Thresholding in PET images of static and moving targets

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.

Calculation Accuracy of Gross Tumor Volume at the Diaphragm Boundary Evaluated Using Respiratory-gated PET/CT

OBJECTIVE

The present study aimed to clarify gross tumor volume (GTV) contouring accuracy at the diaphragm boundary using respiratory-gated PET/CT.

METHODS

The lung/diaphragm boundary was simulated using a phantom containing ¹⁸F solution (10.6 kBq/mL). Tumors were simulated using spheres (diameter, 11-38 mm) containing ¹⁸F and located at the positions of the lungs and liver. The tumor background ratios (TBR) were 2, 4, and 8. The phantom was moved from the superior to inferior direction with a 20-mm motion displacement at 3.6 s intervals. The recovery coefficient (RC), volume RC (VRC), and standardized uptake value (SUV) threshold were calculated using stationary, non-gated (3D), and gated (4D) PET/CT.

RESULTS

In lung cancer simulation, RC and VRC in 3D PET images were, respectively, underestimated and overestimated in smaller tumors, whereas both improved in 4D PET images regardless of tumor size and TBR. The optimal SUV threshold was about 30% in 4D PET images. In liver cancer simulation, RC and VRC were, respectively, underestimated and overestimated in smaller tumors, and when the TBR was lower, but both improved in 4D PET images when tumors were >17 mm and the TBR was >4. The optimal SUV threshold tended to depend on the TBR.

CONCLUSIONS

The contouring accuracy of GTV was improved by considering TBR and using an optimal SUV threshold acquired from 4D PET images.

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.

Overall and disease-free survival outcomes of patients receiving intensity-modulated radiation therapy (IMRT) with PET-CT-based planning for cancers of the head and neck

Introduction

Combined modality treatment regimens have provided modest gains in locoregional control rates of cancers of the head and neck (HNC), and intensity-modulated radiation therapy (IMRT) has gained widespread use. The methodology for determining contours of the gross tumour volume (GTV) in the radiation treatment plan is often based on combined anatomic and metabolic data from positron emission tomography–computed tomography (PET-CT). This study aimed to retrospectively evaluate the overall survival and disease-free survival outcomes of patients with HNC who received definitive IMRT with or without chemotherapy, planned with PET-CT.

Materials and Methods

A total of 1,200 patients underwent treatment for HNC during the study period, from 1 January 2002 to 31 December 2010. Of those, 261 cases had evaluable data that met the inclusion criteria for the study. The incidence and timing of locoregional recurrence, distant metastatic disease, new primary malignancies and death were evaluated retrospectively. Overall and disease-free survival (survival to time of first recurrence) were determined by the life table method. Incidence of distance metastatic disease and additional cancers were also studied.

Results

Median follow-up from treatment initiation was 26·4 months (range 1·2–84·7 months). Overall survival and disease-free survival rates were 0·883 and 0·791, respectively, at 1 year; 0·793 and 0·688, respectively, at 2 years; and 0·732 and 0·619, respectively, at 3 years. The cumulative risk of recurrence was 22·6% at 3 years following definitive IMRT and the median time to recurrence was 345 days. There was an overall low incidence of distant metastatic disease (3·07%) and additional cancers (8·05%).

Conclusion

Overall and disease-free survival outcomes of a large cohort of HNC patients treated with definitive IMRT radiotherapy following treatment planning with PET-CT shows a similar high level of disease control and mortality rate as previously published outcome studies of shorter terms and/or smaller numbers of patients.

The use of positron emission tomography/computed tomography imaging in radiation therapy: a phantom study for setting internal target volume of biological target volume

BACKGROUND

Fluorodeoxyglucose ((18)F-FDG) positron emission tomography/computed tomography (PET/CT) is an important method for detecting tumours, planning radiotherapy treatment, and evaluating treatment responses. However, using the standardized uptake value (SUV) threshold with PET imaging may be suitable not to determine gross tumour volume but to determine biological target volume (BTV). The aim of this study was to extract internal target volume of BTV from PET images.

METHODS

Three spherical densities of (18)F-FDG were employed in a phantom with an air or water background with repetitive motion amplitudes of 0-30 mm. The PET data were reconstructed with attenuation correction (AC) based on CT images obtained by slow CT scanning (SCS) or helical CT scanning (HCS). The errors in measured SUVmax and volumes calculated using SUV threshold values based on SUVmax (THmax) in experiments performed with varying extents of respiratory motion and AC were analysed.

