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

Comparison of semi-automatic and manual segmentation methods for tumor delineation on head and neck squamous cell carcinoma (HNSCC) positron emission tomography (PET) images

Objective. Accurate and reproducible tumor delineation on positron emission tomography (PET) images is required to validate predictive and prognostic models based on PET radiomic features. Manual segmentation of tumors is time-consuming whereas semi-automatic methods are easily implementable and inexpensive. This study assessed the reliability of semi-automatic segmentation methods over manual segmentation for tumor delineation in head and neck squamous cell carcinoma (HNSCC) PET images.Approach. We employed manual and six semi-automatic segmentation methods (just enough interaction (JEI), watershed, grow from seeds (GfS), flood filling (FF), 30% SUVmax and 40%SUVmax threshold) using 3D slicer software to extract 128 radiomic features from FDG-PET images of 100 HNSCC patients independently by three operators. We assessed the distributional properties of all features and considered 92 log-transformed features for subsequent analysis. For each paired comparison of a feature, we fitted a separate linear mixed effect model using the method (two levels; manual versus one semi-automatic method) as a fixed effect and the subject and the operator as the random effects. We estimated different statistics-the intraclass correlation coefficient agreement (aICC), limits of agreement (LoA), total deviation index (TDI), coverage probability (CP) and coefficient of individual agreement (CIA)-to evaluate the agreement between the manual and semi-automatic methods.Main results. Accounting for all statistics across 92 features, the JEI method consistently demonstrated acceptable agreement with the manual method, with median values of aICC = 0.86, TDI = 0.94, CP = 0.66, and CIA = 0.91.Significance. This study demonstrated that JEI method is a reliable semi-automatic method for tumor delineation on HNSCC PET images.

Application of a smart 18F-FDG-PET adaptive threshold segmentation algorithm for the biological target volume delineation in head and neck cancer

BACKGROUND

The aim of the present study is to evaluate the reliability of a 18F-fluorodeoxyglucose (18F-FDG) PET adaptive threshold segmentation (ATS) algorithm, previously validated in a preclinical setting on several scanners, for the biological target volume (BTV) delineation of head and neck radiotherapy planning.

METHODS

[18F]FDG PET ATS algorithm was studied in treatment plans of head and neck squamous cell carcinoma on a dedicated workstation (iTaRT, Tecnologie Avanzate, Turin, Italy). BTVs segmented by the present ATS algorithm (BTVATS) were compared with those manually segmented for the original radiotherapy treatment planning (BTVVIS). We performed a qualitative and quantitative volumetric analysis with a comparison tool within the ImSimQA TM software package (Oncology Systems Limited, Shrewsbury, UK). We reported figures of merit (FOMs) to convey complementary information: Dice Similarity Coefficient, Sensitivity Index, and Inclusiveness Index.

RESULTS

The study was conducted on 32 treatment plans. Median BTVATS was 11 cm3 while median BTVVIS was 14 cm3. The median Dice Similarity Coefficient, Sensitivity Index, Inclusiveness Index were 0.72, 63%, 88%, respectively. Interestingly, the median volume and the median distance of the voxels that are over contoured by ATS were respectively 1 cm3 and 1 mm.

CONCLUSIONS

ATS algorithm could be a smart and an independent operator tool when implemented for 18F-FDG-PET-based tumor volume delineation. Furthermore, it might be relevant in case of BTV-based dose painting.

Metabolic response after 68Ga-PSMA-PET/CT-directed IGRT/SBRT for oligometastases prostate cancer

BACKGROUND

We used 68Ga PSMA PET/CT in the current investigation to assess the metabolic response and local control of metastasis in patients with oligometastatic prostate cancer receiving SBRT.

MATERIALS AND PROCEDURES

We performed a retrospective evaluation of the medical data of all patients with oligometastatic prostate cancer who underwent stereotactic body radiation therapy (SBRT) between 2017 and 2021. Our analysis only included medical records of patients who had SBRT for oligometastatic prostate cancer and had pre and post-SBRT 68Ga PSMA PET/CT images. Patient-related (age), disease-related (Gleason score, location of metastases), and treatment-related (factors and outcomes) data were collected from the medical files.

RESULTS

A total of 17 patients (28 lesions) with a median age of 69 years were included in the research. A median follow-up of 16.6 months was used (range 6-36 months). The median follow-up period for 68 Ga PSMA PET/CT was 8 months (the range was 5-24 months). The median pre-treatment PSA level was 1.7 ng/mL (range 0.39-18.3 ng/mL) compared to the post-treatment PSA nadir of 0.05 ng/mL (0.02-4.57). During the follow-up period, local control was 96%, and there was a link between PSMA avidity on PET. In the treated lesions, there were no recurrences. During follow-up, none of the patients experienced toxicities of grade 3 or above.

CONCLUSIONS

SBRT is a highly successful and safe way of treating patients with oligometastatic prostate cancer. Additional research is needed to examine 68Ga PSMA PET/CT to assess further for demarcation and follow-up.

Adaptive Individualized high-dose preoperAtive (AIDA) chemoradiation in high-risk rectal cancer: a phase II trial

PURPOSE

To evaluate the pathological complete response (pCR) rate of locally advanced rectal cancer (LARC) after adaptive high-dose neoadjuvant chemoradiation (CRT) based on 18 F-fluorodeoxyglucose positron emission tomography/computed tomography (18 F-FDG-PET/CT).

METHODS

The primary endpoint was the pCR rate. Secondary endpoints were the predictive value of 18 F-FDG-PET/CT on pathological response and acute and late toxicity. All patients performed 18 F-FDG-PET/CT at baseline (PET0) and after 2 weeks during CRT (PET1). The metabolic PET parameters were calculated both at the PET0 and PET1. The total CRT dose was 45 Gy to the pelvic lymph nodes and 50 Gy to the primary tumor, corresponding mesorectum, and to metastatic lymph nodes. Furthermore, a sequential boost was delivered to a biological target volume defined by PET1 with an additional dose of 5 Gy in 2 fractions. Capecitabine (825 mg/m2 twice daily orally) was prescribed for the entire treatment duration.

RESULTS

Eighteen patients (13 males, 5 females; median age 55 years [range, 41-77 years]) were enrolled in the trial. Patients underwent surgical resection at 8-9 weeks after the end of neoadjuvant CRT. No patient showed grade > 1 acute radiation-induced toxicity. Seven patients (38.8%) had TRG = 0 (complete regression), 5 (27.0%) showed TRG = 2, and 6 (33.0%) had TRG = 3. Based on the TRG results, patients were classified in two groups: TRG = 0 (pCR) and TRG = 1, 2, 3 (non pCR). Accepting p < 0.05 as the level of significance, at the Kruskal-Wallis test, the medians of baseline-MTV, interim-SUVmax, interim-SUVmean, interim-MTV, interim-TLG, and the MTV reduction were significantly different between the two groups. 18 F-FDG-PET/CT was able to predict the pCR in 77.8% of cases through compared evaluation of both baseline PET/CT and interim PET/CT.

CONCLUSIONS

Our results showed that a dose escalation on a reduced target in the final phase of CRT is well tolerated and able to provide a high pCR rate.

Automated lung tumor delineation on positron emission tomography/computed tomography via a hybrid regional network

BACKGROUND

Multimodality positron emission tomography/computed tomography (PET/CT) imaging combines the anatomical information of CT with the functional information of PET. In the diagnosis and treatment of many cancers, such as non-small cell lung cancer (NSCLC), PET/CT imaging allows more accurate delineation of tumor or involved lymph nodes for radiation planning.

PURPOSE

In this paper, we propose a hybrid regional network method of automatically segmenting lung tumors from PET/CT images.

METHODS

The hybrid regional network architecture synthesizes the functional and anatomical information from the two image modalities, whereas the mask regional convolutional neural network (R-CNN) and scoring fine-tune the regional location and quality of the output segmentation. This model consists of five major subnetworks, that is, a dual feature representation network (DFRN), a regional proposal network (RPN), a specific tumor-wise R-CNN, a mask-Net, and a score head. Given a PET/CT image as inputs, the DFRN extracts feature maps from the PET and CT images. Then, the RPN and R-CNN work together to localize lung tumors and reduce the image size and feature map size by removing irrelevant regions. The mask-Net is used to segment tumor within a volume-of-interest (VOI) with a score head evaluating the segmentation performed by the mask-Net. Finally, the segmented tumor within the VOI was mapped back to the volumetric coordinate system based on the location information derived via the RPN and R-CNN. We trained, validated, and tested the proposed neural network using 100 PET/CT images of patients with NSCLC. A fivefold cross-validation study was performed. The segmentation was evaluated with two indicators: (1) multiple metrics, including the Dice similarity coefficient, Jacard, 95th percentile Hausdorff distance, mean surface distance (MSD), residual mean square distance, and center-of-mass distance; (2) Bland-Altman analysis and volumetric Pearson correlation analysis.

RESULTS

In fivefold cross-validation, this method achieved Dice and MSD of 0.84 ± 0.15 and 1.38 ± 2.2 mm, respectively. A new PET/CT can be segmented in 1 s by this model. External validation on The Cancer Imaging Archive dataset (63 PET/CT images) indicates that the proposed model has superior performance compared to other methods.

CONCLUSION

The proposed method shows great promise to automatically delineate NSCLC tumors on PET/CT images, thereby allowing for a more streamlined clinical workflow that is faster and reduces physician effort.

