A statistically optimized regional thresholding method (SORT) for bone lesion detection in 18F-NaF PET/CT imaging

Quantitative Analysis of Serial Positron Emission Tomography Imaging in Men with Metastatic Castration-resistant Prostate Cancer Treated with Enzalutamide

BACKGROUND

The emergence of positron emission tomography (PET) in prostate cancer is impacting clinical practice, but little is known about PET imaging as a tool to determine treatment failure in metastatic castration-resistant prostate cancer (mCRPC).

OBJECTIVE

To evaluate PET imaging dynamics in mCRPC patients on enzalutamide with stable computed tomography (CT) and technetium-99m (Tc99) bone scans.

DESIGN, SETTING, AND PARTICIPANTS

All patients were on treatment with enzalutamide for first-line mCRPC in a clinical trial at the National Cancer Institute (Bethesda, MD, USA). A volunteer sample had serial 18F-sodium fluoride (NaF) PET in parallel with CT and Tc99. Regions of interest (ROIs) on NaF were analyzed quantitatively for response.

INTERVENTION

Patients were randomized to enzalutamide with/without a cancer immunotherapy, Prostvac.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

A post hoc, descriptive analysis was performed comparing the changes seen on CT and Tc99 as per RECIST 1.1 with NaF PET scans including the use of a quantitative analysis.

RESULTS AND LIMITATIONS

Eighteen mCRPC patients had 67 NaF scans. A total of 233 ROIs resolved after treatment, 52 (22%) of which eventually retuned while on therapy. In all, 394 new ROIs were seen, but 112(28%) resolved subsequently. Of 18 patients, 14 had new ROIs that ultimately resolved after appearing. Many patients experienced progression in a minority of lesions, and one patient with radiation intervention to oligoprogression had a remarkable response. This study is limited by its small number of patients and post hoc nature.

CONCLUSIONS

These data highlight the dynamic nature of NaF PET in mCRPC patients treated with enzalutamide, where not all new findings were ultimately related to disease progression. This analysis also provides a potential strategy to identify and intervene in oligoprogression in prostate cancer.

PATIENT SUMMARY

In this small analysis of patients with prostate cancer on enzalutamide, changes on 18F-sodium fluoride positron emission tomography (PET) imaging were not always associated with treatment failure. Caution may be indicated when using PET imaging to determine whether new therapy is needed.

18 F-sodium fluoride positron emission tomography quantitation of bone metastases in African American and non-African American men with metastatic prostate cancer

BACKGROUND

Bone is the most common site of metastases in men with prostate cancer. The objective of this study was to explore potential racial differences in the distribution of tumor metastases in the axial and appendicular skeleton.

METHODS

We conducted a retrospective review of patients with metastatic prostate cancer to the bone as detected by 18 F-sodium fluoride positron emission tomography/computed tomography (18 F-NaF PET/CT) scans. In addition to describing patients' demographics and clinical characteristics, the metastatic bone lesions, and healthy bone regions were detected and quantified volumetrically using a quantitative imaging platform (TRAQinform IQ, AIQ Solutions).

RESULTS

Forty men met the inclusion criteria with 17 (42%) identifying as African Americans and 23 (58%) identifying as non-African Americans. Most of the patients had axial (skull, ribcage, and spine) disease. The location and the number of lesions in the skeleton of metastatic prostate cancer patients with low disease burden were not different by race.

CONCLUSIONS

In low-disease burden patients with metastatic prostate cancer, there were no overall differences by race in the location and number of lesions in axial or appendicular skeleton. Therefore, given equal access to molecular imaging, African Americans might derive similar benefits. Whether this holds true for patients with a higher disease burden or for other molecular imaging techniques is a topic for further study.

Systematic Review of Tumor Segmentation Strategies for Bone Metastases

Purpose: To investigate the segmentation approaches for bone metastases in differentiating benign from malignant bone lesions and characterizing malignant bone lesions. Method: The literature search was conducted in Scopus, PubMed, IEEE and MedLine, and Web of Science electronic databases following the guidelines of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). A total of 77 original articles, 24 review articles, and 1 comparison paper published between January 2010 and March 2022 were included in the review. Results: The results showed that most studies used neural network-based approaches (58.44%) and CT-based imaging (50.65%) out of 77 original articles. However, the review highlights the lack of a gold standard for tumor boundaries and the need for manual correction of the segmentation output, which largely explains the absence of clinical translation studies. Moreover, only 19 studies (24.67%) specifically mentioned the feasibility of their proposed methods for use in clinical practice. Conclusion: Development of tumor segmentation techniques that combine anatomical information and metabolic activities is encouraging despite not having an optimal tumor segmentation method for all applications or can compensate for all the difficulties built into data limitations.

