Sorting lung tumor volumes from 4D-MRI data using an automatic tumor-based signal reduces stitching artifacts

PURPOSE

To investigate whether a novel signal derived from tumor motion allows more precise sorting of 4D-magnetic resonance (4D-MR) image data than do signals based on normal anatomy, reducing levels of stitching artifacts within sorted lung tumor volumes.

METHODS

(4D-MRI) scans were collected for 10 lung cancer patients using a 2D T2-weighted single-shot turbo spin echo sequence, obtaining 25 repeat frames per image slice. For each slice, a tumor-motion signal was generated using the first principal component of movement in the tumor neighborhood (TumorPC1). Signals were also generated from displacements of the diaphragm (DIA) and upper and lower chest wall (UCW/LCW) and from slice body area changes (BA). Pearson r coefficients of correlations between observed tumor movement and respiratory signals were determined. TumorPC1, DIA, and UCW signals were used to compile image stacks showing each patient's tumor volume in a respiratory phase. Unsorted image stacks were also built for comparison. For each image stack, the presence of stitching artifacts was assessed by measuring the roughness of the compiled tumor surface according to a roughness metric (Rg). Statistical differences in weighted means of Rg between any two signals were determined using an exact permutation test.

RESULTS

The TumorPC1 signal was most strongly correlated with superior-inferior tumor motion, and had significantly higher Pearson r values (median 0.86) than those determined for correlations of UCW, LCW, and BA with superior-inferior tumor motion (p < 0.05). Weighted means of ratios of Rg values in TumorPC1 image stacks to those in unsorted, UCW, and DIA stacks were 0.67, 0.69, and 0.71, all significantly favoring TumorPC1 (p = 0.02-0.05). For other pairs of signals, weighted mean ratios did not differ significantly from one.

CONCLUSION

Tumor volumes were smoother in 3D image stacks compiled using the first principal component of tumor motion than in stacks compiled with signals based on normal anatomy.

Single Institution Preliminary Evaluation of a National Study for the Development of Daily Online Magnetic Resonance Image Guided Radiotherapy

PURPOSE/OBJECTIVE(S)

A 4-stage non-comparative prospective feasibility study to assess and develop imaging protocols for MRIgRT was opened at the first two centers using MR Linac technology in the UK. The primary aims of this study were to determine a) the acceptability of MR images for target and organ at risk delineation and registration; b) inter/intra observer registration and delineation variation. This work reports on the initial results from a single center.

MATERIALS/METHODS

In June 2019, following ethical and regulatory approvals the 2nd UK centre began study recruitment as follows: Stage A: non-patient volunteer imaging to determine sequence suitability for normal tissue in 6 anatomical sites (head & neck (H&N), chest wall/breast, lung/esophagus, abdomen, male and female pelvis). Volunteers were recruited in cohorts of 3 participants per region, and image quality was assessed by 3 independent observers using a visual guidance assessment tool (VGA). Stage B: the most suitable sequences defined in stage A used to assess the visibility of targets/normal tissues in patient volunteers using the same methods as in stage A. Stage C: patient volunteers were imaged using sequences selected from stage B to determine inter and intra observer segmentation and registration variation. Stage D recruitment of patient and non-patient volunteers for further image develop and refinement of MRIgRT workflows. All participants completed experience questionnaires to optimize workflows. Participants were asked to undergo 1-12 imaging sessions, lasting no more than 60.

RESULTS

To date 151 participants (61 non-patients; 90 patients) have undergone 231 imaging sessions. From stage B, vendor provided, in-workflow sequences have been agreed from 47 completed VGAs by prioritizing high scores in either the tumor (e.g., lung) or organs at risk (e.g., cervix). T2w 3D sequences scored best in cervix, pancreas, prostate, bladder, liver, soft-tissue metastases and rectal cancers; T1w 3D sequences for H&N, and patient a specific approach for lung. No suitable sequences have been selected for partial breast. Research sequences (e.g., diffusion weighted or motion corrected imaging) have been agreed or are in development in stages C & D for H&N, cervix, bladder and prostate cancers. The mean interobserver (n = 8) vector variation in 5 H&N patients was largest (3.6mm) using T1-CT boney registrations and smallest (2.1mm) using T1-T1 soft-tissue registrations (mean observer match confidence 3.7/5). Analyses using MR to CT, MR to MR and CT to CT registrations in lung, pancreas, cervix, bladder, and prostate have also been completed. Interobserver delineation studies are on-going.

