the decision of 3DCRT versus IMRT. The current literature rationalises the increasing use of IMRT, including 4D imaging plus PET/CT, and encourages the applicable knowledge-based and individualised dose escalation using advanced daily image-guided radiotherapy.

Time-adjusted internal target volume: a novel approach focusing on heterogeneity of tumor motion based on 4-dimensional computed tomography imaging for radiation therapy planning of lung cancer

PURPOSE

To consider nonuniform tumor motion within the internal target volume (ITV) by defining time-adjusted ITV (TTV), a volume designed to include heterogeneity of tumor existence on the basis of 4-dimensional computed tomography (4D-CT).

METHODS AND MATERIALS

We evaluated 30 lung cancer patients. Breath-hold CT (BH-CT) and free-breathing 4D-CT scans were acquired for each patient. The tumors were manually delineated using a lung CT window setting (window, 1600 HU; level, -300 HU). Tumor in BH-CT images was defined as gross tumor volume (GTV), and the sum of tumors in 4D-CT images was defined as ITV-4D. The TTV images were generated from the 4D-CT datasets, and the tumor existence probability within ITV-4D was calculated. We calculated the TTV80 value, which is the percentage of the volume with a tumor existence probability that exceeded 80% on ITV-4D. Several factors that affected the TTV80 value, such as the ITV-4D/GTV ratio or tumor centroid deviation, were evaluated.

RESULTS

Time-adjusted ITV images were acquired for all patients, and tumor respiratory motion heterogeneity was visualized. The median (range) ITV-4D/GTV ratio and median tumor centroid deviation were 1.6 (1.0-4.1) and 6.3 mm (0.1-30.3 mm), respectively. The median TTV80 value was 43.3% (2.9-98.7%). Strong correlations were observed between the TTV80 value and the ITV-4D/GTV ratio (R=-0.71) and tumor centroid deviation (R=-0.72). The TTV images revealed the tumor motion pattern features within ITV.

CONCLUSIONS

The TTV images reflected nonuniform tumor motion, and they revealed the tumor motion pattern features, suggesting that the TTV concept may facilitate various aspects of radiation therapy planning of lung cancer while incorporating respiratory motion in the future.

Geometrical differences in target volumes based on 18F-fluorodeoxyglucose positron emission tomography/computed tomography and four-dimensional computed tomography maximum intensity projection images of primary thoracic esophageal cancer

The objective of the study was to compare geometrical differences of target volumes based on four-dimensional computed tomography (4DCT) maximum intensity projection (MIP) and 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) images of primary thoracic esophageal cancer for radiation treatment. Twenty-one patients with thoracic esophageal cancer sequentially underwent contrast-enhanced three-dimensional computed tomography (3DCT), 4DCT, and 18F-FDG PET/CT thoracic simulation scans during normal free breathing. The internal gross target volume defined as IGTVMIP was obtained by contouring on MIP images. The gross target volumes based on PET/CT images (GTVPET ) were determined with nine different standardized uptake value (SUV) thresholds and manual contouring: SUV≥2.0, 2.5, 3.0, 3.5 (SUVn); ≥20%, 25%, 30%, 35%, 40% of the maximum (percentages of SUVmax, SUVn%). The differences in volume ratio (VR), conformity index (CI), and degree of inclusion (DI) between IGTVMIP and GTVPET were investigated. The mean centroid distance between GTVPET and IGTVMIP ranged from 4.98 mm to 6.53 mm. The VR ranged from 0.37 to 1.34, being significantly (P<0.05) closest to 1 at SUV2.5 (0.94), SUV20% (1.07), or manual contouring (1.10). The mean CI ranged from 0.34 to 0.58, being significantly closest to 1 (P<0.05) at SUV2.0 (0.55), SUV2.5 (0.56), SUV20% (0.56), SUV25% (0.53), or manual contouring (0.58). The mean DI of GTVPET in IGTVMIP ranged from 0.61 to 0.91, and the mean DI of IGTVMIP in GTVPET ranged from 0.34 to 0.86. The SUV threshold setting of SUV2.5, SUV20% or manual contouring yields the best tumor VR and CI with internal-gross target volume contoured on MIP of 4DCT dataset, but 3DPET/CT and 4DCT MIP could not replace each other for motion encompassing target volume delineation for radiation treatment.

