The role of PET/CT scanning in radiotherapy planning

Spectral CT image reconstruction using a constrained optimization approach-An algorithm for AAPM 2022 spectral CT grand challenge and beyond

BACKGROUND

CT reconstruction is of essential importance in medical imaging. In 2022, the American Association of Physicists in Medicine (AAPM) sponsored a Grand Challenge to investigate the challenging inverse problem of spectral CT reconstruction, with the aim of achieving the most accurate reconstruction results. The authors of this paper participated in the challenge and won as a runner-up team.

PURPOSE

This paper reports details of our PROSPECT algorithm (Prior-based Restricted-variable Optimization for SPEctral CT) and follow-up studies regarding the algorithm's accuracy and enhancement of its convergence speed.

METHODS

We formulated the reconstruction task as an optimization problem. PROSPECT employed a one-step backward iterative scheme to solve this optimization problem by allowing estimation of and correction for the difference between the actual polychromatic projection model and the monochromatic model used in the optimization problem. PROSPECT incorporated various forms of prior information derived by analyzing training data provided by the Grand Challenge to reduce the number of unknown variables. We investigated the impact of projection data precision on the resulting solution accuracy and improved convergence speed of the PROSPECT algorithm by incorporating a beam-hardening correction (BHC) step in the iterative process. We also studied the algorithm's performance under noisy projection data.

RESULTS

Prior knowledge allowed a reduction of the number of unknown variables by85.9 % $85.9\%$ . PROSPECT algorithm achieved the average root of mean square error (RMSE) of3.3 × 10 - 6 $3.3\,\times \,10^{-6}$ in the test data set provided by the Grand Challenge. Performing the reconstruction with the same algorithm but using double-precision projection data reduced RMSE to1.2 × 10 - 11 $1.2\,\times \,10^{-11}$ . Including the BHC step in the PROSPECT algorithm accelerated the iteration process with a 40% reduction in computation time.

CONCLUSIONS

PROSPECT algorithm achieved a high degree of accuracy and computational efficiency.

Joint EANM/SNMMI/ESTRO practice recommendations for the use of 2-[18F]FDG PET/CT external beam radiation treatment planning in lung cancer V1.0

PURPOSE

2-[18F]FDG PET/CT is of utmost importance for radiation treatment (RT) planning and response monitoring in lung cancer patients, in both non-small and small cell lung cancer (NSCLC and SCLC). This topic has been addressed in guidelines composed by experts within the field of radiation oncology. However, up to present, there is no procedural guideline on this subject, with involvement of the nuclear medicine societies.

METHODS

A literature review was performed, followed by a discussion between a multidisciplinary team of experts in the different fields involved in the RT planning of lung cancer, in order to guide clinical management. The project was led by experts of the two nuclear medicine societies (EANM and SNMMI) and radiation oncology (ESTRO).

RESULTS AND CONCLUSION

This guideline results from a joint and dynamic collaboration between the relevant disciplines for this topic. It provides a worldwide, state of the art, and multidisciplinary guide to 2-[18F]FDG PET/CT RT planning in NSCLC and SCLC. These practical recommendations describe applicable updates for existing clinical practices, highlight potential flaws, and provide solutions to overcome these as well. Finally, the recent developments considered for future application are also reviewed.

Transcriptomics in cancer revealed by Positron Emission Tomography radiomics

Metabolic images from Positron Emission Tomography (PET) are used routinely for diagnosis, follow-up or treatment planning purposes of cancer patients. In this study we aimed at determining if radiomic features extracted from 18F-Fluoro Deoxy Glucose (FDG) PET images could mirror tumor transcriptomics. In this study we analyzed 45 patients with locally advanced head and neck cancer (H&N) that underwent FDG-PET scans at the time of diagnosis and transcriptome analysis using RNAs from both cancer and healthy tissues on microarrays. Association between PET radiomics and transcriptomics was carried out with the Genomica software and a functional annotation was used to associate PET radiomics, gene expression and altered biological pathways. We identified relationships between PET radiomics and genes involved in cell-cycle, disease, DNA repair, extracellular matrix organization, immune system, metabolism or signal transduction pathways, according to the Reactome classification. Our results suggest that these FDG PET radiomic features could be used to infer tissue gene expression and cellular pathway activity in H&N cancers. These observations strengthen the value of radiomics as a promising approach to personalize treatments through targeting tumor-specific molecular processes.

A phantom study to assess the reproducibility, robustness and accuracy of PET image segmentation methods against statistical fluctuations

Background

Automatic and semi-automatic segmentation methods for PET serve as alternatives to manual delineation and eliminate observer variability. The robustness of these segmentation methods against statistical fluctuations arising from variable size, contrast and noise are vital for providing reliable clinical outcomes for diagnosis and treatment response assessment. In this study, the performances of several segmentation methods have been investigated using the torso NEMA phantom against statistical fluctuations.

Methods

The six hot spheres (0.5-27ml) and the background of the phantom were filled with different activities of ¹⁸F to yield 2:1 and 4:1 contrast ratios. The phantom was scanned on a TrueV PET-CT scanner for 120 minutes. The images were reconstructed using OSEM (4iterations-21subsets) for different durations (15, 20, 34 and 67 minutes) to represent different noise levels and smoothed with a 4-mm Gaussian filter. Each sphere with different settings was delineated using a fixed 40% threshold (40T), fuzzy clustering mean (FCM), adaptive threshold and region based variational (C-V) segmentation methods and compared with the gold standard volume, which was estimated from the known diameter and position of each sphere.

Results

The smallest three spheres at the 2:1 contrast level are not evaluable for the 40T method. For the other spheres, the 40T method grossly overestimates the volumes and the segmented volumes are highly dependent on the statistical variations. These volumes are the least reproducible (80%) with a mean Dice Similarity Coefficient (DSC) of 0.67 and 90% classification error (CE). The other three methods reduce the dependency on noise and contrast in a similar manner by providing low bias (<10%) and CE (<25%) as well as a high DSC (0.88) and reproducibility (30%) for objects >17mm in diameter. However, for the smallest three spheres at a 2:1 contrast level, the performances of all three methods were significantly low, with the adaptive method being superior to the FCM and C-V (mean bias 168% and 350%, mean DSC 0.65 and 0.50, mean CE 227% and 454% for the adaptive and other two methods (approximately similar for FCM and C-V), respectively).

