Quantification of metabolic tumor activity and burden in patients with non-small-cell lung cancer: Is manual adjustment of semiautomatic gradient-based measurements necessary?

Prediction of Response to 177Lu-PSMA Therapy Based on Tumor-to-Kidney Ratio on Pretherapeutic PSMA PET/CT and Posttherapeutic Tumor-Dose Evaluation in mCRPC

The aim of this study was to analyze the absorbed dose of 177Lu-PSMA in osseous versus lymphatic metastases in patients with metastatic castration-resistant prostate cancer across therapy cycles and to relate those data to therapeutic success. In addition, pretherapeutic prostate-specific membrane antigen (PSMA) PET/CT was evaluated for its ability to predict response behavior. Methods: The study comprised 30 patients with metastatic castration-resistant prostate cancer, each receiving at least 3 cycles of 177Lu-PSMA therapy. Prostate-specific antigen (PSA) values between baseline and 6 wk after the third therapy cycle were used to classify the patients as responders (PSA decline ≥ 50%) or nonresponders (unchanged or increasing PSA level). Quantitative SPECT/CT images were acquired 24, 48, and 168 h after application of 177Lu-PSMA. The absorbed dose for tumor lesions was calculated with dosimetry software. From the pretherapeutic PET/CT scan, the tumor-to-kidney uptake ratio was determined for different SUVs. Results: Regardless of patient response, the kidneys received a mean dose of 0.55 ± 0.20 Gy/GBq per cycle. In the first therapy cycle, the lymph node lesions received a mean dose of 3.73 ± 1.65 Gy/GBq in responders and 1.86 ± 1.25 Gy/GBq in nonresponders (P < 0.01). For bone lesions, the respective mean doses were 3.47 ± 2.00 Gy/GBq and 1.48 ± 0.95 Gy/GBq (P < 0.01). When successive therapy cycles were compared, the mean dose was found to have been reduced from the first to the second cycle by 27% for lymph nodes and by 33% for bone lesions. A significant difference (P < 0.01) in the ratio of lymph node and bone lesion uptake to kidney uptake between responders and nonresponders could be deduced from the pretherapeutic PET/CT scan. Conclusion: Significantly higher doses were achieved for lymph node and bone lesions in responders. The highest absorbed dose, for both lymphatic and osseous lesions, was achieved in the first cycle, decreasing in the second therapy cycle thereafter despite unchanged therapy activities. It may be possible to estimate the response to therapy from the ratio of tumor uptake to kidney uptake obtained from the pretherapeutic PSMA PET/CT scans.

Gradient-based Volumetric PET Parameters on Immediate Pre-ablation FDG-PET Predict Local Tumor Progression in Patients with Colorectal Liver Metastasis Treated by Microwave Ablation

PURPOSE

This study aimed to evaluate the optimal method of segmentation of colorectal liver metastasis (CLM) on immediate pre-ablation PET scans and assess the prognostic value of quantitative pre-ablation PET parameters with regards to local tumor control. A secondary objective was to correlate the target tumor size estimation by PET methods with the tumor measurements on anatomical imaging.

METHODOLOGY

A prospectively accrued cohort of 55 CLMs (46 patients) treated with real-time ¹⁸F-FDG-PET/CT-guided percutaneous microwave ablation was followed-up for a median of 10.8 months (interquartile: 5.5-20.2). Total lesion glycolysis (TLG) and metabolic tumor volume (MTV) values of each CLM were derived from pre-ablation ¹⁸F-FDG-PET with gradient and threshold PET segmentation methodologies. The event was defined as local tumor progression (LTP). Time-dependent receiver operating characteristic (ROC) curve analyses were used to assess area under the curves (AUCs). Intraclass correlation (ICC) and 95.0% confidence interval (CI) were performed to measure the linear relationships between the continuous variables.

RESULTS

AUCs for prediction of LTP obtained from time-dependent ROC analysis for the gradient technique were higher in comparison to the threshold methodologies (AUCs for TLG and volume were: 0.790 and 0.807, respectively). ICC between PET gradient-based and anatomical measurements were higher in comparison to threshold methodologies (ICC for the longest diameter: 733 (95.0% CI 0.538-0.846), ICC for the shortest diameter: .747 (95.0% CI 0.546-0.859), p-values < 0.001).