Respiratory gated multistatic PET reconstructions to delineate radiotherapy target volume in patients with mobile lung tumors

BACKGROUND

PET-CT with ¹⁸F-FDG or other radiopharmaceuticals is a recommended tool to help the delineation of lung cancers candidate to radiotherapy. The motion artifacts caused by respiratory movements are reduced by 4D acquisitions. We introduced an extended reconstruction algorithm (multiple reconstruct register and average [multi-RRA]) which requires much shorter acquisition times than standard 4D PET-CT. Our aim was to evaluate the interest on multi-RRA images as an alternative of 3D and 4D PET-CT for the delineation of lung lesion.

METHODS

PET acquisitions synchronized to the respiratory signal were obtained in 18 patients with mobile lung tumors. We compared the tumor volumes delineated on Multi-RRA images to 3D and 4D PET-CT, considering the 4D CT as a reference. The tumor volumes were delineated and compared with topologic similarity indexes (Dice, Jaccard and overlap).

RESULTS

Twenty tumors were delineated. The volumes delineated with multi-RRA and 4D PET were not significantly different (mean difference of 0.2±0.7 mL). Comparison by pairs (Tukey-Kramer test) showed that 3D-PET volumes were significantly smaller than 4D-PET and multi-RRA volumes (P<0.001). Topologic similarity indexes with 4D-PET were slightly statistically higher with multi-RRA than with 3D-PET (Dice and Jaccard) or 4D-CT (Dice, Jaccard and Overlap).

CONCLUSIONS

The tumor volumes delineated on multi-RRA are similar to the volumes obtained with 4D PET, with shorter acquisition time.

Prognostic Value of Interim 18F-DOPA and 18F-FDG PET/CT Findings in Stage 3-4 Pediatric Neuroblastoma

PURPOSE

This retrospective study aimed to determine the prognostic value of imaging parameters derived from midtherapy 18F-fluorodihydroxyphenylalanine (18F-DOPA) and 18F-FDG PET in pediatric patients with stage 3-4 neuroblastoma.

METHODS

We enrolled 32 stage 3-4 pediatric neuroblastoma patients who underwent 18F-DOPA and 18F-FDG PET/CT scans before and after 3 chemotherapy cycles. We measured metabolic and volumetric parameters and applied a metabolic burden scoring system to evaluate the primary tumor extent and soft tissue metastases and that of bone/bone marrow involvement. The associations between these parameters and clinical outcomes were investigated.

RESULTS

Over a median follow-up period of 47 months (range, 3-137 months), 16 patients experienced disease progression, and 13 died. After adjustment for clinical factors, multivariate Cox proportional hazard models showed that interim tumor FDG/FDOPA SUVmax (hazard ratio [HR], 5.94; 95% confidence interval [CI], 1.10-34.98) and interim FDOPA whole-body metabolic burden scores (WBMB) (HR, 7.30; 95% CI, 1.50-35.50) were significant prognostic factors for overall survival (OS). Only interim FDOPA WBMB scores (HR, 7.05; 95% CI, 1.02-48.7) were predictive of progression-free survival. Based on median cutoff values, prognosis (OS and progression-free survival) was significantly associated with an interim FDOPA WBMB score ≥21.92 (all P < 0.05) and interim tumor FDG/FDOPA (SUVmax) score ≥0.57 with poor OS (P < 0.05).

CONCLUSIONS

Our results indicate that midtreatment FDG and FDOPA PET/CT could serve as prognostic markers in stage 3-4 neuroblastoma patients.

Hypoxia and Its Influence on Radiotherapy Response of HPV-Positive and HPV-Negative Head and Neck Cancer

Head and neck squamous cancers are a heterogeneous group of cancers that arise from the upper aerodigestive tract. Etiologically, these tumors are linked to alcohol/tobacco abuse and infections with high-risk human papillomavirus (HPV). HPV-positive HNSCCs are characterized by a different biology and also demonstrate better therapy response and survival compared to alcohol/tobacco-related HNSCCs. Despite this advantageous therapy response and the clear biological differences, all locally advanced HNSCCs are treated with the same chemo-radiotherapy schedules. Although we have a better understanding of the biology of both groups of HNSCC, the biological factors associated with the increased radiotherapy response are still unclear. Hypoxia, i.e., low oxygen levels because of an imbalance between oxygen demand and supply, is an important biological factor associated with radiotherapy response and has been linked with HPV infections. In this review, we discuss the effects of hypoxia on radiotherapy response, on the tumor biology, and the tumor microenvironment of HPV-positive and HPV-negative HNSCCs by pointing out the differences between these two tumor types. In addition, we provide an overview of the current strategies to detect and target hypoxia.

PSMA PET/CT to evaluate response to SBRT for prostate cancer bone metastases

Background

In the current study we evaluated ⁶⁸Ga PSMA PET/ CT to measure local control of bone metastasis in oligometastatic prostate cancer patients treated with SBRT.

Materials and methods

After the institutional review board approval, a retrospective review of medical records of consecutive prostate cancer patients treated between 2014 and 2018 was conducted. Only medical records of patients that were treated with SBRT for bone metastasis and had pre-and post-SBRT ⁶⁸Ga PSMA PET/CT scans were included in our study. Data extracted from the medical files included patient-related (age), disease-related (Gleason score, site of metastasis), and treatment-related factors and outcomes.

Results

During the study period, a total of 12 patients (15 lesions) were included, with a median age of 73 years. The median follow-up was 26.5 months (range 13-45 months). Median time of ⁶⁸Ga PSMA PET/ CT follow up was 17.0 months (range 3-39 months). The median pre-treatment PSA was 2 ng/mL (range 0.56-44 ng/mL) vs. post treatment PSA nadir of 0.01 ng/mL (0.01-4.32) with a median time to nadir of 7 months (range, 2-12). Local control was 93% during the follow up period and there was correlation with PS MA avidity on PE T. None patients developed recurrences in the treated bone. None of the patients had grade 3 or more toxicities during follow-up.

Conclusions

SBRT is a highly effective and safe method for treatment of prostate cancer bone metastases. More studies are required to determine if SBRT provides greater clinical benefit than standard fractionation for oligometastatic prostate cancer patients. ⁶⁸Ga PSMA PET/CT should be further investigated for delineation and follow-up.

Deconvolution-based partial volume correction of PET images with parallel level set regularization

The partial volume effect (PVE), caused by the limited spatial resolution of positron emission tomography (PET), degrades images both qualitatively and quantitatively. Anatomical information provided by magnetic resonance (MR) images has the potential to play an important role in partial volume correction (PVC) methods. Post-reconstruction MR-guided PVC methods typically use segmented MR tissue maps, and further, assume that PET activity distribution is uniform in each region, imposing considerable constraints through anatomical guidance. In this work, we present a post-reconstruction PVC method based on deconvolution with parallel level set (PLS) regularization. We frame the problem as an iterative deconvolution task with PLS regularization that incorporates anatomical information without requiring MR segmentation or assuming uniformity of PET distributions within regions. An efficient algorithm for non-smooth optimization of the objective function (invoking split Bregman framework) is developed so that the proposed method can be feasibly applied to 3D images and produces sharper images compared to PLS method with smooth optimization. The proposed method was evaluated together with several other PVC methods using both realistic simulation experiments based on the BrainWeb phantom as well asin vivohuman data. Our proposed method showed enhanced quantitative performance when realistic MR guidance was provided. Further, the proposed method is able to reduce image noise while preserving structure details onin vivohuman data, and shows the potential to better differentiate amyloid positive and amyloid negative scans. Overall, our results demonstrate promise to provide superior performance in clinical imaging scenarios.

Radiomics in radiation oncology for gynecological malignancies: a review of literature

Radiomics is the extraction of a significant number of quantitative imaging features with the aim of detecting information in correlation with useful clinical outcomes. Features are extracted, after delineation of an area of interest, from a single or a combined set of imaging modalities (including X-ray, US, CT, PET/CT and MRI). Given the high dimensionality, the analytical process requires the use of artificial intelligence algorithms. Firstly developed for diagnostic performance in radiology, it has now been translated to radiation oncology mainly to predict tumor response and patient outcome but other applications have been developed such as dose painting, prediction of side-effects, and quality assurance. In gynecological cancers, most studies have focused on outcomes of cervical cancers after chemoradiation. This review highlights the role of this new tool for the radiation oncologists with particular focus on female GU oncology.

Diagnostic efficiency of hybrid imaging using PSMA ligands, PET/CT, PET/MRI and MRI in identifying malignant prostate lesions

OBJECTIVE

The objective of this study was to assess the accuracy of 68Ga-PSMA-11 PET/MRI, 18F-PSMA-1007 PET/CT, 68Ga-PSMA-11 PET/CT, and multiparametric (mp)MRI for the delineating of dominant intraprostatic lesions (IPL).

MATERIALS AND METHODS

35 patients with organ-confined prostate cancer who were assigned to definitive radiotherapy (RT) were divided into three groups based on imaging techniques: 68Ga-PSMA-PET/MRI (n = 9), 18F-PSMA-PET/CT (n = 16) and 68Ga-PSMA-PET/CT (n = 10). All patients without PSMA-PET/MRI received an additional mpMRI. PSMA-PET-based automatic isocontours and manual contours of the dominant IPLs were generated for each modality. The biopsy results were then used to validate whether any of the prostate biopsies were positive in the marked lesion using Dice similarity coefficient (DSC), Youden index (YI), sensitivity and specificity. Factors that can predict the accuracy of IPLs contouring were analysed.

