Phase 3 Assessment of the Automated Bone Scan Index as a Prognostic Imaging Biomarker of Overall Survival in Men With Metastatic Castration-Resistant Prostate Cancer: A Secondary Analysis of a Randomized Clinical Trial

Flare phenomenon visualized by 99mTc-bone scintigraphy has prognostic value for patients with metastatic castration-resistant prostate cancer

OBJECTIVE

This study aimed to determine the prognostic value of the flare phenomenon in patients with metastatic castration-resistant prostate cancer (mCRPC) using the bone scan index (BSI) derived from 99mTc-methylenediphosphonate (MDP) bone scintigraphy images.

METHODS

We categorized 72 patients from the PROSTAT-BSI registry with mCRPC who were followed-up for 2 years after starting docetaxel chemotherapy to groups based on pre-chemotherapy BSI values of < 1, 1-4, and > 4. We assessed the effects of the flare phenomenon (defined as a > 10% increase in the BSI within 3 months of starting chemotherapy, followed by > 10% improvement within the next 3 months) on survival using Kaplan-Meier curves and Cox proportional hazard analyses.

RESULTS

The flare phenomenon was found in 26 (36%) of the 72 patients. Prostate-specific antigen (PSA), alkaline phosphatase (ALP), and hemoglobin (Hb) levels steadily increased, then deteriorated in patients with and without flare, respectively. Elevated BSI and PSA values at 3 months after starting therapy and the absence of abiraterone or/and enzalutamide therapy led to poor 2-year overall survival (OS) in the group without flare. In contrast, no influence was noticeable in the group with flare. The results of multivariable analyses that included only factors associated with PSA and BSI showed that increased baseline BSI (hazard ratio [HR], 1.39; 95% confidence interval [CI], 1.04-1.86; P = 0.023) and PSA (HR, 7.15; 95% CI 2.13-24.04; P = 0.0015) values could be independent risk factors for patients with mCRPC without flare. However, these factors lost significance during flare. The risk for all-cause death was significantly higher among patients with BSI > 4 without, than with flare. The results of univariable analyses indicated that flare positively impacted survival (HR, 0.24; 95% CI 0.06‒0.91; P = 0.035). Multivariable analysis did not identify any factors that could predict outcomes.

CONCLUSION

Favorable prognosis, with fewer disturbances from other factors such as the use of abiraterone or/and enzalutamide, PSA changes, and BSI, was attainable in cases when the mCRPC patient demonstrated flare phenomenon. Follow-up bone scintigraphy at least every 3 months could help to determine the prognosis of patients with bone metastasis of mCRPC.

Evaluation of two-dimensional total bone uptake (2D-TBU) and bone scan index (BSI) extracted from active bone metastatic burden on the bone scintigraphy in patients with radium-223 treatment

OBJECTIVE

Radium-223 is a first alpha-emitting radionuclide treatment for metastatic castration-resistant prostate cancer (mCRPC) patients with bone metastases. Although the spread-based bone scan index (BSI) and novel index of the intensity-based two-dimensional total bone uptake (2D-TBU) from bone scintigraphy may provide useful input in radium-223 treatment, they have not been evaluated in detail yet. This study aimed to fill this gap by evaluating BSI and 2D-TBU in patients treated with radium-223.

METHODS

Twenty-seven Japanese patients with mCRPC treated with radium-223 were retrospectively analyzed. The patients were evaluated via blood tests and bone scans at baseline and 3 cycles intervals of treatment. BSI and 2D-TBU were analyzed via VSBONE BSI in terms of correlations, response to radium-223 treatment, association with treatment completion, and the Kaplan-Meier survival analysis was performed.

RESULTS

Nineteen patients (70.4%) completed six cycles of radium-223 treatment, whereas eight patients (29.6%) did not complete the treatment regimen. A significant difference in baseline BSI and 2D-TBU was observed between these groups of patients. Both BSI and 2D-TBU were highly correlated (r = 0.96, p < 0.001). Univariate analysis showed an association between radium-223 completion in median BSI and 2D-TBU values (p = 0.015) and completion percentage differences (91.7% vs. 45.5%; p = 0.027). The Kaplan-Meier product limit estimator showed that the median overall survival was 25.2 months (95% CI 14.0-33.6 months) in the completion group and 7.5 months (95% CI 3.3-14.2 months) in the without completion group (p < 0.001). The overall survival based on median cutoff levels showed a significant difference in 2D-TBU (p = 0.007), but not in BSI (p = 0.15).

CONCLUSIONS

The 2D-TBU may offer advantages over BSI in classifying patients towards radium-223 treatment based on the degree of progression of bone metastases. This study supports the importance of preliminary assessment of bone metastasis status using BSI and 2D-TBU extracted from VSBONE BSI for radium-223 treatment decisions.

Quantitative analysis of liver standardized uptake value repeatability in SPECT/CT implications for clinical practice

Purpose. The aim of this study was to assess the repeatability of the SUV normalized by liver volume (SUVL) between two liver receptor SPECT/CT studies performed on different days in patients with ICG-R15 values within normal range.Methods. 935 patients who underwent liver receptor scintigraphy between January 2010 and August 2018 were included. Patients who underwent liver resection, hepatic arterial embolization or had ICG-R15 >10% between scans were excluded, and 38 patients were finally included in the analysis. The repeatability of SUVL between scans was assessed using the intraclass correlation coefficient (ICC) (1.1) between SUVLmax, SUVLpeak and SUVLmean at the first and second scan and the additive and proportional errors from the Bland-Altman analysis.Results. In ICC (1,1), SUVLmax, SUVLpeak and SUVLmean were all greater than 0.8, indicating almost perfect repeatability; neither additive nor proportional errors were observed in the Bland-Altman analysis.Conclusions. In patients with ICG-R15 values within the normal range, the SUV Liver (SUVL) between two liver receptor SPECT/CT studies performed on different days was repeatability over time. It was suggested that the SUVL of liver receptor scintigraphy could be an indicator that could be used for follow-up over time in the assessment of liver fibrosis.

Advances in the study of S100A9 in cardiovascular diseases

Cardiovascular disease (CVD) is a group of diseases that primarily affect the heart or blood vessels, with high disability and mortality rates, posing a serious threat to human health. The causative factors, pathogenesis, and characteristics of common CVD differ, but they all involve common pathological processes such as inflammation, oxidative stress, and fibrosis. S100A9 belongs to the S100 family of calcium-binding proteins, which are mainly secreted by myeloid cells and bind to the Toll-like receptor 4 and receptor for advanced glycation end products and is involved in regulating pathological processes such as inflammatory response, fibrosis, vascular calcification, and endothelial barrier function in CVD. The latest research has found that S100A9 is a key biomarker for diagnosing and predicting various CVD. Therefore, this article reviews the latest research progress on the diagnostic and predictive, and therapeutic value of S100A9 in inflammatory-related CVD such as atherosclerosis, myocardial infarction, and arterial aneurysm and summarizes its molecular mechanisms in the progression of CVD, aiming to explore new predictive methods and to identify potential intervention targets for CVD in clinical practice.

Stability of standardized uptake values for quantitative bone SPECT for jawbone lesions: a single-center cross-sectional study

BACKGROUND

The long time required for bone uptake of radiopharmaceutical material after injection for bone scintigraphy is a burden for patients with poor health. Thus, to assess whether the uptake time could be reduced for single-photon emission computed tomography (SPECT) of the jawbone, this study evaluated differences in maximum standardized uptake values (SUVmax) within patients using SPECT imaging at 2 and 3 hours after radiopharmaceutical injection.

METHODS

A total of 33 patients undergoing treatment or in post-treatment follow-up for medication-related osteonecrosis of the jaw, who visited our hospital between July 2020 and August 2021 and could receive SPECT twice on the same day, were enrolled in the study. Patients were injected with technetium-99 m hydroxymethylene diphosphonate (Tc-99 m HMDP) intravenously. The SUVmax for healthy parietal bones and jawbone lesions were calculated from the SPECT images using quantitative analysis software, and the SUVmax were compared between 2- and 3-hour uptake times.

RESULTS

After exclusion, 30 patients were included in the study. In the 2-hour and 3-hour images, the median SUVmax of the parietal bones were 1.90 and 1.81, respectively, and those of the jawbone lesions were 9.25 and 9.39, respectively. The limits of agreement (LOA) ranged from - 0.33 to 0.25 in the parietal bones, and the %LOA ranged from - 9.8 to 17.3% in the jawbone lesions, showing high equivalence between the two uptake durations. The SUVmax showed no clinical differences between the 2- and 3-hour uptake durations for Tc-99 m HMDP SPECT of the jawbone.

CONCLUSIONS

The results of this study justify a 2-3-hour uptake window when performing quantitative SPECT of the jawbone. Therefore, the minimum uptake time can potentially be reduced to only 2 hours.

Molecular imaging reveals the heterogeneous progression of tumor cells and tumor stroma: a practice of FDG PET and FAPI PET in diagnosing PSMA-negative bone metastases of progressive prostate cancer

Tumors are often with complex and heterogeneous biological processes, such as glycometabolism and fibrosis, which are the main biochemical pathways that determine therapeutic effects. Specifically, this study aims to assess the diagnosing performance of 18F-FDG and 68Ga-FAPI-04 PET for different stages of progressive bone metastases with PSMA-negative pathology. Bone metastatic mouse model of prostate cancer was constructed via intra-bone injection of PSMA-negative prostate cancer PC3 cells. Cellular uptakes of 18F-FDG and 68Ga-FAPI-04 were separately performed on PC3, NIH-3T3 (FAP-positive) and a mixture. 68Ga-PSMA-11, 18F-FDG and 68Ga-FAPI-04 PET/CT imaging were performed at 2, 4 weeks after tumor cell transplantation. Furthermore, PSMA and FAP expression in bone metastases were assessed by immunohistochemistry, and then compared with the imageological findings. On the cellular level, the independent tracer uptake on the basis of glycometabolism and fibrosis was observed. For animal imaging, 68Ga-PSMA-11 imaging showed weak or absent tracer uptake in PSMA-negative bone metastatic lesions. In contrast, 68Ga-FAPI-04 PET of bone metastases had a higher uptake and tumor-to-muscle (T/M) ratio than 18F-FDG PET that was relative steady during the observation, but T/M ratio of fibrosis gradually decreased with increasing tumor growth, which ranged from 5.11 ± 1.26 at 2 weeks to 3.54 ± 0.23 at 4 weeks, revealing the delayed formation of tumor stroma in rapid proliferation. In addition, PET imaging results were corroborated by immunohistochemical assessment. In conclusion, molecular imaging approach revealed the heterogeneous progression of tumor cells and tumor stroma of bone metastasis of prostate cancer, and further confirming the necessity of multi-molecular imaging in cancer imaging.