CONCLUSIONS

The gradient-based technique had a higher AUC for prediction of LTP after microwave ablation of CLM and showed the highest correlation with anatomical imaging tumor measurements.

Identifying the location of locoregional recurrences after definitive radiotherapy for head and neck cancer using metabolic parameters of baseline and mid-treatment 18F-FDG-PET scans

INTRODUCTION

Tumour recurrences after treatment of head and neck squamous cell carcinoma (HNSCC) are more likely to originate from regions of high-baseline FDG-PET uptake. Mid-treatment functional imaging can potentially predict for higher risk of tumour recurrence. The aim of this study is to correlate the location of locoregional tumour recurrence with baseline FDG-PET metabolic volumes and mid-treatment FDG-PET metabolic volumes in patients with HNSCC following definitive radiotherapy.

METHODS

A total of 23 patients with 26 local and/or regional recurrences underwent baseline (W0-PET) and mid-treatment (W3-PET) 18F-FDG PET scans as part of their radiotherapy. FDG-PET-based metabolic volumes (MTV20%, MTV40%, MTV60%, MTV80%, SUV2.5, SUVpeak and PET_EDGE) were delineated onto the FDG-PET scans. The recurrence nidus was identified on FDG-PET at the time of recurrence (REC-PET). DIR-based fusion was performed for REC-PET to W0-PET, and REC-PET to W3-PET. The location of the recurrence nidus was correlated with the FDG-PET volumes. Further analysis included a comparison of the recurrence density to FDG-PET metabolic volumes.

RESULTS

Most recurrences occurred within the MTV20%, MTV40% and SUV 2.5 volumes. Sixty-nine per cent of recurrences (18 of 26) occurred within both the W0 MTV40% and W3 MTV40% volumes. A higher recurrence density was seen for iso-SUV contours closer to the maximum SUV for both W0 and W3. For a number of the FDG-PET volumes, including MTV20%, MTV40% and SUV2.5, the recurrence density was improved for W3 compared to W0, however, this improvement was small in magnitude. The average volume of MTV40% contours was considerably smaller than MTV20% and SUV2.5 contours.

CONCLUSION

The metabolic parameters of SUV2.5, MTV20% and MTV40% delineated on the baseline and mid-treatment FDG-PET scans encompassed the majority of recurrences. The MTV40% is significantly smaller, hence, we prefer this volume for future dose escalation studies.

Investigating and modeling positron emission tomography factors associated with large cell transformation from low-grade lymphomas

Low-grade lymphomas have a 1%-3% annual risk of transformation to a high-grade histology, and prognostic factors remain undefined. We set to investigate the role of positron emission tomography (PET) metrics in identification of transformation in a retrospective case-control series of patients matched by histology and follow-up time. We measured PET parameters including maximum standard uptake value (SUV-max) and total lesion glycolysis (TLG), and developed a PET feature and lactate dehydrogenase (LDH)-based model to identify transformation status within discovery and validation cohorts. For our discovery cohort, we identified 53 patients with transformation and 53 controls with a similar distribution of follicular lymphoma (FL). Time to transformation and control follow-up time was similar. We observed a significant incremental increase in SUV-max and TLG between control, pretransformation and post-transformation groups (P < 0.05). By multivariable analysis, we identified a significant interaction between SUV-max and TLG such that SUV-max had highest significance for low volume cases (P = 0.04). We developed a scoring model incorporating SUV-max, TLG, and serum LDH with improved identification of transformation (area under the curve [AUC] = 0.91). Our model performed similarly for our validation cohort of 23 patients (AUC = 0.90). With external and prospective validation, our scoring model may provide a specific and noninvasive tool for risk stratification for patients with low-grade lymphoma.

Chordoma: 18F-FDG PET/CT and MRI imaging features

OBJECTIVE

Examine the ¹⁸F-FDG PET/CT and MRI imaging characteristics of chordoma.

MATERIALS AND METHODS

Biopsy-proven chordoma with a pre-therapy ¹⁸F-FDG PET/CT from 2001 through 2019 in patients > 18 years old were retrospectively reviewed. Multiple PET/CT and MRI imaging parameters were assessed.

