Radiotherapy treatment planning for patients with non-small cell lung cancer using positron emission tomography (PET)

Biological target volume based on fluorine-18-fluorode-oxyglucose positron emission tomography/computed tomography imaging: a spurious proposition?

PURPOSE

To assess whether the high metabolic region of fluorine-18-fluorode-oxyglucose (¹⁸F-FDG) in the primary lesion is the crux for recurrence in patients with nasopharyngeal carcinoma (NPC), to assess the feasibility and rationale for use of biological target volume (BTV) based on ¹⁸F-FDG positron emission tomography/computed tomography (¹⁸F-FDG-PET/CT).

METHODS

The retrospective study included 33 patients with NPC who underwent ¹⁸F-FDG-PET/CT at the time of initial diagnosis as well as the time of diagnosis of local recurrence. Paired ¹⁸F-FDG-PET/CT images for primary and recurrent lesion were matched by deformation coregistration method to determine the cross-failure rate between two lesions.

RESULTS

The median volume of the V_pri (primary tumor volume using the SUV thresholds of 2.5), the V_high (the volume of high FDG uptake using the SUV50%max isocontour), and the V_recur (the recurrent tumor volume using the SUV thresholds of 2.5) were 22.85, 5.57, and 9.98 cm³, respectively. The cross-failure rate of V_recur∩high showed that 82.82% (27/33) of local recurrent lesions had < 50% overlap volume with the region of high FDG uptake. The cross-failure rate of V_recur∩pri showed that 96.97% (32/33) of local recurrent lesions had > 20% overlap volume with the primary tumor lesions and the median cross rate was up to 71.74%.

CONCLUSION

¹⁸F-FDG-PET/CT may be a powerful tool for automatic target volume delineation, but it may not be the optimal imaging modality for dose escalation radiotherapy based on applicable isocontour. The combination of other functional imaging could delineate the BTV more accurately.

Variability of Low-Z Inhomogeneity Correction in IMRT/SBRT: A Multi-Institutional Collaborative Study

Dose-calculation algorithms are critical for radiation treatment outcomes that vary among treatment planning systems (TPS). Modern algorithms use sophisticated radiation transport calculation with detailed three-dimensional beam modeling to provide accurate doses, especially in heterogeneous medium and small fields used in IMRT/SBRT. While the dosimetric accuracy in heterogeneous mediums (lung) is qualitatively known, the accuracy is unknown. The aim of this work is to analyze the calculated dose in lung patients and compare the validity of dose-calculation algorithms by measurements in a low-Z phantom for two main classes of algorithms: type A (pencil beam) and type B (collapse cone). The CT scans with volumes (target and organs at risk, OARs) of a lung patient and a phantom build to replicate the human lung data were sent to nine institutions for planning. Doses at different depths and field sizes were measured in the phantom with and without inhomogeneity correction across multiple institutions to understand the impact of clinically used dose algorithms. Wide dosimetric variations were observed in target and OAR coverage in patient plans. The correction factor for collapsed cone algorithms was less than pencil beam algorithms in the small fields used in SBRT. The pencil beam showed ≈70% variations between measured and calculated correction factors for various field sizes and depths. For large field sizes the trends of both types of algorithms were similar. The differences in measured versus calculated dose for type-B algorithms were within ±10%. Significant variations in the target and OARs were observed among various TPS. The results suggest that the pencil beam algorithm does not provide an accurate dose and should not be considered with small fields (IMRT/SBRT). Type-B collapsed-cone algorithms provide better agreement with measurements, but still vary among various systems.

A Comprehensive Survey on the Progress, Process, and Challenges of Lung Cancer Detection and Classification

Lung cancer is the primary reason of cancer deaths worldwide, and the percentage of death rate is increasing step by step. There are chances of recovering from lung cancer by detecting it early. In any case, because the number of radiologists is limited and they have been working overtime, the increase in image data makes it hard for them to evaluate the images accurately. As a result, many researchers have come up with automated ways to predict the growth of cancer cells using medical imaging methods in a quick and accurate way. Previously, a lot of work was done on computer-aided detection (CADe) and computer-aided diagnosis (CADx) in computed tomography (CT) scan, magnetic resonance imaging (MRI), and X-ray with the goal of effective detection and segmentation of pulmonary nodule, as well as classifying nodules as malignant or benign. But still, no complete comprehensive review that includes all aspects of lung cancer has been done. In this paper, every aspect of lung cancer is discussed in detail, including datasets, image preprocessing, segmentation methods, optimal feature extraction and selection methods, evaluation measurement matrices, and classifiers. Finally, the study looks into several lung cancer-related issues with possible solutions.

Cross modality fusion for modality-specific lung tumor segmentation in PET-CT images

Although positron emission tomography-computed tomography (PET-CT) images have been widely used, it is still challenging to accurately segment the lung tumor. The respiration, movement and imaging modality lead to large modality discrepancy of the lung tumors between PET images and CT images. To overcome these difficulties, a novel network is designed to simultaneously obtain the corresponding lung tumors of PET images and CT images. The proposed network can fuse the complementary information and preserve modality-specific features of PET images and CT images. Due to the complementarity between PET images and CT images, the two modality images should be fused for automatic lung tumor segmentation. Therefore, cross modality decoding blocks are designed to extract modality-specific features of PET images and CT images with the constraints of the other modality. The edge consistency loss is also designed to solve the problem of blurred boundaries of PET images and CT images. The proposed method is tested on 126 PET-CT images with non-small cell lung cancer, and Dice similarity coefficient scores of lung tumor segmentation reach 75.66 ± 19.42 in CT images and 79.85 ± 16.76 in PET images, respectively. Extensive comparisons with state-of-the-art lung tumor segmentation methods have also been performed to demonstrate the superiority of the proposed network.

Multi-Modal Co-Learning for Liver Lesion Segmentation on PET-CT Images

Liver lesion segmentation is an essential process to assist doctors in hepatocellular carcinoma diagnosis and treatment planning. Multi-modal positron emission tomography and computed tomography (PET-CT) scans are widely utilized due to their complementary feature information for this purpose. However, current methods ignore the interaction of information across the two modalities during feature extraction, omit the co-learning of the feature maps of different resolutions, and do not ensure that shallow and deep features complement each others sufficiently. In this paper, our proposed model can achieve feature interaction across multi-modal channels by sharing the down-sampling blocks between two encoding branches to eliminate misleading features. Furthermore, we combine feature maps of different resolutions to derive spatially varying fusion maps and enhance the lesions information. In addition, we introduce a similarity loss function for consistency constraint in case that predictions of separated refactoring branches for the same regions vary a lot. We evaluate our model for liver tumor segmentation using a PET-CT scans dataset, compare our method with the baseline techniques for multi-modal (multi-branches, multi-channels and cascaded networks) and then demonstrate that our method has a significantly higher accuracy ( ) than the baseline models.

A Formula to Calculate the Threshold for Radiotherapy Targets on PET Images: Simulation Study

Background

Positron emission tomography (PET) images are being applied for defining radiotherapy targets. However, a recognized method for defining radiotherapy targets is lacking. We investigate the threshold to outline the radiotherapy target of a tumor on PET images and its influencing factors, and then expressed it by formula.

Methods

PET imaging for spherical tumors with a different tumor diameter (D), under different system resolutions [full width at half maximum (FWHM)], in different backgrounds with different pixel sizes, was simulated. PET images were analyzed to determine the relationship between the threshold and the factors mentioned above. Finally, the simulation results were verified by phantom experiments.