Conclusions

The segmentation accuracy of the fixed threshold-based method depends on size, contrast and noise. The intensity thresholds determined by the adaptive threshold methods are less sensitive to noise and therefore, the segmented volumes are more reproducible across different acquisition durations. A similar performance can be achieved with the FCM and C-V methods. Though, for small lesions (< 2cm diameter) with low counts and contrast, the adaptive threshold-based method outperforms the FCM and C-V methods, and the performance of neither of these methods is optimal for volumes <2cm in diameter. These three methods can only reliably be used to delineate tumours for diagnostic and monitoring purposes provided that the contrast between the tumour and background is not below a 2:1 ratio and the size of the tumour does not fall not below 2cm in diameter in response to treatment. They can also be used for different radiotracers with variable uptake. However, the FCM and C-V methods have the advantage of not requiring calibrations for different scanners and settings.

Three-dimensional structure tensor based PET/CT fusion in gradient domain

Gradient based image fusion can more effectively incorporate edge details using structure tensor, which is successfully used in 2D image fusion. In this study, we generalized and applied this gradient based image fusion method into 3D for non-small cell lung cancer PET/CT image fusion. According the characteristic of lung PET/CT images, we proposed a novel 3D structure tensor based feature, which can be used to construct a weighted structure tensor containing important local detail of both PET and CT images. The fusion gradient domain is deduced from a rank one tensor, which is the closest approximation of the weighted structure tensor in geometry. Based on the fusion gradient domain, final PET/CT fusion image is obtained by solving a Poisson equation. Comparing with the wavelet transform based fusion result, the average information entropy and average gradient measure of proposed fusion method increase 13.5% and 42.3%, respectively. The experimental results show that the proposed fusion method enables to effectively preserve lung vessel structure and sphere-like lesion detail while produces clear, stable and well consistent fusion images.

Delineation of lung cancer with FDG PET/CT during radiation therapy

OBJECTIVES

To propose an easily applicable segmentation method (perPET-RT) for delineation of tumour volume during radiotherapy on interim fluorine 18 fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) in patients with non-small cell lung cancer (NSCLC).

MATERIAL AND METHODS

Sixty-seven patients (51 primary tumours, 60 lymph nodes), from 4 prospective studies, underwent an FDG PET/CT scan during the fifth week of radiation therapy, using different generations of PET/CT. Per-therapeutic PET/CT scans were delineated in consensus by two experienced physicians leading to the gold standard threshold to be applied. The mathematical expression of Th_opt, the optimal threshold to be applied as a function of the maximum standard uptake value (SUV_max), was determined. The performance of this method (perPET-RT) was assessed by computing the DICE similarity coefficient (DSC) and was compared with 8 fixed threshold values and 3 adaptive thresholding methods.

RESULTS

Th_opt verified the following expression: Th_opt = A.ln(1/SUV_max) + B where A and B were 2 constants. A and B were independent from the generation of PET/CT, but depended on the type of lesions (primary lung tumours vs. lymph nodes). PerPET-RT showed good to very good agreement in comparison to the gold standard. The mean and standard deviation of DSC value was 0.81 ± 0.13 for lung lesions and 0.78 ± 0.15 for lymph nodes. PerPET-RT showed a significant better agreement than the other segmentation methods (p < 0.001), except for one of the adaptive thresholding method ADT (p = 0.11).

CONCLUSION

On the database used, perPET-RT has proven its reliability and accuracy for tumour delineation on per-therapeutic FDG PET/CT using only SUV_max measurement. This method may be used to delineate tumour volume for dose-escalation planning.

TRIAL REGISTRATION

NCT01261598 , NCT01261585 , NCT01576796 .

Is SUVmax Helpful in the Differential Diagnosis of Enlarged Mediastinal Lymph Nodes? A Pilot Study

Objective

To explore the diagnostic value of maximum standard uptake value (SUVmax) from ¹⁸F-FDG PET/CT images in enlarged mediastinal lymph nodes of unknown etiology.

Methods

We performed a retrospective study of patients with enlarged mediastinal lymph nodes on ¹⁸F-FDG PET/CT scans. SUVmax and the short axis and long axis of lymph nodes were recorded. These parameters were compared among the five commonest causes of mediastinal lymphadenopathy: lymphoma, metastatic disease, sarcoidosis, tuberculosis, and lymphadenitis. Histopathologic diagnosis was recorded as the final golden standard.

Results

A total of 94 patients (62 men and 32 women; age range 7-85 y) were included with final diagnoses of 42 patients with benign pathology and 52 patients with malignancies. The sensitivity, specificity, and the accuracy of PET/CT in diagnosis of the benign and malignant mediastinal lymph nodes were 94.2%, 73.8%, and 85.1%, respectively. The SUVmax of benign and malignant groups were 13.10 ± 5.21 and 12.59 ± 5.50, respectively, which had no statistical difference (P > 0.05). However, the long axis and the short axis of lymph nodes in the benign and malignant groups were 2.86 ± 1.02 cm, 1.77 ± 0.60 cm and 6.04 ± 3.83 cm, 3.95 ± 2.08 cm, respectively (P < 0.05). The diagnostic values of PET/CT were higher than those of the long or short axis. However, the specificity of PET/CT was lower (73.8%) than that from the long or short axis (90.5% and 92.9%, respectively), although no statistical difference existed. Among the five common causes of mediastinal lymphadenopathy, significant differences could be seen in SUVmax and in the long axis and the short axis of lymph nodes (P < 0.05).

Conclusions

SUVmax, a commonly used semiquantitative measurement, was not helpful for differentiation between benign and malignant lesions in patients with enlarged mediastinal lymph nodes in this study. Many benign lesions, such as sarcoidosis and tuberculosis, had high FDG uptake, possibly a trend that the size of the lymph nodes seems to have some diagnostic value.

Combined fuzzy logic and random walker algorithm for PET image tumor delineation

PURPOSE

The random walk (RW) technique serves as a powerful tool for PET tumor delineation, which typically involves significant noise and/or blurring. One challenging step is hard decision-making in pixel labeling. Fuzzy logic techniques have achieved increasing application in edge detection. We aimed to combine the advantages of fuzzy edge detection with the RW technique to improve PET tumor delineation.

