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

Metabolic tumor volume from baseline [18 F]FDG PET/CT at diagnosis improves the IPI stratification in patients with diffuse large B-cell lymphoma

PURPOSE

Although several different parameters of PET/CT were reported to be predictive of survival in DLBCL, the best parameter remains to be elucidated and whether it could improve the risk stratification of IPI in patients with DLBCL.

PROCEDURES

262 DLBCL patients including in the training and validation cohort were retrospectively analyzed in this study.

RESULTS

Among different parameters, MTV was identified as the optimal prognostic parameter with a maximum area under the curve (AUC) of 0.652 ± 0.112 than TLG and SDmax (0.645 ± 0.113 and 0.600 ± 0.117, respectively). Patients with high MTV were associated with inferior PFS (p < 0.001 and p = 0.021, respectively) and OS (p < 0.001 and p < 0.001, respectively) in both the training and validation cohort. The multivariate analysis revealed that high MTV was an unfavorable factor for PFS (relative ratio [RR], 2.295; 95% confidence interval [CI], 1.457-3.615; p < 0.01) and OS (RR, 2.929; 95% CI 1.679-5.109; p < 0.01) independent of IPI.

CONCLUSIONS

Further analysis showed MTV could improve the risk stratification of IPI for both PFS and OS (p < 0.01 and p < 0.01, respectively). In conclusion, our study suggests that MTV was an optimal prognostic parameter of PET/CT for survival and it could improve the risk stratification of IPI in DLBCL, which may help to guide treatment in clinical trial.

Brentuximab Vedotin Plus AVD for First-Line Treatment of Early-Stage Unfavorable Hodgkin Lymphoma (BREACH): A Multicenter, Open-Label, Randomized, Phase II Trial

PURPOSE

The prognosis of patients with early-stage unfavorable Hodgkin lymphoma remains unsatisfactory. We assessed the efficacy and safety of brentuximab vedotin plus doxorubicin, vinblastine, and dacarbazine (BV-AVD) in previously untreated, early-stage unfavorable Hodgkin lymphoma (ClinicalTrials.gov identifier: NCT02292979).

METHODS

BREACH is a multicenter, randomized, open-label, phase II trial. Eligible patients were age 18-60 years with ≥ 1 unfavorable EORTC/LYSA criterion. Patients were randomly assigned (2:1) to four cycles of BV-AVD or standard doxorubicin, bleomycin, vincristine, and dacarbazine (ABVD), followed by 30 Gy involved node radiotherapy. The primary end point was the positron emission tomography (PET) response rate after two cycles by expert independent review using the Deauville score. The study was designed to test if the PET-negative rate after two cycles of BV-AVD was superior to 75%. We hypothesized a 10% increase in the PET-negative rate after two cycles of BV-AVD.

RESULTS

Between March 2015 and October 2016, 170 patients were enrolled. After two cycles, the primary end point of the study was met: 93 (82.3%; 90% CI, 75.3 to 88.0) of 113 patients in the BV-AVD arm were PET-negative (Deauville score 1-3) compared with 43 (75.4%; 90% CI, 64.3% to 84.5%) of 57 in the ABVD arm. The 2-year progression-free survival (PFS) was 97.3% (95% CI, 91.9 to 99.1) and 92.6% (95% CI, 81.4% to 97.2%) in the BV-AVD and ABVD arms, respectively. High total metabolic tumor volume was associated with a significantly shorter PFS (hazard ratio, 17.9; 95% CI, 2.2 to 145.5; P < .001). For patients with high total metabolic tumor volume, the 2-year PFS rate was 90.9% (95% CI, 74.4 to 97.0) and 70.7% (95% CI, 39.4% to 87.9%) in the BV-AVD and ABVD arms, respectively.

CONCLUSION

BV-AVD demonstrated an improvement in the PET-negative rate compared with ABVD after two cycles.

Utility and limitations of metabolic parameters in head and neck cancer: finding a practical segmentation method

PURPOSE

Although metabolic tumor volume (MTV) and total lesion glycolysis (TLG) have shown good prognostic value in head and neck cancer (HNC), there are still many issues to resolve before their potential application in standard clinical practice. The purpose of this study was to compare the discrimination ability of two relevant segmentation methods in HNC and to evaluate the potential benefit of adding lymph nodes' metabolism (LNM) to the measurements.

METHODS

We retrospectively analyzed a recently published database of 62 patients with HNC treated with chemoradiotherapy. MTV and TLG were measured using an absolute threshold of SUV2.5. Comparison analysis with previously published background-level threshold (BLT) results was done through Concordance index (C-index) in eight prognostic models.

RESULTS

BLT obtained better C-index values in five out of the eight models. The addition of LNM improved C-index values in six of the prognostic models.

CONCLUSION

We found a potential benefit in adding LNM to the main tumor measurements, as well as in using a BLT for MTV segmentation compared to the most commonly used SUV2.5 threshold. Despite its limitations, this study suggests a practical and simple manner to use these parameters in standard clinical practice, aiming to help elaborate a general consensus.

Adding value to tumor staging in head and neck cancer: The role of metabolic parameters as prognostic factors

BACKGROUND

Validated biomarkers in head and neck squamous cell carcinoma (HNSCC) are scarce.

METHODS

We retrospectively analyzed 62 patients with HNSCC treated with radiotherapy +/- concurrent chemotherapy. Pretreatment metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were measured in a ¹⁸ F-FDG positron emission tomography using a liver dependent standardized uptake value threshold. Cox regression analyses were performed to find associations with disease-free survival (DFS) and overall survival (OS).

RESULTS

High values of MTV (>37 ml) were independently associated with a worse DFS (hazard ratio [HR] = 3.45; 95% confidence interval [CI], 1.52-7.84) and OS (HR = 3.27; 95% CI, 1.41-7.57). Similar results were found for high values of TLG (>247 g) for DFS (HR = 3.32; 95% CI, 1.44-7.65) and OS (HR = 3.42; 95% CI, 1.45-8.07).

CONCLUSIONS

MTV and TLG can be considered as independent prognostic factors for DFS and OS in patients with HNSCC. Considering how easily obtainable they are, they may be useful for predicting clinical outcomes in these patients.

PET Molecular Imaging: A Holistic Review of Current Practice and Emerging Perspectives for Diagnosis, Therapeutic Evaluation and Prognosis in Clinical Oncology

PET/CT molecular imaging has been imposed in clinical oncological practice over the past 20 years, driven by its two well-grounded foundations: quantification and radiolabeled molecular probe vectorization. From basic visual interpretation to more sophisticated full kinetic modeling, PET technology provides a unique opportunity to characterize various biological processes with different levels of analysis. In clinical practice, many efforts have been made during the last two decades to standardize image analyses at the international level, but advanced metrics are still under use in practice. In parallel, the integration of PET imaging with radionuclide therapy, also known as radiolabeled theranostics, has paved the way towards highly sensitive radionuclide-based precision medicine, with major breakthroughs emerging in neuroendocrine tumors and prostate cancer. PET imaging of tumor immunity and beyond is also emerging, emphasizing the unique capabilities of PET molecular imaging to constantly adapt to emerging oncological challenges. However, these new horizons face the growing complexity of multidimensional data. In the era of precision medicine, statistical and computer sciences are currently revolutionizing image-based decision making, paving the way for more holistic cancer molecular imaging analyses at the whole-body level.

Total metabolic tumor volume and spleen metabolism on baseline [18F]-FDG PET/CT as independent prognostic biomarkers of recurrence in resected breast cancer

PURPOSE

We evaluated whether biomarkers on baseline [¹⁸F]-FDG PET/CT are associated with recurrence after surgery in patients with invasive breast cancer of no special type (NST).