Results

The threshold decreased sharply with D for D < 2 FWHM, reached the minimum of 31% at D = 2 FWHM and then increased slowly, and it tended to constant for D > 8 FWHM. The threshold decreased with FWHM for FWHM < D/2, reached a minimum at FWHM = D/2, and then increased. The threshold increased with pixel size for D ≤ FWHM and decreased for D > FWHM. The threshold was independent of the background. The relationship between the threshold and its influencing factors was expressed as a formula. The results of the phantom verification indicated that the error of the target volume delineation that was calculated by the formula was less than 9%.

Conclusions

The threshold changes with tumor size, resolution of the PET system and pixel size according to certain rules. The formula to calculate the threshold could provide a method to estimate threshold to outline the radiotherapy target (tumor).

Moving Beyond the Pillars of Cancer Treatment: Perspectives From Nanotechnology

Nanotechnology has made a significant impact on basic and clinical cancer research over the past two decades. Owing to multidisciplinary advances, cancer nanotechnology aims to address the problems in current cancer treatment paradigms, with the ultimate goal to improve treatment efficacy, increase patient survival, and decrease toxic side-effects. The potential for use of nanomedicine in cancer targeting and therapy has grown, and is now used to advance the four traditional pillars of cancer treatment: surgery, chemotherapy, radiation therapy and the newest pillar, immunotherapy. In this review we provide an overview of notable advances of nanomedicine in improving drug delivery, radiation therapy and immunotherapy. Potential barriers in the translation of nanomedicine from bench to bedside as well as strategies to overcome these barriers are also discussed. Promising preclinical findings highlight the translational and clinical potential of integrating nanotechnology approaches into cancer care.

Dosimetric Comparison of Lung-Sparing Radiation Therapy between Volumetric Arc Therapy and Helical Tomotherapy for Unresectable Malignant Pleural Mesothelioma

Objective

To compare volumetric arc therapy (VMAT) and helical tomotherapy (HT) plans in terms of dosimetric parameters in positron emission tomography- (PET-) computerized tomography- (CT-) based radiation therapy planning in unresectable malignant pleural mesothelioma (MPM).

Methods

CT and coregistered PET-CT data from seven patients with histologically-proven MPM were utilized for VMAT and HT plans. Target volumes and organs at risk (OARs) were delineated. The prescription doses for planning target volume 1 (PTV₁) and PTV₂ were 45.0 Gy and 54 Gy in 1.8 Gy/fr, respectively. Each technique was evaluated in terms of target volume coverage and OAR doses.

Findings

Although the maximum (p=0.001) and mean (p < 0.001) doses of PTV₁, and PTV₂ (p < 0.001 for maximum and p=0.001 for mean doses) favored the HT technique over VMAT, both techniques efficiently covered the target volumes. Additionally, HT also provided more homogeneous dose distribution (p < 0.001) and numerically lower doses received by most OARs, but again both rotational techniques were successful in keeping the OAR doses below the universally accepted limits. The major disadvantage of the HT technique was the requirement for longer treatment times (7.4 versus 2.5 minutes/fr; p < 0.001) to accomplish the intended treatment.

Conclusion

Results of this dosimetric comparison clearly demonstrated the possibility of safe hemithoracic irradiation of medically/technically unresectable MPM patients with either of the two rotational RT techniques, namely the VMAT and HT. Clinically, considering their poor prognosis, these promising findings may open a potential new window for curative treatment of unresectable MPM patients, if further confirmed by future clinical studies.

Real-time control of respiratory motion: Beyond radiation therapy

Motion management in radiation oncology is an important aspect of modern treatment planning and delivery. Special attention has been paid to control respiratory motion in recent years. However, other medical procedures related to both diagnosis and treatment are likely to benefit from the explicit control of breathing motion. Quantitative imaging - including increasingly important tools in radiology and nuclear medicine - is among the fields where a rapid development of motion control is most likely, due to the need for quantification accuracy. Emerging treatment modalities like focussed-ultrasound tumor ablation are also likely to benefit from a significant evolution of motion control in the near future. In the present article an overview of available respiratory motion systems along with ongoing research in this area is provided. Furthermore, an attempt is made to envision some of the most expected developments in this field in the near future.

Task Group 174 Report: Utilization of [18 F]Fluorodeoxyglucose Positron Emission Tomography ([18 F]FDG-PET) in Radiation Therapy

The use of positron emission tomography (PET) in radiation therapy (RT) is rapidly increasing in the areas of staging, segmentation, treatment planning, and response assessment. The most common radiotracer is ¹⁸ F-fluorodeoxyglucose ([¹⁸ F]FDG), a glucose analog with demonstrated efficacy in cancer diagnosis and staging. However, diagnosis and RT planning are different endeavors with unique requirements, and very little literature is available for guiding physicists and clinicians in the utilization of [¹⁸ F]FDG-PET in RT. The two goals of this report are to educate and provide recommendations. The report provides background and education on current PET imaging systems, PET tracers, intensity quantification, and current utilization in RT (staging, segmentation, image registration, treatment planning, and therapy response assessment). Recommendations are provided on acceptance testing, annual and monthly quality assurance, scanning protocols to ensure consistency between interpatient scans and intrapatient longitudinal scans, reporting of patient and scan parameters in literature, requirements for incorporation of [¹⁸ F]FDG-PET in treatment planning systems, and image registration. The recommendations provided here are minimum requirements and are not meant to cover all aspects of the use of [¹⁸ F]FDG-PET for RT.

The Impact of 18F-deoxyglucose Positron Emission Tomography on Tumor Staging, Treatment Strategy and Treatment Planning for Radiotherapy in a Department of Radiation Oncology

Aims and Background

The study analyzed the potential contribution of positron emission tomography (PET) in patient selection for radiotherapy and in radiation therapy planning.

Methods

Eighty-seven patients with a histological cancer diagnosis were accrued for the study from December 2000 to December 2001. Demographic characteristics included a median age of 54 years and male/female ratio of 51/36. All patients staged by conventional workup who were candidates for radiotherapy had PET imaging and were allocated to a conventional “pre/post-PET stage”. The treatment protocol and the shape and/or size of the portals was directly related to PET results. We examined 26 lung cancers, 15 gastrointestinal tumors, 22 genitourinary cancers and 24 hematologic malignancies.

Results

In the lung cancer group, the stage was modified in 10/26 patients (38.5%) by PET, with a change in management in 13 (50%) and a change in radiotherapy planning in 6 (23.1%). In the hematological group, stage was modified by PET in 8/24 cases (33.3%), with a change in treatment strategy in 9 (37.5%) and a change in radiotherapy planning in 3 (12.5%). In the gastrointestinal group, the stage was modified by PET in 2/15 cases (13.4%), with a change inn treatment strategy in 4 (26.7%) and a change in the decision for radiotherapy in 8 (no radiotherapy in 53.3%). In the mixed group (genitourinary, breast and other), the stage was modified by PET in 6/22 cases (27.3%), with a change in treatment strategy in 11 (50%) and a very low rate of change in radiotherapy planning.

Conclusions

PET contributed to a modification of stage in 26/87 patients (30%), to a changing in treatment strategy in 37/87 (42.5%), and to a substantial change of the shape and/or size of radiotherapy portals in 13/43 (30%) who underwent radiotherapy.