CONCLUSION

Using a 4-stage non-comparative prospective feasibility study has facilitated clinical implementation MRIgRT of multiple treatment sites at our institution.

Dose-Response Analysis Describes Particularly Rapid Repopulation of Non-Small Cell Lung Cancer during Concurrent Chemoradiotherapy

(1) Purpose: We analysed overall survival (OS) rates following radiotherapy (RT) and chemo-RT of locally-advanced non-small cell lung cancer (LA-NSCLC) to investigate whether tumour repopulation varies with treatment-type, and to further characterise the low α/β ratio found in a previous study. (2) Materials and methods: Our dataset comprised 2-year OS rates for 4866 NSCLC patients (90.5% stage IIIA/B) belonging to 51 cohorts treated with definitive RT, sequential chemo-RT (sCRT) or concurrent chemo-RT (cCRT) given in doses-per-fraction ≤3 Gy over 16-60 days. Progressively more detailed dose-response models were fitted, beginning with a probit model, adding chemotherapy effects and survival-limiting toxicity, and allowing tumour repopulation and α/β to vary with treatment-type and stage. Models were fitted using the maximum-likelihood technique, then assessed via the Akaike information criterion and cross-validation. (3) Results: The most detailed model performed best, with repopulation offsetting 1.47 Gy/day (95% confidence interval, CI: 0.36, 2.57 Gy/day) for cCRT but only 0.30 Gy/day (95% CI: 0.18, 0.47 Gy/day) for RT/sCRT. The overall fitted tumour α/β ratio was 3.0 Gy (95% CI: 1.6, 5.6 Gy). (4) Conclusion: The fitted repopulation rates indicate that cCRT schedule durations should be shortened to the minimum in which prescribed doses can be tolerated. The low α/β ratio suggests hypofractionation should be efficacious.

Early prediction of tumour-response to radiotherapy in NSCLC patients

Objective. In this study we developed an automatic method to predict tumour volume and shape in weeks 3 and 4 of radiotherapy (RT), using cone-beam computed tomography (CBCT) scans acquired up to week 2, allowing identification of large tumour changes.Approach. 240 non-small cell lung cancer (NSCLC) patients, treated with 55 Gy in 20 fractions, were collected. CBCTs were rigidly registered to the planning CT. Intensity values were extracted in each voxel of the planning target volume across all CBCT images from days 1, 2, 3, 7 and 14. For each patient and in each voxel, four regression models were fitted to voxel intensity; applying linear, Gaussian, quadratic and cubic methods. These models predicted the intensity value for each voxel in weeks 3 and 4, and the tumour volume found by thresholding. Each model was evaluated by computing the root mean square error in pixel value and structural similarity index metric (SSIM) for all patients. Finally, the sensitivity and specificity to predict a 30% change in volume were calculated for each model.Main results. The linear, Gaussian, quadratic and cubic models achieved a comparable similarity score, the average SSIM for all patients was 0.94, 0.94, 0.90, 0.83 in week 3, respectively. At week 3, a sensitivity of 84%, 53%, 90% and 88%, and specificity of 99%, 100%, 91% and 42% were observed for the linear, Gaussian, quadratic and cubic models respectively. Overall, the linear model performed best at predicting those patients that will benefit from RT adaptation. The linear model identified 21% and 23% of patients in our cohort with more than 30% tumour volume reduction to benefit from treatment adaptation in weeks 3 and 4 respectively.Significance. We have shown that it is feasible to predict the shape and volume of NSCLC tumours from routine CBCTs and effectively identify patients who will respond to treatment early.

Identification of modes of tumor regression in non-small cell lung cancer patients during radiotherapy

PURPOSE

Observed gross tumor volume (GTV) shrinkage during radiotherapy (RT) raises the question of whether to adapt treatment to changes observed on the acquired images. In the literature, two modes of tumor regression have been described: elastic and non-elastic. These modes of tumor regression will affect the safety of treatment adaptation. This study applies a novel approach, using routine cone-beam computed tomography (CBCT) and deformable image registration to automatically distinguish between elastic and non-elastic tumor regression.