METHODS

A fuzzy inference system was designed for tumor edge detection from RW probabilities. Three clinical PET/computed tomography datasets containing 12 liver, 13 lung, and 18 abdomen tumors were analyzed, with manual expert tumor contouring as ground truth. The standard RW and proposed combined method were compared quantitatively using the dice similarity coefficient, the Hausdorff distance, and the mean standard uptake value.

RESULTS

The dice similarity coefficient of the proposed method versus standard RW showed significant mean improvements of 21.0±7.2, 12.3±5.8, and 18.4%±6.1% for liver, lung, and abdominal tumors, respectively, whereas the mean improvements in the Hausdorff distance were 3.6±1.4, 1.3±0.4, 1.8±0.8 mm, and the mean improvements in SUVmean error were 15.5±6.3, 11.7±8.6, and 14.1±6.8% (all P's<0.001). For all tumor sizes, the proposed method outperformed the RW algorithm. Furthermore, tumor edge analysis demonstrated further enhancement of the performance of the algorithm, relative to the RW method, with decreasing edge gradients.

CONCLUSION

The proposed technique improves PET lesion delineation at different tumor sites. It depicts greater effectiveness in tumors with smaller size and/or low edge gradients, wherein most PET segmentation algorithms encounter serious challenges. Favorable execution time and accurate performance of the algorithm make it a great tool for clinical applications.

Use of PET/CT instead of CT-only when planning for radiation therapy does not notably increase life years lost in children being treated for cancer

BACKGROUND

PET/CT may be more helpful than CT alone for radiation therapy planning, but the added risk due to higher doses of ionizing radiation is unknown.

OBJECTIVE

To estimate the risk of cancer induction and mortality attributable to the [F-18]2-fluoro-2-deoxyglucose (FDG) PET and CT scans used for radiation therapy planning in children with cancer, and compare to the risks attributable to the cancer treatment.

MATERIALS AND METHODS

Organ doses and effective doses were estimated for 40 children (2-18 years old) who had been scanned using PET/CT as part of radiation therapy planning. The risk of inducing secondary cancer was estimated using the models in BEIR VII. The prognosis of an induced cancer was taken into account and the reduction in life expectancy, in terms of life years lost, was estimated for the diagnostics and compared to the life years lost attributable to the therapy. Multivariate linear regression was performed to find predictors for a high contribution to life years lost from the radiation therapy planning diagnostics.

RESULTS

The mean contribution from PET to the effective dose from one PET/CT scan was 24% (range: 7-64%). The average proportion of life years lost attributable to the nuclear medicine dose component from one PET/CT scan was 15% (range: 3-41%). The ratio of life years lost from the radiation therapy planning PET/CT scans and that of the cancer treatment was on average 0.02 (range: 0.01-0.09). Female gender was associated with increased life years lost from the scans (P < 0.001).

CONCLUSION

Using FDG-PET/CT instead of CT only when defining the target volumes for radiation therapy of children with cancer does not notably increase the number of life years lost attributable to diagnostic examinations.

PET/CT-guided treatment planning for paediatric cancer patients: a simulation study of proton and conventional photon therapy

OBJECTIVE

To investigate the impact of including fluorine-18 fludeoxyglucose ((18)F-FDG) positron emission tomography (PET) scanning in the planning of paediatric radiotherapy (RT).

METHODS

Target volumes were first delineated without and subsequently re-delineated with access to (18)F-FDG PET scan information, on duplicate CT sets. RT plans were generated for three-dimensional conformal photon RT (3DCRT) and intensity-modulated proton therapy (IMPT). The results were evaluated by comparison of target volumes, target dose coverage parameters, normal tissue complication probability (NTCP) and estimated risk of secondary cancer (SC).

RESULTS

Considerable deviations between CT- and PET/CT-guided target volumes were seen in 3 out of the 11 patients studied. However, averaging over the whole cohort, CT or PET/CT guidance introduced no significant difference in the shape or size of the target volumes, target dose coverage, irradiated volumes, estimated NTCP or SC risk, neither for IMPT nor 3DCRT.

CONCLUSION

Our results imply that the inclusion of PET/CT scans in the RT planning process could have considerable impact for individual patients. There were no general trends of increasing or decreasing irradiated volumes, suggesting that the long-term morbidity of RT in childhood would on average remain largely unaffected.

ADVANCES IN KNOWLEDGE

(18)F-FDG PET-based RT planning does not systematically change NTCP or SC risk for paediatric cancer patients compared with CT only. 3 out of 11 patients had a distinct change of target volumes when PET-guided planning was introduced. Dice and mismatch metrics are not sufficient to assess the consequences of target volume differences in the context of RT.

Visual versus quantitative assessment of intratumor 18F-FDG PET uptake heterogeneity: prognostic value in non-small cell lung cancer

The goal of this study was to compare visual assessment of intratumor (18)F-FDG PET uptake distribution with a textural-features (TF) automated quantification and to establish their respective prognostic value in non-small cell lung cancer (NSCLC).

METHODS

The study retrospectively included 102 consecutive patients. Only primary tumors were considered. Intratumor heterogeneity was visually scored (3-level scale [Hvisu]) by 2 nuclear medicine physicians. Tumor volumes were automatically delineated, and heterogeneity was quantified with TF. Mean and maximum standardized uptake value were also included. Visual interobserver agreement and correlations with quantitative assessment were evaluated using the κ test and Spearman rank (ρ) coefficient, respectively. Association with overall survival and recurrence-free survival was investigated using the Kaplan-Meier method and Cox regression models.

RESULTS

Moderate correlations (0.4 < ρ < 0.6) between TF parameters and Hvisu were observed. Interobserver agreement for Hvisu was moderate (κ = 0.64, discrepancies in 27% of the cases). High standardized uptake value, large metabolic volumes, and high heterogeneity according to TF were associated with poorer overall survival and recurrence-free survival and remained an independent prognostic factor of overall survival with respect to clinical variables.

CONCLUSION

Quantification of (18)F-FDG uptake heterogeneity in NSCLC through TF was correlated with visual assessment by experts. However, TF also constitutes an objective heterogeneity quantification, with reduced interobserver variability, and independent prognostic value potentially useful for patient stratification and management.

[Target volume segmentation of PET images by an iterative method based on threshold value]

OBJECTIVES

An automatic segmentation method is presented for PET images based on an iterative approximation by threshold value that includes the influence of both lesion size and background present during the acquisition.