RESULTS

Diagnostic performance was significantly superior both for manual and automatic IPLs contouring using 68Ga-PSMA-PET/MRI (DSC/YI SUV70%-0.62/0.51), 18F-PSMA-PET/CT (DSC/YI SUV70%-0.67/0.53) or 68Ga-PSMA-PET/CT (DSC/YI SUV70%-0.63/0.51) compared to mpMRI (DSC/YI-0.47/0.41; p < 0.001). The accuracy for delineating IPLs was not improved by combination of PET/CT and mpMRI images compared to PET/CT alone. Significantly superior diagnostic accuracy was found for large prostate lesions (at least 15% from the prostate volume) and higher Gleason score (at least 7b) comparing to smaller lesions with lower GS.

CONCLUSION

IPL localization was significantly improved when using PSMA-imaging procedures compared to mpMRI. No significant difference for delineating IPLs was found between hybrid method PSMA-PET/MRI and PSMA-PET/CT. PSMA-based imaging technique should be considered for the diagnostics of IPLs and focal treatment modality.

Motion-compensated FDG PET/CT for oesophageal cancer

PURPOSE

Respiratory-induced motion of oesophageal tumours and lymph nodes can influence positron-emission tomography/computed tomography (PET/CT). The aim was to compare standard three-dimensional (3D) and motion-compensated PET/CT regarding standardized uptake value (SUV), metabolic tumour volume (MTV) and detection of lymph node metastases.

METHODS

This prospective observational study (NCT02424864) included 37 newly diagnosed oesophageal cancer patients. Diagnostic PET/CT was reconstructed in 3D and motion-compensated PET/CT. MTVs of the primary tumour were calculated using an automated region-growing algorithm with SUV thresholds of 2.5 (MTV2.5) and ≥ 50% of SUVmax (MTV50%). Blinded for reconstruction method, a nuclear medicine physician assessed all lymph nodes showing ¹⁸F‑fluorodeoxyglucose uptake for their degree of suspicion.

RESULTS

The mean (95% CI) SUVmax of the primary tumour was 13.1 (10.6-15.5) versus 13.0 (10.4-15.6) for 3D and motion-compensated PET/CT, respectively. MTVs were also similar between the two techniques. Bland-Altman analysis showed mean differences between both measurements (95% limits of agreement) of 0.08 (-3.60-3.75), -0.26 (-2.34-1.82), 4.66 (-29.61-38.92) cm³ and -0.95 (-19.9-18.0) cm³ for tumour SUVmax, lymph node SUVmax, MTV2.5 and MTV50%, respectively. Lymph nodes were classified as highly suspicious (30/34 nodes), suspicious (20/22) and dubious (66/59) for metastases on 3D/motion-compensated PET/CT. No additional lymph node metastases were found on motion-compensated PET/CT. SUVmax of the most intense lymph nodes was similar for both scans: mean (95% CI) 6.6 (4.3-8.8) and 6.8 (4.5-9.1) for 3D and motion-compensated, respectively.

CONCLUSION

SUVmax of the primary oesophageal tumour and lymph nodes was comparable on 3D and motion-compensated PET/CT. The use of motion-compensated PET/CT did not improve lymph node detection.

Positron emission tomography for radiotherapy planning in head and neck cancer: What impact?

PET-computed tomography (CT) plays a growing role to guide target volume delineation for head and neck cancer in radiation oncology. Pretherapeutic [18F]FDG PET-CT adds information to morphological imaging. First, as a whole-body imaging modality, it reveals regional or distant metastases that induce major therapeutic changes in more than 10% of the cases. Moreover, it allows better pathological lymph node selection which improves overall regional control and overall survival. Second, locally, it allows us to define the metabolic tumoral volume, which is a reliable prognostic feature for survival outcome. [18F]FDG PET-CT-based gross tumor volume (GTV) is on average significantly smaller than GTV based on CT. Nevertheless, the overlap is incomplete and more evaluation of composite GTV based on PET and GTV based on CT are needed. However, in clinical practice, the study showed that using GTV PET alone for treatment planning was similar to using GTVCT for local control and dose distribution was better as a dose to organs at risk significantly decreased. In addition to FDG, pretherapeutic PET could give access to different biological tumoral volumes - thanks to different tracers - guiding heterogeneous dose delivery (dose painting concept) to resistant subvolumes. During radiotherapy treatment, follow-up [18F]FDG PET-CT revealed an earlier and more important diminution of GTV than other imaging modality. It may be a valuable support for adaptative radiotherapy as a new treatment plan with a significant impact on dose distribution became possible. Finally, additional studies are required to prospectively validate long-term outcomes and lower toxicity resulting from the use of PET-CT in treatment planning.

Intensity threshold based solid tumour segmentation method for Positron Emission Tomography (PET) images: A review

Accurate, robust and reproducible delineation of tumour in Positron Emission Tomography (PET) is essential for diagnosis, treatment planning and response assessment. Since standardized uptake value (SUV) – a normalized semiquantitative parameter used in PET is represented by the intensity of the PET images and related to the radiotracer uptake, a SUV based threshold method is a natural choice to delineate the tumour. However, determination of an optimum threshold value is a challenging task due to low spatial resolution, and signal-to-noise ratio (SNR) along with finite image sampling constraint. The aim of the review is to summarize different fixed and adaptive threshold-based PET image segmentation approaches under a common mathematical framework Advantages and disadvantages of different threshold based methods are also highlighted from the perspectives of diagnosis, treatment planning and response assessment. Several fixed threshold values (30%–70% of the maximum SUV of the tumour (SUV_maxT)) have been investigated. It has been reported that the fixed threshold-based method is very much dependent on the SNR, tumour to background ratio (TBR) and the size of the tumour. Adaptive threshold-based method, an alternative to fixed threshold, can minimize these dependencies by accounting for tumour to background ratio (TBR) and tumour size. However, the parameters for the adaptive methods need to be calibrated for each PET camera system (e.g., scanner geometry, image acquisition protocol, reconstruction algorithm etc.) and it is not straight forward to implement the same procedure to other PET systems to obtain similar results. It has been reported that the performance of the adaptive methods is also not optimum for smaller volumes with lower TBR and SNR. Statistical analysis carried out on the NEMA thorax phantom images also indicates that regions segmented by the fixed threshold method are significantly different for all cases. On the other hand, the adaptive method provides significantly different segmented regions only for low TBR with different SNR. From this viewpoint, a robust threshold based segmentation method that will be less sensitive to SUVmaxT, SNR, TBR and volume needs to be developed. It was really challenging to compare the performance of different threshold-based methods because the performance of each method was tested on dissimilar data set with different data acquisition and reconstruction protocols along with different TBR, SNR and volumes. To avoid such difficulties, it will be desirable to have a common database of clinical PET images acquired with different image acquisition protocols and different PET cameras to compare the performance of automatic segmentation methods. It is also suggested to report the changes in SNR and TBR while reporting the response using threshold based methods.

Radiodynamic therapy using 15-MV radiation combined with 5-aminolevulinic acid and carbamide peroxide for prostate cancer in vivo

Photodynamic therapy has been clinically proven to be effective, but its effect is limited to relatively shallow tumors because of its use of visible light. Radiodynamic therapy (RDT) has therefore been investigated as a means to treat deep-seated tumors. In this study, the treatment effect of a novel form of RDT consisting of radiation combined with 5-aminolevulinic acid (5-ALA) and carbamide peroxide was investigated using a mouse model. Male nude mice were injected bilaterally and subcutaneously with human prostate cancer (PC-3) cells and randomized into 8 treatment groups, consisting of various combinations of 15-MV radiotherapy (RT), 5-ALA, and carbamide peroxide. The treatment effect of a single fraction of treatment was measured by calculating tumor growth delay, monitored using weekly MR scans. The ability of the drugs to be delivered to the tumors was qualitatively measured using ¹⁸ F-FDG PET/CT scans. RDT was shown to significantly delay the tumor growth for the mouse model and tumor cell line investigated in this work. Tumors treated with RDT showed a decrease in tumor growth of 24 ± 9% and 21 ± 8% at one and two weeks post-treatment, respectively. Peroxide and 5-ALA did not contribute significantly to tumor growth delay when administered alone or separately with RT. Blood perfusion was shown to be able to deliver agents to the tumors investigated in this work, although uptake of ¹⁸ F-FDG was shown to be non-uniform.

Prognostic Impact of Pretherapeutic FDG-PET in Localized Anal Cancer

Due to the heterogeneity of tumour mass segmentation methods and lack of consensus, our study evaluated the prognostic value of pretherapeutic positron emission tomography with fluorodeoxyglucose (FDG-PET) metabolic parameters using different segmentation methods in patients with localized anal squamous cell carcinoma (SCC). Eighty-one patients with FDG-PET before radiochemotherapy were retrospectively analyzed. Semiquantitative data were measured with three fixed thresholds (35%, 41% and 50% of Maximum Standardized Uptake Value (SUVmax)) and four segmentation methods based on iterative approaches (Black, Adaptive, Nestle and Fitting). Metabolic volumes of primary anal tumour (P-MTV) and total tumour load (T-MTV: P-MTV+ lymph node MTV) were calculated. The primary endpoint was event-free survival (EFS). Seven multivariate models were created to compare FDG-PET tumour volumes prognostic impact. For all segmentation thresholds, PET metabolic volume parameters were independent prognostic factor and T-MTV variable was consistently better associated with EFS than P-MTV. Patient's sex was an independent variable and significantly correlated with EFS. With fixed threshold segmentation methods, 35% of SUVmax threshold seemed better correlated with EFS and the best cut-off for discrimination between a low and high risk of event occurrence was 40 cm3. Determination of T-MTV by FDG-PET using fixed threshold segmentation is useful for predicting EFS for primary anal SCC. If these data are confirmed in larger studies, FDG-PET could contribute to individualized patient therapies.