METHODS

In this retrospective single-center study, we included consecutive patients with non-metastatic breast cancer of NST who underwent [¹⁸F]-FDG PET/CT before treatment, including surgery, between 2011 and 2016. Clinicopathological data were collected. Tumor SUVmax, total metabolic tumor volume (TMTV), and spleen- and bone marrow-to-liver SUVmax ratios (SLR, BLR) were measured from the PET images. Cut-off values were determined using predictiveness curves to predict 5-year recurrence-free survival (5y-RFS). A multivariable prediction model was developed using Cox regression. The association with stromal tumor-infiltrating lymphocytes (TILs) levels (low if <50%) was studied by logistic regression.

RESULTS

Three hundred and three women were eligible, including 93 (31%) with triple-negative breast carcinoma. After a median follow-up of 6.2 years, 56 and 35 patients experienced recurrence and death, respectively. The 5y-RFS rate was 86%. In multivariable analyses, high TMTV (>20 cm3) and high SLR (>0.76) were associated with shorter 5y-RFS (HR 2.4, 95%CI 1.3-4.5, and HR 1.9, 95%CI 1.0-3.6). In logistic regression, high SLR was the only independent factor associated with low stromal TILs (OR 2.8, 95%CI 1.4-5.7).

CONCLUSION

High total metabolic tumor volume and high spleen glucose metabolism on baseline [¹⁸F]-FDG PET/CT were associated with poor 5y-RFS after surgical resection in patients with breast cancer of NST. Spleen metabolism was inversely correlated with stromal TILs and might be a surrogate for an immunosuppressive tumor microenvironment.

Evaluation of an Automatic Classification Algorithm Using Convolutional Neural Networks in Oncological Positron Emission Tomography

Introduction: Our aim was to evaluate the performance in clinical research and in clinical routine of a research prototype, called positron emission tomography (PET) Assisted Reporting System (PARS) (Siemens Healthineers) and based on a convolutional neural network (CNN), which is designed to detect suspected cancer sites in fluorine-18 fluorodeoxyglucose (¹⁸F-FDG) PET/computed tomography (CT).

Method: We retrospectively studied two cohorts of patients. The first cohort consisted of research-based patients who underwent PET scans as part of the initial workup for diffuse large B-cell lymphoma (DLBCL). The second cohort consisted of patients who underwent PET scans as part of the evaluation of miscellaneous cancers in clinical routine. In both cohorts, we assessed the correlation between manually and automatically segmented total metabolic tumor volumes (TMTVs), and the overlap between both segmentations (Dice score). For the research cohort, we also compared the prognostic value for progression-free survival (PFS) and overall survival (OS) of manually and automatically obtained TMTVs.

Results: For the first cohort (research cohort), data from 119 patients were retrospectively analyzed. The median Dice score between automatic and manual segmentations was 0.65. The intraclass correlation coefficient between automatically and manually obtained TMTVs was 0.68. Both TMTV results were predictive of PFS (hazard ratio: 2.1 and 3.3 for automatically based and manually based TMTVs, respectively) and OS (hazard ratio: 2.4 and 3.1 for automatically based and manually based TMTVs, respectively). For the second cohort (routine cohort), data from 430 patients were retrospectively analyzed. The median Dice score between automatic and manual segmentations was 0.48. The intraclass correlation coefficient between automatically and manually obtained TMTVs was 0.61.

Conclusion: The TMTVs determined for the research cohort remain predictive of total and PFS for DLBCL. However, the segmentations and TMTVs determined automatically by the algorithm need to be verified and, sometimes, corrected to be similar to the manual segmentation.

Reproducibility of Baseline Tumour Metabolic Volume Measurements in Diffuse Large B-Cell LymphomA: Is There a Superior Method?

The metabolic tumour volume (MTV) is an independent prognostic indicator in diffuse large B-cell lymphoma (DLBCL). However, its measurement is not standardised and is subject to wide variations depending on the method used. This study aimed to compare the reproducibility of MTV measurement as well as the thresholds obtained for each method and their prognostic values. The baseline MTV was measured in 239 consecutive patients treated at Henri Becquerel Centre by two blinded evaluators. Eight methods were compared: 3 absolute (SUV (standardised uptake value) ≥ 2.5; SUV≥ liver SUVmax; SUV≥ PERCIST SUV), 1 percentage SUV threshold method (SUV ≥ 41% SUVmax) and 4 adaptive methods (Daisne, Nestle, Fitting, Black). The intraclass correlation coefficients were excellent, from 0.91 to 0.96, for the absolute SUV methods, Black and Nestle methods, and good for 41% SUVmax, Fitting and Daisne methods (0.82 to 0.88), with a significantly lower variability with absolute methods compared to 41% SUVmax (p < 0.04). Thresholds were found to be specific to each segmentation method and ranged from 295 to 552 cm³. There was a strong correlation between the MTV and patient prognosis regardless of the segmentation method used (p = 0.001 for PFS and OS). The largest inter-observer cut-off variability was observed in the 41% SUVmax method, which resulted in more inter-observer disagreements in the classification of patients between high and low MTV groups. MTV measurements based on absolute SUV criteria were found to be significantly more reproducible than those based on 41% SUVmax criteria. The threshold was specific for each of eight segmentation methods, but all predicted prognosis.

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.

Retrospective analysis of the prognostic value of PD-L1 expression and 18F-FDG PET/CT metabolic parameters in colorectal cancer

Background: It has been rarely reported whether ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) uptake in colorectal cancer cells is associated with the expression of PD-L1. We performed a clinical pathology study to evaluate PD-L1 expression in patients undergoing surgical resection of colorectal cancer with preoperative ¹⁸F-FDG PET/CT imaging, with the aim of predicting the response of CRC patients to immune checkpoint inhibitors.

Material and Methods: A retrospective analysis of patients with CRC who underwent FDG-PET imaging before surgery was performed to measure the parameters of FDG-PET imaging: the maximum standardized uptake value (SUVmax), the metabolic tumor volume (MTV), and the total lesion glycolysis (TLG) were evaluated to determine whether each parameter was associated with clinical pathology. Tumor specimens were subjected to PD-L1 staining by immunohistochemistry. Analysis of whether there is a correlation between PD-L1 expression and ¹⁸F-FDG uptake parameters in CRC.

Results: PD-L1 expression level was significantly correlated with SUVmax, MTV3.0 and TLG3.0. Multivariate analysis showed that PD-L1 and TLG3.0 were independent predictors of poor DFS in patients with CRC (P=0.009; P=0.016), PD-L1 expression is closely related to the patient's lesion (TLG3.0) (P<0.01).

Conclusion: The results of this study indicate that there was a significant correlation between PD-L1 expression and TLG3.0 which suggested that FDG-PET could serve as a noninvasive tool to assess the tumor microenvironment and as a predictor of PD-L1 inhibitor activity to determine the optimal therapeutic strategy for CRC. High PD-L1 expression levels and high TLG3.0 are independent risk factors for DFS differences in CRC patients.

PET-Derived Quantitative Metrics for Response and Prognosis in Lymphoma

Lymphoma is a potentially curable disease; however, the clinical challenge lies in further improvement of outcomes. PET with fludeoxyglucose is an effective imaging tool. PET-derived quantitative metrics have raised significant interest to be used as a prognostic factor to complement clinical parameters for treatment decisions. The most optimized use of these quantitative PET metrics, however, will be possible with the standardization of imaging procedures. In this article, we review the technical and methodological considerations related to PET-derived quantitative metrics, and the relevant published data to emphasize the potential value of these metrics in patient prognosis and treatment response in lymphoma.