MATERIAL AND METHODS

Optimal threshold values that represent a correct segmentation of volumes were determined based on a PET phantom study that contained different sizes spheres and different known radiation environments. These optimal values were normalized to background and adjusted by regression techniques to a two-variable function: lesion volume and signal-to-background ratio (SBR). This adjustment function was used to build an iterative segmentation method and then, based in this mention, a procedure of automatic delineation was proposed. This procedure was validated on phantom images and its viability was confirmed by retrospectively applying it on two oncology patients.

RESULTS

The resulting adjustment function obtained had a linear dependence with the SBR and was inversely proportional and negative with the volume. During the validation of the proposed method, it was found that the volume deviations respect to its real value and CT volume were below 10% and 9%, respectively, except for lesions with a volume below 0.6 ml.

CONCLUSIONS

The automatic segmentation method proposed can be applied in clinical practice to tumor radiotherapy treatment planning in a simple and reliable way with a precision close to the resolution of PET images.

[Validation of segmentation techniques for positron emission tomography using ex-vivo images of oncological surgical specimens]

OBJECTIVE

To design a novel ex-vivo acquisition technique to establish a common framework to validate different segmentation techniques for oncological PET images. To evaluate several automatic segmentation algorithms on this set of images.

MATERIAL AND METHODS

In 15 patients with cancer, ex-vivo PET studies of surgical specimens removed during surgery were performed after injection of (18)F-FDG. Images were acquired in two scanners: a clinical PET/CT and a high-resolution PET scanner. Real tumor volume was determined in each patient, and a reference image was generated for segmentation of each tumor. Images were segmented with 12 automatic algorithms and with a standard method for PET (relative threshold at 42%) and results were evaluated by quantitative parameters.

RESULTS

It has been possible to demonstrate by segmentation of PET images of surgical specimens that on high resolution PET images, 8 out of 12 evaluated segmentation techniques outperformed the standard method, whose value is 42%. However, none of the algorithms outperformed the standard method when applied on images from the clinical PET/CT. Due to the great interest of this set of PET images, all studies have been published on the Internet in order to provide a common framework for validation and comparison of different segmentation techniques.

CONCLUSIONS

We have proposed a novel technique to validate segmentation techniques for oncological PET images, acquiring ex-vivo PET studies of surgical specimens. We have demonstrated the usefulness of this set of PET images by evaluating several automatic segmentation algorithms.

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.

Comparison of different methods of incorporating respiratory motion for lung cancer tumor volume delineation on PET images: a simulation study

The interest of PET complementary information for the delineation of the target volume in radiotherapy of lung cancer is increasing. However, respiratory motion requires the determination of a functional internal target volume (ITV) on PET images for which several strategies have been proposed. The purpose of this study was the comparison of these strategies for taking into account respiratory motion and deriving the ITV: (1) adding fixed margins to the volume defined on a single binned image, (2) segmenting a motion averaged image and (3) considering the union of volumes delineated on binned frames. For this third strategy, binned frames were either non-corrected for motion, or corrected using two different methods: elastic registration or super resolution. The strategies' performances were assessed on realistic simulated datasets combining the NCAT phantom with a PET Philips GEMINI scanner model in GATE, and containing various configurations of tumor to background contrast, with both regular and irregular respiratory motion (with a range of motion amplitudes). The obtained ITVs' sensitivity (SE) and positive predictive value (PVE) with respect to the known true ITV were significantly higher (from 0.8 to 0.95) than all other techniques when using binned frames corrected for motion, independently of motion regularity, amplitude, or tumor to background contrast. Although the absolute difference was small and not always significant, images corrected using super resolution led to systematically better results than using elastic registration. The worst results were obtained when using the motion averaged image for SE (around 0.5-0.6) and using the margins added to a single frame for PPV (0.6-0.7), respectively. The best strategy to account for breathing motion for tumor ITV delineation in radiotherapy planning is to rely on the use of the union of volumes delineated on super resolution-corrected binned images.

Image change detection using paradoxical theory for patient follow-up quantitation and therapy assessment

In clinical oncology, positron emission tomography (PET) imaging can be used to assess therapeutic response by quantifying the evolution of semi-quantitative values such as standardized uptake value, early during treatment or after treatment. Current guidelines do not include metabolically active tumor volume (MATV) measurements and derived parameters such as total lesion glycolysis (TLG) to characterize the response to the treatment. To achieve automatic MATV variation estimation during treatment, we propose an approach based on the change detection principle using the recent paradoxical theory, which models imprecision, uncertainty, and conflict between sources. It was applied here simultaneously to pre- and post-treatment PET scans. The proposed method was applied to both simulated and clinical datasets, and its performance was compared to adaptive thresholding applied separately on pre- and post-treatment PET scans. On simulated datasets, the adaptive threshold was associated with significantly higher classification errors than the developed approach. On clinical datasets, the proposed method led to results more consistent with the known partial responder status of these patients. The method requires accurate rigid registration of both scans which can be obtained only in specific body regions and does not explicitly model uptake heterogeneity. In further investigations, the change detection of intra-MATV tracer uptake heterogeneity will be developed by incorporating textural features into the proposed approach.

Recommendations for the use of PET and PET-CT for radiotherapy planning in research projects

With the increasing use of positron emission tomography (PET) for disease staging, follow-up and therapy monitoring in a number of oncological indications there is growing interest in the use of PET and PET-CT for radiation treatment planning. In order to create a strong clinical evidence base for this, it is important to ensure that research data are clinically relevant and of a high quality. Therefore the National Cancer Research Institute PET Research Network make these recommendations to assist investigators in the development of radiotherapy clinical trials involving the use of PET and PET-CT. These recommendations provide an overview of the current literature in this rapidly evolving field, including standards for PET in clinical trials, disease staging, volume delineation, intensity modulated radiotherapy and PET-augmented planning techniques, and are targeted at a general audience. We conclude with specific recommendations for the use of PET in radiotherapy planning in research projects.