METHODS

In this retrospective study, 150 locally advanced non-small cell lung cancer patients treated with 55 Gray of radiotherapy were included. First, the two modes of tumor regression were simulated. For each mode of tumor regression, one timepoint was simulated. Based on the results of simulated data, the approach used for analysis in real patients was developed. CBCTs were non-rigidly registered to the baseline CBCT using a cubic B-spline algorithm, NiftyReg. Next, the Jacobian determinants were computed from the deformation vector fields. To capture local volume changes, 10 Jacobian values were sampled perpendicular to the surface of the GTV, across the lung-tumor boundary. From the simulated data, we can distinguish elastic from non-elastic tumor regression by comparing the Jacobian values samples between 5 and 12.5 mm inside and 5 and 12.5 mm outside the planning GTV. Finally, morphometric results were compared between tumors of different histologies.

RESULTS

Most patients (92.3%) in our cohort showed stable disease in the first week of treatment and non-elastic shrinkage in the later weeks of treatment. At week 2, 125 patients (88%) showed stable disease, three patients (2.1%) disease progression, and 11 patients (8%) regression. By treatment completion, 91 patients (64%) had stable disease, one patient (0.7%) progression and 46 patients (32%) regression. A slight difference in the mode of tumor change was observed between tumors of different histologies.

CONCLUSION

Our novel approach shows that it may be possible to automatically quantify and identify global changes in lung cancer patients during RT, using routine CBCT images. Our results show that different regions of the tumor change in different ways. Therefore, careful consideration should be taken when adapting RT.

The Impact of Intra-thoracic Anatomical Changes upon the Delivery of Lung Stereotactic Ablative Radiotherapy

AIMS

So far, the impact of intra-thoracic anatomical changes (ITACs) on patients treated with stereotactic ablative radiotherapy (SABR) for early-stage non-small cell lung cancer is unknown. Studying these is important, as ITACs have the potential to impact the workflow and reduce treatment quality. The aim of this study was to assess and categorise ITACs, as detected on cone beam computed tomography scans (CBCT), and their subsequent impact upon treatment in lung cancer patients treated with SABR.

MATERIALS AND METHODS

CBCTs from 100 patients treated with SABR for early non-small cell lung cancer were retrospectively reviewed. The presence of the following ITACs was assessed: atelectasis, infiltrative change, pleural effusion, baseline shift and gross tumour volume (GTV) increase and decrease. ITACs were graded using a traffic light protocol. This was adapted from a tool previously developed to assesses potential target undercoverage or organ at risk overdose. The frequency of physics or clinician review was noted. A linear mixed effects model was used to assess the relationship between ITAC grade and set-up time (time from first CBCT to beam delivery).

RESULTS

ITACs were observed in 22% of patients. Twenty-one per cent of these were categorised as 'red', implying a risk of underdosage to the GTV. Most were 'yellow' (51%), indicating little impact upon planning target volume coverage of the GTV. Physics or clinician review was required in 10% of all treatment fractions overall. Three patients needed their treatment replanned. The mixed effect model analysis showed that ITACs cause a significant prolongation of set-up time (Χ2(3) = 9.22, P = 0.02).

CONCLUSION

Most ITACs were minor, but associated with unplanned physics or clinician review, representing a potentially significant resource burden. ITACs also had a significant impact upon set-up time, with consequences for the wider workflow and intra-fraction motion. Detailed guidance on the management of ITACs is needed to provide support for therapeutic radiographers delivering lung SABR.

MRI and CBCT for lymph node identification and registration in patients with NSCLC undergoing radical radiotherapy

PURPOSE

This study compared MRI to CBCT for the identification and registration of lymph nodes (LN) in patients with locally advanced (LA)-NSCLC, to assess the suitability of targeting LNs in future MR-image guided radiotherapy (MRgRT) workflows.

METHOD

Radiotherapy radiographers carried out Visual Grading Analysis (VGA) assessment of image quality, LN registration and graded their confidence in registration for each of the 24 LNs on CBCT and two MR sequences, MR1 (T2w Turbo Spin Echo) and MR2 (T1w DIXON water only image).

RESULTS

Pre-registration image quality assessment revealed MR1 and MR2 as significantly superior to CBCT in terms of image quality (p ≤ 0.01). No significant differences were noted in interobserver variability for LN registration between CBCT, MR1 and MR2. Observers were more confident in their MR registrations compared to their CBCT based LN registrations (p ≤ 0.02).

SUMMARY

Interobserver setup correction variability was not found to be significantly different between CBCT and MR. Image quality and registration confidence were found to be superior for MRI sequences. This is a promising step towards MR-guided radiotherapy for the treatment of LA-NSCLC.