Role of Computed Tomographyand [18F] Fluorodeoxyglucose Positron Emission Tomography Image Fusion in Conformal Radiotherapy of Non-Small Cell Lung Cancer: A Comparison with Standard Techniques with and without Elective Nodal Irradiation

Aims and background

Mediastinal elective node irradiation (ENI) in patients with non-small cell lung cancer candidate to radical radiotherapy is controversial. In this study, the impact of co-registered [18F]fluorodeoxyglucose-positron emission tomography (PET) and standard computed tomography (CT) on definition of target volumes and toxicity parameters was evaluated, by comparison with standard CT-based simulation with and without ENI.

Methods

CT-based gross tumor volume (GTVCT) was first contoured by a single observer without knowledge of PET results. Subsequently, the integrated GTV based on PET/CT coregistered images (GTVPET/CT) was defined. Each patient was planned according to three different treatment techniques: 1) radiotherapy with ENI using the CT data set alone (ENI plan); 2) radiotherapy without ENI using the CT data set alone (no ENI plan); 3) radiotherapy without ENI using PET/CT fusion data set (PET plan). Rival plans were compared for each patient with respect to dose to the normal tissues (spinal cord, healthy lungs, heart and esophagus).

Results

The addition of PET-modified TNM staging in 10/21 enrolled patients (48%); 3/21 were shifted to palliative treatment due to detection of metastatic disease or large tumor not amenable to high-dose radiotherapy. In 7/18 (39%) patients treated with radical radiotherapy, a significant (≥25%) change in volume between GTVCT and GTVPET/CT was observed. For all the organs at risk, ENI plans had dose values significantly greater than no-ENI and PET plans. Comparing no ENI and PET plans, no statistically significant difference was observed, except for maximum point dose to the spinal cord Dmax, which was significantly lower in PET plans. Notably, even in patients in whom PET/CT planning resulted in an increased GTV, toxicity parameters were fairly acceptable, and always more favorable than with ENI plans.

Conclusions

Our study suggests that [18F]-fluorodeoxyglucose-PET should be integrated in no-ENI techniques, as it improves target volume delineation without a major increase in predicted toxicity.

Comparison of different automated lesion delineation methods for metabolic tumor volume of 18F-FDG PET/CT in patients with stage I lung adenocarcinoma

The aim of the study was to investigate the suitable segmentation method in small, low uptake and heterogeneous nodules of stage I lung adenocarcinoma.133 stage I lung adenocarcinoma patients with F-FDG PET/CT scans were enrolled in this retrospective study. All lesions were divided into different groups according to nodule density, nodule size, and the maximum standard uptake value (SUVmax) level. Four different PET segmentation methods were performed, including percentage threshold of SUVmax (T42% and T42% × RC), gradient-based threshold (adaptive iterative algorithm, AT-AIA), and background-related threshold (adaptive thresholding at 40% SUVmax, AT40%) approaches. The MTVs were evaluated and compared with CT volume (CTV). Percentage volume error (%VE) compared to CTV was calculated and the correlations between MTVs and CTV were analyzed.AT-AIA had the highest accuracy in large, high uptake, and solid nodules (72.5%, 72.4%, and 65.6%, respectively). AT40% had the highest accuracy in small, low uptake and nonsolid nodules (56.6%, 56.1%, and 62.6%, respectively). In part-solid nodules, the accuracy of AT-AIA (60.0%) and AT40% (56.7%) were higher than that of T42% and T42% × RC. The MTV of AT-AIA was in excellent correlation with the CTV in solid nodules (R = 0.831, P < .001) and in high uptake nodules (R = 0.830, P < .001). The MTV of AT40% was in good correlation with the CTV in nonsolid nodules (R = 0.686, P = .003) and in part-solid nodules (R = 0.731, P < .001).AT40% showed best performance in small, low uptake, nonsolid and part-solid lesions. AT-AIA was suitable for large, high uptake, and solid lesions.

Hybrid PET/MRI co-segmentation based on joint fuzzy connectedness and graph cut

BACKGROUND AND OBJECTIVE

Tumor segmentation from hybrid PET/MRI scans may be highly beneficial in radiotherapy treatment planning. Indeed, it gives for both modalities the suitable information that could make the delineation of tumors more accurate than using each one apart. We aim in this work to propose a co-segmentation method that deals with several challenges, notably the lack of one-to-one correspondence between tumors of the two modalities and the boundaries' smoothing.

METHODS

The proposed method is designed to surpass these limits, we propose a segmentation method based on the GC_sum^max technique. The method takes the advantage of Iterative Relative Fuzzy Connectedness (IRFC) on seeds initialization, and the standard min-cut/max-flow technique for the boundary smoothing. Seed initialization was accurately performed thanks to high uptake regions on PET. Besides, a visibility weighting scheme was adapted to achieve the task of co-segmentation using the IRFC algorithm. Then, given the co-segmented regions, we introduce a morphological-based technique that provides object seeds to standard Graph Cut (GC) allowing it to avoid the shrinking problem. Finally, for each modality, the segmentation task is formulated as an energy minimization problem which is resolved by a min-cut/max-flow technique.

RESULTS

The overlap ratio (denoted DSC) between our segmentation results and the ground-truth for PET images is 92.63  ±  1.03, while the DSC for MRI images is 90.61  ±  3.70.

CONCLUSIONS

The proposed method was tested on different types of diseases and it outperformed the state-of-the-art methods. We show its superiority in terms of assymetric relation between PET and MRI and tumors heterogeneity.

Automatic concentration and reformulation of PET tracers via microfluidic membrane distillation

Short-lived radiolabeled tracers for positron emission tomography (PET) must be rapidly synthesized, purified, and formulated into injectable solution just prior to imaging. Current radiosynthesizers are generally designed for clinical use, and the HPLC purification and SPE formulation processes often result in a final volume that is too large for preclinical and emerging in vitro applications. Conventional technologies and techniques for reducing this volume tend to be slow, resulting in radioactive decay of the product, and often require manual handling of the radioactive materials. We present a fully-automated microfluidic system based on sweeping gas membrane distillation to rapidly perform the concentration and formulation process. After detailed characterization of the system, we demonstrate fast and efficient concentration and formulation of several PET tracers, evaluate residual solvent content to establish the safety of the formulated tracers for injection, and show that the formulated tracer can be used for in vivo imaging.

Variabilities of Magnetic Resonance Imaging-, Computed Tomography-, and Positron Emission Tomography-Computed Tomography-Based Tumor and Lymph Node Delineations for Lung Cancer Radiation Therapy Planning

PURPOSE

To investigate interobserver delineation variability for gross tumor volumes of primary lung tumors and associated pathologic lymph nodes using magnetic resonance imaging (MRI), and to compare the results with computed tomography (CT) alone- and positron emission tomography (PET)-CT-based delineations.

METHODS AND MATERIALS

Seven physicians delineated the tumor volumes of 10 patients for the following scenarios: (1) CT only, (2) PET-CT fusion images registered to CT ("clinical standard"), and (3) postcontrast T1-weighted MRI registered with diffusion-weighted MRI. To compute interobserver variability, the median surface was generated from all observers' contours and used as the reference surface. A physician labeled the interface types (tumor to lung, atelectasis (collapsed lung), hilum, mediastinum, or chest wall) on the median surface. Contoured volumes and bidirectional local distances between individual observers' contours and the reference contour were analyzed.