RESULTS

A total of 23 chordoma patients were included (16 M, 7 F; average age of 60.1 ± 13.0 years) with comparative MRI available in 22 cases. This included 13 sacrococcygeal, 9 mobile spine, and one clival lesions. On ¹⁸F-FDG PET/CT, chordomas demonstrated an average SUVmax of 5.8 ± 3.7, average metabolic tumor volume (MTV) of 160.2 ± 263.8 cm³, and average total lesion glycolysis (TLG) of 542.6 ± 1210 g. All demonstrated heterogeneous FDG activity. On MRI, chordomas were predominantly T2 hyperintense (22/22) and T1 isointense (18/22), contained small foci of T1 hyperintensity (17/22), and demonstrated heterogeneous enhancement (14/20). There were no statistically significant associations found between ¹⁸F-FDG PET/CT and MRI imaging features. There was no relationship of SUVmax (p = 0.53), MTV (p = 0.47), TLG (p = 0.48), maximal dimension (p = 0.92), or volume (p = 0.45) to the development of recurrent or metastatic disease which occurred in 6/22 patients over a mean follow-up duration of 4.1 ± 2.0 years.

CONCLUSION

On ¹⁸F-FDG PET/CT imaging, chordomas demonstrate moderate, heterogeneous FDG uptake. Predominant T2 hyperintensity and small foci of internal increased T1 signal are common on MRI. The inherent FDG avidity of chordomas suggests that ¹⁸F-FDG PET/CT may be a useful modality for staging, evaluating treatment response, and assessing for recurrent or metastatic disease.

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.

Accurate FDG PET tumor segmentation using the peritumoral halo layer method: a study in patients with esophageal squamous cell carcinoma

Background

In a previous study, FDG PET tumor segmentation (SegPHL) using the peritumoral halo layer (PHL) was more reliable than fixed threshold methods in patients with thyroid cancer. We performed this study to validate the reliability and accuracy of the PHL method in patients with esophageal squamous cell carcinomas (ESCCs), which can be larger and more heterogeneous than thyroid cancers.

Methods

A total of 121 ESCC patients (FDG avid = 85 (70.2%); FDG non-avid = 36 (29.8%)) were enrolled in this study. In FDG avid ESCCs, metabolic tumor length (ML) using SegPHL (ML_PHL), fixed SUV 2.5 threshold (ML_2.5), and fixed 40% of maximum SUV (SUVmax) (ML_40%) were measured. Regression and Bland-Altman analyses were performed to evaluate associations between ML, endoscopic tumor length (EL), and pathologic tumor length (PL). A comparison test was performed to evaluate the absolute difference between ML and PL. Correlation with tumor threshold determined by the PHL method (PHL tumor threshold) and SUVmax was evaluated.

Results

ML_PHL, ML_2.5, and ML_40% correlated well with EL (R² = 0.6464, 0.5789, 0.3321, respectively; p < 0.001) and PL (R² = 0.8778, 0.8365, 0.6266, respectively; p < 0.001). However, ML_2.5 and ML_40% showed significant proportional error with regard to PL; there was no significant error between ML_PHL and PL. ML_PHL showed the smallest standard deviation on Bland-Altman analyses. The absolute differences between ML and PL were significantly smaller for ML_PHL and ML_40% than for ML_2.5 (p < 0.0001). The PHL tumor threshold showed an inverse correlation with SUVmax (σ = − 0.923, p < 0.0001).

Conclusions

SegPHL was more accurate than fixed threshold methods in ESCC. The PHL tumor threshold was adjusted according to SUVmax of ESCC.

Developing and validating a novel metabolic tumor volume risk stratification system for supplementing non-small cell lung cancer staging

PURPOSE

We hypothesized that whole-body metabolic tumor volume (MTVwb) could be used to supplement non-small cell lung cancer (NSCLC) staging due to its independent prognostic value. The goal of this study was to develop and validate a novel MTVwb risk stratification system to supplement NSCLC staging.

METHODS

We performed an IRB-approved retrospective review of 935 patients with NSCLC and FDG-avid tumor divided into modeling and validation cohorts based on the type of PET/CT scanner used for imaging. In addition, sensitivity analysis was conducted by dividing the patient population into two randomized cohorts. Cox regression and Kaplan-Meier survival analyses were performed to determine the prognostic value of the MTVwb risk stratification system.

