[89Zr]Zr-DFO-girentuximab and [18F]FDG PET/CT to Predict Watchful Waiting Duration in Patients with Metastatic Clear-cell Renal Cell Carcinoma

PURPOSE

Watchful waiting (WW) can be considered for patients with metastatic clear-cell renal cell carcinoma (mccRCC) with good or intermediate prognosis, especially those with <2 International Metastatic RCC Database Consortium criteria and ≤2 metastatic sites [referred to as watch and wait ("W&W") criteria]. The IMaging PAtients for Cancer drug SelecTion-Renal Cell Carcinoma study objective was to assess the predictive value of [18F]FDG PET/CT and [89Zr]Zr-DFO-girentuximab PET/CT for WW duration in patients with mccRCC.

EXPERIMENTAL DESIGN

Between February 2015 and March 2018, 48 patients were enrolled, including 40 evaluable patients with good (n = 14) and intermediate (n = 26) prognosis. Baseline contrast-enhanced CT, [18F]FDG and [89Zr]Zr-DFO-girentuximab PET/CT were performed. Primary endpoint was the time to disease progression warranting systemic treatment. Maximum standardized uptake values (SUVmax) were measured using lesions on CT images coregistered to PET/CT. High and low uptake groups were defined on the basis of median geometric mean SUVmax of RECIST-measurable lesions across patients.

RESULTS

The median WW time was 16.1 months [95% confidence interval (CI): 9.0-31.7]. The median WW period was shorter in patients with high [18F]FDG tumor uptake than those with low uptake (9.0 vs. 36.2 months; HR, 5.6; 95% CI: 2.4-14.7; P < 0.001). Patients with high [89Zr]Zr-DFO-girentuximab tumor uptake had a median WW period of 9.3 versus 21.3 months with low uptake (HR, 1.7; 95% CI: 0.9-3.3; P = 0.13). Patients with "W&W criteria" had a longer median WW period of 21.3 compared with patients without: 9.3 months (HR, 1.9; 95% CI: 0.9-3.9; Pone-sided = 0.034). Adding [18F]FDG uptake to the "W&W criteria" improved the prediction of WW duration (P < 0.001); whereas [89Zr]Zr-DFO-girentuximab did not (P = 0.53).

CONCLUSIONS

In patients with good- or intermediate-risk mccRCC, low [18F]FDG uptake is associated with prolonged WW. This study shows the predictive value of the "W&W criteria" for WW duration and shows the potential of [18F]FDG-PET/CT to further improve this.

Meta-Analysis of the Test-Retest Repeatability of [18F]-Fluorodeoxyglucose Standardized Uptake Values: Implications for Assessment of Tumor Response

PURPOSE

Currently, guidelines for PET with 18F-fluorodeoxyglucose (FDG-PET) interpretation for assessment of therapy response in oncology primarily involve visual evaluation of FDG-PET/CT scans. However, quantitative measurements of the metabolic activity in tumors may be even more useful in evaluating response to treatment. Guidelines based on such measurements, including the European Organization for Research and Treatment of Cancer Criteria and PET Response Criteria in Solid Tumors, have been proposed. However, more rigorous analysis of response criteria based on FDG-PET measurements is needed to adopt regular use in practice.

EXPERIMENTAL DESIGN

Well-defined boundaries of repeatability and reproducibility of quantitative measurements to discriminate noise from true signal changes are a needed initial step. An extension of the meta-analysis from de Langen and colleagues (2012) of the test-retest repeatability of quantitative FDG-PET measurements, including mean, maximum, and peak standardized uptake values (SUVmax, SUVmean, and SUVpeak, respectively), was performed. Data from 11 studies in the literature were used to estimate the relationship between the variance in test-retest measurements with uptake level and various study-level, patient-level, and lesion-level characteristics.

RESULTS

Test-retest repeatability of percentage fluctuations for all three types of SUV measurement (max, mean, and peak) improved with higher FDG uptake levels. Repeatability in all three SUV measurements varied for different lesion locations. Worse repeatability in SUVmean was also associated with higher tumor volumes.

CONCLUSIONS

On the basis of these results, recommendations regarding SUV measurements for assessing minimal detectable changes based on repeatability and reproducibility are proposed. These should be applied to differentiate between response categories for a future set of FDG-PET-based criteria that assess clinically significant changes in tumor response.

The Impact of Semiautomatic Segmentation Methods on Metabolic Tumor Volume, Intensity, and Dissemination Radiomics in 18F-FDG PET Scans of Patients with Classical Hodgkin Lymphoma

Consensus about a standard segmentation method to derive metabolic tumor volume (MTV) in classical Hodgkin lymphoma (cHL) is lacking, and it is unknown how different segmentation methods influence quantitative PET features. Therefore, we aimed to evaluate the delineation and completeness of lesion selection and the need for manual adaptation with different segmentation methods, and to assess the influence of segmentation methods on the prognostic value of MTV, intensity, and dissemination radiomics features in cHL patients. Methods: We analyzed a total of 105 ¹⁸F-FDG PET/CT scans from patients with newly diagnosed (n = 35) and relapsed/refractory (n = 70) cHL with 6 segmentation methods: 2 fixed thresholds on SUV4.0 and SUV2.5, 2 relative methods of 41% of SUV_max (41max) and a contrast-corrected 50% of SUV_peak (A50P), and 2 combination majority vote (MV) methods (MV2, MV3). Segmentation quality was assessed by 2 reviewers on the basis of predefined quality criteria: completeness of selection, the need for manual adaptation, and delineation of lesion borders. Correlations and prognostic performance of resulting radiomics features were compared among the methods. Results: SUV4.0 required the least manual adaptation but tended to underestimate MTV and often missed small lesions with low ¹⁸F-FDG uptake. SUV2.5 most frequently included all lesions but required minor manual adaptations and generally overestimated MTV. In contrast, few lesions were missed when using 41max, A50P, MV2, and MV3, but these segmentation methods required extensive manual adaptation and overestimated MTV in most cases. MTV and dissemination features significantly differed among the methods. However, correlations among methods were high for MTV and most intensity and dissemination features. There were no significant differences in prognostic performance for all features among the methods. Conclusion: A high correlation existed between MTV, intensity, and most dissemination features derived with the different segmentation methods, and the prognostic performance is similar. Despite frequently missing small lesions with low ¹⁸F-FDG avidity, segmentation with a fixed threshold of SUV4.0 required the least manual adaptation, which is critical for future research and implementation in clinical practice. However, the importance of small, low ¹⁸F-FDG-avidity lesions should be addressed in a larger cohort of cHL patients.

Convolutional neural networks for automatic image quality control and EARL compliance of PET images

Background

Machine learning studies require a large number of images often obtained on different PET scanners. When merging these images, the use of harmonized images following EARL-standards is essential. However, when including retrospective images, EARL accreditation might not have been in place. The aim of this study was to develop a convolutional neural network (CNN) that can identify retrospectively if an image is EARL compliant and if it is meeting older or newer EARL-standards.

Materials and methods

96 PET images acquired on three PET/CT systems were included in the study. All images were reconstructed with the locally clinically preferred, EARL1, and EARL2 compliant reconstruction protocols. After image pre-processing, one CNN was trained to separate clinical and EARL compliant reconstructions. A second CNN was optimized to identify EARL1 and EARL2 compliant images. The accuracy of both CNNs was assessed using fivefold cross-validation. The CNNs were validated on 24 images acquired on a PET scanner not included in the training data. To assess the impact of image noise on the CNN decision, the 24 images were reconstructed with different scan durations.

Results

In the cross-validation, the first CNN classified all images correctly. When identifying EARL1 and EARL2 compliant images, the second CNN identified 100% EARL1 compliant and 85% EARL2 compliant images correctly. The accuracy in the independent dataset was comparable to the cross-validation accuracy. The scan duration had almost no impact on the results.

Conclusion

The two CNNs trained in this study can be used to retrospectively include images in a multi-center setting by, e.g., adding additional smoothing. This method is especially important for machine learning studies where the harmonization of images from different PET systems is essential.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40658-022-00468-w.

Comparing lesion and feature selections to predict progression in newly diagnosed DLBCL patients with FDG PET/CT radiomics features

PURPOSE

Biomarkers that can accurately predict outcome in DLBCL patients are urgently needed. Radiomics features extracted from baseline [¹⁸F]-FDG PET/CT scans have shown promising results. This study aims to investigate which lesion- and feature-selection approaches/methods resulted in the best prediction of progression after 2 years.

METHODS

A total of 296 patients were included. 485 radiomics features (n = 5 conventional PET, n = 22 morphology, n = 50 intensity, n = 408 texture) were extracted for all individual lesions and at patient level, where all lesions were aggregated into one VOI. 18 features quantifying dissemination were extracted at patient level. Several lesion selection approaches were tested (largest or hottest lesion, patient level [all with/without dissemination], maximum or median of all lesions) and compared to the predictive value of our previously published model. Several data reduction methods were applied (principal component analysis, recursive feature elimination (RFE), factor analysis, and univariate selection). The predictive value of all models was tested using a fivefold cross-validation approach with 50 repeats with and without oversampling, yielding the mean cross-validated AUC (CV-AUC). Additionally, the relative importance of individual radiomics features was determined.

RESULTS

Models with conventional PET and dissemination features showed the highest predictive value (CV-AUC: 0.72-0.75). Dissemination features had the highest relative importance in these models. No lesion selection approach showed significantly higher predictive value compared to our previous model. Oversampling combined with RFE resulted in highest CV-AUCs.

CONCLUSION

Regardless of the applied lesion selection or feature selection approach and feature reduction methods, patient level conventional PET features and dissemination features have the highest predictive value. Trial registration number and date: EudraCT: 2006-005174-42, 01-08-2008.

Proposed New Dynamic Prognostic Index for Diffuse Large B-Cell Lymphoma: International Metabolic Prognostic Index

PURPOSE

Baseline metabolic tumor volume (MTV) is a promising biomarker in diffuse large B-cell lymphoma (DLBCL). Our aims were to determine the best statistical relationship between MTV and survival and to compare MTV with the International Prognostic Index (IPI) and its individual components to derive the best prognostic model.

METHODS

PET scans and clinical data were included from five published studies in newly diagnosed diffuse large B-cell lymphoma. Transformations of MTV were compared with the primary end points of 3-year progression-free survival (PFS) and overall survival (OS) to derive the best relationship for further analyses. MTV was compared with IPI categories and individual components to derive the best model. Patients were grouped into three groups for survival analysis using Kaplan-Meier analysis; 10% at highest risk, 30% intermediate risk, and 60% lowest risk, corresponding with expected clinical outcome. Validation of the best model was performed using four studies as a test set and the fifth study for validation and repeated five times.

RESULTS

The best relationship for MTV and survival was a linear spline model with one knot located at the median MTV value of 307.9 cm3. MTV was a better predictor than IPI for PFS and OS. The best model combined MTV with age as continuous variables and individual stage as I-IV. The MTV-age-stage model performed better than IPI and was also better at defining a high-risk group (3-year PFS 46.3% v 58.0% and 3-year OS 51.5% v 66.4% for the new model and IPI, respectively). A regression formula was derived to estimate individual patient survival probabilities.

CONCLUSION

A new prognostic index is proposed using MTV, age, and stage, which outperforms IPI and enables individualized estimates of patient outcome.