Contribution of PET-CT to staging, gross tumour volume definition, planning and response assessment in IMRT for nasopharyngeal carcinoma

The effectiveness of PET-CT (positron emission tomography–computed tomography) was investigated for staging target delineation compared with CT-MR (computed tomography–magnetic resonance) and early response of intensity-modulated radiotherapy (IMRT). Gross tumour volume–clinical target volume (GTV-CTV) differences between PET-CT and CT-MR for 14 nasopharyngeal carcinoma (NPC) patients were compared. Evaluation of doses of organs at risk (OARs) was done by IMRT plans. Responses of IMRT were evaluated with both sets. PET-CT changed MR-based TNM (Tumour Lymph Nodes Metastasis) in 11 of 14 patients. The median GTVNP (nasopharyx gross tumour volume) was 49.25 and 18.8 cm3 for CT-MR and PET-CT, respectively. In eight cases, GTVNP in the PET-CT was smaller than the CT-MR. The PET-CT presented a larger GTVNP than the CT-MR for six cases. Mean doses for the parotid glands were found to be higher than in CT-MR-based plan in one patient although he had smaller GTVNP at the PET-CT. The median follow-up was 16 months. Only one patient experienced recurrence in the CTVNP (nasopharyx clinical target volume). MR showed a decrease in the size-number of lymph nodes in four patients whereas PET-CT showed no uptake. All patients had positive responses to IMRT in their second control MR and PET-CT. PET-CT could improve tumour delineation. This enables an increase in dose inside the CTV. PET-CT provided significant information on the control scans for most of our patients whose MR imaging showed residual or recurrence.

[Metabolically active volumes automatic delineation methodologies in PET imaging: review and perspectives]

PET imaging is now considered a gold standard tool in clinical oncology, especially for diagnosis purposes. More recent applications such as therapy follow-up or tumor targeting in radiotherapy require a fast, accurate and robust metabolically active tumor volumes delineation on emission images, which cannot be obtained through manual contouring. This clinical need has sprung a large number of methodological developments regarding automatic methods to define tumor volumes on PET images. This paper reviews most of the methodologies that have been recently proposed and discusses their framework and methodological and/or clinical validation. Perspectives regarding the future work to be done are also suggested.

Multi-observation PET image analysis for patient follow-up quantitation and therapy assessment

In positron emission tomography (PET) imaging, an early therapeutic response is usually characterized by variations of semi-quantitative parameters restricted to maximum SUV measured in PET scans during the treatment. Such measurements do not reflect overall tumor volume and radiotracer uptake variations. The proposed approach is based on multi-observation image analysis for merging several PET acquisitions to assess tumor metabolic volume and uptake variations. The fusion algorithm is based on iterative estimation using a stochastic expectation maximization (SEM) algorithm. The proposed method was applied to simulated and clinical follow-up PET images. We compared the multi-observation fusion performance to threshold-based methods, proposed for the assessment of the therapeutic response based on functional volumes. On simulated datasets the adaptive threshold applied independently on both images led to higher errors than the ASEM fusion and on clinical datasets it failed to provide coherent measurements for four patients out of seven due to aberrant delineations. The ASEM method demonstrated improved and more robust estimation of the evaluation leading to more pertinent measurements. Future work will consist in extending the methodology and applying it to clinical multi-tracer datasets in order to evaluate its potential impact on the biological tumor volume definition for radiotherapy applications.

Non-small cell lung carcinoma: accuracy of PET/CT in determining the size of T1 and T2 primary tumors

OBJECTIVE

The purpose of this study was to compare the measurements of primary T1 and T2 non-small cell lung carcinomas (NSCLCs) at PET/CT to determine which modality has the more accurate correlation with the histologic findings.

MATERIALS AND METHODS

A retrospective study was performed with the images of 59 patients who underwent surgical resection of T1 and T2 NSCLC and preoperative PET/CT. The maximum measurement of the primary lung tumor was recorded on the PET and unenhanced CT (soft-tissue and lung windows) scans in the largest plane and compared with the maximum dimensions of the histologic specimen.

RESULTS

PET and CT measurements both had high concordance with the histologic measurements. CT soft-tissue window measurements had the highest concordance with histologic measurements, but PET had a smaller SD. The greatest linear correlation was between CT soft-tissue and CT lung window measurements, indicating they can be used interchangeably. Outliers were found in both the PET (four tumors) and the two CT (five tumors) groups owing to low (18)F-FDG uptake due to tumor type and surrounding consolidation, respectively.

CONCLUSION

PET is better for delineating primary NSCLC if surrounding collapse or consolidation is present. Otherwise, CT with either soft-tissue or lung windows is accurate. Owing to low FDG accumulation, CT is more accurate for assessment of alveolar cell carcinoma.

Positron emission tomography imaging approaches for external beam radiation therapies: current status and future developments

In an era in which it is possible to deliver radiation with high precision, there is a heightened need for enhanced imaging capabilities to improve tumour localisation for diagnostic, planning and delivery purposes. This is necessary to increase the accuracy and overall efficacy of all types of external beam radiotherapy (RT), including particle therapies. Positron emission tomography (PET) has the potential to fulfil this need by imaging fundamental aspects of tumour biology. The key areas in which PET may support the RT process include improving disease diagnosis and staging; assisting tumour volume delineation; defining tumour phenotype or biological tumour volume; assessment of treatment response; and in-beam monitoring of radiation dosimetry. The role of PET and its current developmental status in these key areas are overviewed in this review, highlighting the advantages and drawbacks.

PET functional volume delineation: a robustness and repeatability study

PURPOSE

Current state-of-the-art algorithms for functional uptake volume segmentation in PET imaging consist of threshold-based approaches, whose parameters often require specific optimization for a given scanner and associated reconstruction algorithms. Different advanced image segmentation approaches previously proposed and extensively validated, such as among others fuzzy C-means (FCM) clustering, or fuzzy locally adaptive bayesian (FLAB) algorithm have the potential to improve the robustness of functional uptake volume measurements. The objective of this study was to investigate robustness and repeatability with respect to various scanner models, reconstruction algorithms and acquisition conditions.

METHODS AND MATERIALS

Robustness was evaluated using a series of IEC phantom acquisitions carried out on different PET/CT scanners (Philips Gemini and Gemini Time-of-Flight, Siemens Biograph and GE Discovery LS) with their associated reconstruction algorithms (RAMLA, TF MLEM, OSEM). A range of acquisition parameters (contrast, duration) and reconstruction parameters (voxel size) were considered for each scanner model, and the repeatability of each method was evaluated on simulated and clinical tumours and compared to manual delineation.