Circulating and Imaging Biomarkers of Radium-223 Response in Metastatic Castration-Resistant Prostate Cancer

PURPOSE

Radium-223 improves overall survival (OS) and reduces skeletal events in patients with bone metastatic castration-resistant prostate cancer (CRPC), but relevant biomarkers are lacking. We evaluated automated bone scan index (aBSI) and circulating tumor cell (CTC) analyses as potential biomarkers of prognosis and activity.

PATIENTS AND METHODS

Patients with bone metastatic CRPC were enrolled on a prospective single-arm study of standard radium-223. 99mTc-MDP bone scan images at baseline, 2 months, and 6 months were quantitated using aBSI. CTCs at baseline, 1 month, and 2 months were enumerated and assessed for RNA expression of prostate cancer-specific genes using microfluidic enrichment followed by droplet digital polymerase chain reaction.

RESULTS

The median OS was 21.3 months in 22 patients. Lower baseline aBSI and minimal change in aBSI (<+0.7) from baseline to 2 months were each associated with better OS (P = .00341 and P = .0139, respectively). The higher baseline CTC count of ≥5 CTC/7.5 mL was associated with worse OS (median, 10.1 v 32.9 months; P = .00568). CTCs declined at 2 months in four of 15 patients with detectable baseline CTCs. Among individual genes in CTCs, baseline expression of the splice variant AR-V7 was significantly associated with worse OS (hazard ratio, 5.20 [95% CI, 1.657 to 16.31]; P = .00195). Baseline detectable AR-V7, higher aBSI, and CTC count ≥5 CTC/7.5 mL continued to have a significant independent negative impact on OS after controlling for prostate-specific antigen or alkaline phosphatase.

CONCLUSION

Quantitative bone scan assessment with aBSI and CTC analyses are prognostic markers in patients treated with radium-223. AR-V7 expression in CTCs is a particularly promising prognostic biomarker and warrants validation in larger cohorts.

Applications of Artificial Intelligence in PSMA PET/CT for Prostate Cancer Imaging

Prostate-specific membrane antigen (PSMA) positron emission tomography/computed tomography (PET/CT) has emerged as an important imaging technique for prostate cancer. The use of PSMA PET/CT is rapidly increasing, while the number of nuclear medicine physicians and radiologists to interpret these scans is limited. Additionally, there is variability in interpretation among readers. Artificial intelligence techniques, including traditional machine learning and deep learning algorithms, are being used to address these challenges and provide additional insights from the images. The aim of this scoping review was to summarize the available research on the development and applications of AI in PSMA PET/CT for prostate cancer imaging. A systematic literature search was performed in PubMed, Embase and Cinahl according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A total of 26 publications were included in the synthesis. The included studies focus on different aspects of artificial intelligence in PSMA PET/CT, including detection of primary tumor, local recurrence and metastatic lesions, lesion classification, tumor quantification and prediction/prognostication. Several studies show similar performances of artificial intelligence algorithms compared to human interpretation. Few artificial intelligence tools are approved for use in clinical practice. Major limitations include the lack of external validation and prospective design. Demonstrating the clinical impact and utility of artificial intelligence tools is crucial for their adoption in healthcare settings. To take the next step towards a clinically valuable artificial intelligence tool that provides quantitative data, independent validation studies are needed across institutions and equipment to ensure robustness.

Skeleton Segmentation on Bone Scintigraphy for BSI Computation

Bone Scan Index (BSI) is an image biomarker for quantifying bone metastasis of cancers. To compute BSI, not only the hotspots (metastasis) but also the bones have to be segmented. Most related research focus on binary classification in bone scintigraphy: having metastasis or none. Rare studies focus on pixel-wise segmentation. This study compares three advanced convolutional neural network (CNN) based models to explore bone segmentation on a dataset in-house. The best model is Mask R-CNN, which reaches the precision, sensitivity, and F1-score: 0.93, 0.87, 0.90 for prostate cancer patients and 0.92, 0.86, and 0.88 for breast cancer patients, respectively. The results are the average of 10-fold cross-validation, which reveals the reliability of clinical use on bone segmentation.

Literature review: Imaging in prostate cancer

Imaging plays an increasingly important role in the detection and characterization of prostate cancer (PC). This review summarizes the key conventional and advanced imaging modalities including multiparametric magnetic resonance imaging (MRI) and positron emission tomography (PET) imaging and tries to instruct clinicians in finding the best image modality depending on the patient`s PC-stage. We aim to give an overview of the different image modalities and their benefits and weaknesses in imaging PC. Emphasis is put on primary prostate cancer detection and staging as well as on recurrent and castration resistant prostate cancer. Results from studies using various imaging techniques are discussed and compared. For the different stages of PC, advantages and disadvantages of the different imaging modalities are discussed. Moreover, this review aims to give an outlook about upcoming, new imaging modalities and how they might be implemented in the future into clinical routine. Imaging patients suffering from PC should aim for exact diagnosis, accurate detection of PC lesions and should mirror the true tumor burden. Imaging should lead to the best patient treatment available in the current PC-stage and should avoid unnecessary therapeutic interventions. New image modalities such as long axial field of view PET/CT with photon-counting CT and radiopharmaceuticals like androgen receptor targeting radiopharmaceuticals open up new possibilities. In conclusion, PC imaging is growing and each image modality is aiming for improvement.

Assessing Therapeutic Response to Radium-223 with an Automated Bone Scan Index among Metastatic Castration-Resistant Prostate Cancer Patients: Data from Patients in the J-RAP-BSI Trial

To evaluate the usefulness of change in the automated bone scan index (aBSI) value derived from bone scintigraphy findings as an imaging biomarker for the assessment of treatment response and survival prediction in metastatic castration-resistant prostate cancer (mCRPC) patients treated with Ra-223. This study was a retrospective investigation of a Japanese cohort of 205 mCRPC patients who received Ra-223 in 14 hospitals between July 2016 and August 2020 and for whom bone scintigraphy before and after radium-223 treatment was available. Correlations of aBSI change, with changes in the serum markers alkaline phosphatase (ALP) and prostate-specific antigen (PSA) were evaluated. Additionally, the association of those changes with overall survival (OS) was assessed using the Cox proportional-hazards model and Kaplan-Meier curve results. Of the 205 patients enrolled, 165 (80.5%) completed six cycles of Ra-223. Following treatment, ALP decline (%ALP < 0%) was noted in 72.2% (148/205), aBSI decline (%aBSI < 0%) in 52.7% (108/205), and PSA decline (%PSA < 0%) in 27.8% (57/205). Furthermore, a reduction in both aBSI and ALP was seen in 87 (42.4%), a reduction in only ALP was seen in 61 (29.8%), a reduction in only aBSI was seen in 21 (10.2%), and in both aBSI and ALP increasing/stable (≥0%) was seen in 36 (17.6%) patients. Multiparametric analysis showed changes in PSA [hazard ratio (HR) 4.30, 95% confidence interval (CI) 2.32-8.77, p < 0.0001], aBSI (HR 2.22, 95%CI 1.43-3.59, p = 0.0003), and ALP (HR 2.06, 95%CI 1.35-3.14, p = 0.0008) as significant prognostic factors for OS. For mCRPC patients treated with Ra-223, aBSI change is useful as an imaging biomarker for treatment response assessment and survival prediction.

A Prognostic Risk Score for Prostate Cancer Based on PSMA PET-derived Organ-specific Tumor Volumes

Background Prostate-specific membrane antigen (PSMA) PET has high specificity in localizing primary tumors and metastases in patients with prostate cancer, but the individual overall survival probability is still difficult to estimate. Purpose To develop a prognostic risk score using PSMA PET-derived organ-specific total tumor volumes for predicting overall survival in patients with prostate cancer. Materials and Methods Men with prostate cancer who underwent PSMA PET/CT from January 2014 to December 2018 were evaluated retrospectively. All patients from center A were split into training (80%) and internal validation (20%) cohorts. Randomly selected patients from center B were used for external validation. Organ-specific tumor volumes were automatically quantified from PSMA PET scans by a neural network. A prognostic score was selected using multivariable Cox regression guided by the Akaike information criterion (AIC). The final prognostic risk score fitted on the training set was applied to both validation cohorts. Results A total of 1348 men (mean age, 70 years ± 8 [SD]) were included, with 918 patients in the training cohort, 230 in the internal validation cohort, and 200 in the external validation cohort. The median follow-up time was 55.7 months (IQR, 46.7-65.1 months; >4 years; 429 deaths occurred). A body weight-adjusted prognostic risk score integrating total, bone, and visceral tumor volumes obtained high C index values in the internal (0.82) and external (0.74) validation cohorts, as well as in patients with castration-resistant (0.75) and hormone-sensitive (0.68) disease. The fit of the statistical model for the prognostic score was improved compared with a model containing total tumor volume only (AIC, 3324 vs 3351; likelihood ratio test, P < .001). Calibration plots ascertained good model fit. Conclusion The newly developed risk score that included prostate-specific membrane antigen PET-derived organ-specific tumor volumes had good model fit for predicting overall survival in both internal and external validation cohorts. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Civelek in this issue.