RESULTS

Computed tomography- and MRI-based tumor volumes normalized relative to PET-CT-based volumes were 1.62 ± 0.76 (mean ± standard deviation) and 1.38 ± 0.44, respectively. Volume differences between the imaging modalities were not significant. Between observers, the mean normalized volumes per patient averaged over all patients varied significantly by a factor of 1.6 (MRI) and 2.0 (CT and PET-CT) (P=4.10 × 10^-5 to 3.82 × 10^-9). The tumor-atelectasis interface had a significantly higher variability than other interfaces for all modalities combined (P=.0006). The interfaces with the smallest uncertainties were tumor-lung (on CT) and tumor-mediastinum (on PET-CT and MRI).

CONCLUSIONS

Although MRI-based contouring showed overall larger variability than PET-CT, contouring variability depended on the interface type and was not significantly different between modalities, despite the limited observer experience with MRI. Multimodality imaging and combining different imaging characteristics might be the best approach to define the tumor volume most accurately.

CT-based texture analysis potentially provides prognostic information complementary to interim fdg-pet for patients with hodgkin's and aggressive non-hodgkin's lymphomas

OBJECTIVES

The purpose of this study was to investigate the ability of computed tomography texture analysis (CTTA) to provide additional prognostic information in patients with Hodgkin's lymphoma (HL) and high-grade non-Hodgkin's lymphoma (NHL).

METHODS

This retrospective, pilot-study approved by the IRB comprised 45 lymphoma patients undergoing routine 18F-FDG-PET-CT. Progression-free survival (PFS) was determined from clinical follow-up (mean-duration: 40 months; range: 10-62 months). Non-contrast-enhanced low-dose CT images were submitted to CTTA comprising image filtration to highlight features of different sizes followed by histogram-analysis using kurtosis. Prognostic value of CTTA was compared to PET FDG-uptake value, tumour-stage, tumour-bulk, lymphoma-type, treatment-regime, and interim FDG-PET (iPET) status using Kaplan-Meier analysis. Cox regression analysis determined the independence of significantly prognostic imaging and clinical features.

RESULTS

A total of 27 patients had aggressive NHL and 18 had HL. Mean PFS was 48.5 months. There was no significant difference in pre-treatment CTTA between the lymphoma sub-types. Kaplan-Meier analysis found pre-treatment CTTA (medium feature scale, p=0.010) and iPET status (p<0.001) to be significant predictors of PFS. Cox analysis revealed that an interaction between pre-treatment CTTA and iPET status was the only independent predictor of PFS (HR: 25.5, 95% CI: 5.4-120, p<0.001). Specifically, pre-treatment CTTA risk stratified patients with negative iPET.

CONCLUSION

CTTA can potentially provide prognostic information complementary to iPET for patients with HL and aggressive NHL.

KEY POINTS

• CT texture-analysis (CTTA) provides prognostic information complementary to interim FDG-PET in Lymphoma. • Pre-treatment CTTA and interim PET status were significant predictors of progression-free survival. • Patients with negative interim PET could be further stratified by pre-treatment CTTA. • Provide precision surveillance where additional imaging reserved for patients at greatest recurrence-risk. • Assists in risk-adapted treatment strategy based on interim PET and CTTA.

Potential for adaptive dose escalation in radiotherapy for patients with locally advanced non-small-cell lung cancer in a low mid income setting

OBJECTIVE

To evaluate the effect of tumour volume regression on adaptive treatment planning, reduction in doses to organs at risk (OARs) and dose escalation.

METHODS

20 patients undergoing radical chemoradiotherapy were imaged in the fifth week of radiotherapy (CT_45) to evaluate differences in tumour volume regression between concurrent and sequential chemoradiotherapy. Replanning was carried out in the CT_45 in those with >20% regression (n = 10) and evaluated for change in target coverage indices (the coverage index and external volume index) and doses to the OAR [mean lung dose, V₂₀ and V₅ of whole and ipsilateral lung (MLD_WL, V_20WL, V_5WL, MLD_IL, V_20IL, V_5IL); mean oesophagus dose, V_50oesophagus; and maximum spinal cord doses]. The feasibility of maximum dose escalation was explored keeping the limit of the OAR below their tolerance limits.

RESULTS

Tumour regression was higher with concurrent chemoradiotherapy as compared with sequential chemoradiotherapy (p = 0.02). With the adaptive plan, the mean coverage index improved from 0.96 (±0.14) to 1.29 (±0.36), the mean external volume index changed from 1.39(±0.60) to 1.41(±0.56) and the reduction in doses to the OARs were MLD_WL 10.6%, V_20WL 1.3%, V_5WL 1.2%, MLD_IL 6.6%, V_20IL 1.5%, V_5IL 2.3%, mean oesophagus dose 7%, V_50oesophagus 31% and maximum cord dose 0.35%. Dose escalation was possible in four patients in CT_45.

CONCLUSION

There is 35% reduction in tumour volume with chemoradiotherapy at 45 Gy which allows improvement in conformality, reduction in doses to the OARs and dose escalation in 40% of patients. Advances in knowledge: This article emphasizes that adaptive planning with a single diagnostic scan at 45 Gy has the potential for improvement of radiotherapy planning indices, dose escalation while respecting the dose to the OAR. This simple strategy can be helpful in radiotherapy planning upto 60 Gy in 40% of the patients of locally advanced non-small-cell lung cancer in countries with limited resources.

Single-Channel Sparse Non-Negative Blind Source Separation Method for Automatic 3-D Delineation of Lung Tumor in PET Images

In this paper, we propose a novel method for single-channel blind separation of nonoverlapped sources and, to the best of our knowledge, apply it for the first time to automatic segmentation of lung tumors in positron emission tomography (PET) images. Our approach first converts a 3-D PET image into a pseudo-multichannel image. Afterward, regularization free sparseness constrained non-negative matrix factorization is used to separate tumor from other tissues. By using complexity based criterion, we select tumor component as the one with minimal complexity. We have compared the proposed method with threshold based on 40% and 50% maximum standardized uptake value (SUV), graph cuts (GC), random walks (RW), and affinity propagation (AP) algorithms on 18 nonsmall cell lung cancer datasets with respect to ground truth (GT) provided by two radiologists. Dice similarity coefficient averaged with respect to two GTs is: 0.78 ± 0.12 by the proposed algorithm, 0.78 ± 0.1 by GC, 0.77 ± 0.13 by AP, 0.77 ± 0.07 by RW, and 0.75 ± 0.13 by 50% maximum SUV threshold. Since the proposed method achieved performance comparable with interactive methods, considering the unique challenges of lung tumor segmentation from PET images, our findings support possibility of using our fully automated method in routine clinics. The source codes will be available at www.mipav.net/English/research/research.html.