Detection and segmentation of lymphomas in 3D PET images via clustering with entropy-based optimization strategy

PURPOSE

Lymphoma detection and segmentation from PET images are critical tasks for cancer staging and treatment monitoring. However, it is still a challenge owing to the complexities of lymphoma PET data themselves, and the huge computational burdens and memory requirements for 3D volume data. In this work, an entropy-based optimization strategy for clustering is proposed to detect and segment lymphomas in 3D PET images.

METHODS

To reduce computational complexity and add more feature information, billions of voxels in 3D volume data are first aggregated into supervoxels. Then, such supervoxels serve as basic data units for further clustering by using DBSCAN algorithm, in which some new feature attributes based on physical spatial information and prior knowledge are proposed. In addition, more importantly, an entropy-based objective function is constructed to search the most appropriate parameters of DBSCAN to obtain the optimal clustering results by using a genetic algorithm. This step allows to automatically adapt the parameters to each patient. Finally, a series of comparison experiments among various feature attributes are performed.

RESULTS

48 patient data are conducted, showing the combination of three features, supervoxel intensity, geographic coordinates and organ distributions, can achieve good performance and the proposed entropy-based optimization scheme has more advantages than the existing methods.

CONCLUSION

The proposed entropy-based optimization strategy for clustering by integrating physical spatial attributes and prior knowledge can achieve better performance than traditional methods.

Prognostic Significance of Metabolic Parameters and Textural Features on 18F-FDG PET/CT in Invasive Ductal Carcinoma of Breast

To investigate the prognostic significance of metabolic parameters and texture analysis on ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) in patients with breast invasive ductal carcinoma (IDC), from August 2005 to May 2015, IDC patients who had undergone pre-treatment FDG PET/CT were enrolled. The metabolic parameters, including maximal standardized uptake value of breast tumor (SUVbt) and ipsilateral axillary lymph node (SUVln), metabolic tumor volume (MTVbt) and total lesion glycolysis (TLGbt) of breast tumor, whole-body MTV (MTVwb) and whole-body TLG (TLGwb) were recorded. Nine textural features of tumor (four co-occurrence matrices and five SUV-based statistics) were measured. The prognostic significance of above parameters and clinical factors was assessed by univariate and multivariate analyses. Thirty-five patients were enrolled. Patients with low and high MTVwb had 5-year progression-free survival (PFS) of 81.0 and 14.3% (p < 0.0001). The 5-year overall survival for low and high MTVwb was 88.5% and 43.6% (p = 0.0005). Multivariate analyses showed MTVwb was an independent prognostic factor for PFS (HR: 8.29, 95% CI: 2.17–31.64, p = 0.0020). The SUV, TLG and textural features were not independently predictive. Elevated MTVwb was an independent predictor for shorter PFS in patients with breast IDC.

The role of PET/CT in the modern treatment of Hodgkin lymphoma

Classical Hodgkin Lymphoma is distinguished from other lymphomas by its peculiar biology and heterogeneous chemosensitivity. Most of the patients respond to the standard first-line treatment and are cured, however, in selected cases, the disease relapses or remains primarily refractory. Among predictive/prognostic factors ¹⁸FDG positron emission tomography (PET), fully integrated with computed tomography (PET/CT) proved to be extremely useful in identifying patients with poor prognosis at the time of diagnosis, during and at the end of treatment. The aim of this review is to present the current role of PET/CT in cHL at staging, interim and end of therapy assessment and its ability to guide treatment with a response- and risk-adapted strategy in clinical practice. Finally, quantitative PET measurement and the concurrent use of PET with selected biomarkers are discussed.

Time to Prepare for Risk Adaptation in Lymphoma by Standardizing Measurement of Metabolic Tumor Burden

Increased tumor burden is associated with inferior outcomes in many lymphoma subtypes. Surrogates of tumor burden that are easy to measure, such as the maximum tumor dimension of the bulkiest lesion on CT, have been used as prognostic indices for many years. Recently, total metabolic tumor volume (MTV) and tumor lesion glycolysis have emerged as promising and robust biomarkers of outcome in various lymphomas. The median MTV and the optimal cutoffs to separate patients into risk groups in a study population are, however, highly dependent on the population characteristics and the delineation method used to outline tumor on the PET image. This issue has precluded the use of MTV for risk stratification in trials and clinical practice. Standardization of the methodology is timely to allow the potential for risk adaptation to be explored in addition to response adaptation using PET. Meetings between representatives from research groups active in the field were held under the auspices of the PET International Lymphoma and Myeloma Workshop. A summary of those discussions, which included a review of the literature and a practical assessment of methods used for outlining, including various software options, is presented. Finally, a proposal is made to perform a technical validation of MTV measurement enabling benchmark reference ranges to be derived for published delineation approaches used for outlining with various software. This process would require collation of representative imaging data sets of the most common lymphoma subtypes; agreement on pragmatic criteria for the selection of lesions; generation of a range of MTVs, with consensus to be reached on final contours in a training set; and development of automated software solutions with a set of minimum functionalities to reduce measurement variability. Methods developed in the above training exercise could then be applied to another data set, with a final set of contours and values generated. This final data set would provide a benchmark against which end-users could test their ability to measure MTVs that are consistent with expected values. The data set and automated software solutions could be shared with manufacturers with the aim of including these in standard workflows to allow standardization of MTV measurement across the world.

Semi-automatic lymphoma detection and segmentation using fully conditional random fields

The detection and delineation of the lymphoma volume are a critical step for its treatment and its outcome prediction. Positron Emission Tomography (PET) is widely used for lymphoma detection. Two common types of approaches can be distinguished for lymphoma detection and segmentation in PET. The first one is ROI dependent which needs a ROI defined by physicians. The second one is based on machine learning methods which need a large learning database. However, such a large standard database is quite rare in medical field. Considering these problems, we propose a new approach that combines PET (metabolic information) with CT (anatomical information). Our approach is semi-automatic, it consists of three steps. First, an anatomical multi-atlas segmentation is applied on CT to locate and remove the organs having physiologic hypermetabolism in PET. Then, CRFs (Conditional Random Fields) detect and segment a set of possible lymphoma volumes in PET. The conditional probabilities used in CRFs are usually estimated by a learning step. In this work, we propose to estimate them in an unsupervised way. The final step is to visualize the detected lymphoma volumes and select the real ones by simply clicking on them. The false detection is low thanks to the first step. Our method is tested on 11 patients. The rate of good detection of lymphoma is 100%. The average of Dice indexes for measuring the lymphoma segmentation performance is 84.4% compared to the manual lymphoma segmentation. Comparing with other methods in terms of Dice index shows the best performance of our method.

Diagnostic and Prognostic Role of 18-FDG PET/CT in the Management of Resectable Biliary Tract Cancer

OBJECTIVES

Role of 18-FDG PET/CT had been well established in other more prevalent malignancies such as colorectal and lung cancer; however, this is not as well defined in cholangiocarcinoma. Literature focusing on the prognostic values of preoperative PET/CT for resectable cholangiocarcinoma is scarce.

METHOD

This is a retrospective cohort of 66 consecutive patients who had received curative resection for cholangiocarcinoma from 2010 to 2015. All patients had preoperative 18-FDG PET/CT performed. Accuracy of metastatic lymph node detection of PET/CT and the prognostic value of maximum standard uptake value (SUV-max) was explored.