Novel nomogram developed for determining suitability of metastatic castration-resistant prostate cancer patients to receive maximum benefit from radium-223 dichloride treatment-Japanese Ra-223 Therapy in Prostate Cancer using Bone Scan Index (J-RAP-BSI) Trial

PURPOSE

To develop a novel nomogram for determining radium-223 dichloride (Ra-223) treatment suitability for metastatic castration-resistant prostate cancer (mCRPC) patients.

METHODS

This Japanese Ra-223 Therapy in Prostate Cancer using Bone Scan Index (J-RAP-BSI) Trial was a retrospective multicenter investigation enrolled 258 mCRPC patients in Japan with Ra-223 treatment between June 2016 and August 2020, with bone scintigraphy findings before treatment, clinical data, and survival outcome available. A nomogram was constructed using prognostic factors for overall survival (OS) based on a least absolute shrinkage and selection operator Cox regression model. A sub-analysis was also conducted for patients meeting European Medicines Agency (EMA) guidelines.

RESULTS

Within a median of 17.4 months after initial Ra-223 treatment, 124 patients (48.1%) died from prostate cancer. Predictive factors included (1) sum of prior treatment history (score 0, never prior novel androgen receptor-targeted agents (ARTA) therapy, never prior taxane-based chemotherapy, and ever prior bisphosphonate/denosumab treatment), (2) Eastern Cooperative Oncology Group (ECOG) performance status, (3) prostate-specific antigen doubling time (PSADT), (4) hemoglobin, (5) lactate dehydrogenase (LDH), and (6) alkaline phosphatase (ALP) levels, and (7) automated bone scan index (aBSI) value based on bone scintigraphy. The nomogram using those factors showed good discrimination, with apparent and optimism-corrected Harrell's concordance index values of 0.748 and 0.734, respectively. Time-dependent area under the curve values at 1, 2, and 3 years were 0.771, 0.818, and 0.771, respectively. In 227 patients meeting EMA recommendation, the nomogram with seven factors showed good discrimination, with apparent and optimism-corrected Harrell's concordance index values of 0.722 and 0.704, respectively. Time-dependent area under the curve values at 1, 2, and 3 years were 0.747, 0.790, and 0.759, respectively.

CONCLUSION

This novel nomogram including aBSI to select mCRPC patients to receive Ra-223 with significantly prolonged OS possibility was found suitable for assisting therapeutic decision-making, regardless of EMA recommendation.

Automated quantification of PET/CT skeletal tumor burden in prostate cancer using artificial intelligence: The PET index

PURPOSE

Consistent assessment of bone metastases is crucial for patient management and clinical trials in prostate cancer (PCa). We aimed to develop a fully automated convolutional neural network (CNN)-based model for calculating PET/CT skeletal tumor burden in patients with PCa.

METHODS

A total of 168 patients from three centers were divided into training, validation, and test groups. Manual annotations of skeletal lesions in [¹⁸F]fluoride PET/CT scans were used to train a CNN. The AI model was evaluated in 26 patients and compared to segmentations by physicians and to a SUV 15 threshold. PET index representing the percentage of skeletal volume taken up by lesions was estimated.

RESULTS

There was no case in which all readers agreed on prevalence of lesions that the AI model failed to detect. PET index by the AI model correlated moderately strong to physician PET index (mean r = 0.69). Threshold PET index correlated fairly with physician PET index (mean r = 0.49). The sensitivity for lesion detection was 65-76% for AI, 68-91% for physicians, and 44-51% for threshold depending on which physician was considered reference.

CONCLUSION

It was possible to develop an AI-based model for automated assessment of PET/CT skeletal tumor burden. The model's performance was superior to using a threshold and provides fully automated calculation of whole-body skeletal tumor burden. It could be further developed to apply to different radiotracers. Objective scan evaluation is a first step toward developing a PET/CT imaging biomarker for PCa skeletal metastases.

Skull metastasis is a poor prognostic factor for prostate cancer patients with bone metastasis: a retrospective study based on a Chinese population

BACKGROUND

Skull is a relatively rare metastasis site for prostate cancer (PCa). There is no evidence regarding the prognostic indication of skull metastasis (SM) in PCa patients. In this study, we analyzed the prognostic value of SM for metastatic PCa patients receiving androgen deprivation therapy (ADT).

METHODS

107 consecutive patients were included from September 2008 to August 2021. All patients were administered with standard ADT. Abiraterone plus glucocorticoid and/or docetaxel chemotherapy were given after failure to castration-resistant prostate cancer. Clinical parameters and follow-up prognostic data were retrospectively analyzed. The association of clinical and pathological parameters with SM were analyzed. The progression-free survival (PFS) and overall survival (OS) were assessed using Kaplan-Meier analysis and Cox regression analyses.

RESULTS

Patients with SM (n = 26) had significantly higher biopsy Gleason scores, higher clinical T stage, higher prostate-specific antigen level at diagnosis, and were more likely to have high-burden metastasis and lymph node metastasis, compared with those without SM (n = 81). They also showed significantly lower level of hemoglobin, albumin and serum calcium, along with higher level of alkaline phosphatase. SM was significantly associated with shorter medium PFS (9.4 vs. 18.3 months, p < 0.001) and OS (22.2 vs. 58.2 months, p < 0.001). Cox analysis demonstrated that SM was an independent risk factor for shorter PFS (hazard ratio 2.327 [1.429-3.789], p = 0.001) and shorter OS (hazard ratio 2.810 [1.615-4.899], p < 0.001).

CONCLUSION

In this study, we found that SM was significantly correlated with more aggressive disease and indicated poor prognosis in PCa patients with bone metastasis. Our study may provide useful reference for the risk stratification of PCa patients.

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.

Novel quantitative software for automatically excluding red bone marrow on whole‐body magnetic resonance imaging in patients with metastatic prostate cancer: A pilot study

OBJECTIVES

To establish a novel quantitative method that automatically excludes the red bone marrow and accurately quantifies the tumor volume on whole-body magnetic resonance imaging using updated imaging software. To also evaluate the association between the quantified tumor volume and the prognosis of patients with metastatic prostate cancer.

METHODS

This prospective analysis included patients diagnosed with metastatic hormone-sensitive or metastatic castration-resistant prostate cancer between 2017 and 2022. We developed an imaging software (Attractive BD_Score) that analyzed whole-body diffusion-weighted and in-phase and opposed-phase T1-weighted images to automatically exclude the red bone marrow. The quantified tumor volume was compared with that quantified by traditional whole-body diffusion-weighted imaging without red bone marrow exclusion. Prostate-specific antigen progression-free survival, time-to-pain progression, and overall survival were evaluated to assess the prognostic value of the quantified tumor volume.

RESULTS

The quantified tumor volume was significantly smaller than that quantified by the traditional method in metastatic hormone-sensitive (median: 81.0 ml vs. 149.4 ml) and metastatic castration-resistant (median: 29.4 ml vs. 63.5 ml) prostate cancer. A highly quantified tumor volume was associated with prostate-specific antigen progression-free survival (p = 0.030), time-to-pain progression (p = 0.003), and overall survival (p = 0.005) in patients with metastatic hormone-sensitive prostate cancer and with poor prostate-specific antigen progression-free survival (p = 0.001) and time-to-pain progression (p = 0.005) in patients with metastatic castration-resistant prostate cancer.

CONCLUSIONS

Our imaging method could accurately quantify the tumor volume in patients with metastatic prostate cancer. The quantified tumor volume can be clinically applied as a new prognostic biomarker for metastatic prostate cancer.

The Value of Phenotypic Precision Medicine in Prostate Cancer

Prostate cancer is the most common cancer among men and the second leading cause of cancer-related death. For patients who develop metastatic disease, tissue-based and circulating-tumor-based molecular and genomic biomarkers have emerged as a means of improving outcomes through the application of precision medicine. However, the benefit is limited to a minority of patients. An additional approach to further characterize the biology of advanced prostate cancer is through the use of phenotypic precision medicine, or the identification and targeting of phenotypic features of an individual patient's cancer. In this review article, we will discuss the background, potential clinical benefits, and limitations of genomic and phenotypic precision medicine in prostate cancer. We will also highlight how the emergence of image-based phenotypic medicine may lead to greater characterization of advanced prostate cancer disease burden and more individualized treatment approaches in patients.

Clinical Significance of the Highest Regional Bone Scan Index in Patients with Metastatic Castration-Resistant Prostate Cancer

Purpose

This study evaluated the clinical utility of the highest bone scan index (BSI), among other BSIs, for each bone metastatic site in patients with bone metastatic castration-resistant prostate cancer (bmCRPC).

Methods

Thirty patients, diagnosed with bmCRPC by bone scintigraphy, were included. Total BSI, the number of hot spots, and regional BSI on each hot spot from bone scintigraphy at diagnosis with bmCRPC were evaluated by VSBONE BSI®. Highest regional BSI was defined as the highest value among regional BSIs on each hot spot in each patient. Related factors to overall survival and skeletal-related events (SREs) were evaluated using the Cox proportional-hazards model.

Results

The median follow-up time from diagnosis with bmCRPC was 29.0 months. During this time, 24 patients died, of which 22 patients died from prostate cancer. On univariate analysis, alkaline phosphatase (ALP) [Hazard ratio (HR): 5.96, 95% confidence interval (CI): 2.05-17.3] and highest regional BSI (HR: 2.01, 95% CI: 1.17-7.05) had significant correlation with overall survival. On multivariate analysis, ALP (HR: 4.79, 95% CI: 1.61-14.2) had significant correlation with overall survival. SREs were found in eight patients. Only the highest regional BSI (HR: 9.99, 95% CI: 2.46-40.6) significantly correlated with SREs on univariate analysis.

Conclusion

Highest regional BSI may provide important information regarding prognosis and SREs in patients with bmCRPC.

