Prognostic biomarkers in men with metastatic castration-resistant prostate cancer receiving [177Lu]-PSMA-617

Ferdinandus, Justin; Violet, John; Sandhu, Shahneen; Hicks, Rodney J.; Kumar, Aravind S. Ravi; Iravani, Amir; Kong, Grace; Akhurst, Tim; Thang, Sue Ping; Murphy, Declan; Williams, Scott; Hofman, Michael S

doi:10.1007/s00259-020-04723-z

Cited by 113 publications

(141 citation statements)

References 11 publications

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“…Therefore, several approaches have been proposed to quantify the total tumor volume in PSMA PET: Gafita et al had proposed qPSMA, a software which segments all malignancy suspicious lesions in PSMA PET acquisitions based on a liver specific threshold [19]. Ferdinandus et al had proposed a method in which all lesions were segmented by employing an SUV threshold of 3 [12]. Seifert et al had proposed a two-step approach in which a liver specific threshold was employed for lesion selection and a regional threshold (50% of the local SUV max ) for lesion segmentation [13].…”

Section: Discussionmentioning

confidence: 99%

“…PSMA-TV is suspected to be a negative prognosticator of survival, whereas SUV mean is suspected to be a positive prognosticator; both effects may antagonize in the PSMA-TLU biomarker [12,13]. Therefore, the TV of each lesion was divided by its SUV mean .…”

Section: Pet Image Analysismentioning

confidence: 99%

“…As Lu-PSMA therapy is applied in fixed doses and not in a disease extent adapted fashion, the tumor volume could be even more predictive of overall survival. However, there are contradictory reports on the prognostic value of the total tumor volume for patients treated by Lu-PSMA therapy: Ferdinandus et al had not observed a statistically significant correlation between PSMA-TV and overall survival in 50 patients treated with Lu-PSMA [12]. Yet, a preliminary analysis by Seifert et al found PSMA-TV to be significantly correlated with the overall survival in patients treated with Lu-PSMA [13].…”

Section: Introductionmentioning

confidence: 99%

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

Seifert

Kessel

Schlack

et al. 2020

Eur J Nucl Med Mol Imaging

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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.

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Section: Discussionmentioning

confidence: 99%

Section: Pet Image Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Seifert

Kessel

Schlack

et al. 2020

Eur J Nucl Med Mol Imaging

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“…85,[92][93][94][95] In contrast, PSMA ligand-based RNT results in on-target, off-tumor radiation exposure to salivary glands and the digestive tract and possible late renal toxicity. [63][64][65]82,[84][85][86][87] Beta particle-emitting 90 Y-and 177 Lu-labeled J591 agents have demonstrated promise as theranostic agents in clinical studies. 85,[92][93][94][95][96][97] In SPECT imaging, 90 Y-(using 111 Indium imaging) and 177 111,112 The FDA has not allowed PSA changes to be considered as an indicator of clinical benefit in prostate cancer trials.…”

Section: Recent Developments In Psma-pet Imagingmentioning

confidence: 99%

“…The median OS of months) 65. Imaging and blood biomarkers from patients on this trial were evaluated to identify any with potential prognostic value.FDG volume and PSMA intensity were identified as most prognostic of OS, followed by lactate dehydrogenase, alkaline phosphatase (ALP), and bone scan index 84. Despite already progressing to testing in a phase 3 trial, the optimal activity dose and maximum tolerated dose (MTD) for177 Lu-PSMA-617 remain undefined, and a conventional phase 1 trial was not previously performed.…”

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confidence: 99%

Meeting report from the Prostate Cancer Foundation PSMA theranostics state of the science meeting

et al. 2020

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Introduction The Prostate Cancer Foundation (PCF) convened a PCF prostate‐specific membrane antigen (PSMA) Theranostics State of the Science Meeting on 18 November 2019, at Weill Cornell Medicine, New York, NY. Methods The meeting was attended by 22 basic, translational, and clinical researchers from around the globe, with expertise in PSMA biology, development and use of PSMA theranostics agents, and clinical trials. The goal of this meeting was to discuss the current state of knowledge, the most important biological and clinical questions, and critical next steps for the clinical development of PSMA positron emission tomography (PET) imaging agents and PSMA‐targeted radionuclide agents for patients with prostate cancer. Results Several major topic areas were discussed including the biology of PSMA, the role of PSMA‐targeted PET imaging in prostate cancer, the physics and performance of different PSMA‐targeted PET imaging agents, the current state of clinical development of PSMA‐targeted radionuclide therapy (RNT) agents, the role of dosimetry in PSMA RNT treatment planning, barriers and challenges in PSMA RNT clinical development, optimization of patient selection for PSMA RNT trials, and promising combination treatment approaches with PSMA RNT. Discussion This article summarizes the presentations from the meeting for the purpose of globally disseminating this knowledge to advance the use of PSMA‐targeted theranostic agents for imaging and treatment of patients with prostate cancer.

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PSMA‐Hornet: Fully‐automated, multi‐target segmentation of healthy organs in PSMA PET/CT images

Klyuzhin,

Chaussé,

Bloise

et al. 2023

Medical Physics

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BackgroundProstate‐specific membrane antigen (PSMA) PET imaging represents a valuable source of information reflecting disease stage, response rate, and treatment optimization options, particularly with PSMA radioligand therapy. Quantification of radiopharmaceutical uptake in healthy organs from PSMA images has the potential to minimize toxicity by extrapolation of the radiation dose delivery towards personalization of therapy. However, segmentation and quantification of uptake in organs requires labor‐intensive organ delineations that are often not feasible in the clinic nor scalable for large clinical trials.PurposeIn this work we develop and test the PSMA Healthy organ segmentation network (PSMA‐Hornet), a fully‐automated deep neural net for simultaneous segmentation of 14 healthy organs representing the normal biodistribution of [18F]DCFPyL on PET/CT images. We also propose a modified U‐net architecture, a self‐supervised pre‐training method for PET/CT images, a multi‐target Dice loss, and multi‐target batch balancing to effectively train PSMA‐Hornet and similar networks.MethodsThe study used manually‐segmented [18F]DCFPyL PET/CT images from 100 subjects, and 526 similar images without segmentations. The unsegmented images were used for self‐supervised model pretraining. For supervised training, Monte‐Carlo cross‐validation was used to evaluate the network performance, with 85 subjects in each trial reserved for model training, 5 for validation, and 10 for testing. Image segmentation and quantification metrics were evaluated on the test folds with respect to manual segmentations by a nuclear medicine physician, and compared to inter‐rater agreement. The model's segmentation performance was also evaluated on a separate set of 19 images with high tumor load.ResultsWith our best model, the lowest mean Dice coefficient on the test set was 0.826 for the sublingual gland, and the highest was 0.964 for liver. The highest mean error in tracer uptake quantification was 13.9% in the sublingual gland. Self‐supervised pretraining improved training convergence, train‐to‐test generalization, and segmentation quality. In addition, we found that a multi‐target network produced significantly higher segmentation accuracy than single‐organ networks.ConclusionsThe developed network can be used to automatically obtain high‐quality organ segmentations for PSMA image analysis tasks. It can be used to reproducibly extract imaging data, and holds promise for clinical applications such as personalized radiation dosimetry and improved radioligand therapy.

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Prognostic biomarkers in men with metastatic castration-resistant prostate cancer receiving [177Lu]-PSMA-617

Cited by 113 publications

References 11 publications

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

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

Meeting report from the Prostate Cancer Foundation PSMA theranostics state of the science meeting

PSMA‐Hornet: Fully‐automated, multi‐target segmentation of healthy organs in PSMA PET/CT images

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