Publications by authors named "Ralph A Bundschuh"

60 Publications

Evaluating a Machine Learning Tool for the Classification of Pathological Uptake in Whole-Body PSMA-PET-CT Scans.

Tomography 2021 07 29;7(3):301-312. Epub 2021 Jul 29.

Department of Nuclear Medicine, University Hospital Bonn, 53127 Bonn, Germany.

The importance of machine learning (ML) in the clinical environment increases constantly. Differentiation of pathological from physiological tracer-uptake in positron emission tomography/computed tomography (PET/CT) images is considered time-consuming and attention intensive, hence crucial for diagnosis and treatment planning. This study aimed at comparing and validating supervised ML algorithms to classify pathological uptake in prostate cancer (PC) patients based on prostate-specific membrane antigen (PSMA)-PET/CT. Retrospective analysis of Ga-PSMA-PET/CTs of 72 PC patients resulted in a total of 77 radiomics features from 2452 manually delineated hotspots for training and labeled pathological (1629) or physiological (823) as ground truth (GT). As the held-out test dataset, 331 hotspots (path.:128, phys.: 203) were delineated in 15 other patients. Three ML classifiers were trained and ranked to assess classification performance. As a result, a high overall average performance (area under the curve (AUC) of 0.98) was achieved, especially to detect pathological uptake (0.97 mean sensitivity). However, there is still room for improvement to detect physiological uptake (0.82 mean specificity), especially for glands. The ML algorithm applied to manually delineated lesions predicts hotspot labels with high accuracy on unseen data and may be an important tool to assist in clinical diagnosis.
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http://dx.doi.org/10.3390/tomography7030027DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8396250PMC
July 2021

Narrative review of generative adversarial networks in medical and molecular imaging.

Ann Transl Med 2021 May;9(9):821

The Russell H. Morgan Department of Radiology and Radiological Science, Division of Nuclear Medicine and Molecular Imaging, Johns Hopkins School of Medicine, Baltimore, MD, USA.

Recent years have witnessed a rapidly expanding use of artificial intelligence and machine learning in medical imaging. Generative adversarial networks (GANs) are techniques to synthesize images based on artificial neural networks and deep learning. In addition to the flexibility and versatility inherent in deep learning on which the GANs are based, the potential problem-solving ability of the GANs has attracted attention and is being vigorously studied in the medical and molecular imaging fields. Here this narrative review provides a comprehensive overview for GANs and discuss their usefulness in medical and molecular imaging on the following topics: (I) data augmentation to increase training data for AI-based computer-aided diagnosis as a solution for the data-hungry nature of such training sets; (II) modality conversion to complement the shortcomings of a single modality that reflects certain physical measurement principles, such as from magnetic resonance (MR) to computed tomography (CT) images or vice versa; (III) de-noising to realize less injection and/or radiation dose for nuclear medicine and CT; (IV) image reconstruction for shortening MR acquisition time while maintaining high image quality; (V) super-resolution to produce a high-resolution image from low-resolution one; (VI) domain adaptation which utilizes knowledge such as supervised labels and annotations from a source domain to the target domain with no or insufficient knowledge; and (VII) image generation with disease severity and radiogenomics. GANs are promising tools for medical and molecular imaging. The progress of model architectures and their applications should continue to be noteworthy.
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http://dx.doi.org/10.21037/atm-20-6325DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8246192PMC
May 2021

Decision-support for treatment with Lu-PSMA: machine learning predicts response with high accuracy based on PSMA-PET/CT and clinical parameters.

Ann Transl Med 2021 May;9(9):818

Department of Nuclear Medicine, University Hospital Bonn, Bonn, Germany.

Background: Treatment with radiolabeled ligands to prostate-specific membrane antigen (PSMA) is gaining importance in the treatment of patients with advanced prostate carcinoma. Previous imaging with positron emission tomography/computed tomography (PET/CT) is mandatory. The aim of this study was to investigate the role of radiomics features in PSMA-PET/CT scans and clinical parameters to predict response to Lu-PSMA treatment given just baseline PSMA scans using state-of-the-art machine learning (ML) methods.