PET/CT in radiation oncology

The progressive integration of positron emission tomography/computed tomography (PET/CT) imaging in radiation therapy has its rationale in the biological intertumoral and intratumoral heterogeneity of malignant lesions that require the individual adjustment of radiation dose to obtain an effective local tumor control in cancer patients. PET/CT provides information on the biological features of tumor lesions such as metabolism, hypoxia, and proliferation that can identify radioresistant regions and be exploited to optimize treatment plans. Here, we provide an overview of the basic principles of PET-based target volume selection and definition using ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) and then we focus on the emerging strategies of dose painting and adaptive radiotherapy using different tracers. Previous studies provided consistent evidence that integration of ¹⁸F-FDG PET/CT in radiotherapy planning improves delineation of target volumes and reduces the uncertainties and variabilities of anatomical delineation of tumor sites. PET-based dose painting and adaptive radiotherapy are feasible strategies although their clinical implementation is highly demanding and requires strong technical, computational, and logistic efforts. Further prospective clinical trials evaluating local tumor control, survival, and toxicity of these emerging strategies will promote the full integration of PET/CT in radiation oncology.

Potential Prognostic Role of 18F-FDG PET/CT in Invasive Epithelial Ovarian Cancer Relapse. A Preliminary Study

Epithelial ovarian cancer (EOC) is the most lethal gynecological malignancy, with relapse occurring in about 70% of advanced cases with poor prognosis. Fluorine-18-2-fluoro-2-deoxy-d-glucose PET/CT (¹⁸F-FDGPET/CT) is the most specific radiological imaging used to assess recurrence. Some intensity-based and volume-based PET parameters, maximum standardized uptake values (SUV_max), metabolic tumor volume (MTV) and total lesion glycolysis (TLG), are indicated to have a correlation with treatment response. The aim of our study is to correlate these parameters with post relapse survival (PRS) and overall survival (OS) in Epithelial Ovarian Cancer (EOC) relapse. The study included 50 patients affected by EOC relapse who underwent ¹⁸F-FDGPET/CT before surgery. All imaging was reviewed and SUV_max, MTV and TLG were calculated and correlated to PRS and OS. PRS and OS were obtained from the first relapse and from the first diagnosis to the last follow up or death, respectively. SUV_max, MTV and TLG were tested in a univariate logistic regression analysis, only SUV_max demonstrated to be significantly associated to PRS and OS (p = 0.005 and p = 0.024 respectively). Multivariate analysis confirmed the results. We found a cut-off of SUV_max of 13 that defined worse or better survival (p = 0.003). In the first relapse of EOC, SUV_max is correlated to PRS and OS, and when SUV_max is greater than 13, it is an unfavorable prognostic factor.

The physics of radioembolization

Radioembolization is an established treatment for chemoresistant and unresectable liver cancers. Currently, treatment planning is often based on semi-empirical methods, which yield acceptable toxicity profiles and have enabled the large-scale application in a palliative setting. However, recently, five large randomized controlled trials using resin microspheres failed to demonstrate a significant improvement in either progression-free survival or overall survival in both hepatocellular carcinoma and metastatic colorectal cancer. One reason for this might be that the activity prescription methods used in these studies are suboptimal for many patients.In this review, the current dosimetric methods and their caveats are evaluated. Furthermore, the current state-of-the-art of image-guided dosimetry and advanced radiobiological modeling is reviewed from a physics' perspective. The current literature is explored for the observation of robust dose-response relationships followed by an overview of recent advancements in quantitative image reconstruction in relation to image-guided dosimetry.This review is concluded with a discussion on areas where further research is necessary in order to arrive at a personalized treatment method that provides optimal tumor control and is clinically feasible.

Prognostic value of posttreatment 18F-FDG PET/CT and predictors of metabolic response to therapy in patients with locally advanced cervical cancer treated with concomitant chemoradiation therapy: an analysis of intensity- and volume-based PET parameters

PURPOSE

To investigate the prognostic value of posttreatment 18F-FDG PET/CT in patients with locally advanced cervical cancer (LACC) treated with concomitant chemoradiation therapy (CCRT). The secondary aim was to assess the possible role of intensity-based and volume-based PET parameters including SUVmax, SUVmean, MTV and TLG, and clinical parameters including age, pathology, FIGO stage and nodal involvement as factors predicting response to treatment.

METHODS

This retrospective study included 82 patients affected by LACC treated with CCRT. All patients underwent 18F-FDG PET/CT both before and after treatment. The posttreatment PET/CT scans were used to classify patients as complete metabolic responders (CMR) or non-complete metabolic responders (N-CMR) according to the EORTC criteria. Kaplan-Meier analysis was used to evaluate differences in overall survival (OS) between the CMR and N-CMR groups. Student's t test, Pearson's chi-squared test and logistic regression were used to investigate the possible value of PET and clinical parameters as predictors of metabolic response to therapy.

RESULTS

Kaplan-Meier analysis showed a highly significant difference in OS between the CMR and N-CMR groups (log-rank test p < 0.0001). Significant independent predictors of response to therapy were MTV (p = 0.019, odds ratio = 1.015, 95% CI = 1.002-1.028, Nagelkerke R2 = 0.110), TLG (p = 0.045, odds ratio = 1.001, 95% CI = 1.000-1.002, Nagelkerke R2 = 0.081) and nodal involvement (p = 0.088, odds ratio = 2.361, 95% CI = 0.879-6.343, Nagelkerke R2 = 0.051).

CONCLUSION

18F-FDG PET/CT-based response assessment using the EORTC criteria reliably predicts OS in LACC patients treated with CCRT. In our cohort of patients, pretreatment MTV and TLG and nodal involvement were predictors of response to therapy. MTV was the best predictor of response. However, its additional risk value seems to be low (MTV odds ratio = 1.015).

Gross tumour delineation on computed tomography and positron emission tomography-computed tomography in oesophageal cancer: A nationwide study

•

Interobserver variability in delineation of the oesophageal GTV can be considerable.

•

Delineation variation is mainly located at the cranial and caudal border.

•

PET significantly influences the delineated GTV in oesophageal cancer.

•

The impact of PET to CT on observer variation of the GTV is limited.

•

Accurate GTV delineation is essential for results of radiation boost-strategies.

Background and purpose

Accurate delineation of the primary tumour is vital to the success of radiotherapy and even more important for successful boost strategies, aiming for improved local control in oesophageal cancer patients. Therefore, the aim was to assess delineation variability of the gross tumour volume (GTV) between CT and combined PET-CT in oesophageal cancer patients in a multi-institutional study.

Materials and methods

Twenty observers from 14 institutes delineated the primary tumour of 6 cases on CT and PET-CT fusion. The delineated volumes, generalized conformity index (CIgen) and standard deviation (SD) in position of the most cranial/caudal slice over the observers were evaluated. For the central delineated region, perpendicular distance between median surface GTV and each individual GTV was evaluated as in-slice SD.

Results

After addition of PET, mean GTVs were significantly smaller in 3 cases and larger in 1 case. No difference in CIgen was observed (average 0.67 on CT, 0.69 on PET-CT). On CT cranial-caudal delineation variation ranged between 0.2 and 1.5 cm SD versus 0.2 and 1.3 cm SD on PET-CT. After addition of PET, the cranial and caudal variation was significantly reduced in 1 and 2 cases, respectively. The in-slice SD was on average 0.16 cm in both phases.

Conclusion

In some cases considerable GTV delineation variability was observed at the cranial-caudal border. PET significantly influenced the delineated volume in four out of six cases, however its impact on observer variation was limited.

Lesion segmentation for MR spectroscopic imaging using the convolution difference method

PURPOSE

Delineation of lesion boundaries from volumetric MRSI metabolite ratio maps using a method that accounts for the spatial response function of the acquisition and variable spectral quality and is robust to signal heterogeneity within the lesion.

METHODS

A novel method for lesion segmentation, termed convolution difference, has been developed that is robust to signal heterogeneity within the lesion and to differences in the spatial response function. Procedures are described for processing metabolite ratio maps and to exclude regions of inadequate spectral quality. This method was evaluated using computer simulations, and the results were compared with an iterative thresholding technique that determines an optimal amplitude threshold, and with the use of a fixed amplitude threshold. These methods were evaluated for segmentation of volumetric MRSI studies of gliomas using maps of the choline to N-acetylaspartate ratio, and a qualitative comparison of lesion volumes carried out.

RESULTS

Simulation studies indicated improved performance for the convolution difference method when applied to ratio maps. Variations in tumor volume were observed for the in vivo studies between the convolution difference and the iterative thresholding methods; however, visual analysis indicates that both showed improved accuracy in comparison to using a fixed amplitude threshold.