RESULTS

A partial volume effect (PVE) was not observed in spheres with diameters of ≥ 28 mm. When calculating SUVmax and THmax, using SCS for AC yielded smaller variance than using HCS (p<0.05). For spheres of 37- and 28-mm diameters in the phantom with either an air or water background, significant differences were observed when mean THmax of 30-, 20-, or 10-mm amplitude were compared with the stationary conditions (p<0.05). The average THmax values for 37-mm and 28-mm spheres with an air background were 0.362 and 0.352 in non-motion, respectively, and the mean THmax values for 37-mm and 28-mm spheres with a water background were 0.404 and 0.387 in non-motion and 0.244 and 0.263 in motion, respectively. When the phantom background was air, regardless of sphere concentration or size, THmax was dependent only on motion amplitude.

CONCLUSIONS

We found that there was no PVE for spheres with ≥ 28-mm diameters, and differences between SUVmax and THmax were reduced by using SCS for AC. In the head-and-neck and the abdomen, the standard values of THmax were 0.25 and 0.40 with and without respiratory movement, respectively. In the lungs, the value of THmax became the approximate expression depending on motion amplitude.

Recent advances in radiotherapy for thoracic tumours

Radiation Oncology technology has continued to advance at a rapid rate and is bringing significant benefits to patients. This review outlines some of the advances in technology and radiotherapy treatment of thoracic cancers including brachytherapy, stereotactic radiotherapy, tomotherapy and intensity modulated radiotherapy. The importance of functional imaging with PET and management of movement are highlighted. Most of the discussion relates to non-small cell lung cancer but management of mesothelioma and small cell lung cancer are also covered. This technology has substantial benefits to patients in terms of decreasing toxicity both in the short and longer term.

A review on segmentation of positron emission tomography images

Positron Emission Tomography (PET), a non-invasive functional imaging method at the molecular level, images the distribution of biologically targeted radiotracers with high sensitivity. PET imaging provides detailed quantitative information about many diseases and is often used to evaluate inflammation, infection, and cancer by detecting emitted photons from a radiotracer localized to abnormal cells. In order to differentiate abnormal tissue from surrounding areas in PET images, image segmentation methods play a vital role; therefore, accurate image segmentation is often necessary for proper disease detection, diagnosis, treatment planning, and follow-ups. In this review paper, we present state-of-the-art PET image segmentation methods, as well as the recent advances in image segmentation techniques. In order to make this manuscript self-contained, we also briefly explain the fundamentals of PET imaging, the challenges of diagnostic PET image analysis, and the effects of these challenges on the segmentation results.

Determination of an optimal standardized uptake value of fluorodeoxyglucose for positron emission tomography imaging to assess pathological volumes of cervical cancer: a prospective study

Purpose

To determine the optimal standardized uptake value (SUV) of ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) for positron emission tomography (PET) imaging, at which the PET-defined gross tumor volume (GTV_PET) best matches with the pathological volume (GTV_PATH) in the cervical cancer.

Materials and Methods

Ten patients with the cervical cancer who underwent surgery were enrolled in this study. The excised specimens were processed for whole-mount serial sections and H-E staining. The tumor borders were outlined in sections under a microscope, histopathological images were scanned and the GTV_PATH calculated. The GTV_PET was delineated automatically by using various percentages relative to the maximal SUV and absolute SUV. The optimal threshold SUV was further obtained as the value at which the GTV_PET best matched with the GTV_PATH.

Results

An average of 85±10% shrinkage of tissue was observed after the formalin fixation. The GTV_PATH was 13.38±2.80 cm³ on average. The optimal threshold on percentile SUV and absolute SUV were 40.50%±3.16% and 7.45±1.10, respectively. The correlation analysis showed that the optimal percentile SUV threshold was inversely correlated with GTV_PATH (p<0.05) and tumor diameter (p<0.05). The absolute SUV was also positively correlated with SUV_max (p<0.05).

Conclusion

The pathological volume could provide the more accurate tumor volume. The optimal SUV of FDG for PET imaging by use of GTV_PATH as standard for cervical cancer target volume delineation was thus determined in this study, and more cases are being evaluated to substantiate this conclusion.

Thoracic tumor volume delineation in 4D-PET/CT by low dose interpolated CT for attenuation correction

PURPOSE

4D-PET/CT imaging is an excellent solution for reducing the breathing-induced effects in both CT and PET images. In 4D-PET/CT, 4D-CT images are selected to match those of 4D-PET phase by phase and the corresponding phases are used for attenuation correction in 4D-PET. However, the high radiation dose that patients acquire while undergoing 4D-CT imaging for diagnostic purposes remains a concern. This study aims to assess low-dose interpolated CT (ICT) for PET attenuation correction (PETICT) in thoracic tumor volume delineation.