Comparison of patient-specific internal gross tumor volume for radiation treatment of primary esophageal cancer based separately on three-dimensional and four-dimensional computed tomography images

To compare the target volume, position and matching index of the patient-specific internal gross tumor volume (IGTV) based on three-dimensional (3D) and four-dimensional (4D) computed tomography (CT) images for primary esophageal cancer. Twenty-nine patients with primary thoracic esophageal cancer underwent 3DCT and 4DCT scans during free breathing. IGTVs were constructed using three approaches: combining the gross target volumes from the 10 respiratory phases of the 4DCT dataset to produce IGTV10 ; IGTV2 was acquired by combining the two extreme phases; and IGTV3D was created from the 3DCT-based gross target volume by enlarging the 95th percentile of motion in each direction measured by the 4DCT. 0.16 cm lateral (LR), 0.14 cm anteroposterior (AP) and 0.29 cm superoinferior (SI) in the upper; 0.18 cm LR, 0.10 cm AP and 0.63 cm SI in the middle; and 0.40 cm LR, 0.58 cm AP and 0.82 cm in the lower thoracic esophagus could account for 95% of respiratory-induced tumor motion. The centroid position shift between IGTV10 and IGTV2 was all below 0.10 cm, and less than 0.20 cm between IGTV10 and IGTV3D . IGTV10 was bigger than IGTV2 ; the mean value of matching index for IGTV2 to IGTV10 was 0.87 ± 0.05, 0.85 ± 0.06 and 0.83 ± 0.05 for upper, middle and distal thoracic esophageal tumors, respectively, and just 0.57 ± 0.11, 0.56 ± 0.13 and 0.40 ± 0.03 between IGTV3D and IGTV10 . 4DCT-based IGTV10 is a reasonable patient-specific IGTV for primary thoracic esophageal cancer, and IGTV2 is considered as an acceptable alternative to IGTV10 . However, it seems unreasonable to use IGTV3D substitute IGTV10 .

Evolution of modern-era radiotherapy strategies for unresectable advanced non-small-cell lung cancer

SUMMARY In patients with advanced non-small-cell lung cancer, the current standard of care is chemoradiotherapy, which offers better outcomes than sequential treatments. Conventional radiotherapy (60–66 Gy) is associated with poor local control and dismal survival. The challenge is to escalate and/or accelerate the radiation dose safely and effectively. Cutting-edge technologies, such as 4D image-based motion management, intensity-modulated radiation therapy, proton therapy and image-guided radiotherapy, have enabled the delivery of higher doses of radiation to the difficult-to-treat moving tumors with lower toxicity risks. Incorporating the motion in 4D planning, such as an average internal target volume, would enable radiation oncologists to integrate the interfractional anatomic changes in the course of treatment for proper estimation of the actual dose delivery. Optimizing the combination of systemic therapy with radiotherapy, using a personalized approach based on using cutting-edge technologies for knowledge-guided dose escalation/acceleration radiotherapy, are crucial to improving the therapeutic ratio of non-small-cell lung cancer.

Use of combined maximum and minimum intensity projections to determine internal target volume in 4-dimensional CT scans for hepatic malignancies

BACKGROUND

To evaluate the accuracy of the combined maximum and minimum intensity projection-based internal target volume (ITV) delineation in 4-dimensional (4D) CT scans for liver malignancies.

METHODS

4D CT with synchronized IV contrast data were acquired from 15 liver cancer patients (4 hepatocellular carcinomas; 11 hepatic metastases). We used five approaches to determine ITVs: (1). ITVAllPhases: contouring gross tumor volume (GTV) on each of 10 respiratory phases of 4D CT data set and combining these GTVs; (2). ITV2Phase: contouring GTV on CT of the peak inhale phase (0% phase) and the peak exhale phase (50%) and then combining the two; (3). ITVMIP: contouring GTV on MIP with modifications based on physician's visual verification of contours in each respiratory phase; (4). ITVMinIP: contouring GTV on MinIP with modification by physician; (5). ITV2M: combining ITVMIP and ITVMinIP. ITVAllPhases was taken as the reference ITV, and the metrics used for comparison were: matching index (MI), under- and over-estimated volume (Vunder and Vover).