CONCLUSION

This study reinforces previous reports indicating that the use of fixed threshold values for segmentation of maps with broad spatial response functions can result in errors in lesion volume definition. A novel segmentation method, termed the convolution difference, has been introduced and demonstrated to be robust for segmentation of volumetric MRSI metabolite data.

Impact of image reconstruction methods on quantitative accuracy and variability of FDG-PET volumetric and textural measures in solid tumors

OBJECTIVE

This study aims to assess the impact of different image reconstruction methods on PET/CT quantitative volumetric and textural parameters and the inter-reconstruction variability of these measurements.

METHODS

A total of 25 oncology patients with 65 lesions (between 2017 and 2018) and a phantom with signal-to-background ratios (SBR) of 2 and 4 were included. All images were retrospectively reconstructed using OSEM, PSF only, TOF only, and TOFPSF with 3-, 5-, and 6.4-mm Gaussian filters. The metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were measured. The relative percent error (ΔMTV and ΔTLG) with respect to true values, volume recovery coefficients, and Dice similarity coefficient, as well as inter-reconstruction variabilities were quantified and assessed. In clinical scans, textural features (coefficient of variation, skewness, and kurtosis) were determined.

RESULTS

Among reconstruction methods, mean ΔMTV differed by -163.5 ± 14.1% to 6.3 ± 6.2% at SBR2 and -42.7 ± 36.7% to 8.6 ± 3.1 at SBR4. Dice similarity coefficient significantly increased by increasing SBR from 2 to 4, ranging from 25.7 to 83.4% between reconstruction methods. Mean ΔTLG was -12.0 ± 1.7 for diameters > 17 mm and -17.8 ± 7.8 for diameters ≤ 17 mm at SBR4. It was -31.7 ± 4.3 for diameters > 17 mm and -14.2 ± 5.8 for diameters ≤ 17 mm at SBR2. Textural features were prone to variations by reconstruction methods (p < 0.05).

CONCLUSIONS

Inter-reconstruction variability was significantly affected by the target size, SBR, and cut-off threshold value. In small tumors, inter-reconstruction variability was noteworthy, and quantitative parameters were strongly affected. TOFPSF reconstruction with small filter size produced greater improvements in performance and accuracy in quantitative PET/CT imaging.

KEY POINTS

• Quantitative volumetric PET evaluation is critical for the analysis of tumors. • However, volumetric and textural evaluation is prone to important variations according to different image reconstruction settings. • TOFPSF reconstruction with small filter size improves quantitative analysis.

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

Background

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

Methods

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

Results

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

Conclusions

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

A smart and operator independent system to delineate tumours in Positron Emission Tomography scans

Positron Emission Tomography (PET) imaging has an enormous potential to improve radiation therapy treatment planning offering complementary functional information with respect to other anatomical imaging approaches. The aim of this study is to develop an operator independent, reliable, and clinically feasible system for biological tumour volume delineation from PET images. Under this design hypothesis, we combine several known approaches in an original way to deploy a system with a high level of automation. The proposed system automatically identifies the optimal region of interest around the tumour and performs a slice-by-slice marching local active contour segmentation. It automatically stops when a "cancer-free" slice is identified. User intervention is limited at drawing an initial rough contour around the cancer region. By design, the algorithm performs the segmentation minimizing any dependence from the initial input, so that the final result is extremely repeatable. To assess the performances under different conditions, our system is evaluated on a dataset comprising five synthetic experiments and fifty oncological lesions located in different anatomical regions (i.e. lung, head and neck, and brain) using PET studies with 18F-fluoro-2-deoxy-d-glucose and 11C-labeled Methionine radio-tracers. Results on synthetic lesions demonstrate enhanced performances when compared against the most common PET segmentation methods. In clinical cases, the proposed system produces accurate segmentations (average dice similarity coefficient: 85.36 ± 2.94%, 85.98 ± 3.40%, 88.02 ± 2.75% in the lung, head and neck, and brain district, respectively) with high agreement with the gold standard (determination coefficient R² = 0.98). We believe that the proposed system could be efficiently used in the everyday clinical routine as a medical decision tool, and to provide the clinicians with additional information, derived from PET, which can be of use in radiation therapy, treatment, and planning.

Assessment of image quality of a radiotherapy-specific hardware solution for PET/MRI in head and neck cancer patients

BACKGROUND AND PURPOSE

Functional PET/MRI has great potential to improve radiotherapy planning (RTP). However, data integration requires imaging with radiotherapy-specific patient positioning. Here, we investigated the feasibility and image quality of radiotherapy-customized PET/MRI in head-and-neck cancer (HNC) patients using a dedicated hardware setup.

MATERIAL AND METHODS

Ten HNC patients were examined with simultaneous PET/MRI before treatment, with radiotherapy and diagnostic scan setup, respectively. We tested feasibility of radiotherapy-specific patient positioning and compared the image quality between both setups by pairwise image analysis of 18F-FDG-PET, T1/T2-weighted and diffusion-weighted MRI. For image quality assessment, similarity measures including average symmetric surface distance (ASSD) of PET and MR-based tumor contours, MR signal-to-noise ratio (SNR) and mean apparent diffusion coefficient (ADC) value were used.

RESULTS

PET/MRI in radiotherapy position was feasible - all patients were successfully examined. ASSD (median/range) of PET and MR contours was 0.6 (0.4-1.2) and 0.9 (0.5-1.3) mm, respectively. For T2-weighted MRI, a reduced SNR of -26.2% (-39.0--11.7) was observed with radiotherapy setup. No significant difference in mean ADC was found.

CONCLUSIONS

Simultaneous PET/MRI in HNC patients using radiotherapy positioning aids is clinically feasible. Though SNR was reduced, the image quality obtained with a radiotherapy setup meets RTP requirements and the data can thus be used for personalized RTP.

Molecular Imaging-Guided Radiotherapy for the Treatment of Head-and-Neck Squamous Cell Carcinoma: Does it Fulfill the Promises?

With the routine use of intensity modulated radiation therapy for the treatment of head-and-neck squamous cell carcinoma allowing highly conformed dose distribution, there is an increasing need for refining both the selection and the delineation of gross tumor volumes (GTV). In this framework, molecular imaging with positron emission tomography and magnetic resonance imaging offers the opportunity to improve diagnostic accuracy and to integrate tumor biology mainly related to the assessment of tumor cell density, tumor hypoxia, and tumor proliferation into the treatment planning equation. Such integration, however, requires a deep comprehension of the technical and methodological issues related to image acquisition, reconstruction, and segmentation. Until now, molecular imaging has had a limited value for the selection of nodal GTV, but there are increasing evidences that both FDG positron emission tomography and diffusion-weighted magnetic resonance imaging has a potential value for the delineation of the primary tumor GTV, effecting on dose distribution. With the apprehension of the heterogeneity in tumor biology through molecular imaging, growing evidences have been collected over the years to support the concept of dose escalation/dose redistribution using a planned heterogeneous dose prescription, the so-called "dose painting" approach. Validation trials are ongoing, and in the coming years, one may expect to position the dose painting approach in the armamentarium for the treatment of patients with head-and-neck squamous cell carcinoma.

Population Pharmacokinetics of Tracers: A New Tool for Medical Imaging?

Positron emission tomography-computed tomography is a medical imaging method measuring the activity of a radiotracer chosen to accumulate in cancer cells. A recent trend of medical imaging analysis is to account for the radiotracer's pharmacokinetic properties at a voxel (three-dimensional-pixel) level to separate the different tissues. These analyses are closely linked to population pharmacokinetic-pharmacodynamic modelling. Kineticists possess the cultural background to improve medical imaging analysis. This article stresses the common points with population pharmacokinetics and highlights the methodological locks that need to be lifted.

Prognostic value of metabolic indices and bone marrow uptake pattern on preoperative 18F-FDG PET/CT in pediatric patients with neuroblastoma

PURPOSE

To evaluate the prognostic value of metabolic parameters and bone marrow uptake (BMU) patterns on pretherapeutic 18-F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) in pediatric patients with neuroblastoma (NB).

PATIENTS AND METHODS

Forty-seven pediatric patients with newly diagnosed neuroblastoma who underwent 18F-FDG PET/CT were retrospectively reviewed. Clinicopathological factors and metabolic parameters including maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), total lesion glycolysis (TLG) and bone marrow uptake patterns on PET/CT were compared to predict recurrence-free survival (RFS) and overall survival (OS) by univariate and multivariate analysis.

RESULTS

During the follow-up period, 27 (57.4%) patients experienced recurrence. MTV (P = 0.001), TLG (P = 0.004) and BMU patterns (P = 0.025) remained significant predictive factors for tumor recurrence, along with tumor size, histology, stage, lactate dehydrogenase (LDH) and other distant metastasis (except bone metastasis). Univariate analysis showed that histology, stage, tumor size (>37.25 cm), other distant metastasis, MTV (>88.10cm³) and TLG (>1045.2 g) and BMU patterns correlated with both RFS and OS (P < 0.05). On multivariate analysis, TLG remained the only independent prognostic factor for RFS (P = 0.016) and OS (P = 0.012), and BMU patterns and MTV were statistically significant for OS (P = 0.024 and P = 0.038, respectively).