Comparison of automated full-body bone metastases delineation methods and their corresponding prognostic power

Objective.Manual disease delineation in full-body imaging of patients with multiple metastases is often impractical due to high disease burden. However, this is a clinically relevant task as quantitative image techniques assessing individual metastases, while limited, have been shown to be predictive of treatment outcome. The goal of this work was to evaluate the efficacy of deep learning-based methods for full-body delineation of skeletal metastases and to compare their performance to existing methods in terms of disease delineation accuracy and prognostic power.Approach.1833 suspicious lesions on 37¹⁸F-NaF PET/CT scans of patients with metastatic castration-resistant prostate cancer (mCRPC) were contoured and classified as malignant, equivocal, or benign by a nuclear medicine physician. Two convolutional neural network (CNN) architectures (DeepMedic and nnUNet)were trained to delineate malignant disease regions with and without three-model ensembling. Malignant disease contours using previously established methods were obtained. The performance of each method was assessed in terms of four different tasks: (1) detection, (2) segmentation, (3) PET SUV metric correlations with physician-based data, and (4) prognostic power of progression-free survival.Main Results.The nnUnet three-model ensemble achieved superior detection performance with a mean (+/- standard deviation) sensitivity of 82.9±ccc 0.1% at the selected operating point. The nnUnet single and three-model ensemble achieved comparable segmentation performance with a mean Dice coefficient of 0.80±0.12 and 0.79±0.12, respectively, both outperforming other methods. The nnUNet ensemble achieved comparable or superior SUV metric correlation performance to gold-standard data. Despite superior disease delineation performance, the nnUNet methods did not display superior prognostic power over other methods.Significance.This work showed that CNN-based (nnUNet) methods are superior to the non-CNN methods for mCRPC disease delineation in full-body¹⁸F-NaF PET/CT. The CNN-based methods, however, do not hold greater prognostic power for predicting clinical outcome. This merits more investigation on the optimal selection of delineation methods for specific clinical tasks.

Applications of Artificial Intelligence in 18F-Sodium Fluoride Positron Emission Tomography/Computed Tomography:: Current State and Future Directions

This review discusses the current state of artificial intelligence (AI) in ¹⁸F-NaF-PET/CT imaging and the potential applications to come in diagnosis, prognostication, and improvement of care in patients with bone diseases, with emphasis on the role of AI algorithms in CT bone segmentation, relying on their prevalence in medical imaging and utility in the extraction of spatial information in combined PET/CT studies.

Radiomics for Identification and Prediction in Metastatic Prostate Cancer: A Review of Studies

Metastatic Prostate Cancer (mPCa) is associated with a poor patient prognosis. mPCa spreads throughout the body, often to bones, with spatial and temporal variations that make the clinical management of the disease difficult. The evolution of the disease leads to spatial heterogeneity that is extremely difficult to characterise with solid biopsies. Imaging provides the opportunity to quantify disease spread. Advanced image analytics methods, including radiomics, offer the opportunity to characterise heterogeneity beyond what can be achieved with simple assessment. Radiomics analysis has the potential to yield useful quantitative imaging biomarkers that can improve the early detection of mPCa, predict disease progression, assess response, and potentially inform the choice of treatment procedures. Traditional radiomics analysis involves modelling with hand-crafted features designed using significant domain knowledge. On the other hand, artificial intelligence techniques such as deep learning can facilitate end-to-end automated feature extraction and model generation with minimal human intervention. Radiomics models have the potential to become vital pieces in the oncology workflow, however, the current limitations of the field, such as limited reproducibility, are impeding their translation into clinical practice. This review provides an overview of the radiomics methodology, detailing critical aspects affecting the reproducibility of features, and providing examples of how artificial intelligence techniques can be incorporated into the workflow. The current landscape of publications utilising radiomics methods in the assessment and treatment of mPCa are surveyed and reviewed. Associated studies have incorporated information from multiple imaging modalities, including bone scintigraphy, CT, PET with varying tracers, multiparametric MRI together with clinical covariates, spanning the prediction of progression through to overall survival in varying cohorts. The methodological quality of each study is quantified using the radiomics quality score. Multiple deficits were identified, with the lack of prospective design and external validation highlighted as major impediments to clinical translation. These results inform some recommendations for future directions of the field.