METHODS AND MATERIALS

Twelve thoracic cancer patients (10 esophageal and 2 lung cancer cases) were recruited. All patients underwent 4D-PET/CT scans. The optical flow method based on image intensity gradient was applied to calculate the motion displacement in three dimensions for each voxel on two original extreme CT phases in the respiratory cycle, end-inspiration and end-expiration. The interpolated CTs were generated from two phases of the original 4D-CT using motion displacement.

RESULTS

Tumor motion due to respiration was estimated in the anterior-posterior dimension, the lateral dimension and the superior-inferior dimension by the optical flow method. The PETICT and ICT (4D-PET ICT/ICT) matched each other spatially in all the phases. The distortion of tumor shape and size resulting from respiratory motion artifacts were not observed in 4D-PETICT. The tumor volume measured by 4D-PET ICT/ICT correlated to the tumor volume measured by 4D-PET/CT (p = 0.98).

CONCLUSIONS

4D-PETICT consistently represented the interpretation of FDG uptake as effectively as 4D-PET. 4D-PET ICT/ICT is a low-dose alternative to 4D-CT and significantly improves the interpretation of PET and CT images, while solving the respiratory motion problem as effectively as 4D-PET/CT.

Unsupervised tumour segmentation in PET using local and global intensity-fitting active surface and alpha matting

This paper proposes an unsupervised tumour segmentation approach for PET data. The method computes the volumes of interest (VOIs) with sub-voxel precision by considering the limited image resolution and partial volume effects. First, an improved anisotropic diffusion filter is used to remove image noise. A hierarchical local and global intensity active surface modelling scheme is then applied to segment VOIs, followed by an alpha matting step to further refine the segmentation boundary. The proposed method is validated on real PET images of head-and-neck cancer patients with ground truth provided by human experts, as well as custom-designed phantom PET images with objective ground truth. Experimental results show that our method outperforms previous automatic approaches in terms of segmentation accuracy.

Recommendations of the Spanish Societies of Radiation Oncology (SEOR), Nuclear Medicine & Molecular Imaging (SEMNiM), and Medical Physics (SEFM) on (18)F-FDG PET-CT for radiotherapy treatment planning

Positron emission tomography (PET) with (18)F-fluorodeoxyglucose (FDG) is a valuable tool for diagnosing and staging malignant lesions. The fusion of PET and computed tomography (CT) yields images that contain both metabolic and morphological information, which, taken together, have improved the diagnostic precision of PET in oncology. The main imaging modality for planning radiotherapy treatment is CT. However, PET-CT is an emerging modality for use in planning treatments because it allows for more accurate treatment volume definition. The use of PET-CT for treatment planning is highly complex, and protocols and standards for its use are still being developed. It seems probable that PET-CT will eventually replace current CT-based planning methods, but this will require a full understanding of the relevant technical aspects of PET-CT planning. The aim of the present document is to review these technical aspects and to provide recommendations for clinical use of this imaging modality in the radiotherapy planning process.

The role of positron emission tomography/computed tomography in radiation therapy planning for patients with lung cancer

Positron emission tomography (PET)/computed tomography (CT) has rapidly assumed a critical role in the management of patients with locoregionally advanced lung cancers who are candidates for definitive radiation therapy (RT). Definitive RT is given with curative intent, but can only be successful in patients without distant metastasis and if all gross tumor is contained within the treated volume. An increasing body of evidence supports the use of PET-based imaging for selection of patients for both surgery and definitive RT. Similarly, the use of PET/CT images for accurate target volume definition in lung cancer is a dynamic area of research. Most available evidence on PET staging of lung cancer relates to non-small cell lung cancer (NSCLC). In general clinical use, (18)F-fluorodeoxyglucose (FDG) is the primary radiopharmaceutical useful in NSCLC. Other tracers, including proliferation markers and hypoxia tracers, may have significant roles in future. Much of the FDG-PET literature describing the impact of PET on actual patient management has concerned candidates for surgical resection. In the few prospective studies where PET was used for staging and patient selection in NSCLC candidates for definitive RT, 25%-30% of patients were denied definitive RT, generally because PET detected unsuspected advanced locoregional or distant metastatic disease. PET/CT and CT findings are often discordant in NSCLC but studies with clinical-pathological correlation always show that PET-assisted staging is more accurate than conventional assessment. In all studies in which "PET-defined" and "non-PET-defined" RT target volumes were compared, there were major differences between PET and non-PET volumes. Therefore, in cases where PET-assisted and non-PET staging are different and biopsy confirmation is unavailable, it is rational to use the most accurate modality (namely PET/CT) to define the target volume. The use of PET/CT in patient selection and target volume definition is likely to lead to improvements in outcome for patients with NSCLC.