CONCLUSION

Pretherapeutic 18F-FDG PET/CT can provide reliable prognostic information for neuroblastoma pediatric patients, and patients with high MTV, TLG and focal bone marrow (unifocal and multifocal) uptake on PET/CT may have inferior outcomes during subsequent treatment.

Respiratory-gated (4D) contrast-enhanced FDG PET-CT for radiotherapy planning of lower oesophageal carcinoma: feasibility and impact on planning target volume

BACKGROUND

To assess the feasibility and potential impact on target delineation of respiratory-gated (4D) contrast-enhanced ¹⁸Fluorine fluorodeoxyglucose (FDG) positron emission tomography - computed tomography (PET-CT), in the treatment planning position, for a prospective cohort of patients with lower third oesophageal cancer.

METHODS

Fifteen patients were recruited into the study. Imaging included 4D PET-CT, 3D PET-CT, endoscopic ultrasound and planning 4D CT. Target volume delineation was performed on 4D CT, 4D CT with co-registered 3D PET and 4D PET-CT. Planning target volumes (PTV) generated with 4D CT (PTV_4DCT), 4D CT co-registered with 3D PET-CT (PTV_3DPET4DCT) and 4D PET-CT (PTV_4DPETCT) were compared with multiple positional metrics.

RESULTS

Mean PTV_4DCT, PTV_3DPET4DCT and PTV_4DPETCT were 582.4 ± 275.1 cm³, 472.5 ± 193.1 cm³ and 480.6 ± 236.9 cm³ respectively (no significant difference). Median DICE similarity coefficients comparing PTV_4DCT with PTV_3DPET4DCT, PTV_4DCT with PTV_4DPETCT and PTV_3DPET4DCT with PTV_4DPETCT were 0.85 (range 0.65-0.9), 0.85 (range 0.69-0.9) and 0.88 (range 0.79-0.9) respectively. The median sensitivity index for overlap comparing PTV_4DCT with PTV_3DPET4DCT, PTV_4DCT with PTV_4DPETCT and PTV_3DPET4DCT with PTV_4DPETCT were 0.78 (range 0.65-0.9), 0.79 (range 0.65-0.9) and 0.89 (range 0.68-0.94) respectively.

CONCLUSIONS

Planning 4D PET-CT is feasible with careful patient selection. PTV generated using 4D CT, 3D PET-CT and 4D PET-CT were of similar volume, however, overlap analysis demonstrated that approximately 20% of PTV_3DPETCT and PTV_4DPETCT are not included in PTV_4DCT, leading to under-coverage of target volume and a potential geometric miss. Additionally, differences between PTV_3DPET4DCT and PTV_4DPETCT suggest a potential benefit for 4D PET-CT.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier - NCT02285660 (Registered 21/10/2014).

Comparison of dose distribution for head and neck cancer patients with and without dose painting escalation during radiotherapy realized with tomotherapy unit

OBJECTIVE

To determine and quantify the percentage dose increase to organs at risk (OARs) with multiple-level dose painting (DP) for patients with head and neck cancer in comparison with standard regimen.

METHODS

12 patients who had undergone fluorine-18 fludeoxyglucose (¹⁸F-FDG) positron emission tomography (PET)/CT scan were retrospectively enrolled. Two treatment plans-one using DP escalation and one without-were optimized for each patient base on PET/CT data. The following variables were assessed: dose to OARs and target volumes; execution time; equivalent uniform dose; and normal tissue complication probability.

RESULTS

No statistically significant differences in beam-on time were observed between plans with and without DP. However, significantly higher doses were observed for all DP-escalated plans in the OARs, with only two exceptions: the brain stem and V_60Gy for the mandible. Multiple-level DP resulted in dose increases ranging from 3.0% to 12.9%, depending on the OAR. The largest increase was seen for the parotid glands and the smallest for the mandible. Significant differences in the equivalent uniform dose were observed only for the parotid glands and spinal column, where the dose without DP was lower. The normal tissue complication probability for most OARs was very small.

CONCLUSION

Importantly, even though DP escalation resulted in higher doses to OARs vs conventional treatment planning, these usually did not exceed the dose tolerance levels. However, clinical trials are necessary to confirm the benefits of DP and to guarantee no additional toxicity. Advances in knowledge: Multiple-level DP by numbers resulted in 3.0-12.9% dose increase, depending on the OAR. Our findings may suggest that DP escalation to very high doses is feasible for about 83% of patients without higher toxicity; however, it still should be confirmed on a larger group of patients.

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

PURPOSE

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

APPROACH

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

FINDINGS

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

CONCLUSIONS

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

Effect of different segmentation algorithms on metabolic tumor volume measured on 18F-FDG PET/CT of cervical primary squamous cell carcinoma

Background and purpose

It is known that fluorine-18 fluorodeoxyglucose PET/computed tomography (CT) segmentation algorithms have an impact on the metabolic tumor volume (MTV). This leads to some uncertainties in PET/CT guidance of tumor radiotherapy. The aim of this study was to investigate the effect of segmentation algorithms on the PET/CT-based MTV and their correlations with the gross tumor volumes (GTVs) of cervical primary squamous cell carcinoma.

Materials and methods

Fifty-five patients with International Federation of Gynecology and Obstetrics stage Ia∼IIb and histologically proven cervical squamous cell carcinoma were enrolled. A fluorine-18 fluorodeoxyglucose PET/CT scan was performed before definitive surgery. GTV was measured on surgical specimens. MTVs were estimated on PET/CT scans using different segmentation algorithms, including a fixed percentage of the maximum standardized uptake value (20∼60% SUV_max) threshold and iterative adaptive algorithm. We divided all patients into four different groups according to the SUV_max within target volume. The comparisons of absolute values and percentage differences between MTVs by segmentation and GTV were performed in different SUV_max subgroups. The optimal threshold percentage was determined from MTV_20%∼MTV_60%, and was correlated with SUV_max. The correlation of MTV_{iterative adaptive} with GTV was also investigated.

Results

MTV_50% and MTV_60% were similar to GTV in the SUV_max up to 5 (P>0.05). MTV_30%∼MTV_60% were similar to GTV (P>0.05) in the 5<SUV_max≤10 group. MTV_20%∼MTV_60% were similar to GTV (P>0.05) in the 10<SUV_max≤15 group. MTV_20% and MTV_30% were similar to GTV (P>0.05) in the SUV_max of at least 15 group. MTV_{iterative adaptive} was similar to GTV in both total and different SUV_max groups (P>0.05). Significant differences were observed among the fixed percentage method and the optimal threshold percentage was inversely correlated with SUV_max. The iterative adaptive segmentation algorithm led to the highest accuracy (6.66±50.83%). A significantly positive correlation was also observed between MTV_{iterative adaptive} and GTV (Pearson’s correlation r=0.87, P<0.0001).

Conclusion

MTV_{iterative adaptive} is independent of SUV_max, more accurate, and correlated with GTV. Iterative adaptive algorithm segmentation may be more suitable than the fixed percentage threshold method to estimate the tumor volume of cervical primary squamous cell carcinoma.

Risk Stratification of Pediatric Patients With Neuroblastoma Using Volumetric Parameters of 18F-FDG and 18F-DOPA PET/CT

PURPOSE

This study determined the prognostic value of volumetric parameters derived from pretreatment F-FDG and F-DOPA PET/CT of neuroblastoma and their correlation with clinical and histopathologic features.

PATIENTS AND METHODS

A total of 25 children with neuroblastoma underwent pretreatment F-FDG and F-DOPA PET/CT within 4 weeks. The SUVmax of primary tumors on F-FDG and F-DOPA PET were recorded as SUVFDG and SUVDOPA, respectively. For volumetric parameters of primary tumors, 40% of SUVmax was used to generate volume of interest. If the 40% of SUVmax was below 2.5, an SUV threshold of 2.5 was used instead. Metabolic tumor volume (MTV), total lesion glycolysis (TLG), dopaminergic tumor volume (DTV), and total lesion F-DOPA activity (TLDA) were recorded as F-FDG and F-DOPA volumetric parameters. All indices were compared between groups distinguished by survival status and clinical features, including bone marrow involvement, lymph node metastasis, amplification of the MYCN oncogene, invasive features on anatomic images, and risk categories. The Kaplan-Meier method and log-rank test were used to compare the survival curves between groups.

RESULTS

The median follow-up period was 28.2 months. Nonsurvivors (20%) tended to have lower SUVDOPA, DTV, and TLDA (P ≤ 0.05), and higher SUVFDG, MTV, and TLG (all P < 0.05). Lower F-DOPA uptake is associated with bone marrow and lymph node metastases (all P < 0.05). Higher F-FDG uptake is associated with MYCN amplification (all P < 0.05) and anatomic invasive features of tumors such as vascular encasement or adjacent organ invasion (TLG, P = 0.05). Only volumetric indices (DTV, TLDA, MTV, and TLG) significantly differed among risk groups (all P < 0.05).

CONCLUSIONS

Pretherapeutic F-DOPA and F-FDG PET provided complementary information, and both can be served for risk stratification. Volumetric indices of F-DOPA and F-FDG PET correlate more highly with risk grouping.

Background based Gaussian mixture model lesion segmentation in PET

PURPOSE

Quantitative (18)F-fluorodeoxyglucose positron emission tomography is limited by the uncertainty in lesion delineation due to poor SNR, low resolution, and partial volume effects, subsequently impacting oncological assessment, treatment planning, and follow-up. The present work develops and validates a segmentation algorithm based on statistical clustering. The introduction of constraints based on background features and contiguity priors is expected to improve robustness vs clinical image characteristics such as lesion dimension, noise, and contrast level.