Proposed New Dynamic Prognostic Index for Diffuse Large B-Cell Lymphoma: International Metabolic Prognostic Index

PURPOSE

Baseline metabolic tumor volume (MTV) is a promising biomarker in diffuse large B-cell lymphoma (DLBCL). Our aims were to determine the best statistical relationship between MTV and survival and to compare MTV with the International Prognostic Index (IPI) and its individual components to derive the best prognostic model.

METHODS

PET scans and clinical data were included from five published studies in newly diagnosed diffuse large B-cell lymphoma. Transformations of MTV were compared with the primary end points of 3-year progression-free survival (PFS) and overall survival (OS) to derive the best relationship for further analyses. MTV was compared with IPI categories and individual components to derive the best model. Patients were grouped into three groups for survival analysis using Kaplan-Meier analysis; 10% at highest risk, 30% intermediate risk, and 60% lowest risk, corresponding with expected clinical outcome. Validation of the best model was performed using four studies as a test set and the fifth study for validation and repeated five times.

RESULTS

The best relationship for MTV and survival was a linear spline model with one knot located at the median MTV value of 307.9 cm³. MTV was a better predictor than IPI for PFS and OS. The best model combined MTV with age as continuous variables and individual stage as I-IV. The MTV-age-stage model performed better than IPI and was also better at defining a high-risk group (3-year PFS 46.3% v 58.0% and 3-year OS 51.5% v 66.4% for the new model and IPI, respectively). A regression formula was derived to estimate individual patient survival probabilities.

CONCLUSION

A new prognostic index is proposed using MTV, age, and stage, which outperforms IPI and enables individualized estimates of patient outcome.

18F-FDG PET Improves Baseline Clinical Predictors of Response in Diffuse Large B-Cell Lymphoma: The HOVON-84 Study

We aimed to determine the added value of baseline metabolic tumor volume (MTV) and interim PET (I-PET) to the age-adjusted international prognostic index (aaIPI) to predict 2-y progression-free survival (PFS) in diffuse large B-cell lymphoma. Secondary objectives were to investigate optimal I-PET response criteria (using Deauville score [DS] or quantitative change in SUV_max [ΔSUV_max] between baseline and I-PET4 [observational I-PET scans after 4 cycles of rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone administered in 2-wk intervals with intensified rituximab in the first 4 cycles [R(R)-CHOP14]). Methods: I-PET4 scans in the HOVON-84 (Hemato-Oncologie voor Volwassenen Nederland [Haemato Oncology Foundation for Adults in the Netherlands]) randomized clinical trial (EudraCT 2006-005174-42) were centrally reviewed using DS (cutoff, 4-5). Additionally, ΔSUV_max (prespecified cutoff, 70%) and baseline MTV were measured. Multivariable hazard ratio (HR), positive predictive value (PPV), and negative predictive value (NPV) were obtained for 2-y PFS. Results: In total, 513 I-PET4 scans were reviewed according to DS, and ΔSUV_max and baseline MTV were available for 367 and 296 patients. The NPV of I-PET ranged between 82% and 86% for all PET response criteria. Univariate HR and PPV were better for ΔSUV_max (4.8% and 53%, respectively) than for DS (3.1% and 38%, respectively). aaIPI and ΔSUV_max independently predicted 2-y PFS (HR, 3.2 and 5.0, respectively); adding MTV brought about a slight improvement. Low or low-intermediate aaIPI combined with a ΔSUV_max of more than 70% (37% of patients) yielded an NPV of 93%, and the combination of high-intermediate or high aaIPI and a ΔSUV_max of 70% or less yielded a PPV of 65%. Conclusion: In this study on diffuse large B-cell lymphoma, I-PET after 4 cycles of R(R)-CHOP14 added predictive value to aaIPI for 2-y PFS, and both were independent response biomarkers in a multivariable Cox model. We externally validated that ΔSUV_max outperformed DS in 2-y PFS prediction.

Dual time point imaging in locally advanced head and neck cancer to assess residual nodal disease after chemoradiotherapy

Background

FDG-PET/CT has a high negative predictive value to detect residual nodal disease in patients with locally advanced squamous cell head and neck cancer after completing concurrent chemoradiotherapy (CCRT). However, the positive predictive value remains suboptimal due to inflammation after radiotherapy, generating unnecessary further investigations and possibly even surgery. We report the results of a preplanned secondary end point of the ECLYPS study regarding the potential advantages of dual time point FDG-PET/CT imaging (DTPI) in this setting. Standardized dedicated head and neck FDG-PET/CT images were obtained 12 weeks after CCRT at 60 and 120 min after tracer administration. We performed a semiquantitative assessment of lymph nodes, and the retention index (RI) was explored to optimize diagnostic performance. The reference standard was histology, negative FDG-PET/CT at 1 year, or > 2 years of clinical follow-up. The time-dependent area under the receiver operator characteristics (AUROC) curves was calculated.

Results

In total, 102 subjects were eligible for analysis. SUV values increased in malignant nodes (median SUV₁ = 2.6 vs. SUV₂ = 2.7; P = 0.04) but not in benign nodes (median SUV₁ = 1.8 vs. SUV₂ = 1.7; P = 0.28). In benign nodes, RI was negative although highly variable (median RI = − 2.6; IQR 21.2), while in malignant nodes RI was positive (median RI = 12.3; IQR 37.2) and significantly higher (P = 0.018) compared to benign nodes. A combined threshold (SUV₁ ≥ 2.2 + RI ≥ 3%) significantly reduced the amount of false-positive cases by 53% (P = 0.02) resulting in an increased specificity (90.8% vs. 80.5%) and PPV (52.9% vs. 37.0%), while sensitivity (60.0% vs. 66.7%) and NPV remained comparably high (92.9% vs. 93.3%). However, AUROC, as overall measure of benefit in diagnostic accuracy, did not significantly improve (P = 0.62). In HPV-related disease (n = 32), there was no significant difference between SUV₁, SUV₂, and RI in malignant and benign nodes, yet this subgroup was small.

Conclusions

DTPI did not improve the overall diagnostic accuracy of FDG-PET/CT to detect residual disease 12 weeks after chemoradiation. Due to differences in tracer kinetics between malignant and benign nodes, DTPI improved the specificity, but at the expense of a loss in sensitivity, albeit minimal. Since false negatives at the 12 weeks PET/CT are mainly due to minimal residual disease, DTPI is not able to significantly improve sensitivity, but repeat scanning at a later time (e.g. after 12 months) could possibly solve this problem. Further study is required in HPV-associated disease.

Cost-Effectiveness of Shortening Treatment Duration Based on Interim PET Outcome in Patients With Diffuse Large B-cell Lymphoma

BACKGROUND

Guideline recommendations for diffuse large-B-cell lymphoma (DLBCL) treatment are shifting from long to short treatment duration, although it is still unclear whether shortening treatment duration does not cause any harm. As interim PET (I-PET) has high negative predictive value for progression, we evaluated the cost-effectiveness of shortening treatment duration dependent on I-PET result.

MATERIALS AND METHODS

We developed a Markov cohort model using the PET Re-Analysis (PETRA) database to evaluate a long treatment duration (LTD) strategy, ie 8x R-CHOP or 6x R-CHOP plus 2 R, and a short treatment duration (STD) strategy, ie 6x R-CHOP. Strategies were evaluated separately in I-PET2 positive and I-PET2 negative patients. Outcomes included total costs and quality-adjusted life-years (QALYs) per patient (pp) from a societal perspective. Net monetary benefit (NMB) per strategy was calculated using a willingness-to-pay threshold of €50,000/QALY. Robustness of model predictions was assessed in sensitivity analyses.

RESULTS

In I-PET2 positive patients, shortening treatment duration led to 50.4 additional deaths per 1000 patients. The STD strategy was less effective (-0.161 [95%CI: -0.343;0.028] QALYs pp) and less costly (-€2768 [95%CI: -€8420;€1105] pp). Shortening treatment duration was not cost-effective (incremental NMB -€5281). In I-PET2 negative patients, shortening treatment duration led to 5.0 additional deaths per 1000 patients and a minor difference in effectiveness (-0.007 [95%CI: -0.136;0.140] QALY pp). The STD strategy was less costly (-€5807 [95%CI: -€10,724;-€2685] pp) and led to an incremental NMB of €5449, indicating that it is cost-effective to shorten treatment duration. Robustness of these findings was underpinned by deterministic and probabilistic sensitivity analyses.

CONCLUSION

Treatment duration should not be shortened in I-PET2 positive patients whereas it is cost-effective to shorten treatment duration in I-PET2 negative patients.

3D Convolutional Neural Network-Based Denoising of Low-Count Whole-Body 18F-Fluorodeoxyglucose and 89Zr-Rituximab PET Scans

Acquisition time and injected activity of ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) PET should ideally be reduced. However, this decreases the signal-to-noise ratio (SNR), which impairs the diagnostic value of these PET scans. In addition, ⁸⁹Zr-antibody PET is known to have a low SNR. To improve the diagnostic value of these scans, a Convolutional Neural Network (CNN) denoising method is proposed. The aim of this study was therefore to develop CNNs to increase SNR for low-count ¹⁸F-FDG and ⁸⁹Zr-antibody PET. Super-low-count, low-count and full-count ¹⁸F-FDG PET scans from 60 primary lung cancer patients and full-count ⁸⁹Zr-rituximab PET scans from five patients with non-Hodgkin lymphoma were acquired. CNNs were built to capture the features and to denoise the PET scans. Additionally, Gaussian smoothing (GS) and Bilateral filtering (BF) were evaluated. The performance of the denoising approaches was assessed based on the tumour recovery coefficient (TRC), coefficient of variance (COV; level of noise), and a qualitative assessment by two nuclear medicine physicians. The CNNs had a higher TRC and comparable or lower COV to GS and BF and was also the preferred method of the two observers for both ¹⁸F-FDG and ⁸⁹Zr-rituximab PET. The CNNs improved the SNR of low-count ¹⁸F-FDG and ⁸⁹Zr-rituximab PET, with almost similar or better clinical performance than the full-count PET, respectively. Additionally, the CNNs showed better performance than GS and BF.

Aberrant patterns of PET response during treatment for DLBCL patients with MYC gene rearrangements

Purpose

MYC gene rearrangements in diffuse large B-cell lymphoma (DLBCL) patients are associated with poor prognosis. Our aim was to compare patterns of 2[¹⁸F]fluoro-2-deoxy-D-glucose positron emission tomography computed tomography (PET/CT) response in MYC + and MYC- DLBCL patients.

Methods

Interim PET/CT (I-PET) and end of treatment PET/CT (EoT-PET) scans of 81 MYC + and 129 MYC- DLBCL patients from 2 HOVON trials were reviewed using the Deauville 5-point scale (DS). DS1-3 was regarded as negative and DS4-5 as positive. Standardized uptake values (SUV) and metabolic tumor volume (MTV) were quantified at baseline, I-PET, and EoT-PET. Negative (NPV) and positive predictive values (PPV) were calculated using 2-year overall survival.

Results

MYC + DLBCL patients had significantly more positive EoT-PET scans than MYC- patients (32.5 vs 15.7%, p = 0.004). I-PET positivity rates were comparable (28.8 vs 23.8%). In MYC + patients 23.2% of the I-PET negative patients converted to positive at EoT-PET, vs only 2% for the MYC- patients (p = 0.002). Nine (34.6%) MYC + DLBCL showed initially uninvolved localizations at EoT-PET, compared to one (5.3%) MYC- patient. A total of 80.8% of EoT-PET positive MYC + patients showed both increased lesional SUV and MTV compared to I-PET. In MYC- patients, 31.6% showed increased SUV and 42.1% showed increased MTV. NPV of I-PET and EoT-PET was high for both MYC subgroups (81.8–94.1%). PPV was highest at EoT-PET for MYC + patients (61.5%).