Use of Positron Emission Tomography/Computed Tomography in Radiation Treatment Planning for Lung Cancer

Radiotherapy (RT) plays an important role in the treatment of lung cancer. Accurate diagnosis and staging are crucial in the delivery of RT with curative intent. Target miss can be prevented by accurate determination of tumor contours during RT planning. Currently, tumor contours are determined manually by computed tomography (CT) during RT planning. This method leads to differences in delineation of tumor volume between users. Given the change in RT tools and methods due to rapidly developing technology, it is now more significant to accurately delineate the tumor tissue. F18 fluorodeoxyglucose positron emission tomography/CT (F18 FDG PET/CT) has been established as an accurate method in correctly staging and detecting tumor dissemination in lung cancer. Since it provides both anatomic and biologic information, F18 FDG PET decreases inter-user variability in tumor delineation. For instance, tumor volumes may be decreased as atelectasis and malignant tissue can be more accurately differentiated, as well as better evaluation of benign and malignant lymph nodes given the difference in FDG uptake. Using F18 FDG PET/CT, the radiation dose can be escalated without serious adverse effects in lung cancer. In this study, we evaluated the contribution of F18 FDG PET/CT for RT planning in lung cancer.

Respiratory motion correction in 4D-PET by simultaneous motion estimation and image reconstruction (SMEIR)

In conventional 4D positron emission tomography (4D-PET), images from different frames are reconstructed individually and aligned by registration methods. Two issues that arise with this approach are as follows: (1) the reconstruction algorithms do not make full use of projection statistics; and (2) the registration between noisy images can result in poor alignment. In this study, we investigated the use of simultaneous motion estimation and image reconstruction (SMEIR) methods for motion estimation/correction in 4D-PET. A modified ordered-subset expectation maximization algorithm coupled with total variation minimization (OSEM-TV) was used to obtain a primary motion-compensated PET (pmc-PET) from all projection data, using Demons derived deformation vector fields (DVFs) as initial motion vectors. A motion model update was performed to obtain an optimal set of DVFs in the pmc-PET and other phases, by matching the forward projection of the deformed pmc-PET with measured projections from other phases. The OSEM-TV image reconstruction was repeated using updated DVFs, and new DVFs were estimated based on updated images. A 4D-XCAT phantom with typical FDG biodistribution was generated to evaluate the performance of the SMEIR algorithm in lung and liver tumors with different contrasts and different diameters (10-40 mm). The image quality of the 4D-PET was greatly improved by the SMEIR algorithm. When all projections were used to reconstruct 3D-PET without motion compensation, motion blurring artifacts were present, leading up to 150% tumor size overestimation and significant quantitative errors, including 50% underestimation of tumor contrast and 59% underestimation of tumor uptake. Errors were reduced to less than 10% in most images by using the SMEIR algorithm, showing its potential in motion estimation/correction in 4D-PET.

3D-Segmentation of the 18F-choline PET Signal for Target Volume Definition in Radiation Therapy of the Prostate

Volumetric assessment of PET signals becomes increasingly relevant for radiotherapy (RT) planning. Here, we investigate the utility of 18F-choline PET signals to serve as a structure for semi-automatic segmentation for forward treatment planning of prostate cancer. 18F-choline PET and CT scans of ten patients with histologically proven prostate cancer without extracapsular growth were acquired using a combined PET/CT scanner. Target volumes were manually delineated on CT images using standard software. Volumes were also obtained from 18F-choline PET images using an asymmetrical segmentation algorithm. PTVs were derived from CT 18F-choline PET based clinical target volumes (CTVs) by automatic expansion and comparative planning was performed. As a read-out for dose given to non-target structures, dose to the rectal wall was assessed. Planning target volumes (PTVs) derived from CT and 18F-choline PET yielded comparable results. Optimal matching of CT and 18F-choline PET derived volumes in the lateral and cranial-caudal directions was obtained using a background-subtracted signal thresholds of 23.0+/-2.6%. In antero-posterior direction, where adaptation compensating for rectal signal overflow was required, optimal matching was achieved with a threshold of 49.5+/-4.6%. 3D-conformal planning with CT or 18F-choline PET resulted in comparable doses to the rectal wall. Choline PET signals of the prostate provide adequate spatial information amendable to standardized asymmetrical region growing algorithms for PET-based target volume definition for external beam RT.

Volumetric and dosimetric comparison of computerised radiotherapy treatment plan between using positron emission tomography/computed tomography (PET/CT) and CT images for target delineation in non-small cell lung cancer patients

Purpose

To compare intensity-modulated radiation therapy (IMRT) treatment planning between using positron emission tomography/computed tomography (PET/CT) and CT for target volume delineation in patients with non-small cell lung cancer (NSCLC).

Methods

Nine NSCLC patients with PET/CT images were enrolled into this study. Gross tumour volumes (GTVs) were delineated by the PET visual assessment (PETvis), the automated PET (PETauto), standardised uptake value (SUV)>2·5 (PET2·5) and threshold 40% SUVmax (PET40), and CT-based method. For each patient, two IMRT treatment plans based on CT and PET/CT delineation were performed. The target coverage and the dose–volume parameters for organs at risk were analysed.

Results

The PETauto referred to PET40 when SUVmax<7 and PET2·5 when SUVmax≥7. The mean GTVs were 15·04, 15·7 and 15·14 cc for PETauto, PETvis and CT based, respectively. The GTV of PETauto was not different from PETvis (p=0·441) and CT based (p=0·594). Based on CT delineation in IMRT planning, only 34% of the cases had sufficient PET/CT planning target volumes coverage, whereas the organs at risk dose parameters were not statistically significant (p>0·05).

Conclusions

PET/CT enables more accurate assessment of tumour delineation for NSCLC, therefore improve target coverage in IMRT plan.

FDG-PET-based differential uptake volume histograms: a possible approach towards definition of biological target volumes

OBJECTIVE

Integration of fluorine-18 fludeoxyglucose ((18)F-FDG)-positron emission tomography (PET) functional data into conventional anatomically based gross tumour volume delineation may lead to optimization of dose to biological target volumes (BTV) in radiotherapy. We describe a method for defining tumour subvolumes using (18)F-FDG-PET data, based on the decomposition of differential uptake volume histograms (dUVHs).

METHODS

For 27 patients with histopathologically proven non-small-cell lung carcinoma (NSCLC), background uptake values were sampled within the healthy lung contralateral to a tumour in those image slices containing tumour and then scaled by the ratio of mass densities between the healthy lung and tumour. Signal-to-background (S/B) uptake values within volumes of interest encompassing the tumour were used to reconstruct the dUVHs. These were subsequently decomposed into the minimum number of analytical functions (in the form of differential uptake values as a function of S/B) that yielded acceptable net fits, as assessed by χ(2) values.

RESULTS

Six subvolumes consistently emerged from the fitted dUVHs over the sampled volume of interest on PET images. Based on the assumption that each function used to decompose the dUVH may correspond to a single subvolume, the intersection between the two adjacent functions could be interpreted as a threshold value that differentiates them. Assuming that the first two subvolumes spread over the tumour boundary, we concentrated on four subvolumes with the highest uptake values, and their S/B thresholds [mean ± standard deviation (SD)] were 2.88 ± 0.98, 4.05 ± 1.55, 5.48 ± 2.06 and 7.34 ± 2.89 for adenocarcinoma, 3.01 ± 0.71, 4.40 ± 0.91, 5.99 ± 1.31 and 8.17 ± 2.42 for large-cell carcinoma and 4.54 ± 2.11, 6.46 ± 2.43, 8.87 ± 5.37 and 12.11 ± 7.28 for squamous cell carcinoma, respectively.