Methods: A total of 2,070 pathological hotspots annotated in 83 prostate cancer patients undergoing PSMA therapy were analyzed. Two main tasks are performed: (I) analyzing correlation of averaged (per patient) values of radiomics features of individual hotspots and clinical parameters with difference in prostate specific antigen levels (ΔPSA) in pre- and post-therapy as a therapy response indicator. (II) ML-based classification of patients into responders and non-responders based on averaged features values and clinical parameters. To achieve this, machine learning (ML) algorithms and linear regression tests are applied. Grid search, cross validation (CV) and permutation test were performed to assure that the results were significant.

Results: Radiomics features (PET_Min, PET_Correlation, CT_Min, CT_Busyness and CT_Coarseness) and clinical parameters such as Alp1 and Gleason score showed best correlations with ΔPSA. For the treatment response prediction task, 80% area under the curve (AUC), 75% sensitivity (SE), and 75% specificity (SP) were obtained, applying ML support vector machine (SVM) classifier with radial basis function (RBF) kernel on a selection of radiomics features and clinical parameters with strong correlations with ΔPSA.

Conclusions: Machine learning based on Ga-PSMA PET/CT radiomics features holds promise for the prediction of response to Lu-PSMA treatment, given only base-line Ga-PSMA scan. In addition, it was shown that, the best correlating set of radiomics features with ΔPSA are superior to clinical parameters for this therapy response prediction task using ML classifiers.
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http://dx.doi.org/10.21037/atm-20-6446DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8246232PMC
May 2021

Longterm Survial after Re-challenge with Radiumdichlorid - a Case Report.

Nuklearmedizin 2021 Aug 18;60(4):299-301. Epub 2021 Feb 18.

Klinik und Poliklinik für Nuklearmedizin, Universitätsklinikum Bonn, Bonn, Germany.

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http://dx.doi.org/10.1055/a-1345-3150DOI Listing
August 2021

Estimating the Potential of Radiomics Features and Radiomics Signature from Pretherapeutic PSMA-PET-CT Scans and Clinical Data for Prediction of Overall Survival When Treated with Lu-PSMA.

Diagnostics (Basel) 2021 Jan 28;11(2). Epub 2021 Jan 28.

Department of Nuclear Medicine, University Hospital Bonn, 53127 Bonn, Germany.

Prostate-specific membrane antigen (PSMA) positron emission tomography/computed tomography (PSMA-PET/CT) scans can facilitate diagnosis and treatment of prostate disease. Radiomics signature (RS) is widely used for the analysis of overall survival (OS) in cancer diseases. This study aims at investigating the role of radiomics features (RFs) and RS from pretherapeutic gallium-68 (Ga)-PSMA-PET/CT findings and patient-specific clinical parameters to analyze overall survival of prostate cancer (PC) patients when treated with lutethium-177 (Lu)-PSMA. A cohort of 83 patients with advanced PC was retrospectively analyzed. Average values of 73 RFs of 2070 malignant hotspots as well as 22 clinical parameters were analyzed for each patient. From the Cox proportional hazard model, the least absolute shrinkage and selection operator (LASSO) regularization method is used to select most relevant features (standardized uptake value (SUV) and kurtosis with the coefficients of 0.984 and -0.118, respectively) and to calculate the RS from the RFs. Kaplan-Meier (KM) estimator was used to analyze the potential of RFs and conventional clinical parameters, such as metabolic tumor volume (MTV) and standardized uptake value (SUV) for the prediction of survival. As a result, SUV, kurtosis, the calculated RS, SUV, as well as Hemoglobin (Hb)1, C-reactive protein (CRP)1, and ECOG1 (clinical parameters) achieved -values less than 0.05, which suggest the potential of findings from Ga-PSMA-PET/CT scans as well as patient-specific clinical parameters for the prediction of OS for patients with advanced PC treated with Lu-PSMA therapy.
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http://dx.doi.org/10.3390/diagnostics11020186DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7912143PMC
January 2021

Machine learning-based differentiation between multiple sclerosis and glioma WHO II°-IV° using O-(2-[18F] fluoroethyl)-L-tyrosine positron emission tomography.

J Neurooncol 2021 Apr 27;152(2):325-332. Epub 2021 Jan 27.

Division of Clinical Neurooncology, Department of Neurology, University Hospital Essen, University Duisburg-Essen, Hufelandstrasse 55, 45147, Essen, Germany.

Introduction: This study aimed to test the diagnostic significance of FET-PET imaging combined with machine learning for the differentiation between multiple sclerosis (MS) and glioma II°-IV°.