RESULTS

There were 38 male and 28 female recruited, and the median age was 66. Intrahepatic cholangiocarcinoma (ICC) constituted the majority (59.1%) of the cases, followed by hilar cholangiocarcinoma (22.8%), gallbladder cancer (13.6%) and common bile duct cancer (4.5%). The 3-year disease-free survival (DFS) and overall survival (OS) of the whole population were 27.1 and 39.2%, respectively. The median follow-up duration was 27 months. The accuracy of PET/CT in metastatic lymph node detection was 72.7% (P = 0.005, 95% CI 0.583-0.871) and 81.8% (P = 0.011, 95% CI 0.635-0.990) in whole population and ICC subgroup analysis, respectively. SUV-max was shown by multivariate analysis to be an independent factor for DFS (P = 0.007 OR 1.16, 95% CI 1.04-1.29) and OS (P = 0.012 OR 1.145, 95% CI 1.030-1.273) after resection. SUV-max of 8 was shown to be a discriminant cut-off for poor oncological outcomes in patients with early cholangiocarcinoma (TNM stage I or II) after curative resection (3-year DFS: 21.2 vs. 63.2%, P = 0.004, and 3-year OS: 29 vs. 74% P = 0.048, respectively).

CONCLUSION

PET/CT is a reliable imaging modality for metastatic lymph node detection in cholangiocarcinoma. Tumour SUV-max is an independent factor for oncological outcomes in patients with resectable disease. For patients who have TNM stage I or II cholangiocarcinoma, tumour SUV-max over 8 is associated with significantly inferior disease-free and overall survival even after curative resection.

Quantitative PET/CT in clinical practice: assessing the agreement of PET tumor indices using different clinical reading platforms

OBJECTIVE

The aim of this study was to determine whether various fluorine-18-fluorodeoxyglucose PET/CT-derived parameters used in oncology vary significantly depending on the interpretation software systems used in clinical practice for multiple human solid tumors.

PATIENTS AND METHODS

A total of 120 fluorine-18-fluorodeoxyglucose PET/CT studies carried out in patients with pancreatic, lung, colorectal, and head and neck cancers were evaluated retrospectively on two different vendor software platforms including Mirada and MIMVista. Regions of interest were placed on the liver to determine the liver mean standardized uptake value at lean body mass (SUL) and on each tumor to determine the SULmax, SULpeak. Total lesion glycolysis (TLG) and metabolic tumor volume (MTV) were determined using fixed thresholds of 50% of SULmax and SULpeak. Inter-reader, intersystem intraclass correlations, systematic bias, and variability reflected by the 95% limits of agreement, and precision were determined.

RESULTS

There was excellent inter-reader reliability between the readers and the two software systems, with intraclass correlations more than 0.9 for all PET metrics, with P values less than 0.0001. The bias and SD on Bland-Altman analysis between the two software platforms for tumor SULmax, SULpeak, Max50MTV, and Peak50MTV, respectively, for Reader 1 were -1.52±2.24, 0.80±3.67, -0.80±13.01, and -4.49±20.6. For Reader 2, the biases were -1.62±1.95, 0.18±3.60, -0.27±4.64, and -3.13±8.30. The precision between the two systems was better for SULmax and SULpeak, with less variance observed, than for volume-based metrics such as Max50MTV and Peak50MTV or TLG.

CONCLUSION

Excellent correlation has been found between two tested software reading platforms for all PET-derived metrics in a dual-reader analysis. Overall, the SULmax and SULpeak values had less bias and better precision compared with the MTV and TLG.

Metabolic Tumor Volume Metrics in Lymphoma

Although visual assessment using the Deauville criteria is strongly recommended by guidelines for treatment response monitoring in all FDG-avid lymphoma histologies, the high rate of false-positives and concerns about interobserver variability have motivated the development of quantitative tools to facilitate objective measurement of tumor response in both routine and clinical trial settings. Imaging studies using functional quantitative measures play a significant role in profiling oncologic processes. These quantitative metrics allow for objective end points in multicenter clinical trials. However, the standardization of imaging procedures including image acquisition parameters, reconstruction and analytic measures, and validation of these methods are essential to enable an individualized treatment approach. A robust quality control program associated with the inclusion of proper scanner calibration, cross-calibration with dose calibrators and across other scanners is required for accurate quantitative measurements. In this section, we will review the technical and methodological considerations related to PET-derived quantitative metrics and the relevant published data to emphasize the potential value of these metrics in the prediction of patient prognosis in lymphoma.

Deep Learning in Nuclear Medicine and Molecular Imaging: Current Perspectives and Future Directions

Recent advances in deep learning have impacted various scientific and industrial fields. Due to the rapid application of deep learning in biomedical data, molecular imaging has also started to adopt this technique. In this regard, it is expected that deep learning will potentially affect the roles of molecular imaging experts as well as clinical decision making. This review firstly offers a basic overview of deep learning particularly for image data analysis to give knowledge to nuclear medicine physicians and researchers. Because of the unique characteristics and distinctive aims of various types of molecular imaging, deep learning applications can be different from other fields. In this context, the review deals with current perspectives of deep learning in molecular imaging particularly in terms of development of biomarkers. Finally, future challenges of deep learning application for molecular imaging and future roles of experts in molecular imaging will be discussed.

Estimation of tumour mass in patients with differentiated thyroid carcinoma using serum thyroglobulin

Serum thyroglobulin (Tg) is a reliable tumour marker in follow-up of patients with differentiated thyroid carcinoma (DTC). A positive correlation between Tg level and tumour mass was recently observed, but no attempts were made to derive a numerical relation. The aim of this study was to derive a numerical relationship between serum Tg level and tumour mass that allows optimizing the diagnostic procedures. Patients, method: 78 DTC patients with tumour lesions in either 124I-NaI or 18F-FDG PET/CT were included. For each patient, the total tumour mass was determined functionally in iodine- and FDG-positive lesions as well as morphologically in only CTpositive lesions. The serum Tg level was measured under TSH stimulation prior to imaging. Regression analyses were performed to derive an approach for estimation of the total tumour mass based on Tg levels. Results: A positive correlation of serum Tg and tumour mass was confirmed and a mathematical expression was given to estimate the tumour mass along with its 95% confidence interval using only the serum Tg level. The results demonstrated that the range of predicted tumour mass was higher per serum Tg unit for iodinepositive lesions than for FDG-positive tumour lesions and was higher for follicular than for papillary thyroid carcinoma. Conclusion: This study provides an approach to estimate the tumour mass and its 95% confidence intervals in DTC patients using the serum Tg level. The range of the estimated tumour mass for a given Tg level is rather large, and therefore, the approach is of limited value in clinical application.

Initial FDG-PET/CT predicts survival in adults Ewing sarcoma family of tumors

Purpose

The aim of this retrospective study was to determine, at baseline, the prognostic value of different FDG-PET/CT quantitative parameters in a homogenous Ewing Sarcoma Family of Tumors (ESFT) adult population, compared with clinically relevant prognostic factors.

Methods

Adult patients from 3 oncological centers, all with proved ESFT, were retrospectively included. Quantitative FDG-PET/CT parameters (SUV (maximum, peak and mean), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) of the primary lesion of each patient were recorded before treatment, as well as usual clinical prognostic factors (stage of disease, location, tumor size, gender and age). Then, their relation with progression free survival (PFS) and overall survival (OS) was evaluated.