RESULTS

The cut-off values (10.0, 53.4 and 155.0 mL) between the MTVwb quartiles of the modeling cohort were applied to both the modeling and validation cohorts to determine each patient's MTVwb risk stratum. The survival analyses showed that a lower MTVwb risk stratum was associated with better overall survival (all p < 0.01), independent of TNM stage together with other clinical prognostic factors, and the discriminatory power of the MTVwb risk stratification system, as measured by Gönen and Heller's concordance index, was not significantly different from that of TNM stage in both cohorts. Also, the prognostic value of the MTVwb risk stratum was robust in the two randomized cohorts. The discordance rate between the MTVwb risk stratum and TNM stage or substage was 45.1% in the modeling cohort and 50.3% in the validation cohort.

CONCLUSION

This study developed and validated a novel MTVwb risk stratification system, which has prognostic value independent of the TNM stage and other clinical prognostic factors in NSCLC, suggesting that it could be used for further NSCLC pretreatment assessment and for refining treatment decisions in individual patients.

Current Methods to Define Metabolic Tumor Volume in Positron Emission Tomography: Which One is Better?

Numerous methods to segment tumors using ¹⁸F-fluorodeoxyglucose positron emission tomography (FDG PET) have been introduced. Metabolic tumor volume (MTV) refers to the metabolically active volume of the tumor segmented using FDG PET, and has been shown to be useful in predicting patient outcome and in assessing treatment response. Also, tumor segmentation using FDG PET has useful applications in radiotherapy treatment planning. Despite extensive research on MTV showing promising results, MTV is not used in standard clinical practice yet, mainly because there is no consensus on the optimal method to segment tumors in FDG PET images. In this review, we discuss currently available methods to measure MTV using FDG PET, and assess the advantages and disadvantages of the methods.

Risk-stratifying capacity of PET/CT metabolic tumor volume in stage IIIA non-small cell lung cancer

OBJECTIVES

Stage IIIA non-small cell lung cancer (NSCLC) is heterogeneous in tumor burden, and its treatment is variable. Whole-body metabolic tumor volume (MTVWB) has been shown to be an independent prognostic index for overall survival (OS). However, the potential of MTVWB to risk-stratify stage IIIA NSCLC has previously been unknown. If we can identify subgroups within the stage exhibiting significant OS differences using MTVWB, MTVWB may lead to adjustments in patients' risk profile evaluations and may, therefore, influence clinical decision making regarding treatment. We estimated the risk-stratifying capacity of MTVWB in stage IIIA by comparing OS of stratified stage IIIA with stage IIB and IIIB NSCLC.

METHODS

We performed a retrospective review of 330 patients with clinical stage IIB, IIIA, and IIIB NSCLC diagnosed between 2004 and 2014. The patients' clinical TNM stage, initial MTVWB, and long-term survival data were collected. Patients with TNM stage IIIA disease were stratified by MTVWB. The optimal MTVWB cutoff value for stage IIIA patients was calculated using sequential log-rank tests. Univariate and multivariate cox regression analyses and Kaplan-Meier OS analysis with log-rank tests were performed.

RESULTS

The optimal MTVWB cut-point was 29.2 mL for the risk-stratification of stage IIIA. We identified statistically significant differences in OS between stage IIB and IIIA patients (p < 0.01), between IIIA and IIIB patients (p < 0.01), and between the stage IIIA patients with low MTVWB (below 29.2 mL) and the stage IIIA patients with high MTVWB (above 29.2 mL) (p < 0.01). There was no OS difference between the low MTVWB stage IIIA and the cohort of stage IIB patients (p = 0.485), or between the high MTVWB stage IIIA patients and the cohort of stage IIIB patients (p = 0.459). Similar risk-stratification capacity of MTVWB was observed in a large range of cutoff values from 15 to 55 mL in stage IIIA patients.

CONCLUSIONS

Using MTVWB cutoff points ranging from 15 to 55 mL with an optimal value of 29.2 mL, stage IIIA NSCLC may be effectively stratified into subgroups with no significant survival difference from stages IIB or IIIB NSCLC. This may result in more accurate survival estimation and more appropriate risk adapted treatment selection in stage IIIA NSCLC.