Methods: Our database was screened for patients in whom FET-PET imaging was performed for the diagnostic workup of newly diagnosed lesions evident on MRI and suggestive of glioma. Among those, we identified patients with histologically confirmed glioma II°-IV°, and those who later turned out to have MS. For each group, tumor-to-brain ratio (TBR) derived features of FET were determined. A support vector machine (SVM) based machine learning algorithm was constructed to enhance classification ability, and Receiver Operating Characteristic (ROC) analysis with area under the curve (AUC) metric served to ascertain model performance.

Results: A total of 41 patients met selection criteria, including seven patients with MS and 34 patients with glioma. TBR values were significantly higher in the glioma group (TBRmax glioma vs. MS: p = 0.002; TBRmean glioma vs. MS: p = 0.014). In a subgroup analysis, TBR values significantly differentiated between MS and glioblastoma (TBRmax glioblastoma vs. MS: p = 0.0003, TBRmean glioblastoma vs. MS: p = 0.0003) and between MS and oligodendroglioma (ODG) (TBRmax ODG vs. MS: p = 0.003; TBRmean ODG vs. MS: p = 0.01). The ability to differentiate between MS and glioma II°-IV° increased from 0.79 using standard TBR analysis to 0.94 using a SVM based machine learning algorithm.

Conclusions: FET-PET imaging may help differentiate MS from glioma II°-IV° and SVM based machine learning approaches can enhance classification performance.
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http://dx.doi.org/10.1007/s11060-021-03701-1DOI Listing
April 2021

High Interobserver Agreement for the Standardized Reporting System SSTR-RADS 1.0 on Somatostatin Receptor PET/CT.

J Nucl Med 2021 04 28;62(4):514-520. Epub 2020 Aug 28.

Nuclear Medicine, Medical Faculty, University of Augsburg, Augsburg, Germany.

Recently, a standardized framework system for interpreting somatostatin receptor (SSTR)-targeted PET/CT, termed the SSTR reporting and data system (RADS) 1.0, was introduced, providing reliable standards and criteria for SSTR-targeted imaging. We determined the interobserver reliability of SSTR-RADS for interpretation of Ga-DOTATOC PET/CT scans in a multicentric, randomized setting. A set of 51 randomized Ga-DOTATOC PET/CT scans was independently assessed by 4 masked readers with different levels of experience (2 experienced readers and 2 inexperienced readers) trained on the SSTR-RADS 1.0 criteria (based on a 5-point scale from 1 [definitively benign] to 5 [high certainty that neuroendocrine neoplasia is present]). For each scan, SSTR-RADS scores were assigned to a maximum of 5 target lesions (TLs). An overall scan impression based on SSTR-RADS was indicated, and interobserver agreement rates on a TL-based, on an organ-based, and on an overall SSTR-RADS score-based level were computed. The readers were also asked to decide whether peptide receptor radionuclide therapy (PRRT) should be considered on the basis of the assigned RADS scores. Among the selected TLs, 153 were chosen by at least 2 readers (all 4 readers selected the same TLs in 58 of 153 [37.9%] instances). The interobserver agreement for SSTR-RADS scoring among identical TLs was good (intraclass correlation coefficient [ICC] ≥ 0.73 for 4, 3, and 2 identical TLs). For lymph node and liver lesions, excellent interobserver agreement rates were derived (ICC, 0.91 and 0.77, respectively). Moreover, the interobserver agreement for an overall scan impression based on SSTR-RADS was excellent (ICC, 0.88). The SSTR-RADS-based decision to use PRRT also demonstrated excellent agreement, with an ICC of 0.80. No significant differences between experienced and inexperienced readers for an overall scan impression and TL-based SSTR-RADS scoring were observed ( ≥ 0.18), thereby suggesting that SSTR-RADS seems to be readily applicable even for less experienced readers. SSTR-RADS-guided assessment demonstrated a high concordance rate, even among readers with different levels of experience, supporting the adoption of SSTR-RADS for trials, clinical routine, or outcome studies.
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http://dx.doi.org/10.2967/jnumed.120.245464DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8049367PMC
April 2021

Machine Learning Facilitates Hotspot Classification in PSMA-PET/CT with Nuclear Medicine Specialist Accuracy.

Diagnostics (Basel) 2020 Aug 22;10(9). Epub 2020 Aug 22.