Motion management in positron emission tomography/computed tomography for radiation treatment planning

Hybrid positron emission tomography (PET)/computed tomography (CT) scanners combine, in a unique gantry, 2 of the most important diagnostic imaging systems, a CT and a PET tomograph, enabling anatomical (CT) and functional (PET) studies to be performed in a single study session. Furthermore, as the 2 scanners use the same spatial coordinate system, the reconstructed CT and PET images are spatially co-registered, allowing an accurate localization of the functional signal over the corresponding anatomical structure. This peculiarity of the hybrid PET/CT system results in improved tumor characterization for oncological applications, and more recently, it was found to be also useful for target volume definition (TVD) and treatment planning in radiotherapy (RT) applications. In fact, the use of combined PET/CT information has been shown to improve the RT treatment plan when compared with that obtained by a CT alone. A limiting factor to the accuracy of TVD by PET/CT is organ and tumor motion, which is mainly due to patient respiration. In fact, respiratory motion has a degrading effect on PET/CT image quality, and this is also critical for TVD, as it can lead to possible tumor missing or undertreatment. Thus, the management of respiratory motion is becoming an increasingly essential component in RT treatment planning; indeed, it has been recognized that the use of personalized motion information can improve TVD and, consequently, permit increased tumor dosage while sparing surrounding healthy tissues and organs at risk. This review describes the methods used for motion management in PET/CT for radiation treatment planning. The article covers the following: (1) problems caused by organ and lesion motion owing to respiration, and the artifacts generated on CT, PET, and PET/CT images; (2) data acquisition and processing techniques used to manage respiratory motion in PET/CT studies; and (3) the use of personalized motion information for TVD and radiation treatment planning.

Determination of internal target volume from a single positron emission tomography/computed tomography scan in lung cancer

PURPOSE

The use of four-dimensional computed tomography (4D-CT) to determine the tumor internal target volume (ITV) is usually characterized by high patient radiation exposure. The objective of this study was to propose and evaluate an approach that relies on a single static positron emission tomography (PET)/CT scan to determine the ITV, thereby eliminating the need for 4D-CT and thus reduce patient radiation dose.

METHODS AND MATERIALS

The proposed approach is based on the concept that the observed PET image is the result of a joint convolution of an ideal PET image (free from motion and partial volume effect) with a motion-blurring kernel (MBK) and partial volume effect. In this regard, the MBK and tumor ITV are then estimated from the deconvolution of this joint model. To test this technique, phantom and patient studies were performed using different sphere/tumor sizes and motion trajectories. In all studies, a 4D-CT and a PET/CT image of the sphere/tumor were acquired. The ITV from the proposed technique was then compared to the maximum intensity projection (MIP) volume of the 4D-CT images. A Dice coefficient of the two volumes was calculated to represent the similarity between the two ITVs.

RESULTS

The average ITVs of the proposed technique were 97.2% ± 0.3% and 81.0% ± 16.7% similar to the MIP volume in the phantom and patient studies, respectively. The average dice coefficients were 0.87 ± 0.05 and 0.73 ± 0.16, respectively, for the two studies.

CONCLUSION

Using the proposed approach, a single static PET/CT scan has the potential to replace a 4D-CT to determine the tumor ITV. This approach has the added advantage of reducing patient radiation exposure and determining the tumor MBK compared to 4D-CT/MIP-CT.

Imaging for target volume delineation in rectal cancer radiotherapy--a systematic review

The global move towards more conformal radiotherapy for rectal cancer requires better imaging modalities that both visualise the disease accurately and are reproducible; to reduce interobserver variation. This review explores the advances in imaging modalities used in target volume delineation, with a view to make recommendations for current clinical practice and to propose future directions for research. A systematic review was conducted using MEDLINE and EMBASE. Articles considered relevant by the authors were included. Planning with orthogonal films is being replaced by computed tomography (CT) simulation. This is now considered the 'gold standard' and allows conformal three-dimensional planning. Magnetic resonance imaging (MRI) has been shown to overcome some of the limitations of CT and can be used either as a diagnostic image to visually aid planning, or as a 'planning' MRI carried out in the treatment position and co-registered with the planning CT. The latter approach has been shown to change the treated volumes compared with CT and in prostate cancer patients has been shown to reduce interobserver variation. There are remaining issues with four-dimensional motion that are yet to be fully appreciated or overcome. 2-[18F] fluoro-2-deoxy-d-glucose positron emission tomography/CT co-registered with planning CT results in smaller volumes than CT alone and also reduces interobserver variation, but requires further validation before routine implementation. Experimental work utilising novel positron emission tomography tracers and diffusion-weighted MRI shows promise and requires further evaluation. Rigorous quality assurance is important with processing of newer imaging modalities. Further work needs to be conducted into both interobserver variation and the formal evaluation of the clinical benefits of newer imaging modalities. Developments in image-guided radiotherapy are also required to ensure that improvements in target definition at the planning stage are reproducible throughout treatment.