RESULTS

4D CT images were successfully acquired from 15 patients and tumor margins were clearly discernable in all patients. There were 9 cases of low density and 6, mixed on CT images. After comparisons of metrics, the tool of ITV2M was the most appropriate to contour ITV for liver malignancies with the highest MI of 0.93 ± 0.04 and the lowest proportion of Vunder (0.07 ± 0.04). Moreover, tumor volume, target motion three-dimensionally and ratio of tumor vertical diameter over tumor motion magnitude in cranio-caudal direction did not significantly influence the values of MI and proportion of Vunder.

CONCLUSION

The tool of ITV2M is recommended as a reliable method for generating ITVs from 4D CT data sets in liver cancer.

Failure mode and effect analysis for delivery of lung stereotactic body radiation therapy

PURPOSE

To improve the quality and safety of our practice of stereotactic body radiation therapy (SBRT), we analyzed the process following the failure mode and effects analysis (FMEA) method.

METHODS

The FMEA was performed by a multidisciplinary team. For each step in the SBRT delivery process, a potential failure occurrence was derived and three factors were assessed: the probability of each occurrence, the severity if the event occurs, and the probability of detection by the treatment team. A rank of 1 to 10 was assigned to each factor, and then the multiplied ranks yielded the relative risks (risk priority numbers). The failure modes with the highest risk priority numbers were then considered to implement process improvement measures.

RESULTS

A total of 28 occurrences were derived, of which nine events scored with significantly high risk priority numbers. The risk priority numbers of the highest ranked events ranged from 20 to 80. These included transcription errors of the stereotactic coordinates and machine failures.

CONCLUSION

Several areas of our SBRT delivery were reconsidered in terms of process improvement, and safety measures, including treatment checklists and a surgical time-out, were added for our practice of gantry-based image-guided SBRT. This study serves as a guide for other users of SBRT to perform FMEA of their own practice.

Improving target delineation on 4-dimensional CT scans in stage I NSCLC using a deformable registration tool

INTRODUCTION

Correct target definition is crucial in stereotactic radiotherapy for lung tumors. We evaluated use of deformable registration (DR) for target contouring on 4-dimensional (4D) CT scans.

MATERIALS AND METHODS

Three clinicians contoured gross tumor volume (GTV) in an end-inspiration phase of 4DCT of 6 patients on two occasions. Two clinicians contoured GTVs in all phases of 4DCT and on maximum intensity projections (MIP). The initial GTV was auto-propagated to 9 other phases using a B-spline algorithm (VelocityAI). Internal target volumes (ITVs) generated were (i) ITV(10manual) encompassing all physician-contoured GTVs, (ii) ITV-MIP(optimized) from MIP after review of individual 4DCT phases, (iii) ITV(10deformed) encompassing auto-propagated GTVs using DR, and (iv) ITV(10deformed-optimized), from an ITV(10deformed) target that was modified to form a 'clinically optimal' ITV. Volume-overlaps were scored using Dice's Similarity Coefficients (DSCs).

RESULTS

Intra-clinician GTV reproducibility was greater than inter-clinician reproducibility (mean DSC 0.93 vs. 0.88, p<0.0004). In five of 6 patients, ITV-MIP(optimized) differed from the ITV(10deformed-optimized). In all patients, the DSC between ITV(10deformed-optimized) and ITV(10deformed) was higher than that between ITV(10deformed-optimized) and ITV-MIP(optimized) (p<0.02 T-test).

CONCLUSION

ITVs created in stage I tumors using DR were closer to 'clinically optimal' ITVs than was the case with a MIP-modified approach.

[Scan acquisition parameter optimization for the treatment of moving tumors in radiotherapy]

AIM OF THE STUDY

In the case of lung tumor treatment, to adjust 3D helical computed tomography (CT) acquisition parameters using a dynamic phantom and compare to the theory the volumes of a moving object.