Conclusion

MYC + DLBCL patients demonstrate aberrant PET response patterns compared to MYC- patients with more frequent progression during treatment after I-PET negative assessment and new lesions at sites that were not initially involved.

Trial registration number and date of registration

HOVON-84: EudraCT: 2006–005,174-42, retrospectively registered 01–08-2008. HOVON-130: EudraCT: 2014–002,654-39, registered 26–01-2015

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-021-05498-7.

Potential and pitfalls of 89Zr-immuno-PET to assess target status: 89Zr-trastuzumab as an example

Background

⁸⁹Zirconium-immuno-positron emission tomography (⁸⁹Zr-immuno-PET) is used for assessment of target status to guide antibody-based therapy. We aim to determine the relation between antibody tumor uptake and target concentration to improve future study design and interpretation.

Methods

The relation between tumor uptake and target concentration was predicted by mathematical modeling of ⁸⁹Zr-labeled antibody disposition in the tumor. Literature values for trastuzumab kinetics were used to provide an example.

Results

⁸⁹Zr-trastuzumab uptake initially increases with increasing target concentration, until it levels off to a constant value. This is determined by the total administered mass dose of trastuzumab. For a commonly used imaging dose of 50 mg ⁸⁹Zr-trastuzumab, uptake can discriminate between immunohistochemistry score (IHC) 0 versus 1–2–3.

Conclusion

The example for ⁸⁹Zr-trastuzumab illustrates the potential to assess target expression. The pitfall of false-positive findings depends on the cut-off to define clinical target positivity (i.e., IHC 3) and the administered mass dose.

PD-L1 PET/CT imaging with radiolabeled durvalumab in patients with advanced stage non-small cell lung cancer

Background: Better biomarkers are needed to predict treatment outcome in NSCLC patients treated with anti PD-(L)1 checkpoint inhibitors. PD-L1 immunohistochemistry has limited predictive value, possibly due to tumor heterogeneity of PD-L1 expression. Noninvasive PD-L1 imaging using ⁸⁹Zr-durvalumab might provide a better reflection of tumor PD-L1 expression and can therefore support treatment decision making. Patients and Methods: NSCLC patients eligible for second line immunotherapy treatment were enrolled. Patients received two injections of ⁸⁹Zr-durvalumab; one without a preceding dose of unlabeled durvalumab ('tracer dose only') and one with a preceding dose of 750 mg durvalumab, directly prior to tracer injection. Up to four PET/CT scans were obtained after tracer injection. Post-imaging acquisition, patients were treated with 750mg durvalumab every two weeks. Tracer biodistribution and tumor uptake were visually assessed and quantified as standardized uptake value (SUV) and both imaging acquisitions were compared. Tumor tracer uptake was correlated with PD-L1 expression and clinical outcome, defined as treatment response to durvalumab treatment. Results: Thirteen patients were included and ten completed all scheduled PET scans. No tracer related adverse events were observed and all patients started durvalumab treatment. Biodistribution analysis showed ⁸⁹Zr-durvalumab accumulation in the blood pool, liver and spleen. Serial imaging showed that image acquisition 120 hours post injection delivered the best tumor to blood pool ratio. Most tumor lesions were visualized with the tracer-dose only versus the co-injection imaging acquisition (25% vs 13.5% of all lesions). Uptake heterogeneity was observed within (range SUVpeak 0.2 to 15.1) and between patients. Tumor uptake was higher in patients with treatment response or stable disease, compared to patients with disease progression according to RECIST 1.1. However, this difference was not statistically significant (median SUVpeak 4.9 vs 2.4, P = 0.06). SUVpeak correlated better with the combined tumor and immune cell PD-L1 score than with PD-L1 expression on tumor cells, although both were not statistically significant (P = 0.06 and P = 0.93, respectively). Conclusion: ⁸⁹Zr-durvalumab was safe without any tracer related adverse events and more tumor lesions were visualized using the tracer dose only imaging acquisition. ⁸⁹Zr-durvalumab tumor uptake was higher in patients with response to durvalumab treatment, but did not correlate with tumor PD-L1 IHC.

Quantitative radiomics features in diffuse large B-cell lymphoma: does segmentation method matter?

INTRODUCTION

Radiomics features may predict outcome in diffuse large B-cell lymphoma (DLBCL). Currently, multiple segmentation methods are used to calculate metabolic tumor volume (MTV). We assessed the influence of segmentation method on the discriminative power of radiomics features in DLBCL for patient level and for the largest lesion. Methods: 50 baseline ¹⁸F-fluorodeoxyglucose positron emission tomography computed tomography (PET/CT) scans of DLBCL patients who progressed or relapsed within 2 years after diagnosis were matched on uptake time and reconstruction method with 50 baseline PET/CT scans of DLBCL patients without progression. Scans were analysed using 6 semi-automatic segmentation methods (standardized uptake value (SUV)4.0, SUV2.5, 41% of the maximum SUV, 50% of the SUVpeak, majority vote (MV)2 and MV3, respectively). Based on these segmentations, 490 radiomics features were extracted at patient level and 486 features for the largest lesion. To quantify the agreement between features extracted from different segmentation methods, the intra-class correlation (ICC) agreement was calculated for each method compared to SUV4.0. The feature space was reduced by deleting features that had high Pearson correlations (≥0.7) with the previously established predictors MTV and/or SUVpeak. Model performance was assessed using stratified repeated cross-validation with 5 folds and 2000 repeats yielding the mean receiver-operating characteristics curve integral (CV-AUC) for all segmentation methods using logistic regression with backward feature selection. Results: The percentage of features yielding an ICC ≥0.75 compared to the SUV4.0 segmentation was lowest for A50P both at patient level and for the largest lesion, with 77.3% and 66.7% of the features yielding an ICC ≥0.75, respectively. Features were not highly correlated with MTV, with at least 435 features at patient level and 409 features for the largest lesion for all segmentation methods with a correlation coefficient <0.7. Features were highly correlated with SUVpeak (at least 190 and 134 were uncorrelated, respectively). CV-AUCs ranged between 0.69±0.11 and 0.84±0.09 for patient level, and between 0.69±0.11 and 0.73±0.10 for lesion level. Conclusion: Even though there are differences in the actual radiomics feature values derived and selected features between segmentation methods, there is no substantial difference in the discriminative power of radiomics features between segmentation methods.

First-in-human study of 89Zr-pembrolizumab PET/CT in patients with advanced stage non-small-cell lung cancer

Background: Tumor programmed-death ligand-1 (PD-L1) proportion score is the current method to select non-small-cell lung cancer (NSCLC) patients for single agent treatment with pembrolizumab, a programmed cell death-1 (PD-1) monoclonal antibody. However, not all patients respond to therapy. Better understanding of in vivo drug behavior may help to select patients that benefit most. Methods: NSCLC patients eligible for pembrolizumab monotherapy as first or later line therapy were enrolled. Patients received two injections of ⁸⁹Zr-pembrolizumab; one without a preceding dose of pembrolizumab and one with 200 mg pembrolizumab, directly prior to tracer injection. Up to four PET/CT scans were obtained after tracer injection. Post-imaging acquisition, patients were treated with 200 mg pembrolizumab, every three weeks. Tumor uptake and tracer biodistribution were visually assessed and quantified as standardized uptake value (SUV). Tumor tracer uptake was correlated with PD-1 and PD-L1 expression and response to pembrolizumab treatment. Results: Twelve NSCLC patients were included. One patient experienced grade 3 myalgia after tracer injection. ⁸⁹Zr-pembrolizumab was observed in the blood pool, liver and spleen. Tracer uptake was visualized in 47,2% of 72 tumor lesions measuring ≥20 mm long axis diameter, and substantial uptake heterogeneity was observed within and between patients. Uptake was higher in patients with response to pembrolizumab treatment (n = 3) compared to patients without a response (n = 9), although this was not statistically significant (median SUVpeak 11.4 vs 5.7, P = 0.066). No significant correlations were found with PD-L1 or PD-1 immunohistochemistry. Conclusion: ⁸⁹Zr-pembrolizumab injection was safe with only one grade 3 adverse event, possibly immune related, out of 12 patients. ⁸⁹Zr-pembrolizumab tumor uptake was higher in patients with response to pembrolizumab treatment, but did not correlate with PD-L1 or PD-1 immunohistochemistry.

11C-Sorafenib and 15O-H2O PET for Early Evaluation of Sorafenib Therapy

Sorafenib leads to clinical benefit in a subgroup of patients, whereas all are exposed to potential toxicity. Currently, no predictive biomarkers are available. The purpose of this study was to evaluate whether ¹¹C-sorafenib and ¹⁵O-H₂O PET have potential to predict treatment efficacy. Methods: In this prospective exploratory study, 8 patients with advanced solid malignancies and an indication for sorafenib treatment were included. Microdose ¹¹C-sorafenib and perfusion ¹⁵O-H₂O dynamic PET scans were performed before and after 2 wk of sorafenib therapy. The main objective was to assess whether tumor ¹¹C-sorafenib uptake predicts sorafenib concentrations during therapy in corresponding tumor biopsy samples measured with liquid chromatography tandem mass spectrometry. Secondary objectives included determining the association of ¹¹C-sorafenib PET findings, perfusion ¹⁵O-H₂O PET findings, and sorafenib concentrations after therapeutic dosing with response. Results: ¹¹C-sorafenib PET findings did not predict sorafenib concentrations in tumor biopsy samples during therapy. In addition, sorafenib plasma and tumor concentrations were not associated with clinical outcome in this exploratory study. Higher ¹¹C-sorafenib accumulation in tumors at baseline and day 14 of treatment showed an association with poorer prognosis and correlated with tumor perfusion (Spearman correlation coefficient = 0.671, P = 0.020). Interestingly, a decrease in tumor perfusion measured with ¹⁵O-H₂O PET after only 14 d of therapy showed an association with response, with a decrease in tumor perfusion of 56% ± 23% (mean ± SD) versus 18% ± 32% in patients with stable and progressive disease, respectively. Conclusion: Microdose ¹¹C-sorafenib PET did not predict intratumoral sorafenib concentrations after therapeutic dosing, but the association between a decrease in tumor perfusion and clinical benefit warrants further investigation.

Spatial concordance of DNA methylation classification in diffuse glioma

Background

Intratumoral heterogeneity is a hallmark of diffuse gliomas. DNA methylation profiling is an emerging approach in the clinical classification of brain tumors. The goal of this study is to investigate the effects of intratumoral heterogeneity on classification confidence.

Methods

We used neuronavigation to acquire 133 image-guided and spatially separated stereotactic biopsy samples from 16 adult patients with a diffuse glioma (7 IDH-wildtype and 2 IDH-mutant glioblastoma, 6 diffuse astrocytoma, IDH-mutant and 1 oligodendroglioma, IDH-mutant and 1p19q codeleted), which we characterized using DNA methylation arrays. Samples were obtained from regions with and without abnormalities on contrast-enhanced T1-weighted and fluid-attenuated inversion recovery MRI. Methylation profiles were analyzed to devise a 3-dimensional reconstruction of (epi)genetic heterogeneity. Tumor purity was assessed from clonal methylation sites.