Outcomes of curative-intent radiotherapy in non-small cell lung cancer (NSCLC) patients with chronic obstructive pulmonary disease (COPD) and interstitial lung disease (ILD)

Outcomes of non-small cell lung cancer (NSCLC) patients with chronic obstructive pulmonary disease (COPD n = 587) and interstitial lung disease (ILD n = 34) treated with curative-intent radiotherapy were retrospectively investigated. Presence of ILD but not decreased forced expiratory volume in 1-second correlated with poor overall survival. Increased breathlessness and oxygen requirements after radiotherapy were observed in severe/very severe COPD and ILD.

Initial Clinical Experience of MR-Guided Radiotherapy for Non-Small Cell Lung Cancer

Curative-intent radiotherapy plays an integral role in the treatment of lung cancer and therefore improving its therapeutic index is vital. MR guided radiotherapy (MRgRT) systems are the latest technological advance which may help with achieving this aim. The majority of MRgRT treatments delivered to date have been stereotactic body radiation therapy (SBRT) based and include the treatment of (ultra-) central tumors. However, there is a move to also implement MRgRT as curative-intent treatment for patients with inoperable locally advanced NSCLC. This paper presents the initial clinical experience of using the two commercially available systems to date: the ViewRay MRIdian and Elekta Unity. The challenges and potential solutions associated with MRgRT in lung cancer will also be highlighted.

Identification of patterns of tumour change measured on CBCT images in NSCLC patients during radiotherapy

In this study, we propose a novel approach to investigate changes in the visible tumour and surrounding tissues with the aim of identifying patterns of tumour change during radiotherapy (RT) without segmentation on the follow-up images. On-treatment cone-beam computed tomography (CBCT) images of 240 non-small cell lung cancer (NSCLC) patients who received 55 Gy of RT were included. CBCTs were automatically aligned onto planning computed tomography (planning CT) scan using a two-step rigid registration process. To explore density changes across the lung-tumour boundary, eight shells confined to the shape of the gross tumour volume (GTV) were created. The shells extended 6 mm inside and outside of the GTV border, and each shell is 1.5 mm thick. After applying intensity correction on CBCTs, the mean intensity was extracted from each shell across all CBCTs. Thereafter, linear fits were created, indicating density change over time in each shell during treatment. The slopes of all eight shells were clustered to explore patterns in the slopes that show how tumours change. Seven clusters were obtained, 97% of the patients were clustered into three groups. After visual inspection, we found that these clusters represented patients with little or no density change, progression and regression. For the three groups, the survival curves were not significantly different between the groups, p-value = 0.51. However, the results show that definite patterns of tumour change exist, suggesting that it may be possible to identify patterns of tumour changes from on-treatment CBCT images.

Looking through the eyes of the multidisciplinary team: the design and clinical evaluation of a decision support system for lung cancer care

Background

Decision-making in lung cancer is complex due to a rapidly increasing amount of diagnostic data and treatment options. The need for timely and accurate diagnosis and delivery of care demands high-quality multidisciplinary team (MDT) collaboration and coordination. Clinical decision support systems (CDSSs) can potentially support MDTs in constructing a shared mental model of a patient case. This enables the team to assess the strength and completeness of collected diagnostic data, stratification for the right personalized therapy driven by clinical stage and other treatment-influencing factors, and adapt care management strategies when needed. Current CDSSs often have a suboptimal fit into the decision-making workflow, which hampers their impact in clinical practice.

Methods

A CDSS for multidisciplinary decision-making in lung cancer was designed to support the abovementioned goals through presentation of relevant clinical data in line with existing mental model structures of the MDT members. The CDSS was tested in a simulated multidisciplinary tumor board meeting for primary diagnosis and treatment selection, based on de-identified primary lung cancer cases (n=8). Decision course analysis, eye-tracking data and questionnaires were used to assess the impact of the CDSS on constructing shared mental models to improve the decision-making process and outcome.

Results

The CDSS supported the team in their self-correcting capacity for accurate diagnosis and TNM classification. It enabled cross-validation of diagnostic findings, surfaced discordance between diagnostic tests and facilitated cancer staging according the diagnostic evidence, as well as spotting contra-indications for personalized treatment selection.

Conclusions

This study shows the potential of CDSS on clinical decision making, when these systems are properly designed in line with clinical thinking. The presented setup enables assessment of the impact of CDSS design on clinical decision making and optimization of CDSSs to maximize their effect on decision quality and confidence.