An innovative iterative thresholding algorithm for tumour segmentation and volumetric quantification on SPECT images: Monte Carlo-based methodology and validation

PURPOSE

Positron emission tomography (PET) and single-photon emission computed tomography (SPECT) imaging play an important role in the segmentation of functioning parts of organs or tumours, but an accurate and reproducible delineation is still a challenging task. In this work, an innovative iterative thresholding method for tumour segmentation has been proposed and implemented for a SPECT system. This method, which is based on experimental threshold-volume calibrations, implements also the recovery coefficients (RC) of the imaging system, so it has been called recovering iterative thresholding method (RIThM). The possibility to employ Monte Carlo (MC) simulations for system calibration was also investigated.

METHODS

The RIThM is an iterative algorithm coded using MATLAB: after an initial rough estimate of the volume of interest, the following calculations are repeated: (i) the corresponding source-to-background ratio (SBR) is measured and corrected by means of the RC curve; (ii) the threshold corresponding to the amended SBR value and the volume estimate is then found using threshold-volume data; (iii) new volume estimate is obtained by image thresholding. The process goes on until convergence. The RIThM was implemented for an Infinia Hawkeye 4 (GE Healthcare) SPECT/CT system, using a Jaszczak phantom and several test objects. Two MC codes were tested to simulate the calibration images: SIMIND and SimSet. For validation, test images consisting of hot spheres and some anatomical structures of the Zubal head phantom were simulated with SIMIND code. Additional test objects (flasks and vials) were also imaged experimentally. Finally, the RIThM was applied to evaluate three cases of brain metastases and two cases of high grade gliomas.

RESULTS

Comparing experimental thresholds and those obtained by MC simulations, a maximum difference of about 4% was found, within the errors (+/- 2% and +/- 5%, for volumes > or = 5 ml or < 5 ml, respectively). Also for the RC data, the comparison showed differences (up to 8%) within the assigned error (+/- 6%). ANOVA test demonstrated that the calibration results (in terms of thresholds or RCs at various volumes) obtained by MC simulations were indistinguishable from those obtained experimentally. The accuracy in volume determination for the simulated hot spheres was between -9% and 15% in the range 4-270 ml, whereas for volumes less than 4 ml (in the range 1-3 ml) the difference increased abruptly reaching values greater than 100%. For the Zubal head phantom, errors ranged between 9% and 18%. For the experimental test images, the accuracy level was within +/- 10%, for volumes in the range 20-110 ml. The preliminary test of application on patients evidenced the suitability of the method in a clinical setting.

CONCLUSIONS

The MC-guided delineation of tumor volume may reduce the acquisition time required for the experimental calibration. Analysis of images of several simulated and experimental test objects, Zubal head phantom and clinical cases demonstrated the robustness, suitability, accuracy, and speed of the proposed method. Nevertheless, studies concerning tumors of irregular shape and/or nonuniform distribution of the background activity are still in progress.

Segmentation of positron emission tomography images: some recommendations for target delineation in radiation oncology

Positron emission tomography can be used in radiation oncology for the delineation of target volumes in the treatment planning stage. Numerous publications deal with this topic and the scientific community has investigated many methodologies, ranging from simple uptake thresholding to very elaborate probabilistic models. Nevertheless, no consensus seems to emerge. This paper reviews delineation techniques that are popular in the literature. Special attention is paid to threshold-based techniques and the caveats of this methodology are pointed out by formal analysis. Next, a simple model of positron emission tomography is suggested in order to shed some light on the difficulties of target delineation and how they might be eventually overcome. Validation aspects are considered as well. Finally, a few recommendations are gathered in the conclusion.