MATERIALS AND METHODS

Three helical CT acquisitions were compared using a Big Bore CT scan : an "initial" 3D CT scan (constructor parameters), an "optimized" 3D CT scan which parameters are chosen to obtain an axial slow scan like acquisition and a 4D CT scan. We used a phantom composed by a ball filled with water set on a dynamic platform moving in the antero-posterior or cranio-caudal direction with a 14 mm amplitude and a 4s period. For each acquisition and modality (static and dynamic), we quantified the ball volume by automatic contouring and we estimated relative errors.

RESULTS

For an antero-posterior displacement, the volume of the moving ball is under estimated by 14.1 % with the "initial" scan, by 0.2 % with the "optimized" scan and over estimated by 0.8 % with the averaged 4D scan. For a cranio-caudal displacement, it is under estimated by about 22 % with the "initial" scan and by about 1 % with the "optimized" scan and the averaged 4D scan.

CONCLUSION

Volume measurements performed with the dynamic phantom allowed us to validate the "optimized" 3D CT scan parameters because it accurately reflects the volume of a moving object. Radiotherapy departments without 4D CT should adapt scan parameters for internal target volume definition.

Thoracic target volume delineation using various maximum-intensity projection computed tomography image sets for radiotherapy treatment planning

PURPOSE

Four-dimensional computed tomography (4D-CT) is commonly used to account for respiratory motion of target volumes in radiotherapy to the thorax. From the 4D-CT acquisition, a maximum-intensity projection (MIP) image set can be created and used to help define the tumor motion envelope or the internal gross tumor volume (iGTV). The purpose of this study was to quantify the differences in automatically contoured target volumes for usage in the delivery of stereotactic body radiation therapy using MIP data sets generated from one of the four methods: (1) 4D-CT phase-binned (PB) based on retrospective phase calculations, (2) 4D-CT phase-corrected phase-binned (PC-PB) based on motion extrema, (3) 4D-CT amplitude-binned (AB), and (4) cine CT built from all available images.

METHODS

MIP image data sets using each of the four methods were generated for a cohort of 28 patients who had prior thoracic 4D-CT scans that exhibited lung tumor motion of at least 1 cm. Each MIP image set was automatically contoured on commercial radiation treatment planning system. Margins were added to the iGTV to observe differences in the final simulated planning target volumes (PTVs).

RESULTS

For all patients, the iGTV measured on the MIP generated from the entire cine CT data set (iGTVcine) was the largest. Expressed as a percentage of iGTVcine, 4D-CT iGTV (all sorting methods) ranged from 83.8% to 99.1%, representing differences in the absolute volume ranging from 0.02 to 4.20 cm3; the largest average and range of 4D-CT iGTV measurements was from the PC-PB data set. Expressed as a percentage of PTVcine (expansions applied to iGTVeine), the 4D-CT PTV ranged from 87.6% to 99.6%, representing differences in the absolute volume ranging from 0.08 to 7.42 cm3. Regions of the measured respiratory waveform corresponding to a rapid change of phase or amplitude showed an increased susceptibility to the selection of identical images for adjacent bins. Duplicate image selection was most common in the AB implementation, followed by the PC-PB method. The authors also found that the image associated with the minimum amplitude measurement did not always correlate with the image that showed maximum tumor motion extent.

CONCLUSIONS

The authors identified cases in which the MIP generated from a 4D-CT sorting process under-represented the iGTV by more than 10% or up to 4.2 cm3 when compared to the iGTVcine. They suggest utilization of a MIP generated from the full cine CT data set to ensure maximum inclusive tumor extent.

Inferring positions of tumor and nodes in Stage III lung cancer from multiple anatomical surrogates using four-dimensional computed tomography

PURPOSE

To investigate the feasibility of modeling Stage III lung cancer tumor and node positions from anatomical surrogates.

METHODS AND MATERIALS

To localize their centroids, the primary tumor and lymph nodes from 16 Stage III lung cancer patients were contoured in 10 equal-phase planning four-dimensional (4D) computed tomography (CT) image sets. The centroids of anatomical respiratory surrogates (carina, xyphoid, nipples, mid-sternum) in each image set were also localized. The correlations between target and surrogate positions were determined, and ordinary least-squares (OLS) and partial least-squares (PLS) regression models based on a subset of respiratory phases (three to eight randomly selected) were created to predict the target positions in the remaining images. The three-phase image sets that provided the best predictive information were used to create models based on either the carina alone or all surrogates.