Results

Molecular aberrations indicated that tumor was found outside imaging abnormalities, underlining the infiltrative nature of this tumor and the limitations of current routine imaging modalities. We demonstrate that tumor purity is highly variable between samples and explains a substantial part of apparent epigenetic spatial heterogeneity. We observed that DNA methylation subtypes are often, but not always, conserved in space taking tumor purity and prediction accuracy into account.

Conclusion

Our results underscore the infiltrative nature of diffuse gliomas and suggest that DNA methylation subtypes are relatively concordant in this tumor type, although some heterogeneity exists.

Interobserver agreement in automated metabolic tumor volume measurements of Deauville score 4 and 5 lesions at interim 18F-FDG PET in DLBCL

Introduction: Metabolic tumor volume (MTV) on interim-PET (I-PET) is a potential prognostic biomarker for diffuse large B-cell lymphoma (DLBCL). Implementation of MTV on I-PET requires consensus which semi-automated segmentation method delineates lesions most successfully with least user interaction. Methods used for baseline PET are not necessarily optimal for I-PET due to lower lesional standardized uptake values (SUV) at I-PET. Therefore, we aimed to evaluate which method provides the best delineation quality of Deauville-score (DS) 4-5 DLBCL lesions on I-PET at best interobserver agreement on delineation quality and, secondly, to assess the effect of lesional SUV_max on delineation quality and performance agreements. Methods: DS4-5 lesions from 45 I-PET scans were delineated using six semi-automated methods i) SUV 2.5, ii) SUV 4.0, iii) adaptive threshold [A50%peak], iv) 41% of maximum SUV [41%max], v) majority vote including voxels detected by ≥2 methods [MV2] and vi) detected by ≥3 methods [MV3]. Delineation quality per MTV was rated by three independent observers as acceptable or non-acceptable. For each method, observer scores on delineation quality, specific agreements and MTV were assessed for all lesions, and per category of lesional SUV_max (<5, 5-10, >10). Results: In 60 DS4-5 lesions on I-PET, MV3 performed best, with acceptable delineation in 90% of lesions, with a positive agreement (PA) of 93%. Delineation quality scores and agreements per method strongly depended on lesional SUV: the best delineation quality scores were obtained using MV3 in lesions with SUV_max<10 and SUV4.0 in more FDG-avid lesions. Consequently, overall delineation quality and PA improved by applying the most preferred method per SUV category instead of using MV3 as single best method. MV3- and SUV4.0-derived MTVs of lesions with SUV_max>10, were comparable after excluding visually failed MV3 contouring. For lesions with SUV_max<10, MTVs using different methods correlated poorly. Conclusion: On I-PET, MV3 performed best and provided the highest interobserver agreement regarding acceptable delineations of DS4-5 DLBCL lesions. However, delineation method preference strongly depended on lesional SUV. Therefore, we suggest to explore an approach that identifies the optimal delineation method per lesion as function of tumor FDG uptake characteristics, i.e. SUV_max.

Pelvic lymph-node staging with 18F-DCFPyL PET/CT prior to extended pelvic lymph-node dissection in primary prostate cancer - the SALT trial

PURPOSE

The detection of lymph-node metastases (N1) with conventional imaging such as magnetic resonance imaging (MRI) and computed tomography (CT) is inadequate for primarily diagnosed prostate cancer (PCa). Prostate-specific membrane antigen (PSMA) PET/CT is successfully introduced for the staging of (biochemically) recurrent PCa. Besides the frequently used 68gallium-labelled PSMA tracers, 18fluorine-labelled PSMA tracers are available. This study examined the diagnostic accuracy of 18F-DCFPyL (PSMA) PET/CT for lymph-node staging in primary PCa.

METHODS

This was a prospective, multicentre cohort study. Patients with primary PCa underwent 18F-DCFPyL PET/CT prior to robot-assisted radical prostatectomy (RARP) with extended pelvic lymph-node dissection (ePLND). Patients were included between October 2017 and January 2020. A Memorial Sloan Kettering Cancer Centre (MSKCC) nomogram risk probability of ≥ 8% of lymph-node metastases was set to perform ePLND. All images were reviewed by two experienced nuclear physicians, and were compared with post-operative histopathologic results.

RESULTS

A total of 117 patients was analysed. Lymph-node metastases (N1) were histologically diagnosed in 17/117 patients (14.5%). The sensitivity, specificity, positive predictive value and negative predictive value for the 18F-DCFPyL PET/CT detection of pelvic lymph-node metastases on a patient level were 41.2% (confidence interval (CI): 19.4-66.5%), 94.0% (CI 86.9-97.5%), 53.8% (CI 26.1-79.6%) and 90.4% (CI 82.6-95.0%), respectively.

CONCLUSION

18F-DCFPyL PET/CT showed a high specificity (94.4%), yet a limited sensitivity (41.2%) for the detection of pelvic lymph-node metastases in primary PCa. This implies that current PSMA PET/CT imaging cannot replace diagnostic ePLND. Further research is necessary to define the exact place of PSMA PET/CT imaging in the primary staging of PCa.

Improved detection of diffuse glioma infiltration with imaging combinations: a diagnostic accuracy study

Background

Surgical resection and irradiation of diffuse glioma are guided by standard MRI: T2/fluid attenuated inversion recovery (FLAIR)–weighted MRI for non-enhancing and T1-weighted gadolinium-enhanced (T1G) MRI for enhancing gliomas. Amino acid PET has been suggested as the new standard. Imaging combinations may improve standard MRI and amino acid PET. The aim of the study was to determine the accuracy of imaging combinations to detect glioma infiltration.

Methods

We included 20 consecutive adults with newly diagnosed non-enhancing glioma (7 diffuse astrocytomas, isocitrate dehydrogenase [IDH] mutant; 1 oligodendroglioma, IDH mutant and 1p/19q codeleted; 1 glioblastoma IDH wildtype) or enhancing glioma (glioblastoma, 9 IDH wildtype and 2 IDH mutant). Standardized preoperative imaging (T1-, T2-, FLAIR-weighted, and T1G MRI, perfusion and diffusion MRI, MR spectroscopy and O-(2-[18F]-fluoroethyl)-L-tyrosine ([¹⁸F]FET) PET) was co-localized with multiregion stereotactic biopsies preceding resection. Tumor presence in the biopsies was assessed by 2 neuropathologists. Diagnostic accuracy was determined using receiver operating characteristic analysis.

Results

A total of 174 biopsies were obtained (63 from 9 non-enhancing and 111 from 11 enhancing gliomas), of which 129 contained tumor (50 from non-enhancing and 79 from enhancing gliomas). In enhancing gliomas, the combination of apparent diffusion coefficient (ADC) with [¹⁸F]FET PET (area under the curve [AUC], 95% CI: 0.89, 0.79‒0.99) detected tumor better than T1G MRI (0.56, 0.39‒0.72; P < 0.001) and [¹⁸F]FET PET (0.76, 0.66‒0.86; P = 0.001). In non-enhancing gliomas, no imaging combination detected tumor significantly better than standard MRI. FLAIR-weighted MRI had an AUC of 0.81 (0.65–0.98) compared with 0.69 (0.56–0.81; P = 0.019) for [¹⁸F]FET PET.

Conclusion

Combining ADC and [¹⁸F]FET PET detects glioma infiltration better than standard MRI and [¹⁸F]FET PET in enhancing gliomas, potentially enabling better guidance of local therapy.

Repeatability of two semi-automatic artificial intelligence approaches for tumor segmentation in PET

Background

Positron emission tomography (PET) is routinely used for cancer staging and treatment follow-up. Metabolic active tumor volume (MATV) as well as total MATV (TMATV—including primary tumor, lymph nodes and metastasis) and/or total lesion glycolysis derived from PET images have been identified as prognostic factor or for the evaluation of treatment efficacy in cancer patients. To this end, a segmentation approach with high precision and repeatability is important. However, the implementation of a repeatable and accurate segmentation algorithm remains an ongoing challenge.

Methods

In this study, we compare two semi-automatic artificial intelligence (AI)-based segmentation methods with conventional semi-automatic segmentation approaches in terms of repeatability. One segmentation approach is based on a textural feature (TF) segmentation approach designed for accurate and repeatable segmentation of primary tumors and metastasis. Moreover, a convolutional neural network (CNN) is trained. The algorithms are trained, validated and tested using a lung cancer PET dataset. The segmentation accuracy of both segmentation approaches is compared using the Jaccard coefficient (JC). Additionally, the approaches are externally tested on a fully independent test–retest dataset. The repeatability of the methods is compared with those of two majority vote (MV2, MV3) approaches, 41%SUV_MAX, and a SUV > 4 segmentation (SUV4). Repeatability is assessed with test–retest coefficients (TRT%) and intraclass correlation coefficient (ICC). An ICC > 0.9 was regarded as representing excellent repeatability.

Results

The accuracy of the segmentations with the reference segmentation was good (JC median TF: 0.7, CNN: 0.73). Both segmentation approaches outperformed most other conventional segmentation methods in terms of test–retest coefficient (TRT% mean: TF: 13.0%, CNN: 13.9%, MV2: 14.1%, MV3: 28.1%, 41%SUV_MAX: 28.1%, SUV4: 18.1%) and ICC (TF: 0.98, MV2: 0.97, CNN: 0.99, MV3: 0.73, SUV4: 0.81, and 41%SUV_MAX: 0.68).

Conclusion

The semi-automatic AI-based segmentation approaches used in this study provided better repeatability than conventional segmentation approaches. Moreover, both algorithms lead to accurate segmentations for both primary tumors as well as metastasis and are therefore good candidates for PET tumor segmentation.

Detection of prostate cancer with 18F-DCFPyL PET/CT compared to final histopathology of radical prostatectomy specimens: is PSMA-targeted biopsy feasible? The DeTeCT trial

PURPOSE

In primary prostate cancer (PCa) patients, accurate staging and histologic grading are crucial to guide treatment decisions. ¹⁸F-DCFPyL (PSMA)-PET/CT has been successfully introduced for (re)staging PCa, showing high accuracy to localise PCa in lymph nodes and/or osseous structures. The diagnostic performance of ¹⁸F-DCFPyL-PET/CT in localizing primary PCa within the prostate gland was assessed, allowing for PSMA-guided targeted-prostate biopsy.

METHODS

Thirty patients with intermediate-/high-risk primary PCa were prospectively enrolled between May 2018 and May 2019 and underwent ¹⁸F-DCFPyL-PET/CT prior to robot-assisted radical prostatectomy (RARP). Two experienced and blinded nuclear medicine physicians assessed tumour localisation within the prostate gland on PET/CT, using a 12-segment mapping model of the prostate. The same model was used by a uro-pathologist for the RARP specimens. Based on PET/CT imaging, a potential biopsy recommendation was given per patient, based on the size and PET-intensity of the suspected PCa localisations. The biopsy recommendation was correlated to final histopathology in the RARP specimen. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for clinically significant PCa (csPCa, Gleason score ≥ 3 + 4 = 7) were assessed.

RESULTS

The segments recommended for potential targeted biopsy harboured csPCA in 28/30 patients (93%), and covered the highest Gleason score PCa segment in 26/30 patient (87%). Overall, 122 of 420 segments (29.0%) contained csPCa at final histopathological examination. Sensitivity, specificity, PPV and NPV for csPCa per segment using ¹⁸F-DCFPyL-PET/CT were 61.4%, 88.3%, 68.1% and 84.8%, respectively.