PET and PET-CT in radiation treatment planning for lung cancer

This review analyzes PET images in radiotherapy treatment planning for lung cancer patients and discusses the most controversial current issues. Computed tomography images are commonly used to assess location and extension of target volumes and organs at risk in radiotherapy treatment planning. Although PET is more sensitive and specific, contouring on PET images is difficult because tumor margins are indistinct, due to heterogeneous (18)fluorodeoxyglucose uptake distribution and limited spatial resolution. The best target delineation criteria have not yet been established. In non-small-cell lung cancer, PET appears to improve sparing of organs at risk and reduce the risk of toxicity; prescribed doses can be increased. Data are scarce on small-cell lung cancer.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Radiation treatment planning using positron emission and computed tomography for lung and pharyngeal cancers: a multiple-threshold method for [(18)F]fluoro-2-deoxyglucose activity

PURPOSE

Clinical applicability of a multiple-threshold method for [(18)F]fluoro-2-deoxyglucose (FDG) activity in radiation treatment planning was evaluated.

METHODS AND MATERIALS

A total of 32 patients who underwent positron emission and computed tomography (PET/CT) simulation were included; 18 patients had lung cancer, and 14 patients had pharyngeal cancer. For tumors of <or=2 cm, 2 to 5 cm, and >5 cm, thresholds were defined as 2.5 standardized uptake value (SUV), 35%, and 20% of the maximum FDG activity, respectively. The cervical and mediastinal lymph nodes with the shortest axial diameter of >or=10 mm were considered to be metastatic on CT (LNCT). The retropharyngeal lymph nodes with the shortest axial diameter of >or=5 mm on CT and MRI were also defined as metastatic. Lymph nodes showing maximum FDG activity greater than the adopted thresholds for radiation therapy planning were designated LNPET-RTP, and lymph nodes with a maximum FDG activity of >or=2.5 SUV were regarded as malignant and were designated LNPET-2.5 SUV.

RESULTS

The sizes of gross tumor volumes on PET (GTVPET) with the adopted thresholds in the axial plane were visually well fitted to those of GTV on CT (GTVCT). However, the volumes of GTVPET were larger than those of GTVCT, with significant differences (p < 0.0001) for lung cancer, due to respiratory motion. For lung cancer, the numbers of LNCT, LNPET-RTP, and LNPET-2.5 SUV were 29, 28, and 34, respectively. For pharyngeal cancer, the numbers of LNCT, LNPET-RTP, and LNPET-2.5 SUV were 14, 9, and 15, respectively.

CONCLUSIONS

Our multiple thresholds were applicable for delineating the primary target on PET/CT simulation. However, these thresholds were inaccurate for depicting malignant lymph nodes.

PET-guided delineation of radiation therapy treatment volumes: a survey of image segmentation techniques

Historically, anatomical CT and MR images were used to delineate the gross tumour volumes (GTVs) for radiotherapy treatment planning. The capabilities offered by modern radiation therapy units and the widespread availability of combined PET/CT scanners stimulated the development of biological PET imaging-guided radiation therapy treatment planning with the aim to produce highly conformal radiation dose distribution to the tumour. One of the most difficult issues facing PET-based treatment planning is the accurate delineation of target regions from typical blurred and noisy functional images. The major problems encountered are image segmentation and imperfect system response function. Image segmentation is defined as the process of classifying the voxels of an image into a set of distinct classes. The difficulty in PET image segmentation is compounded by the low spatial resolution and high noise characteristics of PET images. Despite the difficulties and known limitations, several image segmentation approaches have been proposed and used in the clinical setting including thresholding, edge detection, region growing, clustering, stochastic models, deformable models, classifiers and several other approaches. A detailed description of the various approaches proposed in the literature is reviewed. Moreover, we also briefly discuss some important considerations and limitations of the widely used techniques to guide practitioners in the field of radiation oncology. The strategies followed for validation and comparative assessment of various PET segmentation approaches are described. Future opportunities and the current challenges facing the adoption of PET-guided delineation of target volumes and its role in basic and clinical research are also addressed.

18F-fluorocholine PET-guided target volume delineation techniques for partial prostate re-irradiation in local recurrent prostate cancer

BACKGROUND AND PURPOSE

We evaluate the contribution of (18)F-choline PET/CT in the delineation of gross tumour volume (GTV) in local recurrent prostate cancer after initial irradiation using various PET image segmentation techniques.