RESULTS

For all the scanner models, acquisition parameters and reconstruction algorithms considered, the FLAB algorithm demonstrated higher robustness in delineation of the spheres with low mean errors (10%) and variability (5%), with respect to threshold-based methodologies and FCM. The repeatability provided by all segmentation algorithms considered was very high with a negligible variability of <5% in comparison to that associated with manual delineation (5-35%).

CONCLUSION

The use of advanced image segmentation algorithms may not only allow high accuracy as previously demonstrated, but also provide a robust and repeatable tool to aid physicians as an initial guess in determining functional volumes in PET.

Molecular imaging in oncology: the acceptance of PET/CT and the emergence of MR/PET imaging

In the last decade, PET-only systems have been phased out and replaced with PET-CT systems. This merger of a functional and anatomical imaging modality turned out to be extremely useful in clinical practice. Currently, PET-CT is a major diagnostic tool in oncology. At the dawn of the merger of MRI and PET, another breakthrough in clinical imaging is expected. The combination of these imaging modalities is challenging, but has particular features such as imaging biological processes at the same time in specific body locations.

Comparison of positron emission tomography (PET) and computed tomography (CT) for better target volume definition in radiation therapy planning

BACKGROUND

In cancer patients, positron emission tomography/ computed tomography (PET/CT) fused images present less variability in target contouring, respect to use only CT images, respectively. However, the gold standard has not yet been clearly established between radiation oncologists with regard to PET images and the methodology of contouring targets with confidence using PET/CT fused images. The aim of this study was to determine whether integrated PET/CT fused images provide advantages in virtual simulation compared with morphological contouring only with CT.

MATERIAL AND METHODS

Thirty cancer patients were evaluated in an adapted PET/CT hybrid in radiotherapy (RT) setup position, with 20 of them being suitable for RT: 17 were suitable for curative intent, which was the group of interest in this study. All image series were sent to the RT work station (WS) where CT and PET series were automatically fused by Digital Imaging and Communications in Medicine (DICOM) in each case. PET series were threshold and were subjected to source-to-background contrast algorithms to fi nally redefine the original tumour description. Three different radiotherapy plans (RTP) for each patient were compared after targets were contoured: [1] planning over metabolic (PET) contoured targets, [2] planning over only morphologic (CT) targets, and [3] planning over targets obtained for treatment based on fused PET/CT images.

RESULTS

PET/CT findings altered initial-stage planning in four patients (23.5%) because they had been undergoing chemotherapy. Gross target volume (GTV) and planning target volume (PTV) based only on PET showed more homogeneity to obtain mean doses (p = 0.025) with respect to those based on PET/CT, respectively. However, no percentage differences were observed in median PTV doses between the planning methods, although there was higher variability in PET/CT planning. Morphological (CT) and PET/ CT target volumes were more voluminous than metabolic (PET) volumes. On the other hand, 20% of metabolic (PET) PTV were out of those defined by PET/CT. Thoracic RT plans based on PET preserved better bilateral lung [percentage volume of lung irradiated with a dose of 20 Gy (V20); significance, R(2) = 0.559, p = 0.006].

CONCLUSIONS

For our physicians, PET/CT fused images allowed better contouring of primary tumours in 40% of head and neck cancers and 34% of thoracic cancers. PET/CT provides useful information for virtual simulation therapy. Image treatment and planning in an RT workstation is mandatory.

PET/CT (and CT) instrumentation, image reconstruction and data transfer for radiotherapy planning

The positron emission tomography in combination with CT in hybrid, cross-modality imaging systems (PET/CT) gains more and more importance as a part of the treatment-planning procedure in radiotherapy. Positron emission tomography (PET), as a integral part of nuclear medicine imaging and non-invasive imaging technique, offers the visualization and quantification of pre-selected tracer metabolism. In combination with the structural information from CT, this molecular imaging technique has great potential to support and improve the outcome of the treatment-planning procedure prior to radiotherapy. By the choice of the PET-Tracer, a variety of different metabolic processes can be visualized. First and foremost, this is the glucose metabolism of a tissue as well as for instance hypoxia or cell proliferation. This paper comprises the system characteristics of hybrid PET/CT systems. Acquisition and processing protocols are described in general and modifications to cope with the special needs in radiooncology. This starts with the different position of the patient on a special table top, continues with the use of the same fixation material as used for positioning of the patient in radiooncology while simulation and irradiation and leads to special processing protocols that include the delineation of the volumes that are subject to treatment planning and irradiation (PTV, GTV, CTV, etc.). General CT acquisition and processing parameters as well as the use of contrast enhancement of the CT are described. The possible risks and pitfalls the investigator could face during the hybrid-imaging procedure are explained and listed. The interdisciplinary use of different imaging modalities implies a increase of the volume of data created. These data need to be stored and communicated fast, safe and correct. Therefore, the DICOM-Standard provides objects and classes for this purpose (DICOM RT). Furthermore, the standard DICOM objects and classes for nuclear medicine (NM, PT) and computed tomography (CT) are used to communicate the actual image data created by the modalities. Care must be taken for data security, especially when transferring data across the (network-) borders of different hospitals. Overall, the most important precondition for successful integration of functional imaging in RT treatment planning is the goal orientated as well as close and thorough communication between nuclear medicine and radiotherapy departments on all levels of interaction (personnel, imaging protocols, GTV delineation, and selection of the data transfer method).

Accurate automatic delineation of heterogeneous functional volumes in positron emission tomography for oncology applications

PURPOSE

Accurate contouring of positron emission tomography (PET) functional volumes is now considered crucial in image-guided radiotherapy and other oncology applications because the use of functional imaging allows for biological target definition. In addition, the definition of variable uptake regions within the tumor itself may facilitate dose painting for dosimetry optimization.

METHODS AND MATERIALS

Current state-of-the-art algorithms for functional volume segmentation use adaptive thresholding. We developed an approach called fuzzy locally adaptive Bayesian (FLAB), validated on homogeneous objects, and then improved it by allowing the use of up to three tumor classes for the delineation of inhomogeneous tumors (3-FLAB). Simulated and real tumors with histology data containing homogeneous and heterogeneous activity distributions were used to assess the algorithm's accuracy.