Department of Nuclear Medicine, University Hospital Bonn, 53127 Bonn, Germany.

Gallium-68 prostate-specific membrane antigen positron emission tomography Ga-PSMA-PET) is a highly sensitive method to detect prostate cancer (PC) metastases. Visual discrimination between malignant and physiologic/unspecific tracer accumulation by a nuclear medicine (NM) specialist is essential for image interpretation. In the future, automated machine learning (ML)-based tools will assist physicians in image analysis. The aim of this work was to develop a tool for analysis of Ga-PSMA-PET images and to compare its efficacy to that of human readers. Five different ML methods were compared and tested on multiple positron emission tomography/computed tomography (PET/CT) data-sets. Forty textural features extracted from both PET- and low-dose CT data were analyzed. In total, 2419 hotspots from 72 patients were included. Comparing results from human readers to those of ML-based analyses, up to 98% area under the curve (AUC), 94% sensitivity (SE), and 89% specificity (SP) were achieved. Interestingly, textural features assessed in native low-dose CT increased the accuracy significantly. Thus, ML based on Ga-PSMA-PET/CT radiomics features can classify hotspots with high precision, comparable to that of experienced NM physicians. Additionally, the superiority of multimodal ML-based analysis considering all PET and low-dose CT features was shown. Morphological features seemed to be of special additional importance even though they were extracted from native low-dose CTs.
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http://dx.doi.org/10.3390/diagnostics10090622DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7555620PMC
August 2020

Textural features in FDG-PET/CT can predict outcome in melanoma patients to treatment with Vemurafenib and Ipililumab.

Nuklearmedizin 2020 Jun 7;59(3):228-234. Epub 2020 Apr 7.

Klinik und Poliklinik für Nuklearmedizin, Universitätsklinikum Bonn, Bonn, Germany.

Aim:  Recently, textural parameters assessed in FDG-PET/CT as surrogate marker for tumor heterogeneity have been shown to provide prognostic power. Therefore, we investigated the use of such parameters in FDG-PET/CT examinations before the start of immunotherapy with vemurafenib or ipilimumab in patients with malignant melanoma.

Methods:  In this retrospective analysis 26 patients with histologically proven advanced melanoma were included. FGD-PET/CT was performed before the start of treatment either with vemurafenib (n = 9) or ipilimumab (n = 17) and tumors were analyzed for textural parameters as well as conventional PET features. Lesions were classified as responding or not responding following PERCIST criteria. ROC analysis was performed to analyze the predictive power and cut-off values. In addition, the change of maximum SUV of the lesions between pretherapeutic PET/CT and another PET/CT performed about 12 weeks after start of treatment was evaluated and correlated with the pretreatment parameters.

Results:  In both groups, six textural parameters showed statistically significant predictive power as well as the metabolic tumor volume. In the group treated with vemurafenib eight additional textural parameters as well as the maximum and mean SUV and the TLG showed significance. A statistically significant correlation between the change of maximum SUV in the course of treatment and the pretherapeutic parameters was found in both treatment groups for three textural features.

Conclusion:  In patients with malignant melanoma textural parameters in pretherapeutic FDG-PET/CT examinations seem to have prognostic power for treatment response of immunotherapy with vemurafenib and ipilimumab. This can be an important step towards personalized tumor therapy.
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http://dx.doi.org/10.1055/a-1140-5458DOI Listing
June 2020

Systemic Therapy of Neuroendocrine Neoplasia: Single Center Experience from a Cohort of 110 Consecutive Cases.

Int J Endocrinol 2020 31;2020:1491475. Epub 2020 Jan 31.

Department of Internal Medicine 3, Center of Integrated Oncology Aachen-Bonn-Cologne-Duesseldorf, University Hospital of Bonn, Bonn, Germany.

Objective: Neuroendocrine neoplasias (NENs) represent a rare and biologically heterogeneous group of malignancies. Treatment of NEN patients remains challenging due to lack of prospective evidence on the choice of ideal therapeutic sequence and therapeutic efficacy in specific individual scenarios.

Methods: Clinical data on 110 consecutive patients suffering from NEN treated at a single German university center were analyzed, therapeutic regimens applied were assessed, and the outcome was evaluated.