New index to assess the extent of bone disease in patients with prostate cancer using SPECT/CT

OBJECTIVE

Assessing the extent of bone metastases in patients with prostate cancer is very important to predict patient prognosis. Therefore, the bone scan index (BSI), which is easy to use, has been used; however, the accuracy is not that high. In this study, we proposed a new index for the extent of bone disease using single-photon emission computed tomography with computed tomography (SPECT/CT) images and assessed the accuracy of calculation.

METHODS

In this study, a total of 46 bone scans from 12 patients with prostate cancer treated for bone metastases with Radium-223 were included. Whole-body planar images were obtained 150-180 min after an intravenous injection of ^99mTc-methylene diphosphonate, and cervical-to-pelvic SPECT/CT was immediately obtained. The total bone volume (TBV) and regional metabolic bone volume (MBV) were defined as Hounsfield unit of > 120, standardized uptake value (SUV) of > 0.5, and SUV of > 5-8 in four levels, respectively. Bone metabolism volumetric index (BMVI) was calculated as the percentage of the total MBV divided by TBV. The variability of the TBV measurement was evaluated by the percentage coefficient of variance (%CV) of TBV within individual patients. We evaluated the correlation of TBV with age, height, weight, and body mass index and the correlation and agreement between BSI and BMVI.

RESULTS

The mean and %CV of TBV were 4661.7 cm³ and 2.8%, respectively, and TBV was strongly correlated with body weight. BMVI was significantly higher than BSI and correlated with alkaline phosphatase. For patients with progressive bone metastases, BSI was clearly underestimated, whereas BMVI was elevated.

CONCLUSIONS

Although assessed in a small number of cases, the new index for assessing the extent of bone disease using SPECT/CT imaging was highly value than BSI and was significantly correlated with alkaline phosphatase. Therefore, this study suggests that BMVI could improve the low sensitivity of BSI in patients with low extent of disease grade.

Serum prolactin level as a predictive factor for abiraterone response in patients with metastatic castration-resistant prostate cancer

BACKGROUND

To investigate the prognostic value and potential therapeutic target of the baseline serum hormones in patients with metastatic castration-resistant prostate cancer (mCRPC) treated with abiraterone.

METHODS

This retrospective study was performed in patients with mCRPC receiving abiraterone acetate (AA) from July 2016 to September 2020. Patients who had serum hormone tests within 2 weeks before AA treatment were included. Univariate analysis and Cox regression were performed to evaluate the correlation of sex hormones with progression-free survival (PFS) and overall survival (OS). Prolactin (PRL) expression in the clinical specimens was evaluated by immunohistochemistry. Bone metastases were quantified by automated Bone Scan Index (aBSI).

RESULTS

The study included 61 patients with a median follow-up of 19.0 months. Patients with lower baseline PRL levels (median) responded better to AA than those with higher baseline PRL levels as indicated by prostate-specific antigen (PSA) reduction (PSA90, 66.7% vs. 25.8%, p = 0.001), PFS (19.6 vs. 7.9 months), and OS (52.8 vs. 19.2 months). Cox regression adjusted for clinical factors also confirmed that baseline PRL level was an independent predictive factor for PFS (hazard ratio = 1.096, p = 0.007). Prostatic PRL expression increased as the disease progressed. PRL expression was also detected in biopsy samples from bone metastasis but not in normal bone tissue, and the serum PRL levels were positively correlated with aBSIs (r = 0.28, p = 0.037).

CONCLUSIONS

Serum PRL levels are predictive of response to AA in patients with mCRPC. Serum PRL levels are positively correlated with the volume of metastatic bone disease.

Comparison of skeletal segmentation by deep learning-based and atlas-based segmentation in prostate cancer patients

OBJECTIVE

We aimed to compare the deep learning-based (VSBONE BSI) and atlas-based (BONENAVI) segmentation accuracy that have been developed to measure the bone scan index based on skeletal segmentation.

METHODS

We retrospectively conducted bone scans for 383 patients with prostate cancer. These patients were divided into two groups: 208 patients were injected with ^99mTc-hydroxymethylene diphosphonate processed by VSBONE BSI, and 175 patients were injected with ^99mTc-methylene diphosphonate processed by BONENAVI. Three observers classified the skeletal segmentations as either a "Match" or "Mismatch" in the following regions: the skull, cervical vertebrae, thoracic vertebrae, lumbar vertebrae, pelvis, sacrum, humerus, rib, sternum, clavicle, scapula, and femur. Segmentation error was defined if two or more observers selected "Mismatch" in the same region. We calculated the segmentation error rate according to each administration group and evaluated the presence of hot spots suspected bone metastases in "Mismatch" regions. Multivariate logistic regression analysis was used to determine the association between segmentation error and variables like age, uptake time, total counts, extent of disease, and gamma cameras.

RESULTS

The regions of "Mismatch" were more common in the long tube bones for VSBONE BSI and in the pelvis and axial skeletons for BONENAVI. Segmentation error was observed in 49 cases (23.6%) with VSBONE BSI and 58 cases (33.1%) with BONENAVI. VSBONE BSI tended that "Mismatch" regions contained hot spots suspected of bone metastases in patients with multiple bone metastases and showed that patients with higher extent of disease (odds ratio = 8.34) were associated with segmentation error in multivariate logistic regression analysis.

CONCLUSIONS

VSBONE BSI has a potential to be higher segmentation accuracy compared with BONENAVI. However, the segmentation error in VSBONE BSI occurred dependent on bone metastases burden. We need to be careful when evaluating multiple bone metastases using VSBONE BSI.

Automated Classification of PET‐CT Lesions in Lung Cancer: An Independent Validation Study

Introduction

Recently, a tool called the positron emission tomography (PET)‐assisted reporting system (PARS) was developed and presented to classify lesions in PET/computed tomography (CT) studies in patients with lung cancer or lymphoma. The aim of this study was to validate PARS with an independent group of lung‐cancer patients using manual lesion segmentations as a reference standard, as well as to evaluate the association between PARS‐based measurements and overall survival (OS).

Methods

This study retrospectively included 115 patients who had undergone clinically indicated (18F)‐fluorodeoxyglucose (FDG) PET/CT due to suspected or known lung cancer. The patients had a median age of 66 years (interquartile range [IQR]: 61–72 years). Segmentations were made manually by visual inspection in a consensus reading by two nuclear medicine specialists and used as a reference. The research prototype PARS was used to automatically analyse all the PET/CT studies. The PET foci classified as suspicious by PARS were compared with the manual segmentations. No manual corrections were applied. Total lesion glycolysis (TLG) was calculated based on the manual and PARS‐based lung‐tumour segmentations. Associations between TLG and OS were investigated using Cox analysis.

Results

PARS showed sensitivities for lung tumours of 55.6% per lesion and 80.2% per patient. Both manual and PARS TLG were significantly associated with OS.

Conclusion

Automatically calculated TLG by PARS contains prognostic information comparable to manually measured TLG in patients with known or suspected lung cancer. The low sensitivity at both the lesion and patient levels makes the present version of PARS less useful to support clinical reading, reporting and staging.

Automated Bone Scan Index to Optimize Prostate Cancer Working Group Radiographic Progression Criteria for Men With Metastatic Castration-Resistant Prostate Cancer

INTRODUCTION

Radiographic progression-free survival (rPFS) by Prostate Cancer Working Group (PCWG) criteria is a radiographic endpoint. The automated bone scan index (aBSI) quantifies osseous disease burden on bone scintigraphy as a percentage of total skeletal weight. Using the aBSI, we sought to quantify increase in tumor burden represented by PCWG progression criteria, and to determine the interval increase that best associates with overall survival (OS).

PATIENT AND METHODS

Retrospective analysis of trials using androgen receptor axis-targeted drugs for metastatic castration resistant prostate cancer patients (mCRPC). aBSI increase in bone disease was assessed from baseline scan to time-to-progression (per PCWG criteria). Threshold for time to aBSI increase were explored and the association between each time-to-threshold and OS was computed.

RESULTS

A total of 169 mCPRC patients had bone scans available for aBSI analysis. Of these, 90 (53%) had progression in bone meeting PCWG criteria. Total aBSI increase in patients meeting PCWG criteria was 1.22 (interquartile range [IQR]: 0.65-2.49), with a median relative increase of 109% (IQR: 40%-377%). Median aBSI at baseline was 3.1 (IQR: 1.3-7.1). The best association between OS and time-to-progression occurred with an absolute increase in aBSI equal to 0.6 (Kendall's tau 0.52).

CONCLUSION

An absolute increase of 0.6 or more in aBSI from the first follow-up scan results in the highest association with OS in patients with mCRPC. The rPFS by PCWG, identified progression at nearly twice this tumor burden, suggesting that aBSI may be used to further develop the PCWG criteria without degrading its association with OS.

Single Cell RNA Sequencing Identifies a Unique Inflammatory Macrophage Subset as a Druggable Target for Alleviating Acute Kidney Injury

Acute kidney injury (AKI) is a complex clinical disorder associated with poor outcomes. Targeted regulation of the degree of inflammation has been a potential strategy for AKI management. Macrophages are the main effector cells of kidney inflammation. However, macrophage heterogeneity in ischemia reperfusion injury induced AKI (IRI-AKI) remains unclear. Using single-cell RNA sequencing of the mononuclear phagocytic system in the murine IRI model, the authors demonstrate the complementary roles of kidney resident macrophages (KRMs) and monocyte-derived infiltrated macrophages (IMs) in modulating tissue inflammation and promoting tissue repair. A unique population of S100a9^hi Ly6c^hi IMs is identified as an early responder to AKI, mediating the initiation and amplification of kidney inflammation. Kidney infiltration of S100A8/A9⁺ macrophages and the relevance of renal S100A8/A9 to tissue injury is confirmed in human AKI. Targeting the S100a8/a9 signaling with small-molecule inhibitors exhibits renal protective effects represented by improved renal function and reduced mortality in bilateral IRI model, and decreased inflammatory response, ameliorated kidney injury, and improved long-term outcome with decreased renal fibrosis in the unilateral IRI model. The findings support S100A8/A9 blockade as a feasible and clinically relevant therapy potentially waiting for translation in human AKI.