Results

32 patients were included. Median age was 21 years (range, 15 to 61). Nineteen patients (59%) were initially metastatic. On multivariate analysis, high SUV_max remained independent predictor of worst OS (p=0.02) and PFS (p=0.019), metastatic disease of worst PFS (p=0.01) and high SUVpeak of worst OS (p=0.01). Optimal prognostic cut-off of SUV_peak was found at 12.5 in multivariate analyses for PFS and OS (p=0.0001).

Conclusions

FDG-PET/CT, recommended at ESFT diagnosis for initial staging, can be a useful tool for predicting long-term adult patients outcome through semi-quantitative parameters.

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

PURPOSE

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

APPROACH

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

FINDINGS

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

CONCLUSIONS

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

Prognostic value of 18F-FDG-PET/CT in patients with nasopharyngeal carcinoma: a systematic review and meta-analysis

BACKGROUND

The prognostic role of 18F-fluorodeoxyglucose positron emission tomography CT (18F-FDG PET/CT) parameters is still controversial in nasopharyngeal carcinoma patients. We sought to perform a systematic review and meta-analysis to explore the prognostic value of maximal standardized uptake value (SUVmax), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) on event-free survival (EFS) and overall survival (OS) in nasopharyngeal carcinoma patients.

RESULTS

Fifteen studies comprising 1,938 patients were included in this study. The combined hazard ratios (HRs) for EFS were 2.63 (95%CI 1.71-4.05) for SUVmax, 2.55 (95%CI 1.49-4.35) for MTV, and 3.32 (95%CI 1.23-8.95) for TLG. The pooled HRs for OS were 2.07 (95%CI 1.54-2.79) for SUVmax, 3.86 (95%CI 1.85-8.06) for MTV, and 2.60 (95%CI 1.55-4.34) for TLG. The prognostic role of SUVmax, MTV and TLG remained similar in the sub-group analyses.

METHODS

A systematic literature search was performed to identify studies which associated 18F-FDG PET/CT to clinical survival outcomes of nasopharyngeal carcinoma patients. The summarized HRs for EFS and OS were estimated by using fixed- or random-effect models according to heterogeneity between trials.

CONCLUSIONS

The present meta-analysis confirms that high values of SUVmax, MTV and TLG predicted a higher risk of adverse events or death in patients with nasopharyngeal carcinoma, despite clinically heterogeneous nasopharyngeal carcinoma patients and the various methods adopted between these studies.

A Computer-Aided Analysis Method of SPECT Brain Images for Quantitative Treatment Monitoring: Performance Evaluations and Clinical Applications

The objective and quantitative analysis of longitudinal single photon emission computed tomography (SPECT) images are significant for the treatment monitoring of brain disorders. Therefore, a computer aided analysis (CAA) method is introduced to extract a change-rate map (CRM) as a parametric image for quantifying the changes of regional cerebral blood flow (rCBF) in longitudinal SPECT brain images. The performances of the CAA-CRM approach in treatment monitoring are evaluated by the computer simulations and clinical applications. The results of computer simulations show that the derived CRMs have high similarities with their ground truths when the lesion size is larger than system spatial resolution and the change rate is higher than 20%. In clinical applications, the CAA-CRM approach is used to assess the treatment of 50 patients with brain ischemia. The results demonstrate that CAA-CRM approach has a 93.4% accuracy of recovered region's localization. Moreover, the quantitative indexes of recovered regions derived from CRM are all significantly different among the groups and highly correlated with the experienced clinical diagnosis. In conclusion, the proposed CAA-CRM approach provides a convenient solution to generate a parametric image and derive the quantitative indexes from the longitudinal SPECT brain images for treatment monitoring.

Semiautomated segmentation of head and neck cancers in 18F-FDG PET scans: A just-enough-interaction approach

Purpose:

The purpose of this work was to develop, validate, and compare a highly computer-aided method for the segmentation of hot lesions in head and neck 18F-FDG PET scans.

Methods:

A semiautomated segmentation method was developed, which transforms the segmentation problem into a graph-based optimization problem. For this purpose, a graph structure around a user-provided approximate lesion centerpoint is constructed and a suitable cost function is derived based on local image statistics. To handle frequently occurring situations that are ambiguous (e.g., lesions adjacent to each other versus lesion with inhomogeneous uptake), several segmentation modes are introduced that adapt the behavior of the base algorithm accordingly. In addition, the authors present approaches for the efficient interactive local and global refinement of initial segmentations that are based on the “just-enough-interaction” principle. For method validation, 60 PET/CT scans from 59 different subjects with 230 head and neck lesions were utilized. All patients had squamous cell carcinoma of the head and neck. A detailed comparison with the current clinically relevant standard manual segmentation approach was performed based on 2760 segmentations produced by three experts.

Results:

Segmentation accuracy measured by the Dice coefficient of the proposed semiautomated and standard manual segmentation approach was 0.766 and 0.764, respectively. This difference was not statistically significant (p = 0.2145). However, the intra- and interoperator standard deviations were significantly lower for the semiautomated method. In addition, the proposed method was found to be significantly faster and resulted in significantly higher intra- and interoperator segmentation agreement when compared to the manual segmentation approach.

Conclusions:

Lack of consistency in tumor definition is a critical barrier for radiation treatment targeting as well as for response assessment in clinical trials and in clinical oncology decision-making. The properties of the authors approach make it well suited for applications in image-guided radiation oncology, response assessment, or treatment outcome prediction.

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.

Metabolic Tumor Volume and Total Lesion Glycolysis in PET/CT Correlate With the Pathological Findings of Colorectal Cancer and Allow Its Accurate Staging

INTRODUCTION

PET/CT plays an important role in cancer diagnosis. Recently, novel metabolic parameters in PET/CT such as metabolic tumor volume (MTV) and total lesion glycolysis (TLG) have been reported to be diagnostic and prognostic biomarkers of various cancers. We evaluated the diagnostic value of these metabolic parameters in colorectal cancer (CRC).

METHODS

The study included 138 patients who underwent surgical resection of CRCs between August 2012 and March 2014. The MTVs and TLGs of tumors were measured using various SUV thresholds. The diagnostic abilities of the metabolic parameters were analyzed using ROC curves and classification and regression trees.

RESULTS

The AUCs of the MTVs and TLGs for predicting T stage (0.881-0.892) were significantly higher than the AUC of the SUVmax (0.824). In the M stage, the AUCs of MTVs and TLGs (0.688-0.723) were significantly higher than that of the SUVmax (0.606). Recursive partitioning applying classification and regression trees demonstrated that the optimal cutoff values of the most important variables for discriminating T, N, and M stages are MTV2.5 = 9.35 and 63.33 mL, TLG50% = 328.1, and TLG50% = 94.81, respectively.

CONCLUSION

Metabolic tumor volumes and TLGs in PET/CT are reliable diagnostic biomarkers. Using these parameters, more accurate preoperative diagnoses for CRC can be made.

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.

Baseline Total Metabolic Tumor Volume Measured with Fixed or Different Adaptive Thresholding Methods Equally Predicts Outcome in Peripheral T Cell Lymphoma

The purpose of this study was to compare in a large series of peripheral T cell lymphoma, as a model of diffuse disease, the prognostic value of baseline total metabolic tumor volume (TMTV) measured on ¹⁸F-FDG PET/CT with adaptive thresholding methods with TMTV measured with a fixed 41% SUV_max threshold method.