Whole-Body [18F]-Fluoride PET SUV Imaging to Monitor Response to Dasatinib Therapy in Castration-Resistant Prostate Cancer Bone Metastases: Secondary Results from ACRIN 6687

ACRIN 6687, a multi-center clinical trial evaluating differential response of bone metastases to dasatinib in men with metastatic castration-resistant prostate cancer (mCRPC), used [¹⁸F]-fluoride (NaF) PET imaging. We extend previous ACRIN 6687 dynamic imaging results by examining NaF whole-body (WB) static SUV PET scans acquired after dynamic scanning. Eighteen patients underwent WB NaF imaging prior to and 12 weeks into dasatinib treatment. Regional VOI analysis of the most NaF avid bone metastases and an automated whole-body method using Quantitative Total Bone Imaging software (QTBI; AIQ Solutions, Inc., Madison, WI, USA) were used. We assessed differences in tumor and normal bone, between pre- and on-treatment dasatinib, and evaluated parameters in association with PFS and OS. Significant decrease in average SUV_max and average SUV_peak occurred in response to dasatinib. Univariate and multivariate analysis showed NaF uptake had significant association with PFS. Pharmacodynamic changes with dasatinib in tumor bone can be identified by WB NaF PET in men with mCRPC. WB PET has the benefit of examining the entire body and is less complicated than single FOV dynamic imaging.

Prostate cancer GTV delineation with biparametric MRI and 68Ga-PSMA-PET: comparison of expert contours and semi-automated methods

OBJECTIVE

The optimal method for delineation of dominant intraprostatic lesions (DIL) for targeted radiotherapy dose escalation is unclear. This study evaluated interobserver and intermodality variability of delineations on biparametric MRI (bpMRI), consisting of T₂ weighted (T₂W) and diffusion-weighted (DWI) sequences, and ⁶⁸Ga-PSMA-PET/CT; and compared manually delineated GTV contours with semi-automated segmentations based on quantitative thresholding of intraprostatic apparent diffusion coefficient (ADC) and standardised uptake values (SUV).

METHODS

16 patients who had bpMRI and PSMA-PET scanning performed prior to any treatment were eligible for inclusion. Four observers (two radiation oncologists, two radiologists) manually delineated the DIL on: (1) bpMRI (GTV_MRI), (2) PSMA-PET (GTV_PSMA) and (3) co-registered bpMRI/PSMA-PET (GTV_Fused) in separate sittings. Interobserver, intermodality and semi-automated comparisons were evaluated against consensus Simultaneous Truth and Performance Level Estimation (STAPLE) volumes, created from the relevant manual delineations of all observers with equal weighting. Comparisons included the Dice Similarity Coefficient (DSC), mean distance to agreement (MDA) and other metrics.

RESULTS

Interobserver agreement was significantly higher (p < 0.05) for GTV_PSMA (DSC: 0.822, MDA: 1.12 mm) and GTV_Fused (DSC: 0.787, MDA: 1.34 mm) than for GTV_MRI (DSC: 0.705, MDA 2.44 mm). Intermodality agreement between GTV_MRI and GTV_PSMA was low (DSC: 0.440, MDA: 4.64 mm). Agreement between semi-automated volumes and consensus GTV was low for MRI (DSC: 0.370, MDA: 8.16 mm) and significantly higher for PSMA-PET (0.571, MDA: 4.45 mm, p < 0.05).

CONCLUSION

⁶⁸Ga-PSMA-PET appears to improve interobserver consistency of DIL localisation vs bpMRI and may be more viable for simple quantitative delineation approaches; however, more sophisticated approaches to semi-automatic delineation factoring for patient- and disease-related heterogeneity are likely required.

ADVANCES IN KNOWLEDGE

This is the first study to evaluate the interobserver variability of prostate GTV delineations with co-registered bpMRI and ⁶⁸Ga-PSMA-PET.

Optimal 68Ga-PSMA and 18F-PSMA PET window levelling for gross tumour volume delineation in primary prostate cancer

PURPOSE

This study proposes optimal tracer-specific threshold-based window levels for PSMA PET-based intraprostatic gross tumour volume (GTV) contouring to reduce interobserver delineation variability.