CONCLUSION

(18)F-FDG-based PET data may potentially be used to identify BTV within the tumour in patients with NSCLC. Using the one-way analysis of variance statistical tests, we found a significant difference among all threshold levels among adenocarcinomas, large-cell carcinoma and squamous cell carcinomas. On the other hand, the observed significant variability in threshold values throughout the patient cohort (expressed as large SDs) can be explained as a consequence of differences in the physiological status of the tumour volume for each patient at the time of the PET/CT scan. This further suggests that patient-specific threshold values for the definition of BTVs could be determined by creation and curve fitting of dUVHs on a patient-by-patient basis.

ADVANCES IN KNOWLEDGE

The method of (18)F-FDG-PET-based dUVH decomposition described in this work may lead to BTV segmentation in tumours.

Which radiation therapy schedule in combination with chemotherapy for locally advanced NSCLC?

Concurrent chemoradiotherapy is the standard of care in the management of locally advanced NSCLC, with disappointing results in terms of local tumor control and overall survival. Hystorically, it has been demonstrated a strict dose–response relationship in thoracic radiotherapy for lung cancer and, therefore, dose escalation was tested in many prospective trials. In this paper, we briefly review the most relevant publications focusing on dose management in terms of dose escalation with both conventional and altered fractionation schedules.

Random Walk and Graph Cut for Co-Segmentation of Lung Tumor on PET-CT Images

Accurate lung tumor delineation plays an important role in radiotherapy treatment planning. Since the lung tumor has poor boundary in positron emission tomography (PET) images and low contrast in computed tomography (CT) images, segmentation of tumor in the PET and CT images is a challenging task. In this paper, we effectively integrate the two modalities by making fully use of the superior contrast of PET images and superior spatial resolution of CT images. Random walk and graph cut method is integrated to solve the segmentation problem, in which random walk is utilized as an initialization tool to provide object seeds for graph cut segmentation on the PET and CT images. The co-segmentation problem is formulated as an energy minimization problem which is solved by max-flow/min-cut method. A graph, including two sub-graphs and a special link, is constructed, in which one sub-graph is for the PET and another is for CT, and the special link encodes a context term which penalizes the difference of the tumor segmentation on the two modalities. To fully utilize the characteristics of PET and CT images, a novel energy representation is devised. For the PET, a downhill cost and a 3D derivative cost are proposed. For the CT, a shape penalty cost is integrated into the energy function which helps to constrain the tumor region during the segmentation. We validate our algorithm on a data set which consists of 18 PET-CT images. The experimental results indicate that the proposed method is superior to the graph cut method solely using the PET or CT is more accurate compared with the random walk method, random walk co-segmentation method, and non-improved graph cut method.

PET image segmentation using a Gaussian mixture model and Markov random fields

Background

Classification algorithms for positron emission tomography (PET) images support computational treatment planning in radiotherapy. Common clinical practice is based on manual delineation and fixed or iterative threshold methods, the latter of which requires regression curves dependent on many parameters.

Methods

An improved statistical approach using a Gaussian mixture model (GMM) is proposed to obtain initial estimates of a target volume, followed by a correction step based on a Markov random field (MRF) and a Gibbs distribution to account for dependencies among neighboring voxels. In order to evaluate the proposed algorithm, phantom measurements of spherical and non-spherical objects with the smallest diameter being 8 mm were performed at signal-to-background ratios (SBRs) between 2.06 and 9.39. Additionally ⁶⁸Ga-PET data from patients with lesions in the liver and lymph nodes were evaluated.

Results

The proposed algorithm produces stable results for different reconstruction algorithms and different lesion shapes. Furthermore, it outperforms all threshold methods regarding detection rate, determines the spheres’ volumes more accurately than fixed threshold methods, and produces similar values as iterative thresholding. In a comparison with other statistical approaches, the algorithm performs equally well for larger volumes and even shows improvements for small volumes and SBRs. The comparison with experts’ manual delineations on the clinical data shows the same qualitative behavior as for the phantom measurements.

Conclusions

In conclusion, a generic probabilistic approach that does not require data measured beforehand is presented whose performance, robustness, and swiftness make it a feasible choice for PET segmentation.

The role of PET-CT in radiotherapy planning of solid tumours

Background

PET-CT is becoming more and more important in various aspects of oncology. Until recently it was used mainly as part of diagnostic procedures and for evaluation of treatment results. With development of personalized radiotherapy, volumetric and radiobiological characteristics of individual tumour have become integrated in the multistep radiotherapy (RT) planning process. Standard anatomical imaging used to select and delineate RT target volumes can be enriched by the information on tumour biology gained by PET-CT. In this review we explore the current and possible future role of PET-CT in radiotherapy treatment planning. After general explanation, we assess its role in radiotherapy of those solid tumours for which PET-CT is being used most.

Conclusions

In the nearby future PET-CT will be an integral part of the most radiotherapy treatment planning procedures in an every-day clinical practice. Apart from a clear role in radiation planning of lung cancer, with forthcoming clinical trials, we will get more evidence of the optimal use of PET-CT in radiotherapy planning of other solid tumours.

Lung cancer

(18)F-fluorodeoxyglucose-positron emission tomography/computed tomography (FDG-PET/CT) plays a key role in the evaluation of undiagnosed lung nodules, when primary lung cancer is strongly suspected, or when it has already been diagnosed by other techniques. Although technical factors may compromise characterization of small or highly mobile lesions, lesions without apparent FDG uptake can generally be safely observed, whereas FDG-avid lung nodules almost always need further evaluation. FDG-PET/CT is now the primary staging imaging modality for patients with lung cancer who are being considered for curative therapy with either surgery or definitive radiation therapy.

The utility of positron emission tomography in the treatment planning of image-guided radiotherapy for non-small cell lung cancer

In the thorax, the extent of tumor may be more accurately defined with the addition of ¹⁸F-fluorodeoxyglucose (FDG) positron emission tomography (PET) to computed tomography (CT). This led to the increased utility of FDG-PET or PET/CT in the treatment planning of radiotherapy for non-small cell lung cancer (NSCLC). The inclusion of FDG-PET information in target volume delineation not only improves tumor localization but also decreases the amount of normal tissue included in the planning target volume (PTV) in selected patients. Therefore, it has a critical role in image-guided radiotherapy (IGRT) for NSCLC. In this review, the impact of FDG-PET on target volume delineation in radiotherapy for NSCLC, which may increase the possibility of safe dose escalation with IGRT, the commonly used methods for tumor target volume delineation FDG-PET for NSCLC, and its impact on clinical outcome will be discussed.

Strategies of dose escalation in the treatment of locally advanced non-small cell lung cancer: image guidance and beyond

Radiation dose in the setting of chemo-radiation for locally advanced non-small cell lung cancer (NSCLC) has been historically limited by the risk of normal tissue toxicity and this has been hypothesized to correlate with the poor results in regard to local tumor recurrences. Dose escalation, as a means to improve local control, with concurrent chemotherapy has been shown to be feasible with three-dimensional conformal radiotherapy in early phase studies with good clinical outcome. However, the potential superiority of moderate dose escalation to 74 Gy has not been shown in phase III randomized studies. In this review, the limitations in target volume definition in previous studies; and the factors that may be critical to safe dose escalation in the treatment of locally advanced NSCLC, such as respiratory motion management, image guidance, intensity modulation, FDG-positron emission tomography incorporation in the treatment planning process, and adaptive radiotherapy, are discussed. These factors, along with novel treatment approaches that have emerged in recent years, are proposed to warrant further investigation in future trials in a more comprehensive and integrated fashion.