CONCLUSIONS

When comparing the PCa-localisation on ¹⁸F-DCFPyL-PET/CT with the RARP specimens, an accurate per-patient detection (93%) and localisation of csPCa was found. Thus, ¹⁸F-DCFPyL-PET/CT potentially allows for accurate PSMA-targeted biopsy.

Clinical verification of 18F-DCFPyL PET-detected lesions in patients with biochemically recurrent prostate cancer

Purpose

Radiolabeled Prostate-Specific Membrane Antigen (PSMA) PET/CT is the current standard-of-care for lesion detection in patients with biochemically recurrent (BCR) prostate cancer (PCa). However, rigorous verification of detected lesions is not always performed in routine clinical practice. To aid future ¹⁸F-radiolabeled PSMA PET/CT interpretation, we aimed to identify clinical/imaging characteristics that increase the likelihood that a PSMA-avid lesion is malignant.

Materials and methods

262 patients with BCR, who underwent ¹⁸F-DCFPyL PSMA PET/CT, were retrospectively analyzed. The malignant nature of ¹⁸F-DCFPyL PET-detected lesions was verified through any of the following metrics: (1) positive histopathological examination; (2) additional positive imaging; (3) a ≥50% decrease in Prostate-Specific Antigen (PSA) following irradiation of the lesion(s).

Results

In 226/262 PET scans (86.3%) at least one lesion suspicious for recurrent PCa was detected (‘positive scan’). In 84/226 positive scans (37.2%), at least one independent verification metric was available. PSMA PET-detected lesions were most often confirmed to be malignant (PCa) in the presence of a CT-substrate (96.5% vs. 55.6% without CT-substrate), with SUV_peak ≥3.5 (91.4% vs. 60.0% with SUV_peak<3.5), in patients with a PSA-level ≥2.0 ng/mL (83.7% vs. 65.7% in patients with PSA <2.0ng/mL) and in patients with >2 PET-positive lesions (94.1% vs. 64.2% in patients with 1–2 PET-positive lesions; p<0.001–0.03).

Conclusions

In this study, the clinical verification of ¹⁸F-DCFPyL PET-positive lesions in patients with BCR was performed. Diagnostic certainty of PET-detected lesions increases in the presence of characteristic abnormalities on CT, when SUV_peak is ≥3.5, when PSA-levels exceed 2.0 ng/mL or in patients with more than two PET-positive lesions.

Predictive value of quantitative 18F-FDG-PET radiomics analysis in patients with head and neck squamous cell carcinoma

BACKGROUND

Radiomics is aimed at image-based tumor phenotyping, enabling application within clinical-decision-support-systems to improve diagnostic accuracy and allow for personalized treatment. The purpose was to identify predictive 18-fluor-fluoro-2-deoxyglucose (¹⁸F-FDG) positron-emission tomography (PET) radiomic features to predict recurrence, distant metastasis, and overall survival in patients with head and neck squamous cell carcinoma treated with chemoradiotherapy.

METHODS

Between 2012 and 2018, 103 retrospectively (training cohort) and 71 consecutively included patients (validation cohort) underwent ¹⁸F-FDG-PET/CT imaging. The 434 extracted radiomic features were subjected, after redundancy filtering, to a projection resulting in outcome-independent meta-features (factors). Correlations between clinical, first-order ¹⁸F-FDG-PET parameters (e.g., SUVmean), and factors were assessed. Factors were combined with ¹⁸F-FDG-PET and clinical parameters in a multivariable survival regression and validated. A clinically applicable risk-stratification was constructed for patients' outcome.

RESULTS

Based on 124 retained radiomic features from 103 patients, 8 factors were constructed. Recurrence prediction was significantly most accurate by combining HPV-status, SUVmean, SUVpeak, factor 3 (histogram gradient and long-run-low-grey-level-emphasis), factor 4 (volume-difference, coarseness, and grey-level-non-uniformity), and factor 6 (histogram variation coefficient) (CI = 0.645). Distant metastasis prediction was most accurate assessing metabolic-active tumor volume (MATV)(CI = 0.627). Overall survival prediction was most accurate using HPV-status, SUVmean, SUVmax, factor 1 (least-axis-length, non-uniformity, high-dependence-of-high grey-levels), and factor 5 (aspherity, major-axis-length, inversed-compactness and, inversed-flatness) (CI = 0.764).

CONCLUSIONS

Combining HPV-status, first-order ¹⁸F-FDG-PET parameters, and complementary radiomic factors was most accurate for time-to-event prediction. Predictive phenotype-specific tumor characteristics and interactions might be captured and retained using radiomic factors, which allows for personalized risk stratification and optimizing personalized cancer care.

TRIAL REGISTRATION

Trial NL3946 (NTR4111), local ethics commission reference: Prediction 2013.191 and 2016.498. Registered 7 August 2013, https://www.trialregister.nl/trial/3946.

The quantitative assessment of interstitial lung disease with positron emission tomography scanning in systemic sclerosis patients

Objectives

The reversibility of interstitial lung disease (ILD) in SSc is difficult to assess by current diagnostic modalities and there is clinical need for imaging techniques that allow for treatment stratification and monitoring. ¹⁸F-Fluorodeoxyglucose (FDG) PET/CT scanning may be of interest for this purpose by detection of metabolic activity in lung tissue. This study aimed to investigate the potential role of ¹⁸F-FDG PET/CT scanning for the quantitative assessment of SSc-related active ILD.

Methods

¹⁸F-FDG PET/CT scans and high resolution CT scans of eight SSc patients, including five with ILD, were analysed. For comparison, reference groups were included: eight SLE patients and four primary Sjögren’s syndrome (pSS) patients, all without ILD. A total of 22 regions of interest were drawn in each patient at apical, medial and dorsobasal lung levels. ¹⁸F-FDG uptake was measured as mean standardized uptake value (SUVmean) in each region of interest. Subsequently, basal/apical (B/A) and medial/apical (M/A) ratios were calculated at patient level (B/A-p and M/A-p) and at tissue level (B/A-t and M/A-t).

Results

SUVmean values in dorsobasal ROIs and B/A-p ratios were increased in SSc with ILD compared with SSc without ILD (P = 0.04 and P = 0.07, respectively), SLE (P = 0.003 and P = 0.002, respectively) and pSS (P = 0.03 and P = 0.02, respectively). Increased uptake in the dorsobasal lungs and increased B/A-t ratios corresponded to both ground glass and reticulation on high resolution CT.

Conclusion

Semi-quantitative assessment of ¹⁸F-FDG PET/CT is able to distinguish ILD from non-affected lung tissue in SSc, suggesting that it may be used as a new biomarker for SSc-ILD disease activity.

Machine learning-based analysis of [18F]DCFPyL PET radiomics for risk stratification in primary prostate cancer

PURPOSE

Quantitative prostate-specific membrane antigen (PSMA) PET analysis may provide for non-invasive and objective risk stratification of primary prostate cancer (PCa) patients. We determined the ability of machine learning-based analysis of quantitative [¹⁸F]DCFPyL PET metrics to predict metastatic disease or high-risk pathological tumor features.

METHODS

In a prospective cohort study, 76 patients with intermediate- to high-risk PCa scheduled for robot-assisted radical prostatectomy with extended pelvic lymph node dissection underwent pre-operative [¹⁸F]DCFPyL PET-CT. Primary tumors were delineated using 50-70% peak isocontour thresholds on images with and without partial-volume correction (PVC). Four hundred and eighty standardized radiomic features were extracted per tumor. Random forest models were trained to predict lymph node involvement (LNI), presence of any metastasis, Gleason score ≥ 8, and presence of extracapsular extension (ECE). For comparison, models were also trained using standard PET features (SUVs, volume, total PSMA uptake). Model performance was validated using 50 times repeated 5-fold cross-validation yielding the mean receiver-operator characteristic curve AUC.

RESULTS

The radiomics-based machine learning models predicted LNI (AUC 0.86 ± 0.15, p < 0.01), nodal or distant metastasis (AUC 0.86 ± 0.14, p < 0.01), Gleason score (0.81 ± 0.16, p < 0.01), and ECE (0.76 ± 0.12, p < 0.01). The highest AUCs reached using standard PET metrics were lower than those of radiomics-based models. For LNI and metastasis prediction, PVC and a higher delineation threshold improved model stability. Machine learning pre-processing methods had a minor impact on model performance.

CONCLUSION

Machine learning-based analysis of quantitative [¹⁸F]DCFPyL PET metrics can predict LNI and high-risk pathological tumor features in primary PCa patients. These findings indicate that PSMA expression detected on PET is related to both primary tumor histopathology and metastatic tendency. Multicenter external validation is needed to determine the benefits of using radiomics versus standard PET metrics in clinical practice.

Rituximab-CHOP With Early Rituximab Intensification for Diffuse Large B-Cell Lymphoma: A Randomized Phase III Trial of the HOVON and the Nordic Lymphoma Group (HOVON-84)

PURPOSE

Immunochemotherapy with rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) has become standard of care for patients with diffuse large B-cell lymphoma (DLBCL). This randomized trial assessed whether rituximab intensification during the first 4 cycles of R-CHOP could improve the outcome of these patients compared with standard R-CHOP.

PATIENTS AND METHODS

A total of 574 patients with DLBCL age 18 to 80 years were randomly assigned to induction therapy with 6 or 8 cycles of R-CHOP-14 with (RR-CHOP-14) or without (R-CHOP-14) intensification of rituximab in the first 4 cycles. The primary end point was complete remission (CR) on induction. Analyses were performed by intention to treat.

RESULTS

CR was achieved in 254 (89%) of 286 patients in the R-CHOP-14 arm and 249 (86%) of 288 patients in the RR-CHOP-14 arm (hazard ratio [HR], 0.82; 95% CI, 0.50 to 1.36; P = .44). After a median follow-up of 92 months (range, 1-131 months), 3-year failure-free survival was 74% (95% CI, 68% to 78%) in the R-CHOP-14 arm versus 69% (95% CI, 63% to 74%) in the RR-CHOP-14 arm (HR, 1.26; 95% CI, 0.98 to 1.61; P = .07). Progression-free survival at 3 years was 74% (95% CI, 69% to 79%) in the R-CHOP-14 arm versus 71% (95% CI, 66% to 76%) in the RR-CHOP-14 arm (HR, 1.20; 95% CI, 0.94 to 1.55; P = .15). Overall survival at 3 years was 81% (95% CI, 76% to 85%) in the R-CHOP-14 arm versus 76% (95% CI, 70% to 80%) in the RR-CHOP-14 arm (HR, 1.27; 95% CI, 0.97 to 1.67; P = .09). Patients between ages 66 and 80 years experienced significantly more toxicity during the first 4 cycles in the RR-CHOP-14 arm, especially neutropenia and infections.

CONCLUSION

Early rituximab intensification during R-CHOP-14 does not improve outcome in patients with untreated DLBCL.