MATERIALS AND METHODS

Seventeen patients with local-only recurrent prostate cancer (median=5.7 years) after initial irradiation were included in the study. Rebiopsies were performed in 10 patients that confirmed the local recurrence. Following injection of 300 MBq of (18)F-fluorocholine, dynamic PET frames (3 min each) were reconstructed from the list-mode acquisition. Five PET image segmentation techniques were used to delineate the (18)F-choline-based GTVs. These included manual delineation of contours (GTV(man)) by two teams consisting of a radiation oncologist and a nuclear medicine physician each, a fixed threshold of 40% and 50% of the maximum signal intensity (GTV(40%) and GTV(50%)), signal-to-background ratio-based adaptive thresholding (GTV(SBR)), and a region growing (GTV(RG)) algorithm. Geographic mismatches between the GTVs were also assessed using overlap analysis.

RESULTS

Inter-observer variability for manual delineation of GTVs was high but not statistically significant (p=0.459). In addition, the volumes and shapes of GTVs delineated using semi-automated techniques were significantly higher than those of GTVs defined manually.

CONCLUSIONS

Semi-automated segmentation techniques for (18)F-choline PET-guided GTV delineation resulted in substantially higher GTVs compared to manual delineation and might replace the latter for determination of recurrent prostate cancer for partial prostate re-irradiation. The selection of the most appropriate segmentation algorithm still needs to be determined.

Molecular PET/CT imaging-guided radiation therapy treatment planning

The role of positron emission tomography (PET) during the past decade has evolved rapidly from that of a pure research tool to a methodology of enormous clinical potential. (18)F-fluorodeoxyglucose (FDG)-PET is currently the most widely used probe in the diagnosis, staging, assessment of tumor response to treatment, and radiation therapy planning because metabolic changes generally precede the more conventionally measured parameter of change in tumor size. Data accumulated rapidly during the last decade, thus validating the efficacy of FDG imaging and many other tracers in a wide variety of malignant tumors with sensitivities and specificities often in the high 90 percentile range. As a result, PET/computed tomography (CT) had a significant impact on the management of patients because it obviated the need for further evaluation, guided further diagnostic procedures, and assisted in planning therapy for a considerable number of patients. On the other hand, the progress in radiation therapy technology has been enormous during the last two decades, now offering the possibility to plan highly conformal radiation dose distributions through the use of sophisticated beam targeting techniques such as intensity-modulated radiation therapy (IMRT) using tomotherapy, volumetric modulated arc therapy, and many other promising technologies for sculpted three-dimensional (3D) dose distribution. The foundation of molecular imaging-guided radiation therapy lies in the use of advanced imaging technology for improved definition of tumor target volumes, thus relating the absorbed dose information to image-based patient representations. This review documents technological advancements in the field concentrating on the conceptual role of molecular PET/CT imaging in radiation therapy treatment planning and related image processing issues with special emphasis on segmentation of medical images for the purpose of defining target volumes. There is still much more work to be done and many of the techniques reviewed are themselves not yet widely implemented in clinical settings.

Evaluation of the combined effects of target size, respiratory motion and background activity on 3D and 4D PET/CT images

Gated (4D) PET/CT has the potential to greatly improve the accuracy of radiotherapy at treatment sites where internal organ motion is significant. However, the best methodology for applying 4D-PET/CT to target definition is not currently well established. With the goal of better understanding how to best apply 4D information to radiotherapy, initial studies were performed to investigate the effect of target size, respiratory motion and target-to-background activity concentration ratio (TBR) on 3D (ungated) and 4D PET images. Using a PET/CT scanner with 4D or gating capability, a full 3D-PET scan corrected with a 3D attenuation map from 3D-CT scan and a respiratory gated (4D) PET scan corrected with corresponding attenuation maps from 4D-CT were performed by imaging spherical targets (0.5-26.5 mL) filled with (18)F-FDG in a dynamic thorax phantom and NEMA IEC body phantom at different TBRs (infinite, 8 and 4). To simulate respiratory motion, the phantoms were driven sinusoidally in the superior-inferior direction with amplitudes of 0, 1 and 2 cm and a period of 4.5 s. Recovery coefficients were determined on PET images. In addition, gating methods using different numbers of gating bins (1-20 bins) were evaluated with image noise and temporal resolution. For evaluation, volume recovery coefficient, signal-to-noise ratio and contrast-to-noise ratio were calculated as a function of the number of gating bins. Moreover, the optimum thresholds which give accurate moving target volumes were obtained for 3D and 4D images. The partial volume effect and signal loss in the 3D-PET images due to the limited PET resolution and the respiratory motion, respectively were measured. The results show that signal loss depends on both the amplitude and pattern of respiratory motion. However, the 4D-PET successfully recovers most of the loss induced by the respiratory motion. The 5-bin gating method gives the best temporal resolution with acceptable image noise. The results based on the 4D scan protocols can be used to improve the accuracy of determining the gross tumor volume for tumors in the lung and abdomen.