RESULTS

The surrogate most correlated with target motion varied widely. Depending on the number of phases used to build the models, mean OLS and PLS errors were 1.0 to 1.4 mm and 0.8 to 1.0 mm, respectively. Models trained on the 0%, 40%, and 80% respiration phases had mean (+/- standard deviation) PLS errors of 0.8 +/- 0.5 mm and 1.1 +/- 1.1 mm for models based on all surrogates and carina alone, respectively. For target coordinates with motion >5 mm, the mean three-phase PLS error based on all surrogates was 1.1 mm.

CONCLUSIONS

Our results establish the feasibility of inferring primary tumor and nodal motion from anatomical surrogates in 4D CT scans of Stage III lung cancer. Using inferential modeling to decrease the processing time of 4D CT scans may facilitate incorporation of patient-specific treatment margins.

Target definition of moving lung tumors in positron emission tomography: correlation of optimal activity concentration thresholds with object size, motion extent, and source-to-background ratio

PURPOSE

Hardware integration of fluorodeoxyglucose positron emission tomography (PET) with computed tomography (CT) in combined PET/CT scanners has provided radiation oncologists and physicists with new possibilities for 3-D treatment simulation. The use of PET/CT simulation for target delineation of lung cancer is becoming popular and many studies concerning automatic segmentation of PET images have been performed. Several of these studies consider size and source-to-background (SBR) in their segmentation methods but neglect respiratory motion. The purpose of the current study was to develop a functional relationship between optimal activity concentration threshold, tumor volume, motion extent, and SBR using multiple regression techniques by performing an extensive series of phantom scans simulating tumors of varying sizes, SBR, and motion amplitudes. Segmented volumes on PET were compared with the "motion envelope" of the moving sphere defined on cine CT.

METHODS

A NEMA IEC thorax phantom containing six spheres (inner diameters ranging from 10 to 37 mm) was placed on a motion platform and moved sinusoidally at 0-30 mm (at 5 mm intervals) and six different SBRs (ranging from 5:1 to 50:1), producing 252 combinations of experimental parameters. PET images were acquired for 18 min and split into three 6 min acquisitions for reproducibility. The spheres (blurred on PET images due to motion) were segmented at 1% of maximum activity concentration intervals. The optimal threshold was determined by comparing deviations between the threshold volume surfaces with a reference volume surface defined on cine CT. Optimal activity concentration thresholds were normalized to background and multiple regression was used to determine the relationship between optimal threshold, volume, motion, and SBR. Standardized regression coefficients were used to assess the relative influence of each variable. The segmentation model was applied to three lung cancer patients and segmented regions of interest were compared with those segmented on cine CT.

RESULTS

The resulting model and coefficients provided a functional form that fit the phantom data with an adjusted R2 = 0.96. The most significant contributor to threshold level was SBR. Surfaces of PET-segmented volumes of three lung cancer patients were within 2 mm of the reference CT volumes on average.

CONCLUSIONS

The authors successfully developed an expression for optimal activity concentration threshold as a function of object volume, motion, and SBR.

How many sets of 4DCT images are sufficient to determine internal target volume for liver radiotherapy?

BACKGROUND AND PURPOSE

To determine the feasibility of using limited four-dimensional computed tomography (4DCT) images for treatment planning.

MATERIALS AND METHODS

The 4DCT scans of 16 patients with hepatocellular carcinoma (HCC) were analyzed. Gross tumor volumes (GTVs) were manually contoured on all 10 respiratory phases, and different internal clinical target volumes (ICTVs) were derived by encompassing volumes of the respective CTVs. Volume, position, and shape of ICTVs were calculated and compared.

RESULTS

The ICTV(2 phases), ICTV(3 phases), ICTV(4 phases), and ICTV(6 phases) all showed excellent agreement with ICTV(10 phases), and the ICTV(2 phases) encompassed ICTV(10 phases) by 94.1+/-1.8% on average. The 3D shift between the centers of mass of the ICTVs was only 0.6mm. The surface distance between ICTV(10 phases) and ICTV(2 phases) was 1.7+/-0.8mm in the left-right (LR) and anteroposterior (AP) directions.