Classification and evaluation strategies of auto-segmentation approaches for PET: Report of AAPM task group No. 211

PURPOSE

The purpose of this educational report is to provide an overview of the present state-of-the-art PET auto-segmentation (PET-AS) algorithms and their respective validation, with an emphasis on providing the user with help in understanding the challenges and pitfalls associated with selecting and implementing a PET-AS algorithm for a particular application.

APPROACH

A brief description of the different types of PET-AS algorithms is provided using a classification based on method complexity and type. The advantages and the limitations of the current PET-AS algorithms are highlighted based on current publications and existing comparison studies. A review of the available image datasets and contour evaluation metrics in terms of their applicability for establishing a standardized evaluation of PET-AS algorithms is provided. The performance requirements for the algorithms and their dependence on the application, the radiotracer used and the evaluation criteria are described and discussed. Finally, a procedure for algorithm acceptance and implementation, as well as the complementary role of manual and auto-segmentation are addressed.

FINDINGS

A large number of PET-AS algorithms have been developed within the last 20 years. Many of the proposed algorithms are based on either fixed or adaptively selected thresholds. More recently, numerous papers have proposed the use of more advanced image analysis paradigms to perform semi-automated delineation of the PET images. However, the level of algorithm validation is variable and for most published algorithms is either insufficient or inconsistent which prevents recommending a single algorithm. This is compounded by the fact that realistic image configurations with low signal-to-noise ratios (SNR) and heterogeneous tracer distributions have rarely been used. Large variations in the evaluation methods used in the literature point to the need for a standardized evaluation protocol.

CONCLUSIONS

Available comparison studies suggest that PET-AS algorithms relying on advanced image analysis paradigms provide generally more accurate segmentation than approaches based on PET activity thresholds, particularly for realistic configurations. However, this may not be the case for simple shape lesions in situations with a narrower range of parameters, where simpler methods may also perform well. Recent algorithms which employ some type of consensus or automatic selection between several PET-AS methods have potential to overcome the limitations of the individual methods when appropriately trained. In either case, accuracy evaluation is required for each different PET scanner and scanning and image reconstruction protocol. For the simpler, less robust approaches, adaptation to scanning conditions, tumor type, and tumor location by optimization of parameters is necessary. The results from the method evaluation stage can be used to estimate the contouring uncertainty. All PET-AS contours should be critically verified by a physician. A standard test, i.e., a benchmark dedicated to evaluating both existing and future PET-AS algorithms needs to be designed, to aid clinicians in evaluating and selecting PET-AS algorithms and to establish performance limits for their acceptance for clinical use. The initial steps toward designing and building such a standard are undertaken by the task group members.

Prognostic value of quantitative PET/CT in patients with a nonsmall cell lung cancer and another primary cancer

OBJECTIVE

The staging and management of patients with newly diagnosed nonsmall cell lung cancer (NSCLC) in the setting of recently diagnosed other (metachronous or synchronous) primary cancer are challenging. This retrospective cohort study was carried out to test our hypothesis that baseline 2-deoxy-2-[F]fluoro-D-glucose (F-FDG) PET/CT parameters, including whole-body metabolic tumor volume (MTVWB), total lesion glycolysis (TLGWB), and maximum standardized uptake value (SUVmaxWB), are associated with the overall survival (OS) of such patients.

PATIENTS AND METHODS

A total of 110 NSCLC patients (52 men and 58 women, aged 68.6±7.8 years) with other primary malignant cancers who had baseline F-FDG PET/CT scans were retrospectively reviewed. MTVWB, TLGWB, and SUVmaxWB were measured. Kaplan-Meier analysis with the log-rank test and Cox regression models were used to assess the association of OS with F-FDG PET/CT parameters and clinical risk factors.

RESULTS

Kaplan-Meier analysis and univariate Cox regression models showed significant associations of OS with ln(MTVWB), ln(TLGWB), ln(SUVmaxWB), TNM stage, and treatment type (surgery vs. no treatment). Multivariable Cox regression models showed a significant relationship of OS with ln(MTVWB) [hazard ratio (HR)=1.368, P=0.001], ln(TLGWB) (HR=1.313, P<0.001), and ln(SUVmaxWB) (HR=1.739, P=0.006), adjusted for age, treatment type, tumor histology, and TNM stage. The TNM stage was not associated significantly with OS when MTVWB, TLGWB, or SUVmaxWB were included in the multivariable models.