Impact of PET on radiation therapy planning in lung cancer

The superiority of PET imaging to structural imaging in many cancers is rapidly transforming the practice of radiotherapy planning, especially in lung cancer. Although most lung cancers are potentially treatable with radiation therapy, only patients who have truly locoregionally confined disease can be cured by this modality. PET improves selection for high-dose radiation therapy by excluding many patients who have incurable distant metastasis or extensive locoregional spread. In those patients suitable for definitive treatment, PET can help shape the treatment fields to avoid geographic miss and minimize unnecessary irradiation of normal tissues. PET will allow for more accurately targeted dose escalation studies in the future and could potentially lead to better long-term survival.

Intraobserver and interobserver variability in GTV delineation on FDG-PET-CT images of head and neck cancers

PURPOSE

To determine if the addition of fluorodeoxyglucose positron emission tomography (FDG-PET) data changes primary site gross tumor volumes (GTVs) in head and neck cancers.

METHODS AND MATERIALS

Computed tomography (CT), contrast-enhanced CT, and FDG-PET-CT scans were obtained in 10 patients with head and neck cancers. Eight experienced observers (6 head and neck oncologists and 2 neuro-radiologists) with access to clinical and radiologic reports outlined primary site GTVs on each modality. Three cases were recontoured twice to assess intraobserver variability. The magnitudes of the GTVs were compared. Intra- and interobserver variability was assessed by a two-way repeated measures analysis of variance. Inter- and intraobserver reliability were calculated.

RESULTS

There were no significant differences in the GTVs across the image modalities when compared as ensemble averages; the Wilcoxon matched-pairs signed-rank test showed that CT volumes were larger than PET-CT. Observers demonstrated the greatest consistency and were most interchangeable on contrast-enhanced CT; they performed less reliably on PET-CT.

CONCLUSIONS

The addition of PET-CT to primary site GTV delineation of head and neck cancers does not change the volume of the GTV defined by this group of expert observers in this patient sample. An FDG-PET may demonstrate differences in neck node delineation and in other disease sites.

Fully automated segmentation of oncological PET volumes using a combined multiscale and statistical model

The widespread application of positron emission tomography (PET) in clinical oncology has driven this imaging technology into a number of new research and clinical arenas. Increasing numbers of patient scans have led to an urgent need for efficient data handling and the development of new image analysis techniques to aid clinicians in the diagnosis of disease and planning of treatment. Automatic quantitative assessment of metabolic PET data is attractive and will certainly revolutionize the practice of functional imaging since it can lower variability across institutions and may enhance the consistency of image interpretation independent of reader experience. In this paper, a novel automated system for the segmentation of oncological PET data aiming at providing an accurate quantitative analysis tool is proposed. The initial step involves expectation maximization (EM)-based mixture modeling using a k-means clustering procedure, which varies voxel order for initialization. A multiscale Markov model is then used to refine this segmentation by modeling spatial correlations between neighboring image voxels. An experimental study using an anthropomorphic thorax phantom was conducted for quantitative evaluation of the performance of the proposed segmentation algorithm. The comparison of actual tumor volumes to the volumes calculated using different segmentation methodologies including standard k-means, spatial domain Markov Random Field Model (MRFM), and the new multiscale MRFM proposed in this paper showed that the latter dramatically reduces the relative error to less than 8% for small lesions (7 mm radii) and less than 3.5% for larger lesions (9 mm radii). The analysis of the resulting segmentations of clinical oncologic PET data seems to confirm that this methodology shows promise and can successfully segment patient lesions. For problematic images, this technique enables the identification of tumors situated very close to nearby high normal physiologic uptake. The use of this technique to estimate tumor volumes for assessment of response to therapy and to delineate treatment volumes for the purpose of combined PET/CT-based radiation therapy treatment planning is also discussed.

Incorporating PET information in radiation therapy planning

PET scanning, because of its impressive sensitivity and accuracy, is being incorporated into the standard staging workup for many cancers. These include lung cancer, lymphomas, head and neck cancers, and oesophageal cancers. PET often provides incremental information about the patient’s disease status, adding to the data obtained from structural imaging methods, such as, CT scan or MRI. PET commonly upstages patients into more advanced disease categories. Incorporation of PET information into the radiotherapy planning process has the potential to reduce the risks of geographic miss and can help minimise unnecessary irradiation of normal tissues. The best means of incorporating PET information into radiotherapy planning is uncertain, and considerable effort is being expended in this area of research.