Comparison of 68Ga-PSMA PET/CT with fluoride PET/CT for detection of bone metastatic disease in prostate cancer

Background

¹⁸F-NaF positron emission tomography/computed tomography (fluoride PET/CT) is considered the most sensitive technique to detect bone metastasis in prostate cancer (PCa). ⁶⁸Ga-PSMA-11 (PSMA) PET/CT is increasingly used for staging of PCa. This study primarily aimed to compare the diagnostic performance of fluoride PET/CT and gallium-based PSMA PET/CT in identifying bone metastasis followed by a comparison of PSMA PET/CT with contrast-enhanced CT (CE-CT) in identifying soft tissue lesions as a secondary objective.

Methods

Twenty-eight PCa patients with high suspicion of disseminated disease following curative treatment were prospectively evaluated. PET/CT examinations using fluoride and PSMA were performed. All suspicious bone lesions were counted, and the tracer uptake was measured as standardized uptake values (SUV) for both tracers. In patients with multiple findings, ten bone lesions with highest SUV_max were selected from which identical lesions from both scans were considered for direct comparison of SUV_max. Soft tissue findings of local and lymph node lesions from CE-CT were compared with PSMA PET/CT.

Results

Both scans were negative for bone lesions in 7 patients (25%). Of 699 lesions consistent with skeletal metastasis in 21 patients on fluoride PET/CT, PSMA PET/CT identified 579 lesions (83%). In 69 identical bone lesions fluoride PET/CT showed significantly higher uptake (mean SUV_max: 73.1 ± 36.8) compared to PSMA PET/CT (34.5 ± 31.4; p < 0.001). Compared to CE-CT, PSMA PET/CT showed better diagnostic performance in locating local (96% vs 61%, p = 0.004) and lymph node (94% vs 46%, p < 0.001) metastasis.

Conclusion

In this prospective comparative study, PSMA PET/CT detected the majority of bone lesions that were positive on fluoride PET/CT. Further, this study indicates better diagnostic performance of PSMA PET/CT to locate soft tissue lesions compared to CE-CT.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41824-022-00127-4.

Correlation Between Imaging-Based Intermediate Endpoints and Overall Survival in Men With Metastatic Castration-Resistant Prostate Cancer: Analysis of 28 Randomized Trials Using the Prostate Cancer Clinical Trials Working Group (PCWG2) Criteria in 16,511 Patients

INTRODUCTION/BACKGROUND

Radiographic progression-free survival (rPFS) based on Prostate Cancer Working Group 2 (PCWG2) has been increasingly used as a meaningful imaging-based intermediate endpoint (IBIE) for overall survival (OS) in patients with metastatic castration-resistant prostate cancer (mCRPC). In randomized phase III trials, rPFS showed good correlation with OS at the individual trial level. We aimed to assess the correlation between the hazard ratios (HR) of IBIE and OS among PCWG2-based randomized trials.

MATERIALS AND METHODS

PubMed and EMBASE databases were systematically searched for randomized trials evaluating systemic treatments on mCRPC using PCWG2 up to April 15, 2020. Hazard ratios for OS and IBIEs were extracted and their correlation was assessed using weighted linear regression. Subgroup analyses were performed according to various clinical settings: prior chemotherapy, drug category, type of IBIE (rPFS vs. composite IBIE, latter defined as progression by imaging and one or a combination of PSA, pain, skeletal-related events, and performance status), and publication year.

RESULTS

Twenty-eight phase II-III randomized trials (16,511 patients) were included. Correlation between OS and IBIE was good (R² = 0.57, 95% confidence interval [CI], 0.35-0.78). Trials using rPFS showed substantially higher correlation than those using a composite IBIE (R² = 0.58, 95% CI, 0.32-0.82 vs. 0.00, 95% CI, -0.01 to 0.01). Correlations between OS and IBIE in other subgroups were at least moderate in nearly all subgroups (R² = 0.32-0.91).

CONCLUSION

IBIEs in the era of PCWG2 correlate well with OS in randomized trials for systemic drugs in patients with mCRPC. PCWG2-based rPFS should be used instead of a composite IBIE that includes PSA and other clinical variables.

Artificial intelligence applied to musculoskeletal oncology: a systematic review

Developments in artificial intelligence have the potential to improve the care of patients with musculoskeletal tumors. We performed a systematic review of the published scientific literature to identify the current state of the art of artificial intelligence applied to musculoskeletal oncology, including both primary and metastatic tumors, and across the radiology, nuclear medicine, pathology, clinical research, and molecular biology literature. Through this search, we identified 252 primary research articles, of which 58 used deep learning and 194 used other machine learning techniques. Articles involving deep learning have mostly involved bone scintigraphy, histopathology, and radiologic imaging. Articles involving other machine learning techniques have mostly involved transcriptomic analyses, radiomics, and clinical outcome prediction models using medical records. These articles predominantly present proof-of-concept work, other than the automated bone scan index for bone metastasis quantification, which has translated to clinical workflows in some regions. We systematically review and discuss this literature, highlight opportunities for multidisciplinary collaboration, and identify potentially clinically useful topics with a relative paucity of research attention. Musculoskeletal oncology is an inherently multidisciplinary field, and future research will need to integrate and synthesize noisy siloed data from across clinical, imaging, and molecular datasets. Building the data infrastructure for collaboration will help to accelerate progress towards making artificial intelligence truly useful in musculoskeletal oncology.

Reliability of Alkaline Phosphatase for Differentiating Flare Phenomenon from Disease Progression with Bone Scintigraphy

Simple Summary

Bone scintigraphy is the most widely used radionuclide technique to investigate bone metastasis, primarily due to its reasonable time and cost factor. However, it is important to recognize that bone scintigraphy to assess treatment response sometimes shows a “flare phenomenon”, which can be misinterpreted as disease progression. Distinction between flare phenomenon and disease progression could help in the decision to continue effective treatments in patients with flare phenomenon and to cease ineffective treatments and consider other salvage treatment plans in patients with disease progression. Despite many methods having been tried to answer this question, there was still no reliable way to differentiate between flare phenomenon and progression of bone metastases. Our results suggest that ALP is a useful serologic marker to differentiate flare phenomenon from disease progression on bone scintigraphy in breast or prostate cancer patients with bone metastasis.

Abstract

The flare phenomenon (FP) on bone scintigraphy after the initiation of systemic treatment seriously complicates evaluations of therapeutic response in patients with bone metastases. The aim of this study was to evaluate whether serum alkaline phosphatase (ALP) can differentiate FP from disease progression on bone scintigraphy in these patients. Breast or prostate cancer patients with bone metastases who newly underwent systemic therapy were reviewed. Pretreatment baseline and follow-up data, including age, pathologic factors, type of systemic therapy, radiologic and bone scintigraphy findings, and ALP levels, were obtained. Univariate and multivariate analyses of these factors were performed to predict FP. An increased extent and/or new lesions were found in 160 patients on follow-up bone scintigraphy after therapy. Among the 160 patients, 80 (50%) had an improvement on subsequent bone scintigraphy (BS), while subsequent scintigraphy also showed an increased uptake in 80 (50%, progression). Multiple regression analysis revealed that stable or decreased ALP was an independent predictor for FP (p < 0.0001). ALP was an independent predictor for FP on subgroup analysis for breast and prostate cancer (p = 0.001 and p = 0.0223, respectively). Results of the study suggest that ALP is a useful serologic marker to differentiate FP from disease progression on bone scintigraphy in patients with bone metastasis. Clinical interpretation for scintigraphic aggravation can be further improved by the ALP data and it may prevent fruitless changes of therapeutic modality by misdiagnosis of disease progression in cases of FP.

Precise Diagnosis and Therapy of Bone Cancer Using Near-Infrared Lights

Bone is a preferred site for both primary and metastasis tumors. Current diagnosis of osteopathia typically relies on noninvasive skeleton radiography technology. However, due to the limited resolution of ionizing radiation, accurate diagnosis and effective identification impairment areas are still lacking. Near-infrared (NIR) bioimaging, especially in the NIR-II (1000-1700 nm) regions, can provide high sensitivity and spatiotemporal resolution bioimaging compared to the conventional radiography. Thus, NIR bioimaging affords intraoperative visualization and imaging-guided surgery, aiming to overcome challenges associated with theranostics of osteopathia and bone tumors. The present review aimed to summarize the latest evidence on the use of NIR probes for the targeting bone imaging. We further highlight the recent advances in bone photoX (X presents thermal, dynamic, and immuno) therapy through NIR probes, in particular combination with other customized therapeutic agents could provide high-efficiency treatment for bone tumors.

Artificial intelligence-based measurements of PET/CT imaging biomarkers are associated with disease-specific survival of high-risk prostate cancer patients

OBJECTIVE

Artificial intelligence (AI) offers new opportunities for objective quantitative measurements of imaging biomarkers from positron-emission tomography/computed tomography (PET/CT). Clinical image reporting relies predominantly on observer-dependent visual assessment and easily accessible measures like SUV_max, representing lesion uptake in a relatively small amount of tissue. Our hypothesis is that measurements of total volume and lesion uptake of the entire tumour would better reflect the disease`s activity with prognostic significance, compared with conventional measurements.

METHODS

An AI-based algorithm was trained to automatically measure the prostate and its tumour content in PET/CT of 145 patients. The algorithm was then tested retrospectively on 285 high-risk patients, who were examined using ¹⁸F-choline PET/CT for primary staging between April 2008 and July 2015. Prostate tumour volume, tumour fraction of the prostate gland, lesion uptake of the entire tumour, and SUV_max were obtained automatically. Associations between these measurements, age, PSA, Gleason score and prostate cancer-specific survival were studied, using a Cox proportional-hazards regression model.