METHODS

One hundred six patients with peripheral T cell lymphoma, staged with PET/CT, were enrolled from 5 Lymphoma Study Association centers. In this series, TMTV computed with the 41% SUV_max threshold is a strong predictor of outcome. On a dedicated workstation, we measured the TMTV with 4 adaptive thresholding methods based on characteristic image parameters: Daisne (Da) modified, based on signal-to-background ratio; Nestle (Ns), based on tumor and background intensities; Fit, including a 3-dimensional geometric model based on spatial resolution (Fit); and Black (Bl), based on mean SUV_max The TMTV values obtained with each adaptive method were compared with those obtained with the 41% SUV_max method. Their respective prognostic impacts on outcome prediction were compared using receiver-operating-characteristic (ROC) curve analysis and Kaplan-Meier survival curves.

RESULTS

The median value of TMTV_41%, TMTV_Da, TMTV_Ns, TMTV_Fit, and TMTV_Bl were, respectively, 231 cm³ (range, 5-3,824), 175 cm³ (range, 8-3,510), 198 cm³ (range, 3-3,934), 175 cm³ (range, 8-3,512), and 333 cm³ (range, 3-5,113). The intraclass correlation coefficients were excellent, from 0.972 to 0.988, for TMTV_Da, TMTV_Fit, and TMTV_Ns, and less good for TMTV_Bl (0.856). The mean differences obtained from the Bland-Altman plots were 48.5, 47.2, 19.5, and -253.3 cm³, respectively. Except for Black, there was no significant difference within the methods between the ROC curves (P > 0.4) for progression-free survival and overall survival. Survival curves with the ROC optimal cutoff for each method separated the same groups of low-risk (volume ≤ cutoff) from high-risk patients (volume > cutoff), with similar 2-y progression-free survival (range, 66%-72% vs. 26%-29%; hazard ratio, 3.7-4.1) and 2-y overall survival (79%-83% vs. 50%-53%; hazard ratio, 3.0-3.5).

CONCLUSION

The prognostic value of TMTV remained quite similar whatever the methods, adaptive or 41% SUV_max, supporting its use as a strong prognosticator in lymphoma. However, for implementation of TMTV in clinical trials 1 single method easily applicable in a multicentric PET review must be selected and kept all along the trial.

Molecular Imaging and Precision Medicine: PET/Computed Tomography and Therapy Response Assessment in Oncology

A variety of methods have been developed to assess tumor response to therapy. Standardized qualitative criteria based on 18F-fluoro-deoxyglucose PET/computed tomography have been proposed to evaluate the treatment effectiveness in specific cancers and these allow more accurate therapy response assessment and survival prognostication. Multiple studies have addressed the utility of the volumetric PET biomarkers as prognostic indicators but there is no consensus about the preferred segmentation methodology for these metrics. Heterogeneous intratumoral uptake was proposed as a novel PET metric for therapy response assessment. PET imaging techniques will be used to study the biological behavior of cancers during therapy.

Is There a Role for PET/CT Parameters to Characterize Benign, Malignant, and Metastatic Parotid Tumors?

OBJECTIVE

Assessment of benign and malignant lesions of the parotid gland, including metastatic lesions, is challenging with current imaging methods. Fluorine-18 FDG PET/CT is a noninvasive imaging modality that provides both anatomic and metabolic information. Semiquantitative data obtained from PET/CT, also known as PET/CT parameters, are maximum, mean, or peak standardized uptake values (SUVs); metabolic tumor volume; total lesion glycolysis; standardized added metabolic activity; and normalized standardized added metabolic activity. Our aim was to determine whether FDG PET/CT parameters can differentiate benign, malignant, and metastatic parotid tumors.

MATERIALS AND METHODS

Thirty-four patients with parotid neoplasms underwent PET/CT before parotidectomy; maximum SUV, mean SUV, peak SUV, total lesion glycolysis, metabolic tumor volume, standardized added metabolic activity, and normalized standardized added metabolic activity were calculated on a dedicated workstation. Univariate analyses were performed. A ROC analysis was used to determine the ability of PET/CT parameters to predict pathologically proven benign, malignant, and metastatic parotid gland neoplasms.

RESULTS

Fourteen patients had a benign or malignant primary parotid tumor. Twenty had metastases to the parotid gland. When the specificity was set to at least 85% for each parameter to identify cut points, the corresponding sensitivities ranged from 15% to 40%. Assessment of benign versus malignant lesions of parotid tumors, as well as metastasis from squamous cell carcinoma versus other metastatic causes, revealed that none of the PET/CT parameters has enough power to differentiate among these groups.

CONCLUSION

PET/CT parameters, including total lesion glycolysis, metabolic tumor volume, standardized added metabolic activity, and normalized standardized added metabolic activity, are not able to differentiate benign from malignant parotid tumors, primary parotid tumors from metastasis, or metastasis from squamous cell carcinoma and nonsquamous cell carcinoma metastasis.

Atherosclerotic 18F-FDG and MDP uptake in femoral arteries, changes with age

OBJECTIVES

This study was carried out to evaluate the atherosclerotic changes that occur with age in the femoral arteries. To this end, a group of patients were investigated both by a fluorine-18 fluorodeoxyglucose (F-FDG) PET scan and by a whole-body bone scan.

METHODS

We included 38 patients (25 women, 13 men, age range: 25-84 years) in this retrospective analysis. All patients underwent an F-FDG PET scan and a Tc-MDP bone scan. The mean interval time between the bone scans and F-FDG PET scans was 1.2±1.6 months. Patients randomly underwent the bone scan or the PET scan first. The patients were subdivided into four groups, with the following age ranges: 25-50, 51-60, 61-70, and 71-84 years. Regions of interest were drawn both over the femoral arteries and the adjacent background (BKG) both on F-FDG PET examinations and MDP bone scans, and the uptake values were calculated. Finally, we calculated and compared the uptake ratios of F-FDG/BKG and MDP/BKG in the four age groups. These ratios were obtained in the exact same way using equal regions of interest and equal drawing positions.

RESULTS

The uptake ratios of F-FDG/BKG in the femoral arteries increased with age in the four age groups (P<0.05). This ratio was the highest in the oldest age group and the lowest in the youngest age group. MDP/BKG in the four age groups also increased with age in numbers. The ratio was the highest in the oldest patients group and the lowest in the youngest patient group, although this increase with age was not statistically significant.

CONCLUSION

Our results indicate that in the femoral arteries, the uptake ratios of F-FDG/BKG reflects a progression of the inflammatory component of the atherosclerotic activity with age. MDP/BKG in the four age groups in femoral arteries, however, is considered the indicator of severity of the calcification component of atherosclerosis. Calcification in femoral arteries also increased with age, but with a slower progression.

Standardized Uptake Values from PET/MRI in Metastatic Breast Cancer: An Organ-based Comparison With PET/CT

Quantitative standardized uptake values (SUVs) from fluorine-18 (18F) fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) are commonly used to evaluate the extent of disease and response to treatment in breast cancer patients. Recently, PET/magnetic resonance imaging (MRI) has been shown to qualitatively detect metastases from various primary cancers with similar sensitivity to PET/CT. However, quantitative validation of PET/MRI requires assessing the reliability of SUVs from MR attenuation correction (MRAC) relative to CT attenuation correction (CTAC). The purpose of this retrospective study was to assess the utility of PET/MRI-derived SUVs in breast cancer patients by testing the hypothesis that SUVs derived from MRAC correlate well with those from CTAC. Between August 2012 and May 2013, 35 breast cancer patients (age 37-78 years, 1 man) underwent clinical 18F-FDG PET/CT followed by PET/MRI. One hundred seventy metastases were seen in 21 of 35 patients; metastases to bone in 16 patients, to liver in seven patients, and to nonaxillary lymph nodes in eight patients were sufficient for statistical analysis on an organ-specific per patient basis. SUVs in the most FDG-avid metastasis per organ per patient from PET/CT and PET/MRI were measured and compared using Pearson's correlations. Correlations between CTAC- and MRAC-derived SUVmax and SUVmean in 31 metastases to bone, liver, and nonaxillary lymph nodes were strong overall (ρ = 0.80, 0.81). SUVmax and SUVmean correlations were also strong on an organ-specific basis in 16 bone metastases (ρ = 0.76, 0.74), seven liver metastases (ρ = 0.85, 0.83), and eight nonaxillary lymph node metastases (ρ = 0.95, 0.91). These strong organ-specific correlations between SUVs from PET/CT and PET/MRI in breast cancer metastases support the use of SUVs from PET/MRI for quantitation of 18F-FDG activity.