Automated Segmentation of Baseline Metabolic Total Tumor Burden in Diffuse Large B-Cell Lymphoma: Which Method Is Most Successful? A Study on Behalf of the PETRA Consortium

Metabolic tumor volume (MTV) is a promising biomarker of pretreatment risk in diffuse large B-cell lymphoma (DLBCL). Different segmentation methods can be used that predict prognosis equally well but give different optimal cutoffs for risk stratification. Segmentation can be cumbersome; a fast, easy, and robust method is needed. Our aims were to evaluate the best automated MTV workflow in DLBCL; determine whether uptake time, compliance or noncompliance with standardized recommendations for ¹⁸F-FDG scanning, and subsequent disease progression influence the success of segmentation; and assess differences in MTVs and discriminatory power of segmentation methods. Methods: One hundred forty baseline ¹⁸F-FDG PET/CT scans were selected from U.K. and Dutch studies on DLBCL to provide a balance between scans at 60 and 90 min of uptake, parameters compliant and noncompliant with standardized recommendations for scanning, and patients with and without progression. An automated tool was applied for segmentation using an SUV of 2.5 (SUV2.5), an SUV of 4.0 (SUV4.0), adaptive thresholding (A50P), 41% of SUV_max (41%), a majority vote including voxels detected by at least 2 methods (MV2), and a majority vote including voxels detected by at least 3 methods (MV3). Two independent observers rated the success of the tool to delineate MTV. Scans that required minimal interaction were rated as a success; scans that missed more than 50% of the tumor or required more than 2 editing steps were rated as a failure. Results: One hundred thirty-eight scans were evaluable, with significant differences in success and failure ratings among methods. The best performing was SUV4.0, with higher success and lower failure rates than any other method except MV2, which also performed well. SUV4.0 gave a good approximation of MTV in 105 (76%) scans, with simple editing for a satisfactory result in additionally 20% of cases. MTV was significantly different for all methods between patients with and without progression. The 41% segmentation method performed slightly worse, with longer uptake times; otherwise, scanning conditions and patient outcome did not influence the tool's performance. The discriminative power was similar among methods, but MTVs were significantly greater using SUV4.0 and MV2 than using other thresholds, except for SUV2.5. Conclusion: SUV4.0 and MV2 are recommended for further evaluation. Automated estimation of MTV is feasible.

Correction to: [89Zr]Zr-cetuximab PET/CT as biomarker for cetuximab monotherapy in patients with RAS wild-type advanced colorectal cancer

Missing Electronic Supplementary Materials.

Prediction of watchful waiting in newly diagnosed metastatic clear cell renal cell carcinoma patients with a good or intermediate prognosis

5079

Background: In metastatic clear cell renal cell carcinoma (mccRCC), the number of International Metastatic Database Consortium (IMDC) risk factors plus metastatic sites may identify patients with rapid or slow disease progression in a period of watchful waiting (WW) (median WW of 8.4 vs 22.2 months; Rini et al. Lancet Oncol. 2016). We aimed to validate this and prospectively assess the added value of baseline PET with [18F]FDG and [89Zr]Zr-DFO-girentuximab to predict the WW-period in the multicenter IMaging PAtients for Cancer drug selecTion (IMPACT)-RCC cohort study. (NCT02228954). Methods: Between February 2015 and March 2018, 40 treatment-naïve mccRCC patients with a good (n=13) or intermediate prognosis (n=25) according to IMDC, were enrolled. Following baseline CT, [18F]FDG and [89Zr]Zr-DFO-girentuximab-PET, CT scans (RECIST1.1) were acquired at 2, 4, 6, 9, 12 months and thereafter every 4 months. Primary endpoint was time to radiological and/or clinical disease progression, requiring systemic treatment. Patients were assigned to a favorable (<2 IMDC risk factors and <3 metastatic sites) or unfavorable for WW-group (all others; Rini et al). Maximum standardized uptake values (SUVmax) were measured in PET-positive lesions measuring ≥10mm, or 15mm in lymph nodes. High and low-uptake groups were defined based on median geometric mean (gm) SUVmax across patients. A one-sided test was used to validate observations by Rini et al; other tests were two-sided. Results: The median WW-period was 9.3 months in the unfavorable WW-group (n=19) vs 20.4 months in the favorable WW-group (n=21) (HR 1.89 95%CI 0.94-3.89; p=0.037), confirming observations of Rini et al. Patients with high [18F]FDG uptake had a median WW-period of 8.5 months compared to 25.2 months in the low-uptake group (HR 4.08 95%CI 1.89-9.28; p=0.0002). Patients with high [89Zr]Zr-DFO-girentuximab uptake had a median WW-period of 10.7 versus 16.4 months in the low-uptake group (HR 1.37; 95%CI 0.69-2.76; p=0.37). [18F]FDG uptake groups improved a Cox-model for WW based on the prognostic groups of Rini et al (p=0.0015); [89Zr]Zr-DFO-girentuximab did not (p=0.98). Conclusions: The IMPACT-RCC study validated the observations by Rini et al. and shows that adding baseline [18F]FDG PET further improves the prediction of the duration of the WW-period in mccRCC patients. Clinical trial information: NCT02228954 .

Visual and quantitative evaluation of [18F]FES and [18F]FDHT PET in patients with metastatic breast cancer: an interobserver variability study

Purpose

Correct identification of tumour receptor status is important for treatment decisions in breast cancer. [¹⁸F]FES PET and [¹⁸F]FDHT PET allow non-invasive assessment of the oestrogen (ER) and androgen receptor (AR) status of individual lesions within a patient. Despite standardised analysis techniques, interobserver variability can significantly affect the interpretation of PET results and thus clinical applicability. The purpose of this study was to determine visual and quantitative interobserver variability of [¹⁸F]FES PET and [¹⁸F]FDHT PET interpretation in patients with metastatic breast cancer.

Methods

In this prospective, two-centre study, patients with ER-positive metastatic breast cancer underwent both [¹⁸F]FES and [¹⁸F]FDHT PET/CT. In total, 120 lesions were identified in 10 patients with either conventional imaging (bone scan or lesions > 1 cm on high-resolution CT, n = 69) or only with [¹⁸F]FES and [¹⁸F]FDHT PET (n = 51). All lesions were scored visually and quantitatively by two independent observers. A visually PET-positive lesion was defined as uptake above background. For quantification, we used standardised uptake values (SUV): SUV_max, SUV_peak and SUV_mean.

Results

Visual analysis showed an absolute positive and negative interobserver agreement for [¹⁸F]FES PET of 84% and 83%, respectively (kappa = 0.67, 95% CI 0.48–0.87), and 49% and 74% for [¹⁸F]FDHT PET, respectively (kappa = 0.23, 95% CI − 0.04–0.49). Intraclass correlation coefficients (ICC) for quantification of SUV_max, SUV_peak and SUV_mean were 0.98 (95% CI 0.96–0.98), 0.97 (95% CI 0.96–0.98) and 0.89 (95% CI 0.83–0.92) for [¹⁸F]FES, and 0.78 (95% CI 0.66–0.85), 0.76 (95% CI 0.63–0.84) and 0.75 (95% CI 0.62–0.84) for [¹⁸F]FDHT, respectively.

Conclusion

Visual and quantitative evaluation of [¹⁸F]FES PET showed high interobserver agreement. These results support the use of [¹⁸F]FES PET in clinical practice. In contrast, visual agreement for [¹⁸F]FDHT PET was relatively low due to low tumour-background ratios, but quantitative agreement was good. This underscores the relevance of quantitative analysis of [¹⁸F]FDHT PET in breast cancer.

Trial registration

ClinicalTrials.gov, NCT01988324. Registered 20 November 2013, https://clinicaltrials.gov/ct2/show/NCT01988324?term=FDHT+PET&draw=1&rank=2.

Quantitative parametric maps of O-(2-[18F]fluoroethyl)-L-tyrosine kinetics in diffuse glioma

Quantitative parametric images of O-(2-[¹⁸F]fluoroethyl)-L-tyrosine kinetics in diffuse gliomas could be used to improve glioma grading, tumour delineation or the assessment of the uptake distribution of this positron emission tomography tracer. In this study, several parametric images and tumour-to-normal maps were compared in terms of accuracy of region averages (when compared to results from nonlinear regression of a reversible two-tissue compartment plasma input model) and image noise using 90 min of dynamic scan data acquired in seven patients with diffuse glioma. We included plasma input methods (the basis function implementation of the single-tissue compartment model, spectral analysis and Logan graphical analysis) and reference tissue methods (basis function implementations of the simplified reference tissue model, variations of the multilinear reference tissue model and non-invasive Logan graphical analysis) as well as tumour-to-normal ratio maps at three intervals. (Non-invasive) Logan graphical analysis provided volume of distribution maps and distribution volume ratio maps with the lowest level of noise, while the basis function implementations provided the best accuracy. Tumour-to-normal ratio maps provided better results if later interval times were used, i.e. 60-90 min instead of 20-40 min, leading to lower bias (2.9% vs. 10.8%, respectively) and less noise (12.8% vs. 14.4%).

PET segmentation of bulky tumors: Strategies and workflows to improve inter-observer variability

Background

PET-based tumor delineation is an error prone and labor intensive part of image analysis. Especially for patients with advanced disease showing bulky tumor FDG load, segmentations are challenging. Reducing the amount of user-interaction in the segmentation might help to facilitate segmentation tasks especially when labeling bulky and complex tumors. Therefore, this study reports on segmentation workflows/strategies that may reduce the inter-observer variability for large tumors with complex shapes with different levels of user-interaction.

Methods

Twenty PET images of bulky tumors were delineated independently by six observers using four strategies: (I) manual, (II) interactive threshold-based, (III) interactive threshold-based segmentation with the additional presentation of the PET-gradient image and (IV) the selection of the most reasonable result out of four established semi-automatic segmentation algorithms (Select-the-best approach). The segmentations were compared using Jaccard coefficients (JC) and percentage volume differences. To obtain a reference standard, a majority vote (MV) segmentation was calculated including all segmentations of experienced observers. Performed and MV segmentations were compared regarding positive predictive value (PPV), sensitivity (SE), and percentage volume differences.

Results

The results show that with decreasing user-interaction the inter-observer variability decreases. JC values and percentage volume differences of Select-the-best and a workflow including gradient information were significantly better than the measurements of the other segmentation strategies (p-value<0.01). Interactive threshold-based and manual segmentations also result in significant lower and more variable PPV/SE values when compared with the MV segmentation.

Conclusions

FDG PET segmentations of bulky tumors using strategies with lower user-interaction showed less inter-observer variability. None of the methods led to good results in all cases, but use of either the gradient or the Select-the-best workflow did outperform the other strategies tested and may be a good candidate for fast and reliable labeling of bulky and heterogeneous tumors.