RESULTS

The new 3-FLAB algorithm is able to extract the overall tumor from the background tissues and delineate variable uptake regions within the tumors, with higher accuracy and robustness compared with adaptive threshold (T(bckg)) and fuzzy C-means (FCM). 3-FLAB performed with a mean classification error of less than 9% +/- 8% on the simulated tumors, whereas binary-only implementation led to errors of 15% +/- 11%. T(bckg) and FCM led to mean errors of 20% +/- 12% and 17% +/- 14%, respectively. 3-FLAB also led to more robust estimation of the maximum diameters of tumors with histology measurements, with <6% standard deviation, whereas binary FLAB, T(bckg) and FCM lead to 10%, 12%, and 13%, respectively.

CONCLUSION

These encouraging results warrant further investigation in future studies that will investigate the impact of 3-FLAB in radiotherapy treatment planning, diagnosis, and therapy response evaluation.

Comparative assessment of methods for estimating tumor volume and standardized uptake value in (18)F-FDG PET

In (18)F-FDG PET, tumors are often characterized by their metabolically active volume and standardized uptake value (SUV). However, many approaches have been proposed to estimate tumor volume and SUV from (18)F-FDG PET images, none of them being widely agreed upon. We assessed the accuracy and robustness of 5 methods for tumor volume estimates and of 10 methods for SUV estimates in a large variety of configurations.

METHODS

PET acquisitions of an anthropomorphic phantom containing 17 spheres (volumes between 0.43 and 97 mL, sphere-to-surrounding-activity concentration ratios between 2 and 68) were used. Forty-one nonspheric tumors (volumes between 0.6 and 92 mL, SUV of 2, 4, and 8) were also simulated and inserted in a real patient (18)F-FDG PET scan. Four threshold-based methods (including one, T(bgd), accounting for background activity) and a model-based method (Fit) described in the literature were used for tumor volume measurements. The mean SUV in the resulting volumes were calculated, without and with partial-volume effect (PVE) correction, as well as the maximum SUV (SUV(max)). The parameters involved in the tumor segmentation and SUV estimation methods were optimized using 3 approaches, corresponding to getting the best of each method or testing each method in more realistic situations in which the parameters cannot be perfectly optimized.

RESULTS

In the phantom and simulated data, the T(bgd) and Fit methods yielded the most accurate volume estimates, with mean errors of 2% +/- 11% and -8% +/- 21% in the most realistic situations. Considering the simulated data, all SUV not corrected for PVE had a mean bias between -31% and -46%, much larger than the bias observed with SUV(max) (-11% +/- 23%) or with the PVE-corrected SUV based on T(bgd) and Fit (-2% +/- 10% and 3% +/- 24%).

CONCLUSION

The method used to estimate tumor volume and SUV greatly affects the reliability of the estimates. The T(bgd) and Fit methods yielded low errors in volume estimates in a broad range of situations. The PVE-corrected SUV based on T(bgd) and Fit were more accurate and reproducible than SUV(max).

A fuzzy locally adaptive Bayesian segmentation approach for volume determination in PET

Accurate volume estimation in positron emission tomography (PET) is crucial for different oncology applications. The objective of our study was to develop a new fuzzy locally adaptive Bayesian (FLAB) segmentation for automatic lesion volume delineation. FLAB was compared with a threshold approach as well as the previously proposed fuzzy hidden Markov chains (FHMC) and the fuzzy C-Means (FCM) algorithms. The performance of the algorithms was assessed on acquired datasets of the IEC phantom, covering a range of spherical lesion sizes (10-37 mm), contrast ratios (4:1 and 8:1), noise levels (1, 2, and 5 min acquisitions), and voxel sizes (8 and 64 mm(3)). In addition, the performance of the FLAB model was assessed on realistic nonuniform and nonspherical volumes simulated from patient lesions. Results show that FLAB performs better than the other methodologies, particularly for smaller objects. The volume error was 5%-15% for the different sphere sizes (down to 13 mm), contrast and image qualities considered, with a high reproducibility (variation < 4%). By comparison, the thresholding results were greatly dependent on image contrast and noise, whereas FCM results were less dependent on noise but consistently failed to segment lesions < 2 cm. In addition, FLAB performed consistently better for lesions < 2 cm in comparison to the FHMC algorithm. Finally the FLAB model provided errors less than 10% for nonspherical lesions with inhomogeneous activity distributions. Future developments will concentrate on an extension of FLAB in order to allow the segmentation of separate activity distribution regions within the same functional volume as well as a robustness study with respect to different scanners and reconstruction algorithms.

PET imaging in lymphoma

PET has become a cornerstone procedure in modern lymphoma management. This paper reviews, from a clinical point of view, the evidence for using PET in the different subtypes of lymphoma and the different steps of their management. The reader is given an overview of the current PET-based interventional lymphoma trials and an insight into possible future developments in the field, including new PET tracers.

Image guidance in radiation oncology treatment planning: the role of imaging technologies on the planning process

Radiation therapy has evolved from 2-dimensional (2D) to 3-dimensional (3D) treatments and, more recently, to intensity-modulated radiation therapy and image-guided radiation therapy. Improvements in imaging have enabled improvements in targeting and treatment. As computer-processing power has improved during the past few decades, it has facilitated developments in both imaging and treatment. The historical role of imaging from 2D to image-guided radiation therapy is reviewed here. Examples of imaging technologies such as positron emission tomography and magnetic resonance imaging are provided. The role of these imaging technologies, organ motion management approaches and their potential impacts on radiation therapy are described.

The value of dual time point (18)F-FDG PET imaging for the differentiation between malignant and benign lesions

AIM

To assess the clinical value of dual time point 2-[(18)F]-fluoro-2-deoxy-d-glucose positron emission tomography ((18)F-FDG PET) imaging for the differentiation between malignant and benign lesions.

MATERIALS AND METHODS

Ninety-six patients (28 patients with primary lung cancer, 18 patients with digestive system carcinoma, 13 patients with other malignant tumours, and 37 patients with benign lesions) underwent FDG-PET/CT at two time points: examination 1 at 45-55 min and examination 2 at 160+/-24 (150-180) min after the intravenous injection of 233+/-52 (185-370)MBq (18)F-FDG. Reconstructed images were evaluated qualitatively and quantitatively. The maximum standardized uptake values (SUVmax) of the lesions were calculated for both time points. An increase was considered to have occurred if the SUVs at examination 2 had increased by >10% as compared with those at the examination 1.