Comparison between Conventional IMRT Planning and a Novel Real-Time Adaptive Planning Strategy in Hypofractionated Regimes for Prostate Cancer: A Proof-of-Concept Planning Study

In prostate cancer external beam radiation therapy (EBRT), intra-fraction prostate drifts may compromise the treatment efficacy by underdosing the target and/or overdosing the organs at risk. In this study, a recently developed real-time adaptive planning strategy for intensity-modulated radiation therapy (IMRT) for prostate cancer was evaluated in hypofractionated regimes against traditional treatment planning based on a treatment volume margin expansion. The proposed workflow makes use of a “library of plans” corresponding to possible intra-fraction prostate positions. During delivery, at each beam end, the plan prepared for the position of the prostate closest to the current one is selected and the corresponding beam delivered. This adaptive planning strategy was compared with the traditional approach on a clinical prostate cancer case where different prostate shift magnitudes were considered. Five, six and fifteen fraction hypofractionated schemes were considered for each of these scenarios. When shifts larger than the treatment margin were present, using the traditional approach the seminal vesicles were underdosed by 3–4% of the prescribed dose. The adaptive approach instead allowed for correct target dose coverage and lowered the dose on the rectum for each dosimetric endpoint on average by 3–4% in all the fractionation schemes. Standard intensity-modulated radiation therapy planning did not always guarantee a correct dose distribution on the seminal vesicles and the rectum. The adaptive planning strategy proposed resulted insensitive to the intra-fraction prostate drifts, produced a dose distribution in agreement with the dosimetric requirements in every case analysed and significantly lowered the dose on the rectum.

Real-time adaptive planning method for radiotherapy treatment delivery for prostate cancer patients, based on a library of plans accounting for possible anatomy configuration changes

BACKGROUND AND PURPOSE

In prostate cancer treatment with external beam radiation therapy (EBRT), prostate motion and internal changes in tissue distribution can lead to a decrease in plan quality. In most currently used planning methods, the uncertainties due to prostate motion are compensated by irradiating a larger treatment volume. However, this could cause underdosage of the treatment volume and overdosage of the organs at risk (OARs). To reduce this problem, in this proof of principle study we developed and evaluated a novel adaptive planning method. The strategy proposed corrects the dose delivered by each beam according to the actual position of the target in order to produce a final dose distribution dosimetrically as similar as possible to the prescribed one.

MATERIAL AND METHODS

Our adaptive planning method was tested on a phantom case and on a clinical case. For the first, a pilot study was performed on an in-silico pelvic phantom. A "library" of intensity modulated RT (IMRT) plans corresponding to possible positions of the prostate during a treatment fraction was generated at planning stage. Then a 3D random walk model was used to simulate possible displacements of the prostate during the treatment fraction. At treatment stage, at the end of each beam, based on the current position of the target, the beam from the library of plans, which could reproduce the best approximation of the prescribed dose distribution, was selected and delivered. In the clinical case, the same approach was used on two prostate cancer patients: for the first a tissue deformation was simulated in-silico and for the second a cone beam CT (CBCT) taken during the treatment was used to simulate an intra-fraction change. Then, dosimetric comparisons with the standard treatment plan and, for the second patient, also with an isocenter shift correction, were performed.

RESULTS

For the phantom case, the plan generated using the adaptive planning method was able to meet all the dosimetric requirements and to correct for a misdosage of 13% of the dose prescription on the prostate. For the first clinical case, the standard planning method caused underdosage of the seminal vesicles, respectively by 5% and 4% of the prescribed dose, when the position changes for the target were correctly taken into account. The proposed adaptive planning method corrected any possible missed target coverage, reducing at the same time the dose on the OARs. For the second clinical case, both with the standard planning strategy and with the isocenter shift correction target coverage was significantly worsened (in particular uniformity) and some organs exceeded some toxicity objectives. While with our approach, the most uniform coverage for the target was produced and systematically the lowest toxicity values for the organs at risk were achieved.

CONCLUSIONS

In our proof of principle study, the adaptive planning method performed better than the standard planning and the isocenter shift methods for prostate EBRT. It improved the coverage of the treatment volumes and lowered the dose to the OARs. This planning method is particularly promising for hypofractionated IMRT treatments in which a higher precision and control on dose deposition are needed. Further studies will be performed to test more extensively the proposed adaptive planning method and to evaluate it at a full clinical level.