A novel metric for quantification of homogeneous and heterogeneous tumors in PET for enhanced clinical outcome prediction

Oncologic PET images provide valuable information that can enable enhanced prognosis of disease. Nonetheless, such information is simplified significantly in routine clinical assessment to meet workflow constraints. Examples of typical FDG PET metrics include: (i) SUVmax, (2) total lesion glycolysis (TLG), and (3) metabolic tumor volume (MTV). We have derived and implemented a novel metric for tumor quantification, inspired in essence by a model of generalized equivalent uniform dose as used in radiation therapy. The proposed metric, denoted generalized effective total uptake (gETU), is attractive as it encompasses the abovementioned commonly invoked metrics, and generalizes them, for both homogeneous and heterogeneous tumors, using a single parameter a. We evaluated this new metric for improved overall survival (OS) prediction on two different baseline FDG PET/CT datasets: (a) 113 patients with squamous cell cancer of the oropharynx, and (b) 72 patients with locally advanced pancreatic adenocarcinoma. Kaplan-Meier survival analysis was performed, where the subjects were subdivided into two groups using the median threshold, from which the hazard ratios (HR) were computed in Cox proportional hazards regression. For the oropharyngeal cancer dataset, MTV, TLG, SUVmax, SUVmean and SUVpeak produced HR values of 1.86, 3.02, 1.34, 1.36 and 1.62, while the proposed gETU metric for a  = 0.25 (greater emphasis on volume information) enabled significantly enhanced OS prediction with HR  =  3.94. For the pancreatic cancer dataset, MTV, TLG, SUVmax, SUVmean and SUVpeak resulted in HR values of 1.05, 1.25, 1.42, 1.45 and 1.52, while gETU at a  = 3.2 (greater emphasis on SUV information) arrived at an improved HR value of 1.61. Overall, the proposed methodology allows placement of differing degrees of emphasis on tumor volume versus uptake for different types of tumors to enable enhanced clinical outcome prediction.

Multimodality imaging with CT, MR and FDG-PET for radiotherapy target volume delineation in oropharyngeal squamous cell carcinoma

Background

This study aimed to quantify the variation in oropharyngeal squamous cell carcinoma gross tumour volume (GTV) delineation between CT, MR and FDG PET-CT imaging.

Methods

A prospective, single centre, pilot study was undertaken where 11 patients with locally advanced oropharyngeal cancers (2 tonsil, 9 base of tongue primaries) underwent pre-treatment, contrast enhanced, FDG PET-CT and MR imaging, all performed in a radiotherapy treatment mask. CT, MR and CT-MR GTVs were contoured by 5 clinicians (2 radiologists and 3 radiation oncologists). A semi-automated segmentation algorithm was used to contour PET GTVs. Volume and positional analyses were undertaken, accounting for inter-observer variation, using linear mixed effects models and contour comparison metrics respectively.

Results

Significant differences in mean GTV volume were found between CT (11.9 cm³) and CT-MR (14.1 cm³), p < 0.006, CT-MR and PET (9.5 cm³), p < 0.0009, and MR (12.7 cm³) and PET, p < 0.016. Substantial differences in GTV position were found between all modalities with the exception of CT-MR and MR GTVs. A mean of 64 %, 74 % and 77 % of the PET GTVs were included within the CT, MR and CT-MR GTVs respectively. A mean of 57 % of the MR GTVs were included within the CT GTV; conversely a mean of 63 % of the CT GTVs were included within the MR GTV. CT inter-observer variability was found to be significantly higher in terms of position and/or volume than both MR and CT-MR (p < 0.05). Significant differences in GTV volume were found between GTV volumes delineated by radiologists (9.7 cm³) and oncologists (14.6 cm³) for all modalities (p = 0.001).

Conclusions

The use of different imaging modalities produced significantly different GTVs, with no single imaging technique encompassing all potential GTV regions. The use of MR reduced inter-observer variability. These data suggest delineation based on multimodality imaging has the potential to improve accuracy of GTV definition.

Trial registration

ISRCTN Registry: ISRCTN34165059. Registered 2nd February 2015.

Impact of PET/CT image reconstruction methods and liver uptake normalization strategies on quantitative image analysis

BACKGROUND

In oncological imaging using PET/CT, the standardized uptake value has become the most common parameter used to measure tracer accumulation. The aim of this analysis was to evaluate ultra high definition (UHD) and ordered subset expectation maximization (OSEM) PET/CT reconstructions for their potential impact on quantification.

PATIENTS AND METHODS

We analyzed 40 PET/CT scans of lung cancer patients who had undergone PET/CT. Standardized uptake values corrected for body weight (SUV) and lean body mass (SUL) were determined in the single hottest lesion in the lung and normalized to the liver for UHD and OSEM reconstruction. Quantitative uptake values and their normalized ratios for the two reconstruction settings were compared using the Wilcoxon test. The distribution of quantitative uptake values and their ratios in relation to the reconstruction method used were demonstrated in the form of frequency distribution curves, box-plots and scatter plots. The agreement between OSEM and UHD reconstructions was assessed through Bland-Altman analysis.

RESULTS

A significant difference was observed after OSEM and UHD reconstruction for SUV and SUL data tested (p < 0.0005 in all cases). The mean values of the ratios after OSEM and UHD reconstruction showed equally significant differences (p < 0.0005 in all cases). Bland-Altman analysis showed that the SUV and SUL and their normalized values were, on average, up to 60 % higher after UHD reconstruction as compared to OSEM reconstruction.

CONCLUSION

OSEM and HD reconstruction brought a significant difference for SUV and SUL, which remained constantly high after normalization to the liver, indicating that standardization of reconstruction and the use of comparable SUV measurements are crucial when using PET/CT.

18F-FDG PET/CT to Predict Response to Neoadjuvant Chemotherapy and Prognosis in Inflammatory Breast Cancer

The aim of this prospective study was to assess the predictive value of (18)F-FDG PET/CT imaging for pathologic response to neoadjuvant chemotherapy (NACT) and outcome in inflammatory breast cancer (IBC) patients.

METHODS

Twenty-three consecutive patients (51 y ± 12.7) with newly diagnosed IBC, assessed by PET/CT at baseline (PET1), after the third course of NACT (PET2), and before surgery (PET3), were included. The patients were divided into 2 groups according to pathologic response as assessed by the Sataloff classification: pathologic complete response for complete responders (stage TA and NA or NB) and non-pathologic complete response for noncomplete responders (not stage A for tumor or not stage NA or NB for lymph nodes). In addition to maximum standardized uptake value (SUVmax) measurements, a global breast metabolic tumor volume (MTV) was delineated using a semiautomatic segmentation method. Changes in SUVmax and MTV between PET1 and PET2 (ΔSUV1-2; ΔMTV1-2) and PET1 and PET3 (ΔSUV1-3; ΔMTV1-3) were measured.