Quantification of PD-L1 Expression with 18F-BMS-986192 PET/CT in Patients with Advanced-Stage Non-Small Cell Lung Cancer

The aim of this work was to quantify the uptake of ¹⁸F-BMS-986192, a programmed cell death ligand 1 (PD-L1) adnectin PET tracer, in patients with non-small cell lung cancer. To this end, plasma input kinetic modeling of dynamic tumor uptake data with online arterial blood sampling was performed. In addition, the accuracy of simplified uptake metrics such as SUV was investigated. Methods: Data from a study with ¹⁸F-BMS-986192 in patients with advanced-stage non-small cell lung cancer eligible for nivolumab treatment were used if a dynamic scan was available and lesions were present in the field of view of the dynamic scan. After injection of ¹⁸F-BMS-986192, a 60-min dynamic PET/CT scan was started, followed by a 30-min whole-body PET/CT scan. Continuous arterial and discrete arterial and venous blood sampling were performed to determine a plasma input function. Tumor time-activity curves were fitted by several plasma input kinetic models. Simplified uptake parameters included tumor-to-blood ratio as well as several SUV measures. Results: Twenty-two tumors in 9 patients were analyzed. The arterial plasma input single-tissue reversible compartment model with fitted blood volume fraction seems to be the most preferred model as it best fitted 11 of 18 tumor time-activity curves. The distribution volume (V _T ) ranged from 0.4 to 4.8 mL⋅cm^-3 Similar values were obtained with an image-derived input function. From the simplified measures, SUV normalized for body weight at 50 and 67 min after injection correlated best with V _T , with an R ² of more than 0.9. Conclusion: A single-tissue reversible model can be used to quantify tumor uptake of the PD-L1 PET tracer ¹⁸F-BMS-986192. SUV at 60 min after injection, normalized for body weight, is an accurate simplified parameter for uptake assessment of baseline studies. To assess its predictive value for response evaluation during programmed cell death protein 1 or PD-L1 immune checkpoint inhibition, further validation of SUV against V _T based on an image-derived input function is recommended.

Quantification of 18F-fluorodeoxyglucose uptake to detect residual nodal disease in locally advanced head and neck squamous cell carcinoma after chemoradiotherapy: results from the ECLYPS study

BACKGROUND

The Hopkins criteria were introduced for nodal response evaluation after therapy in head and neck cancer, but its superiority over quantification is not yet confirmed.

METHODS

SUV_{body weight} thresholds and lesion-to-background ratios were explored in a prospective multicenter study of standardized FDG-PET/CT 12 weeks after CRT in newly diagnosed locally advanced head and neck squamous cell carcinoma (LAHNSCC) patients (ECLYPS). Reference standard was histology, negative FDG-PET/CT at 12 months after treatment or ≥ 2 years of negative follow-up. Area under the receiver operator characteristics curves (AUROC) were estimated and obtained thresholds were validated in an independent cohort of HNSCC patients (n = 127).

RESULTS

In ECLYPS, 124 patients were available for quantification. With a median follow-up of 20.4 months, 23 (18.5%) nodal neck recurrences were observed. A SUV₇₀ threshold of 2.2 (AUROC = 0.89; sensitivity = 79.7%; specificity = 80.8%) was identified as optimal metric to identify nodal recurrence within 1 year after therapy. For lesion-to-background ratios, an SUV₅₀/SUV_liver threshold of 0.96 (AUROC = 0.89; sensitivity = 79.7%; specificity = 82.8%) had the best performance. Compared with Hopkins criteria (AUROC = 0.81), SUV₇₀ and SUV₅₀/SUV_liver provided a borderline significant (p = 0.040 and p = 0.094, respectively) improvement. Validation of thresholds yielded similar AUROC values (SUV₇₀ = 0.93, SUV₅₀/SUV_liver = 0.95), and were comparable to the Hopkins score (AUROC = 0.91; not statistically significant).

CONCLUSION

FDG quantification detects nodal relapse in LAHNSCC patients. When using EARL standardized PET acquisitions and reconstruction, absolute SUV metrics (SUV₇₀ threshold 2.2) prove robust, yet ratios (SUV₅₀/SUV_liver, threshold 0.96) may be more useful in routine clinical care. In this setting, the diagnostic value of quantification is comparable to the Hopkins criteria.

TRIAL REGISTRATION

US National Library for Medicine, NCT01179360. Registered 11 August 2010, https://clinicaltrials.gov/ct2/show/NCT01179360.

Repeatability of Quantitative 18F-DCFPyL PET/CT Measurements in Metastatic Prostate Cancer

Quantitative evaluation of radiolabeled prostate-specific membrane antigen (PSMA) PET scans may be used to monitor treatment response in patients with prostate cancer (PCa). To interpret longitudinal differences in PSMA uptake, the intrinsic variability of tracer uptake in PCa lesions needs to be defined. The aim of this study was to investigate the repeatability of quantitative PET/CT measurements using ¹⁸F-DCFPyL ([2-(3-(1-carboxy-5-[(6-¹⁸F-fluoro-pyridine-3-carbonyl)-amino]-pentyl)-ureido)-pentanedioic acid], a second-generation ¹⁸F-PSMA-ligand) in patients with PCa. Methods: Twelve patients with metastatic PCa were prospectively included, of whom 2 were excluded from final analyses. Patients received 2 whole-body ¹⁸F-DCFPyL PET/CT scans (median dose, 317 MBq; uptake time, 120 min) within a median of 4 d (range, 1-11 d). After semiautomatic (isocontour-based) tumor delineation, the following lesion-based metrics were derived: mean, peak, and maximum tumor-to-blood ratio; SUV_mean, SUV_peak, and SUV_max normalized to body weight; tumor volume; and total lesion uptake (TLU). Additionally, patient-based total tumor volume (TTV) (sum of PSMA-positive tumor volumes) and total tumor burden (TTB) (sum of all lesion TLUs) were derived. Repeatability was analyzed using repeatability coefficients (RC) and intraclass correlation coefficients. Additionally, the effect of point-spread function (PSF) image reconstruction on the repeatability of uptake metrics was evaluated. Results: In total, 36 ¹⁸F-DCFPyL PET-positive lesions were analyzed (≤5 lesions per patient). The RCs for mean, peak, and maximum tumor-to-blood ratio were 31.8%, 31.7%, and 37.3%, respectively. For SUV_mean, SUV_peak, and SUV_max, the RCs were 24.4%, 25.3%, and 31.0%, respectively. All intraclass correlation coefficients were at least 0.97. Tumor volume delineations were quite repeatable, with an RC of 28.1% for individual lesion volumes and 17.0% for TTV. TTB had an RC of 23.2% and 33.4% when based on SUV_mean and mean tumor-to-blood ratio, respectively. Small lesions (<4.2 cm³) had worse repeatability for volume measurements. The repeatability of SUV_peak, TLU, and all patient-level metrics was not affected by PSF reconstruction. Conclusion: ¹⁸F-DCFPyL uptake measurements are quite repeatable and can be used for clinical validation in future treatment response assessment studies. Patient-based TTV may be preferred for multicenter studies because its repeatability was both high and robust to different image reconstructions.

Quantitative implications of the updated EARL 2019 PET-CT performance standards

PURPOSE

Recently, updated EARL specifications (EARL2) have been developed and announced. This study aims at investigating the impact of the EARL2 specifications on the quantitative reads of clinical PET-CT studies and testing a method to enable the use of the EARL2 standards whilst still generating quantitative reads compliant with current EARL standards (EARL1).

METHODS

Thirteen non-small cell lung cancer (NSCLC) and seventeen lymphoma PET-CT studies were used to derive four image datasets-the first dataset complying with EARL1 specifications and the second reconstructed using parameters as described in EARL2. For the third (EARL2F6) and fourth (EARL2F7) dataset in EARL2, respectively, 6 mm and 7 mm Gaussian post-filtering was applied. We compared the results of quantitative metrics (MATV, SUVmax, SUVpeak, SUVmean, TLG, and tumor-to-liver and tumor-to-blood pool ratios) obtained with these 4 datasets in 55 suspected malignant lesions using three commonly used segmentation/volume of interest (VOI) methods (MAX41, A50P, SUV4).

RESULTS

We found that with EARL2 MAX41 VOI method, MATV decreases by 22%, TLG remains unchanged and SUV values increase by 23-30% depending on the specific metric used. The EARL2F7 dataset produced quantitative metrics best aligning with EARL1, with no significant differences between most of the datasets (p>0.05). Different VOI methods performed similarly with regard to SUV metrics but differences in MATV as well as TLG were observed. No significant difference between NSCLC and lymphoma cancer types was observed.

CONCLUSIONS

Application of EARL2 standards can result in higher SUVs, reduced MATV and slightly changed TLG values relative to EARL1. Applying a Gaussian filter to PET images reconstructed using EARL2 parameters successfully yielded EARL1 compliant data.

[89Zr]Zr-cetuximab PET/CT as biomarker for cetuximab monotherapy in patients with RAS wild-type advanced colorectal cancer

PURPOSE

One-third of patients with RAS wild-type mCRC do not benefit from anti-EGFR monoclonal antibodies. This might be a result of variable pharmacokinetics and insufficient tumor targeting. We evaluated cetuximab tumor accumulation on [⁸⁹Zr]Zr-cetuximab PET/CT as a potential predictive biomarker and determinant for an escalating dosing strategy.

PATIENTS AND METHODS

PET/CT imaging of [⁸⁹Zr]Zr-cetuximab (37 MBq/10 mg) after a therapeutic pre-dose (500 mg/m² ≤ 2 h) cetuximab was performed at the start of treatment. Patients without visual tumor uptake underwent dose escalation and a subsequent [⁸⁹Zr]Zr-cetuximab PET/CT. Treatment benefit was defined as stable disease or response on CT scan evaluation after 8 weeks.

RESULTS

Visual tumor uptake on [⁸⁹Zr]Zr-cetuximab PET/CT was observed in 66% of 35 patients. There was no relationship between PET positivity and treatment benefit (52% versus 80% for PET-negative, P = 0.16), progression-free survival (3.6 versus 5.7 months, P = 0.15), or overall survival (7.1 versus 9.4 months, P = 0.29). However, in 67% of PET-negative patients, cetuximab dose escalation (750-1250 mg/m²) was applied, potentially influencing outcome in this group. None of the second [⁸⁹Zr]Zr-cetuximab PET/CT was positive. Eighty percent of patients without visual tumor uptake had treatment benefit, making [⁸⁹Zr]Zr-cetuximab PET/CT unsuitable as a predictive biomarker. Tumor SUV_peak did not correlate to changes in tumor size on CT (P = 0.23), treatment benefit, nor progression-free survival. Cetuximab pharmacokinetics were not related to treatment benefit. BRAF mutations, right-sidedness, and low sEGFR were correlated with intrinsic resistance to cetuximab.

CONCLUSION

Tumor uptake on [⁸⁹Zr]Zr-cetuximab PET/CT failed to predict treatment benefit in patients with RAS wild-type mCRC receiving cetuximab monotherapy. BRAF mutations, right-sidedness, and low sEGFR correlated with intrinsic resistance to cetuximab.

Updating PET/CT performance standards and PET/CT interpretation criteria should go hand in hand

This letter aims at explaining that adjusting the performance of PET/CT systems to a new standard also requires updating of interpretation criteria. Simply changing one aspect of the imaging procedure, i.e., PET/CT performance and image quality, and not adapting interpretation criteria will result in an increase of false positive (or negative) reads.