Comparison of the accuracy of PET/CT and PET/MRI spatial registration of multiple metastatic lesions

OBJECTIVE

The purpose of this study was to compare the accuracy of the spatial registration of conventional PET/CT with that of hybrid PET/MRI of patients with FDG-avid metastatic lesions.

SUBJECTS AND METHODS

Thirteen patients with known metastatic lesions underwent FDG PET/CT followed by PET/MRI with a hybrid whole-body system. The inclusion criterion for tumor analysis was spherical or oval FDG-avid tumor clearly identified with both CT and MRI. The spatial coordinates (x, y, z) of the visually estimated centers of the lesions were determined for PET/CT (PET and CT independently) and PET/MRI (PET, T1-weighted gradient-echo sequence with radial stack-of-stars trajectory, T2-weighted sequence), and the b0 images of an echo-planar imaging (EPI) diffusion-weighted imaging (DWI) acquisition. All MRI sequences were performed in the axial plane with free breathing. The spatial coordinates of the estimated centers of the lesions were determined for PET and CT and PET and MRI sequences. Distance between the isocenter of the lesion on PET images and on the images obtained with the anatomic modalities was measured, and misregistration (in millimeters) was calculated. The degree of misregistration was compared between PET/CT and PET/MRI with a paired Student t test.

RESULTS

Nineteen lesions were evaluated. On PET/CT images, the average of the total misregistration in all planes of CT compared with PET was 4.13 ± 4.24 mm. On PET/MR images, lesion misregistration between PET and T1-weighted gradient-echo images had a shift of 2.41 ± 1.38 mm and between PET and b0 DW images was 5.97 ± 2.83 mm. Similar results were calculated for 11 lesions on T2-weighted images. The shift on T2-weighted images compared with PET images was 2.24 ± 1.12 mm. Paired Student t test calculations for PET/CT compared with PET/MRI T1-weighted gradient-echo images with a radial stack-of-stars trajectory, b0 DW images, and T2-weighted images showed significant differences (p < 0.05). Similar results were seen in the analysis of six lung lesions.

CONCLUSION

PET/MRI T1-weighted gradient-echo images with a radial stack-of-stars trajectory and T2-weighted images had more accurate spatial registration than PET/CT images. This may be because that the whole-body PET/MRI system used can perform simultaneous acquisition, whereas the PET/CT system acquires data sequentially. However, the EPI-based b0 DWI datasets were significantly misregistered compared with the PET/CT datasets, especially in the thorax. Radiologists reading PET/MR images should be aware of the potential for misregistration on images obtained with EPI-based DWI sequences because of inherent spatial distortion associated with this type of MRI acquisition.

Defining internal target volume using positron emission tomography for radiation therapy planning of moving lung tumors

Substantial disagreement exists over appropriate PET segmentation techniques for non-small cell lung cancer. Currently, no segmentation algorithm explicitly considers tumor motion in determining tumor borders. We developed an automatic PET segmentation model as a function of target volume, motion extent, and source-to-background ratio (the VMSBR model). The purpose of this work was to apply the VMSBR model and six other segmentation algorithms to a sample of lung tumors. PET and 4D CT were performed in the same imaging session for 23 patients (24 tumors) for radiation therapy planning. Internal target volumes (ITVs) were autosegmented on maximum intensity projection (MIP) of cine CT. ITVs were delineated on PET using the following methods: 15%, 35%, and 42% of maximum activity concentration, standardized uptake value (SUV) of 2.5 g/mL, 15% of mean activity concentration plus background, a linear function of mean SUV, and the VMSBR model. Predicted threshold values from each method were compared to measured optimal threshold values, and resulting volume magnitudes were compared to cine-CT-derived ITV. Correlation between predicted and measured threshold values ranged from slopes of 0.29 for the simplest single-threshold techniques to 0.90 for the VMSBR technique. R2 values ranged from 0.07 for the simplest single-threshold techniques to 0.86 for the VMSBR technique. The VMSBR segmentation technique that included volume, motion, and source-to-background ratio, produced accurate ITVs in patients when compared with cine-CT-derived ITV.

Joint segmentation of anatomical and functional images: applications in quantification of lesions from PET, PET-CT, MRI-PET, and MRI-PET-CT images

We present a novel method for the joint segmentation of anatomical and functional images. Our proposed methodology unifies the domains of anatomical and functional images, represents them in a product lattice, and performs simultaneous delineation of regions based on random walk image segmentation. Furthermore, we also propose a simple yet effective object/background seed localization method to make the proposed segmentation process fully automatic. Our study uses PET, PET-CT, MRI-PET, and fused MRI-PET-CT scans (77 studies in all) from 56 patients who had various lesions in different body regions. We validated the effectiveness of the proposed method on different PET phantoms as well as on clinical images with respect to the ground truth segmentation provided by clinicians. Experimental results indicate that the presented method is superior to threshold and Bayesian methods commonly used in PET image segmentation, is more accurate and robust compared to the other PET-CT segmentation methods recently published in the literature, and also it is general in the sense of simultaneously segmenting multiple scans in real-time with high accuracy needed in routine clinical use.

A comparison of amplitude-based and phase-based positron emission tomography gating algorithms for segmentation of internal target volumes of tumors subject to respiratory motion

PURPOSE

To quantitatively compare the accuracy of tumor volume segmentation in amplitude-based and phase-based respiratory gating algorithms in respiratory-correlated positron emission tomography (PET).

METHODS AND MATERIALS

List-mode fluorodeoxyglucose-PET data was acquired for 10 patients with a total of 12 fluorodeoxyglucose-avid tumors and 9 lymph nodes. Additionally, a phantom experiment was performed in which 4 plastic butyrate spheres with inner diameters ranging from 1 to 4 cm were imaged as they underwent 1-dimensional motion based on 2 measured patient breathing trajectories. PET list-mode data were gated into 8 bins using 2 amplitude-based (equal amplitude bins [A1] and equal counts per bin [A2]) and 2 temporal phase-based gating algorithms. Gated images were segmented using a commercially available gradient-based technique and a fixed 40% threshold of maximum uptake. Internal target volumes (ITVs) were generated by taking the union of all 8 contours per gated image. Segmented phantom ITVs were compared with their respective ground-truth ITVs, defined as the volume subtended by the tumor model positions covering 99% of breathing amplitude. Superior-inferior distances between sphere centroids in the end-inhale and end-exhale phases were also calculated.

RESULTS

Tumor ITVs from amplitude-based methods were significantly larger than those from temporal-based techniques (P=.002). For lymph nodes, A2 resulted in ITVs that were significantly larger than either of the temporal-based techniques (P<.0323). A1 produced the largest and most accurate ITVs for spheres with diameters of ≥2 cm (P=.002). No significant difference was shown between algorithms in the 1-cm sphere data set. For phantom spheres, amplitude-based methods recovered an average of 9.5% more motion displacement than temporal-based methods under regular breathing conditions and an average of 45.7% more in the presence of baseline drift (P<.001).

CONCLUSIONS

Target volumes in images generated from amplitude-based gating are larger and more accurate, at levels that are potentially clinically significant, compared with those from temporal phase-based gating.