RESULTS

Twenty-three patients died of prostate cancer during follow-up (median survival 3.8 years). Total tumour volume of the prostate (p = 0.008), tumour fraction of the gland (p = 0.005), total lesion uptake of the prostate (p = 0.02), and age (p = 0.01) were significantly associated with disease-specific survival, whereas SUV_max (p = 0.2), PSA (p = 0.2), and Gleason score (p = 0.8) were not.

CONCLUSION

AI-based assessments of total tumour volume and lesion uptake were significantly associated with disease-specific survival in this patient cohort, whereas SUV_max and Gleason scores were not. The AI-based approach appears well-suited for clinically relevant patient stratification and monitoring of individual therapy.

Radium-223 Treatment of Patients with Metastatic Castration Resistant Prostate Cancer: Biomarkers for Stratification and Response Evaluation

Simple Summary

Radium-223 dichloride ([²²³Ra]RaCl₂; Ra-223) is an alpha-emitting radiopharmaceutical treatment for patients with metastatic castration resistant prostate cancer (mCRPC) with predominantly bone metastases. While responses to chemotherapeutic and antihormonal mCRPC treatments can be assessed by serum PSA levels, a decrease of serum PSA levels is not expected during Ra-223 therapy. Moreover, radiographic evaluation of bone metastases response is challenging. Therefore, novel biomarkers to select patients for Ra-223 treatment and monitoring response are urgently needed. In this review, we discuss the currently used and exploratory biomarkers for this purpose, including soluble and cellular factors detected in the peripheral blood, genetic defects and radiographic assessments. We conclude that some biomarkers, including metabolic products of collagen degradation and novel PET scan techniques, might hold promise as predictors of response to Ra-223 treatment. However, these biomarkers have not been extensively studied. Consequently, currently, no biomarker has established a place in patient stratification and response evaluation.

Abstract

Radium-223 dichloride ([²²³Ra]RaCl₂; Ra-223) is a targeted alpha-emitting radiopharmaceutical which results in an overall survival and health related quality of life (HRQoL) benefit in symptomatic patients with metastatic castration resistant prostate cancer (mCRPC) and predominantly bone metastasis. Although effective, options to select patients who will derive treatment benefit and to monitor and predict treatment outcomes are limited. PSA response and radiographic evaluation are commonly used in mCRPC treatment assessment but are not informative in Ra-223 treated patients. Consequently, there is a clear need for predictive and prognostic tools. In this review, we discuss the physiology of bone metastases and the mechanism of action and efficacy of Ra-223 treatment, as well as offering an outline of current innovative prognostic and predictive biomarkers.

Theranostics in oncology: What radiologists want to know

Combination of radioligand imaging and therapy, so called radiotheranostics, is a novel tool of precision oncology with proven clinical value. In-depth knowledge of functional imaging nuances is critically needed for precise prognostication and guidance of management. Here, we review theranostic applications with up to Phase III type evidence for outcome improvement: Imaging and therapy of neuroendocrine neoplasms (NEN) exploiting high levels of somatostatin receptor (SSTR) expression and radiotheranostics of prostate cancer targeting the prostate specific membrane antigen (PSMA). This narrative review focusses on these two applications and elucidates patient selection and response assessment by radioligand scintigraphy and/or positron emission tomography. Furthermore, we provide a brief outlook on future applications for novel targets outside of NEN and prostate cancer.

Prognosis of patients with prostate cancer and bone metastasis from the Japanese Prostatic Cancer Registry of Standard Hormonal and Chemotherapy Using Bone Scan Index cohort study

Objective

To determine prognostic factors including the Bone Scan Index in prostate cancer patients receiving standard hormonal therapy and chemotherapy.

Methods

This multicenter Prostatic Cancer Registry of Standard Hormonal and Chemotherapy Using Bone Scan Index study involved 30 hospitals and enrolled 247 patients (age 71 ± 8 years) with metastatic hormone‐sensitive prostate cancer (n = 148) under hormone therapy and metastatic castration‐resistant prostate cancer (n = 99) under chemotherapy. The Bone Scan Index (%) was determined by whole‐body bone scintigraphy using ^99mTc‐methylenediphosphonate. Patients were classified into tertiles and binary groups, and predictors of all‐cause death including Bone Scan Index, prostate‐specific antigen, and bone metabolic markers were determined using survival and proportional hazard analyses.

Results

During a mean follow‐up period of 716 ± 404 days, 81 (33%) of the patients died, and 3‐year mortality rates were 20% and 52% in the metastatic hormone‐sensitive prostate cancer and metastatic castration‐resistant prostate cancer groups, respectively. Survival analysis showed that a Bone Scan Index >3.5% was a significant determinant of death in the metastatic hormone‐sensitive prostate cancer group, whereas prostate‐specific antigen >55 ng/mL before chemotherapy was a determinant of prognosis in the metastatic castration‐resistant prostate cancer group. A Bone Scan Index >3.5% was also associated with a high incidence of prostate‐specific antigen progression in the metastatic hormone‐sensitive prostate cancer group. Patients with metastatic hormone‐sensitive prostate cancer and a better Bone Scan Index response (>45%) to treatment had lower mortality rates than those without such response.

Conclusion

The Bone Scan Index and hot spot number are significant determinants of 3‐year mortality, and combining the Bone Scan Index with prostate‐specific antigen should contribute to the management of prostate cancer patients with bone metastasis.

aPROMISE: A Novel Automated-PROMISE platform to Standardize Evaluation of Tumor Burden in 18F-DCFPyL (PSMA) images of Veterans with Prostate Cancer

Rationale: Standardized staging and quantitative reporting is necessary to demonstrate the association of ¹⁸F-DCFPyL PET/CT (PSMA) imaging with clinical outcome. This work introduces an automated platform to implement and extend the Prostate Cancer Molecular Imaging Standardized Evaluation (PROMISE) criteria - aPROMISE. The objective is to validate the performance of aPROMISE in staging and quantifying disease burden in patients with prostate cancer who undergo PSMA Imaging. Methods: This was a retrospective analysis of 109 Veterans with intermediate and high-risk prostate cancer, who underwent PSMA imaging. To validate the performance of aPROMISE, two independent nuclear-medicine physicians conducted aPROMISE-assisted reads, resulting in standardized reports that quantify individual lesions and stage the patients. Patients were staged as having local only disease (miN0M0); regional lymph node only (miN1M0), metastatic disease only (miN0M1), and with both regional and distant metastatic disease (miN1M1). The staging obtained from aPROMISE-assisted reads was compared with the staging by conventional imaging. Cohen's pairwise kappa agreement was used to evaluate the inter-reader variability. Correlation coefficient and ICC was used to evaluate the inter-reader variability of the quantitative assessment (miPSMA-index) in each stage. Kendall Tau and t-test was used to evaluate the association of miPSMA-index with PSA and Gleason Score. Results: All PSMA images of 109 veterans met the DICOM conformity and the requirements for the aPROMISE analysis. Both independent aPROMISE-assisted analyses demonstrated significant upstaging in patients with localized (23%; N = 20/87) and regional tumor burden (25%; N = 2/8). However, a significant number of patients with bone metastases identified on conventional imaging (NaF PET/CT) were downstaged (29%; N = 4/14). The comparison of the two independent aPROMISE-assisted reads demonstrated a high kappa agreement - 0.82 (miN0M0), 0.90 (miN1M0), and 0.77 (miN0M1). The Spearman correlation of quantitative miPSMA-index was 0.93, 0.96 and 0.97, respectively. As a continuous variable, miPSMA index in the prostate (miT) was associated with risk groups defined by the PSA and Gleason.. Conclusion: Here we demonstrate consistency of the aPROMISE platform between readers and observed substantial upstaging in PSMA imaging compared to the conventional imaging. aPROMISE may contribute to the broader standardization of PSMA imaging assessment and to its clinical utility in management of prostate cancer patients.

Pain Biomarkers in Cancer: An Overview

BACKGROUND

Pain is a common symptom in oncologic patients and its management is generally guided with reference to pain individually perceived by patients and expressed through self-reported scales. However, the utility of these tools is limited as it strongly depends on patients' opinions. For this reason, more objective instruments are desirable.

OBJECTIVE

In this overview, scientific articles indicating potential markers to be used for pain management in cancer were collected and discussed.

METHODS

Research was performed on principal electronic scientific databases by using the words "pain", "cancer", "markers" and "biomarkers" as the main keywords, and findings describing potential biomarkers for the management of cancer pain were reported.

RESULTS

Studies on pain markers not specific for cancer typology (inflammatory, genetic markers predicting response to analgesic drugs, neuroimaging markers) and pain markers for specific types of cancer (bone cancer, breast cancer, lung cancer, head and neck cancer, prostate cancer, cancer in pediatrics) have been presented and commented on.

CONCLUSION

This overview supports the view of the involvement of inflammatory mediators in the mechanisms underlying cancer pain. Only a small amount of data from research up till today is available on markers that can help in the management of pain, except for pro-inflammatory cytokines and other inflammatory indexes such as C-reactive protein (CRP). However, biomarkers are a promising strategy useful to predict pain intensity and to objectively quantify analgesic response in guiding decisions regarding individual-tailored treatments for cancer patients.

PSMA PET total tumor volume predicts outcome of patients with advanced prostate cancer receiving [177Lu]Lu-PSMA-617 radioligand therapy in a bicentric analysis

INTRODUCTION

[177Lu]Lu-PSMA-617 (Lu-PSMA) radioligand therapy is an emerging treatment option for patients with end-stage prostate cancer. However, response to Lu-PSMA therapy is only achieved in approximately half of patients. It is clinically important to identify patients at risk of poor outcome. Therefore, the aim of this study was to evaluate pretherapeutic PSMA PET derived total tumor volume and related metrics as prognosticators of overall survival in patients receiving Lu-PSMA therapy.

METHODS

A total number of 110 patients form the Departments of Nuclear Medicine Münster and Essen were included in this retrospective analysis. Baseline PSMA PET-CT was available for all patients. Employing a previously published approach, all tumor lesions were semi-automatically delineated in PSMA PET-CT acquisitions. Total lesion number, total tumor volume (PSMA-TV), total lesion uptake (PSMA-TLU = PSMA-TV * SUVmean), and total lesion quotient (PSMA-TLQ = PSMA-TV / SUVmean) were quantified for each patient. Log2 transformation was used for regressions.