METHODS

Nine ⁶⁸Ga-PSMA-11 and nine ¹⁸F-PSMA-1007 PET scans including GTV delineations of four expert teams (GTV_manual) and a majority-voted GTV (GTV_majority) were assessed with respect to a registered histopathological GTV (GTV_histo) as the gold standard reference. The standard uptake values (SUVs) per voxel were converted to a percentage (SUV%) relative to the SUV_max. The statistically optimised SUV% threshold (SOST) was defined as those that maximises accuracy for threshold-based contouring. A leave-one-out cross-validation receiver operating characteristic (ROC) curve analysis was performed to determine the SOST for each tracer. The SOST analysis was performed twice, first using the GTV_histo contour as training structure (GTV_SOST-H) and second using the GTV_majority contour as training structure (GTV_SOST-MA) to correct for any limited misregistration. The accuracy of both GTV_SOST-H and GTV_SOST-MA was calculated relative to GTV_histo in the 'leave-one-out' patient of each fold and compared with the accuracy of GTV_manual.

RESULTS

ROC curve analysis for ⁶⁸Ga-PSMA-11 PET revealed a median threshold of 25 SUV% (range, 22-27 SUV%) and 41 SUV% (40-43 SUV%) for GTV_SOST-H and GTV_SOST-MA, respectively. For ¹⁸F-PSMA-1007 PET, a median threshold of 42 SUV% (39-45 SUV%) for GTV_SOST-H and 44 SUV% (42-45 SUV%) for GTV_SOST-MA was found. A significant pairwise difference was observed when comparing the accuracy of the GTV_SOST-H contours with the median accuracy of the GTV_manual contours (median, - 2.5%; IQR, - 26.5-0.2%; p = 0.020), whereas no significant pairwise difference was found for the GTV_SOST-MA contours (median, - 0.3%; IQR, - 4.4-0.6%; p = 0.199).

CONCLUSIONS

Threshold-based contouring using GTV_majority-trained SOSTs achieves an accuracy comparable with manual contours in delineating GTV_histo. The median SOSTs of 41 SUV% for ⁶⁸Ga-PSMA-11 PET and 44 SUV% for ¹⁸F-PSMA-1007 PET form a base for tracer-specific window levelling.

TRIAL REGISTRATION

Clinicaltrials.gov ; NCT03327675; 31-10-2017.

Exploring Spatial-Temporal Changes in 18F-Sodium Fluoride PET/CT and Circulating Tumor Cells in Metastatic Castration-Resistant Prostate Cancer Treated With Enzalutamide

PURPOSE

Intrapatient treatment response heterogeneity is under-recognized. Quantitative total bone imaging (QTBI) using ¹⁸F-NaF positron emission tomography/computed tomography (PET/CT) scans is a tool that allows characterization of interlesional treatment response heterogeneity in bone. Understanding spatial-temporal response is important to identify individuals who may benefit from treatment beyond progression.

PATIENTS AND METHODS

Men with progressive metastatic castration-resistant prostate cancer (mCRPC) with at least two lesions on bone scintigraphy were enrolled and treated with enzalutamide 160 mg daily (ClinicalTrials.gov identifier: NCT02384382). ¹⁸F-NaF PET/CT scans were obtained at baseline (PET1), week 13 (PET2), and at the time of prostate-specific antigen (PSA) progression, standard radiographic or clinical progression, or at 2 years without progression (PET3). QTBI was used to determine lesion-level response. The primary end point was the proportion of men with at least one responding bone lesion on PET3 using QTBI.

RESULTS

Twenty-three men were enrolled. Duration on treatment ranged from 1.4 to 34.1 months. In general, global standardized uptake value (SUV) metrics decreased while on enzalutamide (PET2) and increased at the time of progression (PET3). The most robust predictor of PSA progression was change in SUV_hetero (PET1 to PET3; hazard ratio, 3.88; 95% CI, 1.24 to 12.1). Although overall functional disease burden improved during enzalutamide treatment, an increase in total burden (SUV_total) was seen at the time of progression, as measured by ¹⁸F-NaF PET/CT. All (22/22) evaluable men had at least one responding bone lesion at PET3 using QTBI.

CONCLUSION

We found that the proportion of progressing lesions was low, indicating that a substantial number of lesions appear to continue to benefit from enzalutamide beyond progression. Selective targeting of nonresponding lesions may be a reasonable approach to extend benefit.