RESULTS

Mean SUVmax on PET1, PET2, and PET3 did not statistically differ between the 2 pathologic response groups. On receiver-operating-characteristic analysis, a 72% cutoff for ΔSUV1-3 provided the best performance to predict residual disease, with sensitivity, specificity, and accuracy of 61%, 80%, and 65%, respectively. On univariate analysis, the 72% cutoff for ΔSUV1-3 was the best predictor of distant metastasis-free survival (P = 0.05). On multivariate analysis, the 72% cutoff for ΔSUV1-3 was an independent predictor of distant metastasis-free survival (P = 0.01).

CONCLUSION

Our results emphasize the good predictive value of change in SUVmax between baseline and before surgery to assess pathologic response and survival in IBC patients undergoing NACT.

Optimising delineation accuracy of tumours in PET for radiotherapy planning using blind deconvolution

Positron emission tomography (PET) imaging has been proven to be useful in radiotherapy planning for the determination of the metabolically active regions of tumours. Delineation of tumours, however, is a difficult task in part due to high noise levels and the partial volume effects originating mainly from the low camera resolution. The goal of this work is to study the effect of blind deconvolution on tumour volume estimation accuracy for different computer-aided contouring methods. The blind deconvolution estimates the point spread function (PSF) of the imaging system in an iterative manner in a way that the likelihood of the given image being the convolution output is maximised. In this way, the PSF of the imaging system does not need to be known. Data were obtained from a NEMA NU-2 IQ-based phantom with a GE DSTE-16 PET/CT scanner. The artificial tumour diameters were 13, 17, 22, 28 and 37 mm with a target/background ratio of 4:1. The tumours were delineated before and after blind deconvolution. Student's two-tailed paired t-test showed a significant decrease in volume estimation error (p < 0.001) when blind deconvolution was used in conjunction with computer-aided delineation methods. A manual delineation confirmation demonstrated an improvement from 26 to 16 % for the artificial tumour of size 37 mm while an improvement from 57 to 15 % was noted for the small tumour of 13 mm. Therefore, it can be concluded that blind deconvolution of reconstructed PET images may be used to increase tumour delineation accuracy.

An Adaptive Thresholding Method for BTV Estimation Incorporating PET Reconstruction Parameters: A Multicenter Study of the Robustness and the Reliability

OBJECTIVE

The aim of this work was to assess robustness and reliability of an adaptive thresholding algorithm for the biological target volume estimation incorporating reconstruction parameters.

METHOD

In a multicenter study, a phantom with spheres of different diameters (6.5-57.4 mm) was filled with (18)F-FDG at different target-to-background ratios (TBR: 2.5-70) and scanned for different acquisition periods (2-5 min). Image reconstruction algorithms were used varying number of iterations and postreconstruction transaxial smoothing. Optimal thresholds (TS) for volume estimation were determined as percentage of the maximum intensity in the cross section area of the spheres. Multiple regression techniques were used to identify relevant predictors of TS.

RESULTS

The goodness of the model fit was high (R(2): 0.74-0.92). TBR was the most significant predictor of TS. For all scanners, except the Gemini scanners, FWHM was an independent predictor of TS. Significant differences were observed between scanners of different models, but not between different scanners of the same model. The shrinkage on cross validation was small and indicative of excellent reliability of model estimation.

CONCLUSIONS

Incorporation of postreconstruction filtering FWHM in an adaptive thresholding algorithm for the BTV estimation allows obtaining a robust and reliable method to be applied to a variety of different scanners, without scanner-specific individual calibration.

Imaging and dosimetric errors in 4D PET/CT-guided radiotherapy from patient-specific respiratory patterns: a dynamic motion phantom end-to-end study

Effective positron emission tomography / computed tomography (PET/CT) guidance in radiotherapy of lung cancer requires estimation and mitigation of errors due to respiratory motion. An end-to-end workflow was developed to measure patient-specific motion-induced uncertainties in imaging, treatment planning, and radiation delivery with respiratory motion phantoms and dosimeters. A custom torso phantom with inserts mimicking normal lung tissue and lung lesion was filled with [(18)F]FDG. The lung lesion insert was driven by six different patient-specific respiratory patterns or kept stationary. PET/CT images were acquired under motionless ground truth, tidal breathing motion-averaged (3D), and respiratory phase-correlated (4D) conditions. Target volumes were estimated by standardized uptake value (SUV) thresholds that accurately defined the ground-truth lesion volume. Non-uniform dose-painting plans using volumetrically modulated arc therapy were optimized for fixed normal lung and spinal cord objectives and variable PET-based target objectives. Resulting plans were delivered to a cylindrical diode array at rest, in motion on a platform driven by the same respiratory patterns (3D), or motion-compensated by a robotic couch with an infrared camera tracking system (4D). Errors were estimated relative to the static ground truth condition for mean target-to-background (T/Bmean) ratios, target volumes, planned equivalent uniform target doses, and 2%-2 mm gamma delivery passing rates. Relative to motionless ground truth conditions, PET/CT imaging errors were on the order of 10-20%, treatment planning errors were 5-10%, and treatment delivery errors were 5-30% without motion compensation. Errors from residual motion following compensation methods were reduced to 5-10% in PET/CT imaging, <5% in treatment planning, and <2% in treatment delivery. We have demonstrated that estimation of respiratory motion uncertainty and its propagation from PET/CT imaging to RT planning, and RT delivery under a dose painting paradigm is feasible within an integrated respiratory motion phantom workflow. For a limited set of cases, the magnitude of errors was comparable during PET/CT imaging and treatment delivery without motion compensation. Errors were moderately mitigated during PET/CT imaging and significantly mitigated during RT delivery with motion compensation. This dynamic motion phantom end-to-end workflow provides a method for quality assurance of 4D PET/CT-guided radiotherapy, including evaluation of respiratory motion compensation methods during imaging and treatment delivery.

State-Of-The-Art and Recent Advances in Quantification for Therapeutic Follow-Up in Oncology Using PET

¹⁸F-fluoro-2-deoxyglucose (¹⁸F-FDG) positron emission tomography (PET) is an important tool in oncology. Its use has greatly progressed from initial diagnosis to staging and patient monitoring. The information derived from ¹⁸F-FDG-PET allowed the development of a wide range of PET quantitative analysis techniques ranging from simple semi-quantitative methods like the standardized uptake value (SUV) to “high order metrics” that require a segmentation step and additional image processing. In this review, these methods are discussed, focusing particularly on the available methodologies that can be used in clinical trials as well as their current applications in international consensus for PET interpretation in lymphoma and solid tumors.

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

Background

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

Methods

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

Results

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

Conclusions

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

Y90 radioembolization of colorectal cancer liver metastases: response assessment by contrast-enhanced computed tomography with or without PET-CT guidance

PURPOSE

To compare various computed tomography (CT) parameters to the positron emission tomography with computed tomography (PET-CT) response, with or without PET guidance for the response assessment of colorectal cancer (CRC) metastases treated by Y90 radioembolization.

METHODS

Thirty-six CRC metastases were retrospectively evaluated on 18F-Fluoro-Deoxy-Glucose PET-CT and contrast-enhanced computed tomography (CECT) performed at baseline and 2-3 months after Y90 radioembolization.

RESULTS

Median SUVmax values decreased from 11.39 to 6.71 after radioembolization (P<.001), and 23/36 (64%) metastases were categorized metabolic responses according to European Organisation for Research and Treatment of Cancer criteria. Only a decrease of the mean attenuation in the structural (P<.001) and metabolic active volume (P<.001) was observed. The change in these criteria was correlated with the change of SUVmax.