METHODS

An eight-class Gaussian mixture model (GMM) clustering algorithm was modified by constraining the mean and variance parameters of four background classes according to the previous analysis of a lesion-free background volume of interest (background modeling). Hence, expectation maximization operated only on the four classes dedicated to lesion detection. To favor the segmentation of connected objects, a further variant was introduced by inserting priors relevant to the classification of neighbors. The algorithm was applied to simulated datasets and acquired phantom data. Feasibility and robustness toward initialization were assessed on a clinical dataset manually contoured by two expert clinicians. Comparisons were performed with respect to a standard eight-class GMM algorithm and to four different state-of-the-art methods in terms of volume error (VE), Dice index, classification error (CE), and Hausdorff distance (HD).

RESULTS

The proposed GMM segmentation with background modeling outperformed standard GMM and all the other tested methods. Medians of accuracy indexes were VE <3%, Dice >0.88, CE <0.25, and HD <1.2 in simulations; VE <23%, Dice >0.74, CE <0.43, and HD <1.77 in phantom data. Robustness toward image statistic changes (±15%) was shown by the low index changes: <26% for VE, <17% for Dice, and <15% for CE. Finally, robustness toward the user-dependent volume initialization was demonstrated. The inclusion of the spatial prior improved segmentation accuracy only for lesions surrounded by heterogeneous background: in the relevant simulation subset, the median VE significantly decreased from 13% to 7%. Results on clinical data were found in accordance with simulations, with absolute VE <7%, Dice >0.85, CE <0.30, and HD <0.81.

CONCLUSIONS

The sole introduction of constraints based on background modeling outperformed standard GMM and the other tested algorithms. Insertion of a spatial prior improved the accuracy for realistic cases of objects in heterogeneous backgrounds. Moreover, robustness against initialization supports the applicability in a clinical setting. In conclusion, application-driven constraints can generally improve the capabilities of GMM and statistical clustering algorithms.

A Dirichlet process mixture model for automatic (18)F-FDG PET image segmentation: Validation study on phantoms and on lung and esophageal lesions

PURPOSE

The aim of this study was to implement a Dirichlet process mixture (DPM) model for automatic tumor edge identification on (18)F-fluorodeoxyglucose positron emission tomography ((18)F-FDG PET) images by optimizing the parameters on which the algorithm depends, to validate it experimentally, and to test its robustness.

METHODS

The DPM model belongs to the class of the Bayesian nonparametric models and uses the Dirichlet process prior for flexible nonparametric mixture modeling, without any preliminary choice of the number of mixture components. The DPM algorithm implemented in the statistical software package R was used in this work. The contouring accuracy was evaluated on several image data sets: on an IEC phantom (spherical inserts with diameter in the range 10-37 mm) acquired by a Philips Gemini Big Bore PET-CT scanner, using 9 different target-to-background ratios (TBRs) from 2.5 to 70; on a digital phantom simulating spherical/uniform lesions and tumors, irregular in shape and activity; and on 20 clinical cases (10 lung and 10 esophageal cancer patients). The influence of the DPM parameters on contour generation was studied in two steps. In the first one, only the IEC spheres having diameters of 22 and 37 mm and a sphere of the digital phantom (41.6 mm diameter) were studied by varying the main parameters until the diameter of the spheres was obtained within 0.2% of the true value. In the second step, the results obtained for this training set were applied to the entire data set to determine DPM based volumes of all available lesions. These volumes were compared to those obtained by applying already known algorithms (Gaussian mixture model and gradient-based) and to true values, when available.

RESULTS

Only one parameter was found able to significantly influence segmentation accuracy (ANOVA test). This parameter was linearly connected to the uptake variance of the tested region of interest (ROI). In the first step of the study, a calibration curve was determined to automatically generate the optimal parameter from the variance of the ROI. This "calibration curve" was then applied to contour the whole data set. The accuracy (mean discrepancy between DPM model-based contours and reference contours) of volume estimation was below (1 ± 7)% on the whole data set (1 SD). The overlap between true and automatically segmented contours, measured by the Dice similarity coefficient, was 0.93 with a SD of 0.03.

CONCLUSIONS

The proposed DPM model was able to accurately reproduce known volumes of FDG concentration, with high overlap between segmented and true volumes. For all the analyzed inserts of the IEC phantom, the algorithm proved to be robust to variations in radius and in TBR. The main advantage of this algorithm was that no setting of DPM parameters was required in advance, since the proper setting of the only parameter that could significantly influence the segmentation results was automatically related to the uptake variance of the chosen ROI. Furthermore, the algorithm did not need any preliminary choice of the optimum number of classes to describe the ROIs within PET images and no assumption about the shape of the lesion and the uptake heterogeneity of the tracer was required.

Hybrid positron emission tomography segmentation of heterogeneous lung tumors using 3D Slicer: improved GrowCut algorithm with threshold initialization

This paper presents an improved GrowCut (IGC), a positron emission tomography-based segmentation algorithm, and tests its clinical applicability. Contrary to the traditional method that requires the user to provide the initial seeds, the IGC algorithm starts with a threshold-based estimate of the tumor and a three-dimensional morphologically grown shell around the tumor as the foreground and background seeds, respectively. The repeatability of IGC from the same observer at multiple time points was compared with the traditional GrowCut algorithm. The algorithm was tested in 11 nonsmall cell lung cancer lesions and validated against the clinician-defined manual contour and compared against the clinically used 25% of the maximum standardized uptake value [SUV-(max)], 40% [Formula: see text], and adaptive threshold methods. The time to edit IGC-defined functional volume to arrive at the gross tumor volume (GTV) was compared with that of manual contouring. The repeatability of the IGC algorithm was very high compared with the traditional GrowCut ([Formula: see text]) and demonstrated higher agreement with the manual contour with respect to threshold-based methods. Compared with manual contouring, editing the IGC achieved the GTV in significantly less time ([Formula: see text]). The IGC algorithm offers a highly repeatable functional volume and serves as an effective initial guess that can well minimize the time spent on labor-intensive manual contouring.

How to minimize morbidity in radiotherapy of pharyngolaryngeal tumors?

PURPOSE OF REVIEW

Radiotherapy is one of the most effective treatment modalities for head and neck cancer. However, because of the intricacy between tumors and normal tissues, it can induce morbidity, such as mucositis, dermatitis, xerostomia, dysphagia, hearing loss, vision impairment, skin fibrosis, and osteoradionecrosis of the jaw, and it can dramatically impact on patient quality of life.

RECENT FINDINGS

Throughout the last decade, significant improvements have been made in head and neck cancer radiotherapy, especially with the introduction on a routine basis of intensity-modulated radiotherapy.

SUMMARY

In this context, this review manuscript will focus on how the implementation of intensity-modulated radiotherapy influences treatment morbidity. Specifically, the issues of target volume and organ-at-risk delineation, sparing of organs at risk, tailored treatment intensity, adaptive treatment, and the use of proton therapy will be discussed.

The emerging field of radiomics in esophageal cancer: current evidence and future potential

'Radiomics' is the name given to the emerging field of extracting additional information from standard medical images using advanced feature analysis. This innovative form of quantitative image analysis appears to have future potential for clinical practice in patients with esophageal cancer by providing an additional layer of information to the standard imaging assessment. There is a growing body of evidence suggesting that radiomics may provide incremental value for staging, predicting treatment response, and predicting survival in esophageal cancer, for which the current work-up has substantial limitations. This review outlines the available evidence and future potential for the application of radiomics in the management of patients with esophageal cancer. In addition, an overview of the current evidence on the importance of reproducibility of image features and the substantial influence of varying smoothing scales, quantization levels, and segmentation methods is provided.

Generic and robust method for automatic segmentation of PET images using an active contour model

PURPOSE

Although positron emission tomography (PET) images have shown potential to improve the accuracy of targeting in radiation therapy planning and assessment of response to treatment, the boundaries of tumors are not easily distinguishable from surrounding normal tissue owing to the low spatial resolution and inherent noisy characteristics of PET images. The objective of this study is to develop a generic and robust method for automatic delineation of tumor volumes using an active contour model and to evaluate its performance using phantom and clinical studies.

METHODS

MASAC, a method for automatic segmentation using an active contour model, incorporates the histogram fuzzy C-means clustering, and localized and textural information to constrain the active contour to detect boundaries in an accurate and robust manner. Moreover, the lattice Boltzmann method is used as an alternative approach for solving the level set equation to make it faster and suitable for parallel programming. Twenty simulated phantom studies and 16 clinical studies, including six cases of pharyngolaryngeal squamous cell carcinoma and ten cases of nonsmall cell lung cancer, were included to evaluate its performance. Besides, the proposed method was also compared with the contourlet-based active contour algorithm (CAC) and Schaefer's thresholding method (ST). The relative volume error (RE), Dice similarity coefficient (DSC), and classification error (CE) metrics were used to analyze the results quantitatively.