CONCLUSION

MTVWB, TLGWB, and SUVmaxWB from baseline F-FDG PET/CT are associated individually with OS of patients with both NSCLC and other primary malignant tumors independent of age, treatment type, tumor histology, and TNM stage.

Consistency of metabolic tumor volume of non-small-cell lung cancer primary tumor measured using 18F-FDG PET/CT at two different tracer uptake times

OBJECTIVES

The objective of this study was to test the hypothesis that the metabolic tumor volume (MTV) of primary non-small-cell lung cancer is not sensitive to differences in F-fluorodeoxyglucose (F-FDG) uptake time, and to compare this consistency of MTV measurements with that of standardized uptake value (SUV) and total lesion glycolysis (TLG).

METHODS

Under Institutional Review Board approval, 134 consecutive patients with histologically proven non-small-cell lung cancer underwent F-FDG PET/computed tomography scanning at about 1 h (early) and 2 h (delayed) after intravenous injection of F-FDG. MTV, SUV, and TLG of the primary tumor were all measured. Student's t-test and Wilcoxon's signed-rank test for paired data were used to compare MTV, SUV, and TLG between the two scans. The intraclass correlation coefficient (ICC) was used to assess agreement in PET parameters between the two scans and between the measurements made by two observers.

RESULTS

MTV was not significantly different (P=0.17) between the two scans. However, SUVmax, SUVmean, SUVpeak, and TLG increased significantly from the early to the delayed scans (P<0.0001 for all). The median percentage change between the two scans in MTV (1.65%) was smaller than in SUVmax (11.76%), SUVmean(10.57%), SUVpeak(13.51%), and TLG (14.34%); the ICC of MTV (0.996) was greater than that of SUVmax (0.933), SUVmean (0.952), SUVpeak (0.928), and TLG (0.982). Interobserver agreement between the two radiologists was excellent for MTV, SUV, and TLG on both scans (ICC: 0.934-0.999).

CONCLUSION

MTV is not sensitive to common clinical variations in F-FDG uptake time, its consistency is greater than that of SUVmax, SUVmean, SUVpeak, and TLG, and it has excellent interobserver agreement.

Local respiratory motion correction for PET/CT imaging: Application to lung cancer

PURPOSE

Despite multiple methodologies already proposed to correct respiratory motion in the whole PET imaging field of view (FOV), such approaches have not found wide acceptance in clinical routine. An alternative can be the local respiratory motion correction (LRMC) of data corresponding to a given volume of interest (VOI: organ or tumor). Advantages of LRMC include the use of a simple motion model, faster execution times, and organ specific motion correction. The purpose of this study was to evaluate the performance of LMRC using various motion models for oncology (lung lesion) applications.

METHODS

Both simulated (NURBS based 4D cardiac-torso phantom) and clinical studies (six patients) were used in the evaluation of the proposed LRMC approach. PET data were acquired in list-mode and synchronized with respiration. The implemented approach consists first in defining a VOI on the reconstructed motion average image. Gated PET images of the VOI are subsequently reconstructed using only lines of response passing through the selected VOI and are used in combination with a center of gravity or an affine/elastic registration algorithm to derive the transformation maps corresponding to the respiration effects. Those are finally integrated in the reconstruction process to produce a motion free image over the lesion regions.

RESULTS

Although the center of gravity or affine algorithm achieved similar performance for individual lesion motion correction, the elastic model, applied either locally or to the whole FOV, led to an overall superior performance. The spatial tumor location was altered by 89% and 81% for the elastic model applied locally or to the whole FOV, respectively (compared to 44% and 39% for the center of gravity and affine models, respectively). This resulted in similar associated overall tumor volume changes of 84% and 80%, respectively (compared to 75% and 71% for the center of gravity and affine models, respectively). The application of the nonrigid deformation model in LRMC led to over an order of magnitude gain in computational efficiency of the correction relative to the application of the deformable model to the whole FOV.

CONCLUSIONS

The results of this study support the use of LMRC as a flexible and efficient correction approach for respiratory motion effects for single lesions in the thoracic area.