Radiotherapy for the treatment of pain in malignant pleural mesothelioma: a systematic review

Radiotherapy is commonly used to treat pain in malignant pleural mesothelioma (MPM). The purpose of this systematic review is to examine the evidence for this practice. Medline (1946-2013), Embase (1974-2013) and Central (The Cochrane Library Issue 9, 2012) databases were searched. Eligible studies met the following criteria: MPM (histological or radiological diagnosis), radiotherapy given with the intent of improving pain, response rates to radiotherapy reported, dose and fractionation reported and the relationship between radiotherapy and pain response explored. All studies had independent review and were graded according to evidence level. Eight studies met the eligibility criteria. Two studies were prospective single arm phase II studies while the remainder were retrospective case series. All were graded as either Level 2 or Level 3 evidence. Due to marked heterogeneity among studies, quantitative synthesis of results was not possible. No high quality evidence currently exists to support radiotherapy in treating pain in MPM. Studies focusing on clear pain endpoints and improving target delineation are needed. Such studies should also use modern radiotherapy techniques and concentrate on dose escalation.

The impact of PET/CT scanning on the size of target volumes, radiation exposure of organs at risk, TCP and NTCP, in the radiotherapy planning of non-small cell lung cancer

AIM

To compare radiotherapy plans made according to CT and PET/CT and to investigate the impact of changes in target volumes on tumour control probability (TCP), normal tissue complication probability (NTCP) and the impact of PET/CT on the staging and treatment strategy.

BACKGROUND

Contemporary studies have proven that PET/CT attains higher sensitivity and specificity in the diagnosis of lung cancer and also leads to higher accuracy than CT alone in the process of target volume delineation in NSCLC.

MATERIALS AND METHODS

Between October 2009 and March 2012, 31 patients with locally advanced NSCLC, who had been referred to radical radiotherapy were involved in our study. They all underwent planning PET/CT examination. Then we carried out two separate delineations of target volumes and two radiotherapy plans and we compared the following parameters of those plans: staging, treatment purpose, the size of GTV and PTV and the exposure of organs at risk (OAR). TCP and NTCP were also compared.

RESULTS

PET/CT information led to a significant decrease in the sizes of target volumes, which had the impact on the radiation exposure of OARs. The reduction of target volume sizes was not reflected in the significant increase of the TCP value. We found that there is a very strong direct linear relationship between all evaluated dosimetric parameters and NTCP values of all evaluated OARs.

CONCLUSIONS

Our study found that the use of planning PET/CT in the radiotherapy planning of NSCLC has a crucial impact on the precise determination of target volumes, more precise staging of the disease and thus also on possible changes of treatment strategy.

Optimal co-segmentation of tumor in PET-CT images with context information

Positron emission tomography (PET)-computed tomography (CT) images have been widely used in clinical practice for radiotherapy treatment planning of the radiotherapy. Many existing segmentation approaches only work for a single imaging modality, which suffer from the low spatial resolution in PET or low contrast in CT. In this work, we propose a novel method for the co-segmentation of the tumor in both PET and CT images, which makes use of advantages from each modality: the functionality information from PET and the anatomical structure information from CT. The approach formulates the segmentation problem as a minimization problem of a Markov random field model, which encodes the information from both modalities. The optimization is solved using a graph-cut based method. Two sub-graphs are constructed for the segmentation of the PET and the CT images, respectively. To achieve consistent results in two modalities, an adaptive context cost is enforced by adding context arcs between the two sub-graphs. An optimal solution can be obtained by solving a single maximum flow problem, which leads to simultaneous segmentation of the tumor volumes in both modalities. The proposed algorithm was validated in robust delineation of lung tumors on 23 PET-CT datasets and two head-and-neck cancer subjects. Both qualitative and quantitative results show significant improvement compared to the graph cut methods solely using PET or CT.

Evaluation of interpolation effects on upsampling and accuracy of cost functions-based optimized automatic image registration

Interpolation has become a default operation in image processing and medical imaging and is one of the important factors in the success of an intensity-based registration method. Interpolation is needed if the fractional unit of motion is not matched and located on the high resolution (HR) grid. The purpose of this work is to present a systematic evaluation of eight standard interpolation techniques (trilinear, nearest neighbor, cubic Lagrangian, quintic Lagrangian, hepatic Lagrangian, windowed Sinc, B-spline 3rd order, and B-spline 4th order) and to compare the effect of cost functions (least squares (LS), normalized mutual information (NMI), normalized cross correlation (NCC), and correlation ratio (CR)) for optimized automatic image registration (OAIR) on 3D spoiled gradient recalled (SPGR) magnetic resonance images (MRI) of the brain acquired using a 3T GE MR scanner. Subsampling was performed in the axial, sagittal, and coronal directions to emulate three low resolution datasets. Afterwards, the low resolution datasets were upsampled using different interpolation methods, and they were then compared to the high resolution data. The mean squared error, peak signal to noise, joint entropy, and cost functions were computed for quantitative assessment of the method. Magnetic resonance image scans and joint histogram were used for qualitative assessment of the method.

Tumor heterogeneity and permeability as measured on the CT component of PET/CT predict survival in patients with non-small cell lung cancer

PURPOSE

We prospectively examined the role of tumor textural heterogeneity on positron emission tomography/computed tomography (PET/CT) in predicting survival compared with other clinical and imaging parameters in patients with non-small cell lung cancer (NSCLC).

EXPERIMENTAL DESIGN

The feasibility study consisted of 56 assessed consecutive patients with NSCLC (32 males, 24 females; mean age 67 ± 9.7 years) who underwent combined fluorodeoxyglucose (FDG) PET/CT. The validation study population consisted of 66 prospectively recruited consecutive consenting patients with NSCLC (37 males, 29 females; mean age, 67.5 ± 7.8 years) who successfully underwent combined FDG PET/CT-dynamic contrast-enhanced (DCE) CT. Images were used to derive tumoral PET/CT textural heterogeneity, DCE CT permeability, and FDG uptake (SUVmax). The mean follow-up periods were 22.6 ± 13.3 months and 28.5± 13.2 months for the feasibility and validation studies, respectively. Optimum threshold was determined for clinical stage and each of the above biomarkers (where available) from the feasibility study population. Kaplan-Meier analysis was used to assess the ability of the biomarkers to predict survival in the validation study. Cox regression determined survival factor independence.

RESULTS

Univariate analysis revealed that tumor CT-derived heterogeneity (P < 0.001), PET-derived heterogeneity (P = 0.003), CT-derived permeability (P = 0.002), and stage (P < 0.001) were all significant survival predictors. The thresholds used in this study were derived from a previously conducted feasibility study. Tumor SUVmax did not predict survival. Using multivariable analysis, tumor CT textural heterogeneity (P = 0.021), stage (P = 0.001), and permeability (P < 0.001) were independent survival predictors. These predictors were independent of patient treatment.

CONCLUSIONS

Tumor stage and CT-derived textural heterogeneity were the best predictors of survival in NSCLC. The use of CT-derived textural heterogeneity should assist the management of many patients with NSCLC.

Application of FDG-PET/CT in Radiation Oncology

Positron emission tomography (PET)/computed tomography (CT), which combines the advantages of high sensitivity and specificity of PET and high resolution of CT, is a unique tool for cancer management. PET/CT has been widely used in cancer diagnosis and treatment. The article reviews the recent applications of PET/CT in radiation oncology, with a focus on ¹⁸F-fluorodeoxyglucose (FDG)-PET/CT, addressing the applications in treatment planning and treatment response assessment of radiation therapy.