RESULTS

For the simulated phantom studies (PSs), MASAC and CAC provide similar segmentations of the different lesions, while ST fails to achieve reliable results. For the clinical datasets (2 cases with connected high-uptake regions excluded) (CSs), CAC provides for the lowest mean RE (-8.38% ± 27.49%), while MASAC achieves the best mean DSC (0.71 ± 0.09) and mean CE (53.92% ± 12.65%), respectively. MASAC could reliably quantify different types of lesions assessed in this work with good accuracy, resulting in a mean RE of -13.35% ± 11.87% and -11.15% ± 23.66%, a mean DSC of 0.89 ± 0.05 and 0.71 ± 0.09, and a mean CE of 19.19% ± 7.89% and 53.92% ± 12.65%, for PSs and CSs, respectively.

CONCLUSIONS

The authors' results demonstrate that the developed novel PET segmentation algorithm is applicable to various types of lesions in the authors' study and is capable of producing accurate and consistent target volume delineations, potentially resulting in reduced intraobserver and interobserver variabilities observed when using manual delineation and improved accuracy in treatment planning and outcome evaluation.

On the Reliability of Automatic Volume Delineation in Low-Contrast [(18)F]FMISO-PET Imaging

Hypoxia is a marker of poor prognosis in malignant tumors independent from the selected therapeutic method and the therapy should be intensified in such tumors. Hypoxia imaging with positron emission tomography (PET) is limited by low contrast to noise ratios with every available tracer. In radiation oncology appropriate delineation is required to allow therapy and intensification. While manual segmentation results are highly dependent from experience and observers condition (high inter- and intra observer variability), threshold- and gradient-based algorithms for automatic segmentation frequently fail in low contrast data sets. Likewise, calibration of these algorithms using phantoms is not useful. Complex computational models such as swarm intelligence-based algorithms are promising tools for optimized segmentation results and allow observer independent interpretation of multimodal and multidimensional imaging data.

Performance of automatic image segmentation algorithms for calculating total lesion glycolysis for early response monitoring in non-small cell lung cancer patients during concomitant chemoradiotherapy

BACKGROUND AND PURPOSE

This study evaluated the use of total lesion glycolysis (TLG) determined by different automatic segmentation algorithms, for early response monitoring in non-small cell lung cancer (NSCLC) patients during concomitant chemoradiotherapy.

MATERIALS AND METHODS

Twenty-seven patients with locally advanced NSCLC treated with concomitant chemoradiotherapy underwent (18)F-fluorodeoxyglucose (FDG) PET/CT imaging before and in the second week of treatment. Segmentation of the primary tumours and lymph nodes was performed using fixed threshold segmentation at (i) 40% SUVmax (T40), (ii) 50% SUVmax (T50), (iii) relative-threshold-level (RTL), (iv) signal-to-background ratio (SBR), and (v) fuzzy locally adaptive Bayesian (FLAB) segmentation. Association of primary tumour TLG (TLGT), lymph node TLG (TLGLN), summed TLG (TLGS=TLGT+TLGLN), and relative TLG decrease (ΔTLG) with overall-survival (OS) and progression-free survival (PFS) was determined using univariate Cox regression models.

RESULTS

Pretreatment TLGT was predictive for PFS and OS, irrespective of the segmentation method used. Inclusion of TLGLN improved disease and early response assessment, with pretreatment TLGS more strongly associated with PFS and OS than TLGT for all segmentation algorithms. This was also the case for ΔTLGS, which was significantly associated with PFS and OS, with the exception of RTL and T40.

CONCLUSIONS

ΔTLGS was significantly associated with PFS and OS, except for RTL and T40. Inclusion of TLGLN improves early treatment response monitoring during concomitant chemoradiotherapy with FDG-PET.

Efficient visibility-driven medical image visualisation via adaptive binned visibility histogram

'Visibility' is a fundamental optical property that represents the observable, by users, proportion of the voxels in a volume during interactive volume rendering. The manipulation of this 'visibility' improves the volume rendering processes; for instance by ensuring the visibility of regions of interest (ROIs) or by guiding the identification of an optimal rendering view-point. The construction of visibility histograms (VHs), which represent the distribution of all the visibility of all voxels in the rendered volume, enables users to explore the volume with real-time feedback about occlusion patterns among spatially related structures during volume rendering manipulations. Volume rendered medical images have been a primary beneficiary of VH given the need to ensure that specific ROIs are visible relative to the surrounding structures, e.g. the visualisation of tumours that may otherwise be occluded by neighbouring structures. VH construction and its subsequent manipulations, however, are computationally expensive due to the histogram binning of the visibilities. This limits the real-time application of VH to medical images that have large intensity ranges and volume dimensions and require a large number of histogram bins. In this study, we introduce an efficient adaptive binned visibility histogram (AB-VH) in which a smaller number of histogram bins are used to represent the visibility distribution of the full VH. We adaptively bin medical images by using a cluster analysis algorithm that groups the voxels according to their intensity similarities into a smaller subset of bins while preserving the distribution of the intensity range of the original images. We increase efficiency by exploiting the parallel computation and multiple render targets (MRT) extension of the modern graphical processing units (GPUs) and this enables efficient computation of the histogram. We show the application of our method to single-modality computed tomography (CT), magnetic resonance (MR) imaging and multi-modality positron emission tomography-CT (PET-CT). In our experiments, the AB-VH markedly improved the computational efficiency for the VH construction and thus improved the subsequent VH-driven volume manipulations. This efficiency was achieved without major degradation in the VH visually and numerical differences between the AB-VH and its full-bin counterpart. We applied several variants of the K-means clustering algorithm with varying Ks (the number of clusters) and found that higher values of K resulted in better performance at a lower computational gain. The AB-VH also had an improved performance when compared to the conventional method of down-sampling of the histogram bins (equal binning) for volume rendering visualisation.

Use of standardized uptake value thresholding for target volume delineation in pediatric Hodgkin lymphoma

PURPOSE

A limitation of [(18)F] 2-fluoro-2-deoxy-d-glucose positron emission tomography (FDGPET) in radiation planning for Hodgkin lymphoma (HL) is significant variability in delineation of tumor volume. One approach to reduce variability is to apply automatic or semiautomatic segmentation methods such as thresholding based on a percent tumor maximum standardized uptake value (SUVmax). Here, we apply various tumor SUVmax thresholds and examine their effects in involved field radiation therapy (IFRT) and involved site radiation therapy (ISRT) target volumes.

METHODS AND MATERIALS

PET/computed tomography data sets were reviewed for 16 pediatric and young adult patients treated with IFRT. The following percent tumor SUVmax thresholds were applied to the prechemotherapy PET: 15%, 20%, 25%, 30%, 35%, and 40%. Clinical target volumes for IFRT and ISRT plans were manually generated based on these threshold volumes (CTVPET) and compared with clinical target volumes generated using the standard qualitative visual method (CTVQVM). Treatment plans were generated, doses to normal structures were compared, and the optimum threshold, defined as the CTVPET that corresponded to the percent overlap closest to 100% when compared with the CTVQVM, was determined.

RESULTS

On average, there was a 7.6-fold increase in PET volume between 40% and 15% SUVmax. When the 6 SUVmax thresholds were applied in the design of target volumes for IFRT, 2 of 16 patients had a change in treatment volume. There was a 2.4-fold increase in ISRT CTVs generated based on the 15% and 40% SUVmax, which translated into a clinically significant decrease in dose to normal structures when the ISRT plans that were generated using the 15% SUVmax volumes were compared with the 40% SUVmax. In most patients, the optimum threshold was SUVmax 15%.

CONCLUSIONS

Accurate target volume delineation with [(18)F] 2-fluoro-2-deoxy-d-glucose PET in HL is challenging and may require more precise and reproducible segmentation methods as we move toward more conformal therapies.

Relationship Between 18F-Fluorodeoxyglucose Uptake and V-Ki-Ras2 Kirsten Rat Sarcoma Viral Oncogene Homolog Mutation in Colorectal Cancer Patients: Variability Depending on C-Reactive Protein Level

To evaluate clinical values of clinicopathologic and 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT)-related parameters for prediction of v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (KRAS) mutation in colorectal cancer (CRC) and to investigate their variability depending on C-reactive protein (CRP) levels. In total, 179 CRC patients who underwent PET/CT scans before curative resection and KRAS mutation evaluation following surgery were enrolled. Maximum standardized uptake value (SUV max), peak standardized uptake value (SUV peak), metabolic tumor volume, and total lesion glycolysis were determined semiquantitatively. Associations between clinicopathologic and PET/CT-related parameters and KRAS expression were analyzed. Elevated CRP (> 6.0 mg/L; n = 47) was associated with higher primary tumor size, higher SUV max, SUV peak, metabolic tumor volume, and total lesion glycolysis, compared with those for the group with a CRP lower than that the cutoff value (< 6.0 mg/L; n = 132). Interestingly, the CRC patients (having CRP < 6.0 mg/L) with KRAS mutations had significantly higher (P < 0.05) SUV max and SUV peak values than the patients expressing wild-type KRAS mutations. Multivariate analysis revealed SUV max and SUV peak to be significantly associated with KRAS mutations (odds ratio = 3.3, P = 0.005, and odds ratio = 3.9, P = 0.004), together with histologic grade and lymph node metastasis. 18F-FDG uptake was significantly higher in CRC patients with KRAS mutations and with normal CRP levels. A severe local inflammation with raised CRP levels, however, might affect accurate 18F-FDG quantification in CRC tumors. Positron emission tomography/computed tomography-related parameters could supplement genomic analysis to determine KRAS expression in CRC; however, care should be exercised to guarantee proper patient selection.