CONCLUSIONS

Contouring two extreme phases at end-inhalation and end-exhalation is a reasonably safe and labor-saving method of deriving ITV for liver radiotherapy with low and medium tumor motion amplitude (1.6 cm). Whether the larger tumor movement affects the results is the subject of ongoing research.

Dose calculation with respiration-averaged CT processed from cine CT without a respiratory surrogate

Dose calculation for thoracic radiotherapy is commonly performed on a free-breathing helical CT despite artifacts caused by respiratory motion. Four-dimensional computed tomography (4D-CT) is one method to incorporate motion information into the treatment planning process. Some centers now use the respiration-averaged CT (RACT), the pixel-by-pixel average of the ten phases of 4D-CT, for dose calculation. This method, while sparing the tedious task of 4D dose calculation, still requires 4D-CT technology. The authors have recently developed a means to reconstruct RACT directly from unsorted cine CT data from which 4D-CT is formed, bypassing the need for a respiratory surrogate. Using RACT from cine CT for dose calculation may be a means to incorporate motion information into dose calculation without performing 4D-CT. The purpose of this study was to determine if RACT from cine CT can be substituted for RACT from 4D-CT for the purposes of dose calculation, and if increasing the cine duration can decrease differences between the dose distributions. Cine CT data and corresponding 4D-CT simulations for 23 patients with at least two breathing cycles per cine duration were retrieved. RACT was generated four ways: First from ten phases of 4D-CT, second, from 1 breathing cycle of images, third, from 1.5 breathing cycles of images, and fourth, from 2 breathing cycles of images. The clinical treatment plan was transferred to each RACT and dose was recalculated. Dose planes were exported at orthogonal planes through the isocenter (coronal, sagittal, and transverse orientations). The resulting dose distributions were compared using the gamma index within the planning target volume (PTV). Failure criteria were set to 2%/1 mm. A follow-up study with 50 additional lung cancer patients was performed to increase sample size. The same dose recalculation and analysis was performed. In the primary patient group, 22 of 23 patients had 100% of points within the PTV pass y criteria. The average maximum and mean y indices were very low (well below 1), indicating good agreement between dose distributions. Increasing the cine duration generally increased the dose agreement. In the follow-up study, 49 of 50 patients had 100% of points within the PTV pass the y criteria. The average maximum and mean y indices were again well below 1, indicating good agreement. Dose calculation on RACT from cine CT is negligibly different from dose calculation on RACT from 4D-CT. Differences can be decreased further by increasing the cine duration of the cine CT scan.

Determination of patient-specific internal gross tumor volumes for lung cancer using four-dimensional computed tomography

Background

To determine the optimal approach to delineating patient-specific internal gross target volumes (IGTV) from four-dimensional (4-D) computed tomography (CT) image data sets used in the planning of radiation treatment for lung cancers.

Methods

We analyzed 4D-CT image data sets of 27 consecutive patients with non-small-cell lung cancer (stage I: 17, stage III: 10). The IGTV, defined to be the envelope of respiratory motion of the gross tumor volume in each 4D-CT data set was delineated manually using four techniques: (1) combining the gross tumor volume (GTV) contours from ten respiratory phases (IGTV_AllPhases); (2) combining the GTV contours from two extreme respiratory phases (0% and 50%) (IGTV_2Phases); (3) defining the GTV contour using the maximum intensity projection (MIP) (IGTV_MIP); and (4) defining the GTV contour using the MIP with modification based on visual verification of contours in individual respiratory phase (IGTV_MIP-Modified). Using the IGTV_AllPhases as the optimum IGTV, we compared volumes, matching indices, and extent of target missing using the IGTVs based on the other three approaches.

Results

The IGTV_MIP and IGTV_2Phases were significantly smaller than the IGTV_AllPhases (p < 0.006 for stage I and p < 0.002 for stage III). However, the values of the IGTV_MIP-Modified were close to those determined from IGTV_AllPhases (p = 0.08). IGTV_MIP-Modified also matched the best with IGTV_AllPhases.

Conclusion

IGTV_MIP and IGTV_2Phases underestimate IGTVs. IGTV_MIP-Modified is recommended to improve IGTV delineation in lung cancer.