RESULTS

Lesion number, PSMA-TV, and PSMA-TLQ were prognosticators of overall survival (HR = 1.255, p = 0.009; HR = 1.299, p = 0.005; HR = 1.326, p = 0.002). In a stepwise backward Cox regression including lesion number, PSMA-TV, PSA, LDH, and PSMA-TLQ, only the latter two remained independent and statistically significant negative prognosticators of overall survival (HR = 1.632, p = 0.011; HR = 1.239, p = 0.024). PSMA-TLQ and LDH were significant negative prognosticators in multivariate Cox regression in contrast to PSA value.

CONCLUSION

PSMA-TV was a statistically significant negative prognosticator of overall survival in patients receiving Lu-PSMA therapy. PSMA-TLQ was an independent and superior prognosticator of overall survival compared with PSMA-TV.

A randomized phase IIa study of quantified bone scan response in patients with metastatic castration-resistant prostate cancer (mCRPC) treated with radium-223 dichloride alone or in combination with abiraterone acetate/prednisone or enzalutamide

BACKGROUND

In metastatic castration-resistant prostate cancer (mCRPC), assessing treatment response and bone lesions with technetium-99m is limited by image resolution and subjectivity. We evaluated bone scan lesion area (BSLA), a quantitative imaging assessment of response in patients with mCRPC receiving radium-223 alone or in combination with androgen receptor pathway inhibitors (abiraterone/prednisone or enzalutamide).

PATIENTS AND METHODS

This randomized, non-comparative phase IIa three-arm trial (NCT02034552) evaluated technetium-99m-based BSLA response rate (RR), safety, radiologic progression-free survival (rPFS), and time to first symptomatic skeletal event (SSE) in men with mCRPC and bone metastases receiving radium-223 with/without abiraterone/prednisone or enzalutamide. The primary endpoint was week 24 BSLA RR.

RESULTS

Overall, 63 patients received treatment (abiraterone/prednisone combination, n = 22; enzalutamide combination, n = 22; radium-223 monotherapy, n = 19). Median treatment duration (first to last dose of any study treatment) was 12 months (abiraterone/prednisone combination), 10 months (enzalutamide combination), and 3 months (radium-223 monotherapy). Week 24 BSLA RR was 58% [80% confidence interval (CI) 41% to 74%; one-sided P < 0.0001; 11/19 patients] with abiraterone/prednisone combination, 50% (32% to 68%; one-sided P < 0.0001; 8/16 patients) with enzalutamide combination, and 22% (10% to 40%; one-sided P = 0.0109; 4/18 patients) with radium-223 monotherapy. Median rPFS was not evaluable for combination arms and 4 months (80% CI 4 to 12) for monotherapy. SSEs were reported in 32% of patients; median time to first SSE was not estimable. Fatigue and back pain were the most commonly reported treatment-emergent adverse events (TEAEs); more patients receiving combination therapy than monotherapy had TEAEs. Fractures were reported in 18% receiving abiraterone/prednisone, 32% receiving enzalutamide, and 11% receiving radium-223 monotherapy. Fracture rates were lower in patients taking bone health agents versus not taking bone health agents at baseline.

CONCLUSIONS

Technetium-99m imaging BSLA may offer objective, quantifiable assessment of isotope uptake changes, and potentially treatment response, in patients with mCRPC and bone metastases treated with radium-223 alone or in combination with abiraterone/prednisone or enzalutamide. In this largely treatment-naive population, BSLA RR was numerically lower with radium-223 monotherapy versus combination therapy, indicating a limited role as first-line treatment. Use of radium-223 should follow evidence-based treatment guidelines and the licensed indication.

Just another "Clever Hans"? Neural networks and FDG PET-CT to predict the outcome of patients with breast cancer

BACKGROUND

Manual quantification of the metabolic tumor volume (MTV) from whole-body ¹⁸F-FDG PET/CT is time consuming and therefore usually not applied in clinical routine. It has been shown that neural networks might assist nuclear medicine physicians in such quantification tasks. However, little is known if such neural networks have to be designed for a specific type of cancer or whether they can be applied to various cancers. Therefore, the aim of this study was to evaluate the accuracy of a neural network in a cancer that was not used for its training.

METHODS

Fifty consecutive breast cancer patients that underwent ¹⁸F-FDG PET/CT were included in this retrospective analysis. The PET-Assisted Reporting System (PARS) prototype that uses a neural network trained on lymphoma and lung cancer ¹⁸F-FDG PET/CT data had to detect pathological foci and determine their anatomical location. Consensus reads of two nuclear medicine physicians together with follow-up data served as diagnostic reference standard; 1072 ¹⁸F-FDG avid foci were manually segmented. The accuracy of the neural network was evaluated with regard to lesion detection, anatomical position determination, and total tumor volume quantification.

RESULTS

If PERCIST measurable foci were regarded, the neural network displayed high per patient sensitivity and specificity in detecting suspicious ¹⁸F-FDG foci (92%; CI = 79-97% and 98%; CI = 94-99%). If all FDG-avid foci were regarded, the sensitivity degraded (39%; CI = 30-50%). The localization accuracy was high for body part (98%; CI = 95-99%), region (88%; CI = 84-90%), and subregion (79%; CI = 74-84%). There was a high correlation of AI derived and manually segmented MTV (R² = 0.91; p < 0.001). AI-derived whole-body MTV (HR = 1.275; CI = 1.208-1.713; p < 0.001) was a significant prognosticator for overall survival. AI-derived lymph node MTV (HR = 1.190; CI = 1.022-1.384; p = 0.025) and liver MTV (HR = 1.149; CI = 1.001-1.318; p = 0.048) were predictive for overall survival in a multivariate analysis.

CONCLUSION

Although trained on lymphoma and lung cancer, PARS showed good accuracy in the detection of PERCIST measurable lesions. Therefore, the neural network seems not prone to the clever Hans effect. However, the network has poor accuracy if all manually segmented lesions were used as reference standard. Both the whole body and organ-wise MTV were significant prognosticators of overall survival in advanced breast cancer.

Test-retest repeatability of quantitative bone SPECT/CT

OBJECTIVE

Technological innovations in single-photon emission computed tomography (SPECT) have enabled a more accurate quantitative evaluation of the uptake, and the standardized uptake value (SUV) can be measured as a semi-quantitative value, as in positron emission tomography. Nevertheless, the reliability of the SUV of bone SPECT has not been well established. The purpose of this study is to evaluate the test-retest repeatability of the SUV of bone SPECT/CT in clinical settings.

METHODS

This prospective study recruited patients with prostate cancer planning to receive bone SPECT/CT for the evaluation of bone abnormality between August 2017 and September 2019. Bone images were acquired twice by an integrated SPECT/CT scanner (Symbia Intevo, Siemens) within a 4- to 10-day interval. The maximum SUV (SUVmax) and peak SUV (SUVpeak) were calculated for the volumes of interests on the normal bone areas, degeneration/fracture lesions, and metastatic lesions. To determine repeatability, we calculated statistical indicators, including intraclass correlation coefficient (ICC), repeatability coefficient (RC), and mean absolute percentage difference (MAPD). For the ICC, the 95% confidential interval (CI) was also calculated, and an ICC of ≥ 0.8 was defined as an almost perfect correlation.

RESULTS

Twelve male patients were enrolled in the study (58-86 years; median, 71 years), and a total of 229 volumes of the interest were included in the analyses. The ICCs were 0.968 [95% CI (0.959, 0.975)] for SUVmax and 0.976 [95% CI (0.969, 0.981)] for SUVpeak. The RCs of the relative difference were 30.7% for SUVmax and 27.6% for SUVpeak, and the MAPDs (± standardized deviation) of all lesions were 12.3 ± 9.9% for SUVmax and 11.5 ± 8.3% for SUVpeak. The RCs and the MAPDs showed comparable value with the previous report regarding repeatability studies on PET.

CONCLUSION

An almost perfect correlation was demonstrated by repeated SUVmax and SUVpeak measured by quantitative integrated SPECT/CT. The quantitative values could be reliable indicators in patient management.

PET and SPECT Imaging of the Brain: History, Technical Considerations, Applications, and Radiotracers

Advances in nuclear medicine have revolutionized our ability to accurately diagnose patients with a wide array of neurologic pathologies and provide appropriate therapy. The development of new radiopharmaceuticals has made possible the identification of regional differences in brain tissue composition and metabolism. In addition, the evolution of 3-dimensional molecular imaging followed by fusion with computed tomography and magnetic resonance imaging have allowed for more precise localization of pathologies. This review will introduce single photon emission computed tomography and positron emission tomographic imaging of the brain, including the history of their development, technical considerations, and a brief overview of pertinent radiopharmaceuticals and their applications.

Revealing Prognostic Value of Skeletal-Related Parameters in Metastatic Castration-Resistant Prostate Cancer on Overall Survival: A Systematic Review and Meta-Analysis of Randomized Controlled Trial

BACKGROUND

The skeleton is a preferred site for prostate cancer metastasis, and once metastases occur, the disease becomes incurable. Increasing evidence indicates the prognostic value of skeletal-related parameters, but remains controversial.

OBJECTIVE

To perform a systematic review of the existing literature on assessing the prognostic value of alkaline phosphatase (ALP), bone-specific alkaline phosphatase (BSAP), urinary N-telopeptide (uNTx), bone scan index (BSI), and Brief Pain Inventory Short Form (BPI-SF) score in castration-resistant prostate cancer (CRPC) patients with skeleton metastasis.