Phase II Trial of a DNA Vaccine Encoding Prostatic Acid Phosphatase (pTVG-HP [MVI-816]) in Patients With Progressive, Nonmetastatic, Castration-Sensitive Prostate Cancer

PURPOSE

We previously reported the safety and immunologic effects of a DNA vaccine (pTVG-HP [MVI-816]) encoding prostatic acid phosphatase (PAP) in patients with recurrent, nonmetastatic prostate cancer. The current trial evaluated the effects of this vaccine on metastatic progression.

PATIENTS AND METHODS

Ninety-nine patients with castration-sensitive prostate cancer and prostate-specific antigen (PSA) doubling time (DT) of less than 12 months were randomly assigned to treatment with either pTVG-HP co-administered intradermally with 200 μg granulocyte-macrophage colony-stimulating factor (GM-CSF) adjuvant or 200 μg GM-CSF alone six times at 14-day intervals and then quarterly for 2 years. The primary end point was 2-year metastasis-free survival (MFS). Secondary and exploratory end points were median MFS, changes in PSA DT, immunologic effects, and changes in quantitative ¹⁸F-sodium fluoride (NaF) positron emission tomography/computed tomography (PET/CT) imaging.

RESULTS

Two-year MFS was not different between study arms (41.8% vaccine v 42.3%; P = .97). Changes in PSA DT and median MFS were not different between study arms (18.9 v 18.3 months; hazard ratio [HR], 1.6; P = .13). Preplanned subset analysis identified longer MFS in vaccine-treated patients with rapid (< 3 months) pretreatment PSA DT (12.0 v 6.1 months; n = 21; HR, 4.4; P = .03). PAP-specific T cells were detected in both cohorts, including multifunctional PAP-specific T-helper 1-biased T cells. Changes in total activity (total standardized uptake value) on ¹⁸F-NaF PET/CT from months 3 to 6 increased 50% in patients treated with GM-CSF alone and decreased 23% in patients treated with pTVG-HP (n = 31; P = .07).

CONCLUSION

pTVG-HP treatment did not demonstrate an overall increase in 2-year MFS in patients with castration-sensitive prostate cancer, with the possible exception of a subgroup with rapidly progressive disease. Prespecified ¹⁸F-NaF PET/CT imaging conducted in a subset of patients suggests that vaccination had detectable effects on micrometastatic bone disease. Additional trials using pTVG-HP in combination with PD-1 blockade are under way.

Impact of Anatomic Location of Bone Metastases on Prognosis in Metastatic Castration-Resistant Prostate Cancer

BACKGROUND

Whole-body assessments of ¹⁸F-NaF positron emission tomography (PET)/computed tomography (CT) provide promising quantitative imaging biomarkers of metastatic castration-resistant prostate cancer (mCRPC). This study investigated whether the distribution of metastases across anatomic regions is prognostic of progression-free survival.

PATIENTS AND METHODS

Fifty-four mCRPC patients with osseous metastases received baseline NaF PET/CT. Patients received chemotherapy (n = 16) or androgen receptor pathway inhibitors (n = 38). Semiautomated analysis using Quantitative Total Bone Imaging software extracted imaging metrics for the whole, axial, and appendicular skeleton as well as 11 skeletal regions. Five PET metrics were extracted for each region: number of lesions (N_L), standardized maximum uptake value (SUV_max), average uptake (SUV_mean), sum of uptake (SUV_total), and diseased fraction of the skeleton (volume fraction). Progression included that discovered by clinical, biochemical, or radiographic means. Univariate and multivariate Cox proportional hazard regression analyses were performed between imaging metrics and progression-free survival, and were assessed according to their hazard ratios (HR) and concordance (C)-indices.

RESULTS

The strongest univariate models of progression-free survival were pelvic N_L and SUV_max with HR = 1.80 (N_L: false discovery rate adjusted P = .001, SUV_max: adjusted P = .001). Three other region-specific metrics (axial N_L: HR = 1.59, adjusted P = .02, axial SUV_max: HR = 1.61, adjusted P = .02, and skull SUV_max: HR = 1.58, adjusted P = .04) were found to be stronger prognosticators relative to their whole-body counterparts. Multivariate model including region-specific metrics (C-index = 0.727) outperformed that of whole-body metrics (C-index = 0.705). The best performance was obtained when region-specific and whole-body metrics were included (C-index = 0.742).

CONCLUSION

Quantitative characterization of metastatic spread by anatomic location on NaF PET/CT enhances potential prognostication. Further study is warranted to optimize the prognostic and predictive value of NaF PET/CT in mCRPC patients.