Lesion Detection and Interobserver Agreement with Advanced Image Reconstruction for 18F-DCFPyL PET/CT in Patients with Biochemically Recurrent Prostate Cancer

Biochemically recurrent prostate cancer (BCR) is the main indication to perform prostate-specific membrane antigen PET/CT. However, localizing BCR with prostate-specific membrane antigen PET/CT remains challenging in patients with low prostate-specific antigen (PSA) values. Here, we studied the impact of advanced PET image reconstruction methods on BCR localization and interobserver agreement with ¹⁸F-DCFPyL PET/CT scans in patients with BCR and low PSA values. Methods: Twenty-four patients with BCR and a PSA level of less than 2.0 ng/mL were included. PET images were reconstructed with 4-mm voxels and 2-mm voxels, both with and without point-spread function. All scans were interpreted by 4 nuclear medicine physicians. Additionally, PET examinations of 5 patients with primary prostate cancer and confirmed absence of lymph node metastases (after lymph node dissection) were included, to assess the risk of introducing false-positive findings when using advanced reconstruction. Calculation of BCR localization rates (scan positivity) was based on consensus among our readers (≥3 readers regarding a scan positive for BCR), as well as the individual scan interpretations of the readers. Results: In the consensus analysis, BCR localization rates were not higher using advanced reconstruction (62.5%-66.7%) than using 4-mm reconstruction (62.5%). On the basis of individual readings, however, more scans were positive using 2-mm reconstruction (74.0%; 95% confidence interval [CI], 65.0%-82.9%) (P = 0.027) and 2-mm reconstruction with point-spread function (75.0%; 95% CI, 66.2%-83.8%) (P = 0.014) than 4-mm reconstruction (65.6%; 95% CI, 56.0%-75.3%). A higher number of lesions was detected on the 2-mm scans (median, 2 lesions; interquartile range, 1-3) than the 4-mm scans (median, 1; interquartile range, 0-3; P = 0.008). The advanced reconstruction methods did not increase interobserver agreement (80.6%-84.7%), compared with the 4-mm scans (75.7%, P = 0.08-0.25). In the patients with primary prostate cancer, an equal number of false-positive lesions was observed among the different reconstruction methods (overall, n = 13). Conclusion: Applying advanced image reconstruction for ¹⁸F-DCFPyL PET/CT scans did not increase BCR localization in patients with BCR and low PSA values (reader consensus). Yet, the increased number of positive individual readings may imply that further development of image reconstruction methods holds potential to improve BCR localization. No improved interobserver agreement was observed with advanced reconstruction compared with standard 4-mm reconstruction.

Metabolic Biomarker-Based BRAFV600 Mutation Association and Prediction in Melanoma

The aim of this study was to associate and predict B-rapidly accelerated fibrosarcoma valine 600 (BRAFV600) mutation status with both conventional and radiomics ¹⁸F-FDG PET/CT features, while exploring several methods of feature selection in melanoma radiomics. Methods: Seventy unresectable stage III-IV melanoma patients who underwent a baseline ¹⁸F-FDG PET/CT scan were identified. Patients were assigned to the BRAFV600 group or BRAF wild-type group according to mutational status. ¹⁸F-FDG uptake quantification was performed by semiautomatic lesion delineation. Four hundred eighty radiomics features and 4 conventional PET features (SUV_max, SUV_mean, SUV_peak, and total lesion glycolysis) were extracted per lesion. Six different methods of feature selection were implemented, and 10-fold cross-validated predictive models were built for each. Model performances were evaluated with areas under the curve (AUCs) for the receiver operating characteristic curves. Results: Thirty-five BRAFV600 mutated patients (100 lesions) and 35 BRAF wild-type patients (79 lesions) were analyzed. AUCs predicting the BRAFV600 mutation varied from 0.54 to 0.62 and were susceptible to feature selection method. The best AUCs were achieved by feature selection based on literature, a penalized binary logistic regression model, and random forest model. No significant difference was found between the BRAFV600 and BRAF wild-type group in conventional PET features or predictive value. Conclusion: BRAFV600 mutation status is not associated with, nor can it be predicted with, conventional PET features, whereas radiomics features were of low predictive value (AUC = 0.62). We showed feature selection methods to influence predictive model performance, describing and evaluating 6 unique methods. Detecting BRAFV600 status in melanoma based on ¹⁸F-FDG PET/CT alone does not yet provide clinically relevant knowledge.

Sensitivity of 18F-fluorodihydrotestosterone PET-CT to count statistics and reconstruction protocol in metastatic castration-resistant prostate cancer

Objectives

Whole body [¹⁸F]-fluorodihydrotestosterone positron emission tomography ([¹⁸F]FDHT PET) imaging directly targets the androgen receptor and is a promising prognostic and predictive biomarker in metastatic castration-resistant cancer (mCRPC). To optimize [¹⁸F]FDHT PET-CT for diagnostic and response assessment purposes, we assessed how count statistics and reconstruction protocol affect its accuracy, repeatability, and lesion detectability.

Methods

Whole body [¹⁸F]FDHT PET-CT scans were acquired on an analogue PET-CT on two consecutive days in 14 mCRPC patients harbouring a total of 336 FDHT-avid lesions. Images were acquired at 45 min post-injection of 200 MBq [¹⁸F]FDHT at 3 min per bed position. List-mode PET data were split on a count-wise basis, yielding two statistically independent scans with each 50% of counts. Images were reconstructed according to current EANM Research Ltd. (EARL1, 4 mm voxel) and novel EARL2 guidelines (4 mm voxel + PSF). Per lesion, we measured SUVpeak, SUVmax, SUVmean, and contrast-to-noise ratio (CNR). SUV was normalized to dose per bodyweight as well as to the parent plasma input curve integral. Variability was assessed with repeatability coefficients (RCs).

Results

Count reduction increased liver coefficient of variation from 9.0 to 12.5% and from 10.8 to 13.2% for EARL1 and EARL2, respectively. SUVs of EARL2 images were 12.0–21.7% higher than EARL1. SUVs of 100% and 50% count data were highly correlated (R² > 0.98; slope = 0.97–1.01; ICC = 0.99–1.00). Intrascan variability was volume-dependent, and count reduction resulted in higher intrascan variability for EARL2 than EARL1 images. Intrascan RCs were lowest for SUVmean (8.5–10.6%), intermediate for SUVpeak (12.0–16.0%), and highest for SUVmax (17.8–22.2%). Count reduction increased test-retest variance non-significantly (p > 0.05) for all SUV types and normalizations. For SUVpeak at 50% of counts, RCs remained < 30% when small lesions were excluded. Splitting data reduced CNR by median 4.6% (interquartile range 1.2–8.7%) and 4.6% (interquartile range 1.2–8.7%) for EARL1 and EARL2 images, respectively.

Conclusions

Reducing [¹⁸F]FDHT PET acquisition time from 3 min to 1.5 per bed position resulted in a repeatability of SUVpeak (bodyweight) remaining ≤ 30%, which is generally acceptable for response monitoring purposes. However, EARL2 reconstruction was more affected, especially for SUVmax whose repeatability tended to exceed 30%. Lesion detectability was only slightly impaired by reducing acquisition time, which might not be clinically relevant in mCRPC.

Electronic supplementary material

The online version of this article (10.1186/s13550-019-0531-8) contains supplementary material, which is available to authorized users.

Performance Evaluation of a Semi-automated Method for [18F]FDG Uptake in Abdominal Visceral Adipose Tissue

PURPOSE

Severity of abdominal obesity and possibly levels of metabolic activity of abdominal visceral adipose tissue (VAT) are associated with an increased risk for cardiovascular disease (CVD). In this context, the purpose of the current study was to evaluate the reproducibility and repeatability of a semi-automated method for assessment of the metabolic activity of VAT using 2-deoxy-2-[¹⁸F]fluoro-D-glucose ([¹⁸F]FDG) positron emission tomography (PET)/x-ray computed tomography (CT).

PROCEDURES

Ten patients with lung cancer who underwent two baseline whole-body [¹⁸F]FDG PET/low-dose (LD) CT scans within 1 week were included. Abdominal VAT was automatically segmented using CT between levels L1-L5. The initial CT-based segmentation was further optimized using PET data with a standardized uptake value (SUV) threshold approach (range 1.0-2.5) and morphological erosion (range 0-5 pixels). The [¹⁸F]FDG uptake in SUV that was measured by the automated method was compared with manual analysis. The reproducibility and repeatability were quantified using intraclass correlation coefficients (ICCs).

RESULTS

The metabolic assessment of VAT on [¹⁸F]FDG PET/LDCT scans expressed as SUV_mean, using an automated method showed high inter and intra observer (all ICCs > 0.99) and overall repeatability (ICC = 0.98). The manual method showed reproducible inter observer (all ICCs > 0.92), but less intra observer (ICC = 0.57) and less overall repeatability (ICC = 0.78) compared with the automated method.

CONCLUSIONS

Our proposed semi-automated method provided reproducible and repeatable quantitative analysis of [¹⁸F]FDG uptake in VAT. We expect this method to aid future research regarding the role of VAT in development of CVD.

Abstract 1136: Tumor uptake and biodistribution of 89Zirconium-labeled ipilimumab in patients with metastatic melanoma during ipilimumab treatment

Introduction

Ipilimumab, a monoclonal antibody targeting CTLA-4, is approved for the treatment of metastatic melanoma and significantly improves overall survival. Because of the high costs and the potential serious toxicity of ipilimumab, it is of great importance to identify biomarkers that correlate with clinical activity and that can be used to select patients who will benefit from CTLA-4 blockade therapy.

We hypothesize that patients who do not respond to treatment with ipilimumab have lower drug levels in tumor tissues as compared to patients with a good response to therapy. In addition, we hypothesize that immune related adverse events (irAEs) are associated with high drug levels in the affected tissue. As irAEs usually occur approximately 6-8 weeks after the first injection of ipilimumab, we hypothesize that the drug levels in potentially affected tissues will increase at the second injection.

Experimental procedures

To visualize in vivo localization of ipilimumab in patients diagnosed with metastatic melanoma, 37 MBq, 10 mg 89Zr-labeled ipilimumab was injected within 2 hours after their first ipilimumab dose (3 mg/kg). Whole body PET/CT scans were obtained at 2h, 72h and 144h post injection and this procedure was repeated three weeks later at the second ipilimumab cycle. Biodistribution and tumor uptake were assessed visually by a nuclear physician. Focal uptake in tumor lesions exceeding local background was determined in volumes of interest (VOI) and SUVpeak values were obtained. Biodistribution was quantified by defining vital organs (i.e. lungs, kidneys, spleen, liver) and calculating mean %ID/kg. Blood was drawn for dosimetry and immunophenotyping at several time points during the trial. Presented here are initial results of the first three patients, up to 29 patients are planned to be included.

Results

Biodistribution of 89Zr-labeled ipilimumab showed a pattern distinctive for 89Zr-labeled antibodies with uptake in liver and spleen, as well as prolonged circulating antibody in the bloodstream corresponding to the pharmacokinetics of ipilimumab. Visual evaluation confirmed uptake of 89Zr-labeled ipilimumab in 5/12 evaluable tumor lesions, visible at both first and second injection of ipilimumab. Tumor uptake was comparable for 72h and 144h post injection with a mean of 6.9 %ID/kg (range 3.3-10.1) and a SUVpeak of 4.4 (range 2.3-8.9). There were no significant differences in tumor uptake between first and second dose of ipilimumab (mean 7.31 and 6.54 %ID/kg respectively).

Conclusions

Preliminary data of this ongoing study showed that the tracer is able to visualize and quantify uptake of ipilimumab in tumors. Correlations between tumor uptake and response to treatment will be presented. Furthermore, special interest will be given to uptake in lymphoid organs and locations for irAEs.

Citation Format: Iris H. Miedema, Gerben J. Zwezerijnen, Guus A. van Dongen, Daniëlle J. Vugts, Marc C. Huisman, Otto S. Hoekstra, Tanja D. de Gruijl, Hendrik M. Verheul, Catharina W. Menke, Alfons J. van den Eertwegh. Tumor uptake and biodistribution of 89Zirconium-labeled ipilimumab in patients with metastatic melanoma during ipilimumab treatment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1136.