EVIDENCE ACQUISITION

PubMed, Web of Science, Cochrane Library, Medline, OVID, and Embase between 2010 and 2019 were reviewed. Key terms included randomized trials, prostate cancer, alkaline phosphatase, bone-specific alkaline phosphatase, urinary N-telopeptide, bone scan index, and Brief Pain Inventory Short Form. Data were collected, checked, and analyzed from December 2019 to March 2020. Hazard ratios (HRs) and overall survival (OS) were extracted to estimate the relationship between the above parameters and OS in patients with metastatic prostate cancer (mPCa).

EVIDENCE SYNTHESIS

A total of 1,055 studies were identified via initial screening, including 1,032 from database research and 23 from other sources. After deduplication, 164 records were further excluded according to titles and abstracts. The remaining 36 potential articles were carefully screened. In the end, 15 eligible studies syntheses, which were published between 2010 and 2019, comprised data for a total of 11,378 patients, whose mean age ranged from 66 to 72 years. The sample size ranged from 82 to 1,901 patients. And the median follow-up time ranged from 24 to 55 months. Based on 15 randomized controlled trials published between 2010 and 2019, higher ALP levels (HR = 1.60, 95% CI: 1.38-1.87 P < 0.001), higher BSAP levels (HR = 1.31, 95% CI: 1.11-1.54 P = 0.001), higher uNTx levels (HR = 1.40, 95% CI: 1.29-1.52 P < 0.001), BSI progression (HR = 1.18, 95% CI: 1.08-1.29 P < 0.001), and higher BPI-SF score (HR = 1.47, 95% CI: 1.35-1.61 P < 0.001) had an association with inferior OS.

CONCLUSIONS

Higher levels of ALP/BSAP and uNTx, a higher BPI-SF score, and progression of BSI predict inferior OS in patients with mCRPC. More randomized control trials are needed to investigate the promising value of these parameters.

Artificial intelligence-based detection of lymph node metastases by PET/CT predicts prostate cancer-specific survival

INTRODUCTION

Lymph node metastases are a key prognostic factor in prostate cancer (PCa), but detecting lymph node lesions from PET/CT images is a subjective process resulting in inter-reader variability. Artificial intelligence (AI)-based methods can provide an objective image analysis. We aimed at developing and validating an AI-based tool for detection of lymph node lesions.

METHODS

A group of 399 patients with biopsy-proven PCa who had undergone ¹⁸ F-choline PET/CT for staging prior to treatment were used to train (n = 319) and test (n = 80) the AI-based tool. The tool consisted of convolutional neural networks using complete PET/CT scans as inputs. In the test set, the AI-based lymph node detections were compared to those of two independent readers. The association with PCa-specific survival was investigated.

RESULTS

The AI-based tool detected more lymph node lesions than Reader B (98 vs. 87/117; p = .045) using Reader A as reference. AI-based tool and Reader A showed similar performance (90 vs. 87/111; p = .63) using Reader B as reference. The number of lymph node lesions detected by the AI-based tool, PSA, and curative treatment was significantly associated with PCa-specific survival.

CONCLUSION

This study shows the feasibility of using an AI-based tool for automated and objective interpretation of PET/CT images that can provide assessments of lymph node lesions comparable with that of experienced readers and prognostic information in PCa patients.

Artificial Intelligence and Machine Learning in Nuclear Medicine: Future Perspectives

Artificial intelligence and machine learning based approaches are increasingly finding their way into various areas of nuclear medicine imaging. With the technical development of new methods and the expansion to new fields of application, this trend is likely to become even more pronounced in future. Possible means of application range from automated image reading and classification to correlation with clinical outcomes and to technological applications in image processing and reconstruction. In the context of tumor imaging, that is, predominantly FDG or PSMA PET imaging but also bone scintigraphy, artificial intelligence approaches can be used to quantify the whole-body tumor volume, for the segmentation and classification of pathological foci or to facilitate the diagnosis of micro-metastases. More advanced applications aim at the correlation of image features that are derived by artificial intelligence with clinical endpoints, for example, whole-body tumor volume with overall survival. In nuclear medicine imaging of benign diseases, artificial intelligence methods are predominantly used for automated and/or facilitated image classification and clinical decision making. Automated feature selection, segmentation and classification of myocardial perfusion scintigraphy can help in identifying patients that would benefit from intervention and to forecast clinical prognosis. Automated reporting of neurodegenerative diseases such as Alzheimer's disease might be extended to early diagnosis-being of special interest, if targeted treatment options might become available. Technological approaches include artificial intelligence-based attenuation correction of PET images, image reconstruction or anatomical landmarking. Attenuation correction is of special interest for avoiding the need of a coregistered CT scan, in the process of image reconstruction artefacts might be reduced, or ultra low-dose PET images might be denoised. The development of accurate ultra low-dose PET imaging might broaden the method's applicability, for example, toward oncologic PET screening. Most artificial intelligence approaches in nuclear medicine imaging are still in early stages of development, further improvements are necessary for broad clinical applications. In this review, we describe the current trends in the context fields of body oncology, cardiac imaging, and neuroimaging while an additional section puts emphasis on technological trends. Our aim is not only to describe currently available methods, but also to place a special focus on the description of possible future developments.

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.

Prognosis and safety of radium‐223 with concurrent abiraterone acetate or enzalutamide use for metastatic castration‐resistant prostate cancer: Real‐world data of Japanese patients

Objectives

To evaluate the real‐world data on the efficacy and safety of a combination therapy with radium‐223 (Ra‐223) and second‐generation androgen‐receptor targeting agents (ARTAs), including abiraterone acetate (ABI) and enzalutamide (ENZ), among Japanese patients with bone metastatic castration‐resistant prostate cancer (CRPC).

Patients and methods

We retrospectively reviewed 79 patients with bone metastatic CRPC who were treated with Ra‐223. The number of patients with concurrent ARTA use was 24:17 receiving ABI and 7 receiving ENZ. We evaluated the overall survival (OS) according to ARTA use and compared the survival of patients treated with Ra‐223 with or without ARTA using multivariate analysis.

Results

The median survival in the entire cohort was 23.5 months. The patients receiving Ra‐223 combined with ARTA showed a tendency of better OS than patients treated with Ra‐223 alone, although no significant difference was observed (median OS, 26.5 vs 23.5 months; P = .115). A multivariate analysis showed that the extent of disease on bone scan (EOD) scores and pain at baseline were significant predictors of OS. The concurrent use of bone‐modifying agents (BMAs) was not significant for favorable OS (P = .050). However, the concurrent use of second‐generation ARTA was not a significant factor for OS. Regarding safety, a bone fracture occurred in only one (4.2%) of 24 patients treated with combined Ra‐223 and ARTA therapy.

Conclusion

Our real‐world data analysis suggested that Ra‐223 combined with a second‐generation ARTA is well tolerated in Japanese patients. The EOD score and pain at baseline are significant prognostic factors for OS, but the concurrent use of second‐generation ARTA has no influence on OS among men treated with Ra‐223. The concurrent use of BMA yields a marginally favorable OS.

A novel tool for improving the interpretation of isotope bone scans in metastatic prostate cancer

OBJECTIVES

The isotope bone scan (IBS) is the gold-standard imaging modality for detecting skeletal metastases as part of prostate cancer staging. However, its clinical utility for assessing skeletal metastatic burden is limited due to the need for subjective interpretation. We designed and tested a novel custom software tool, the Metastatic Bone Scan Tool (MetsBST), aimed at improving interpretation of IBSs, and compared its performance with that of an established software programme.

METHODS

We used IBS images from 62 patients diagnosed with prostate cancer and suspected bone metastases to design and implement MetsBST in MATLAB by defining thresholds used to identify the texture and size of metastatic bone lesions. The results of MetsBST were compared with those of the commercially available automated Bone Scan Index (aBSI) with regression analysis.

RESULTS

There was strong agreement between the MetsBST and aBSI results (R² = 0.9189). In a subregional analysis, MetsBST quantified the extent of metastatic disease in multiple bone sites in patients receiving multimodality therapy (radium-223 and external beam radiotherapy) to illustrate the differences in bone metastatic response to different treatments.

CONCLUSION

The results of MetsBST and the commercial software aBSI were highly consistent. MetsBST introduces novel clinical utility by its ability to differentiate between the responses of different bone metastases to multimodality therapies.

ADVANCES IN KNOWLEDGE

MetsBST reduces the variability in assessment of tumour burden caused by subjective interpretation. Therefore, it is a useful aid to physicians reporting nuclear medicine scans, and may improve decision-making in the treatment of metastatic prostate cancer.

Resetting the Bar of Castration Resistance - Understanding Androgen Dynamics in Therapy Resistance and Treatment Choice in Prostate Cancer

This review discusses impact of advancements in biologic understanding of prostate cancer (PCa) on definition and diagnosis of castration-resistant PCa (CRPC), predictive factors for progression to CRPC and treatment strategies. More sensitive assays confirm that bilateral orchiectomy reduces serum testosterone (T) closer to < 20 ng/dL than < 50 ng/dL, and evidence suggests that achieving T < 20 ng/dL improves outcomes and delays CRPC emergence. Regular T assessments will evaluate whether T is adequately suppressed in the setting of potential progression to CRPC, given that late dosing may result in T escape. More advanced imaging modalities and biomarker assays allow earlier detection of disease progression. Predictive factors for progression to CRPC include Gleason grade, extent of metastatic spread, germline hereditary factors such as gene mutations affecting androgen receptor amplification or DNA repair deficiency mutations, prostate-specific antigen kinetics, and biomarker analyses. Treatment options for CRPC have expanded beyond androgen deprivation therapy to include therapies that suppress T or inhibit its activity through varying mechanisms. Future directions include therapies with novel biological targets, drug combinations and personalized treatments. Advanced PCa management aims to delay progression to CRPC and prolong survival. With redefinition of castration and advancements in understanding of the biology of disease progression, diagnosis and treatment strategies should be re-evaluated. Definition of CRPC could be updated to reflect the T < 20 ng/dL requirement as this is a 'true' castrate level and may improve outcomes. It is important that androgen deprivation therapy as foundational therapy is continued even as new CRPC therapies are introduced.