RESULTS

The lesions in 24 of 28 (86%) patients with primary lung cancer had an SUVmax > or = 2.5 at examination 1. Of these, SUVmax values increased in 23 patients, but had not changed in one patient, at examination 2. The lesions in the other four patients with primary lung tumour had SUVmax values between 1.5 and 2.5 at examination 1, which were considered as suspected positive, increased SUVmax values were observed in three of these patients at examination 2. The malignant lesions in 17 of 18 patients with digestive system carcinoma showed SUVmax values > or = 2.5 and only one patient had an SUVmax value < 1.5 at examination 1; all lesions showed an increase in SUVmax values at examination 2. In 13 patients with other malignant tumours, all lesions had SUVmax values > or = 2.5 at examination 1 and the SUVmax values were further increased at examination 2. Therefore, the malignant lesions in 54/59 (92%) of patients had SUVmax values > or = 2.5 at examination 1 and showed a further increase in SUVmax value at examination 2. Only 12 of 37 (32%) patients with benign lesions showed SUVmax values > or = 2.5 at examination 1 and nine patients with benign lesions had SUVmax values > or = 2.5 in examination 2. The sensitivity, specificity, accuracy, positive and negative predictive values for the early and delayed imaging were 91.5, 67.6, 82.3, 81.8, and 83.3%, and 98.3, 75.7, 89.6, 86.6, and 96.6%, respectively.

CONCLUSION

The results of the present study provide further evidence that dual time point (18)F-FDG PET imaging is an important noninvasive method for the differentiation of malignant and nonmalignant lesions.

2-[18F]fluoro-2-deoxyglucose positron-emission tomography in staging, response evaluation, and treatment planning of lymphomas

2-[18F]fluoro-2-deoxyglucose positron-emission tomography (FDG-PET) is used increasingly in the clinical management of lymphomas. With regard to staging, FDG-PET is more sensitive and specific than conventional staging methods in FDG avid lymphomas (ie, Hodgkin lymphoma and most aggressive non-Hodgkin lymphomas). Despite methodological problems, in particular the lack of a valid reference test, FDG-PET is approved and generally used for this purpose. With regard to response evaluation, FDG-PET at the end of treatment seems to aid considerably in differentiating between residual masses with or without residual lymphoma. Hence, new revised response criteria have been proposed, incorporating the result of FDG-PET at the end of treatment. An early interim FDG-PET scan after 1 to 3 cycles of chemotherapy is a very strong predictor of outcome, and trials are now in progress testing treatment modifications on this basis. With regard to treatment planning, in the context of combined-modality therapy, radiotherapy for lymphomas is moving toward more conformal techniques reducing the irradiated volume to include only the macroscopic lymphoma. In this situation, accurate imaging is essential, and FDG-PET coregistered with the planning computed tomography (CT) scan is used increasingly. The availability of PET/CT scanners suited for virtual simulation has aided this process. However, clinical data evaluating this technique are at present sparse.

Fuzzy hidden Markov chains segmentation for volume determination and quantitation in PET

Accurate volume of interest (VOI) estimation in PET is crucial in different oncology applications such as response to therapy evaluation and radiotherapy treatment planning. The objective of our study was to evaluate the performance of the proposed algorithm for automatic lesion volume delineation; namely the fuzzy hidden Markov chains (FHMC), with that of current state of the art in clinical practice threshold based techniques. As the classical hidden Markov chain (HMC) algorithm, FHMC takes into account noise, voxel intensity and spatial correlation, in order to classify a voxel as background or functional VOI. However the novelty of the fuzzy model consists of the inclusion of an estimation of imprecision, which should subsequently lead to a better modelling of the 'fuzzy' nature of the object of interest boundaries in emission tomography data. The performance of the algorithms has been assessed on both simulated and acquired datasets of the IEC phantom, covering a large range of spherical lesion sizes (from 10 to 37 mm), contrast ratios (4:1 and 8:1) and image noise levels. Both lesion activity recovery and VOI determination tasks were assessed in reconstructed images using two different voxel sizes (8 mm3 and 64 mm3). In order to account for both the functional volume location and its size, the concept of % classification errors was introduced in the evaluation of volume segmentation using the simulated datasets. Results reveal that FHMC performs substantially better than the threshold based methodology for functional volume determination or activity concentration recovery considering a contrast ratio of 4:1 and lesion sizes of <28 mm. Furthermore differences between classification and volume estimation errors evaluated were smaller for the segmented volumes provided by the FHMC algorithm. Finally, the performance of the automatic algorithms was less susceptible to image noise levels in comparison to the threshold based techniques. The analysis of both simulated and acquired datasets led to similar results and conclusions as far as the performance of segmentation algorithms under evaluation is concerned.

Nuclear imaging of neuroendocrine tumours

The diagnosis of neuroendocrine tumours (NETs) and monitoring of therapy in many patients relies mainly on morphological imaging techniques such as computed tomography (CT), ultrasound (US) and magnetic resonance imaging (MRI). However, functional imaging modalities--such as somatostatin receptor scintigraphy (SRS)--have great impact on patient management by providing tools for better staging of the disease, visualization of occult tumour, and evaluation of eligibility for somatostatin analogue treatment. Positron emission tomography (PET) using (18)F-fluoro-deoxy-glucose (FDG) is a powerful functional modality for oncological imaging. Unfortunately, FDG is not accumulated in NETs except in the case of dedifferentiated tumours and tumours with high proliferative activity. Based on the concept of amine precursor uptake and decarboxylation (APUD), the (18)F- and (11)C-labelled amine precursors L-dihydroxyphenylalanine and 5-hydroxy-L-tryptophan (5-HTP) have been utilized for PET imaging of NETs. In comparative studies of patients with a variety of NETs, (11)C5-HTP-PET proved better than CT and SRS by visualizing additional small lesions. With carbidopa premedication orally before (11)C5-HTP-PET examination the tumour uptake could be increased and the urinary radioactivity concentration considerably reduced. This concept may also be applied to (18)F-L-DOPA-PET, a method which in a limited number of studies has gained additional diagnostic information in NET patients compared to SRS and morphological imaging. (68)Ga is available from an in-house generator and has been utilized for labelling of somatostatin analogues for PET imaging of NETs with promising results in a small number of patients. However, SRS is an established functional imaging method for patients with NETs, whereas the role for PET in the clinical routine needs further evaluation in comparative studies in larger groups of patients.