Results: Histological grading, Ki67 proliferation index, functional activity, and presence of metastases were identified as prognostic markers. 10-year overall survival rates were 92%, 44%, and 0% for G1, G2, and G3 tumors, and 60%, 39%, 69%, 53%, and 0% for Ki67 <2%, 3-5%, 6-20%, 21-49%, and >50%, respectively. Peptide receptor radionuclide therapy (PRRT) and cytostatic chemotherapy were the second most common options, with PRRT being used more frequently in NET G1 and G2 and chemotherapy in NEC G3. Combination chemotherapy with etoposide plus cisplatin or carboplatin showed disease control rates (DCRs) of overall 74%, with a short median progression-free survival (PFS) of 7 or 5 months, respectively. DCR and PFS for PRRT were 89% and 22 months when administered as monotherapy, versus 100% and 27 months upon combination with somatostatin analog (SSA) therapy. Of note, PRRT also achieved disease control as best response in 5/5 (100%) selected cases of NEC G3.

Conclusion: Further prospective studies are warranted to help stratify available options for therapeutic intervention in NEN patients.
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http://dx.doi.org/10.1155/2020/1491475DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7013359PMC
January 2020

Immune Checkpoint Imaging in Oncology: A Game Changer Toward Personalized Immunotherapy?

J Nucl Med 2020 08 10;61(8):1137-1144. Epub 2020 Jan 10.

Department of Nuclear Medicine, University Hospital Bonn, Bonn, Germany; and.

Immune checkpoint blockade represents a promising approach in oncology, showing antitumor activities in various cancers. However, although being generally far better tolerated than classic cytotoxic chemotherapy, this treatment, too, may be accompanied by considerable side effects and not all patients benefit equally. Therefore, careful patient selection and monitoring of the treatment response is mandatory. At present, checkpoint-specific molecular imaging is being increasingly investigated as a tool for patient selection and response evaluation. Here, an overview of the current developments in immune checkpoint imaging is provided.
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http://dx.doi.org/10.2967/jnumed.119.237891DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7413235PMC
August 2020

Letter to the Editor re: "Semiquantitative Parameters in PSMA-Targeted PET Imaging with [F]DCFPyL: Impact of Tumor Burden on Normal Organ Uptake".

Mol Imaging Biol 2020 02;22(1):19-21

Department of Nuclear Medicine, University Hospital Bonn, Venusberg-Campus 1, Gebäude 21, 53127, Bonn, Germany.

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http://dx.doi.org/10.1007/s11307-019-01452-0DOI Listing
February 2020

Biodistribution and post-therapy dosimetric analysis of [Lu]Lu-DOTA in patients with osteoblastic metastases: first results.

EJNMMI Res 2019 Nov 28;9(1):102. Epub 2019 Nov 28.

Department of Nuclear Medicine, University Medical Center Bonn, Bonn, Germany.

Background: Preclinical biodistribution and dosimetric analysis of [Lu]Lu-DOTA suggest the bisphosphonate zoledronate as a promising new radiopharmaceutical for therapy of bone metastases. We evaluated biodistribution and normal organ absorbed doses resulting from therapeutic doses of [Lu]Lu-DOTA in patients with metastatic skeletal disease.

Method: Four patients with metastatic skeletal disease (age range, 64-83 years) secondary to metastatic castration-resistant prostate carcinoma or bronchial carcinoma were treated with a mean dose of 5968 ± 64 MBq (161.3 mCi) of [Lu]Lu-DOTA. Biodistribution was assessed with serial planar whole body scintigraphy at 20 min and 3, 24, and 167 h post injection (p.i.) and blood samples at 20 min and 3, 8, 24, and 167 h p.i. Percent of injected activity in the blood, kidneys, urinary bladder, skeleton, and whole body was determined. Bone marrow self-dose was determined by an indirect blood-based method. Urinary bladder wall residence time was calculated using Cloutier's dynamic urinary bladder model with a 4-h voiding interval. OLINDA/EXM version 2.0 (Hermes Medical Solutions, Stockholm, Sweden) software was used to determine residence times in source organs by applying biexponential curve fitting and to calculate organ absorbed dose.

Results: Qualitative biodistribution analysis revealed early and high uptake of [Lu]Lu-DOTA in the kidneys with fast clearance showing minimal activity by 24 h p.i. Activity in the skeleton increased gradually over time. Mean residence times were found to be highest in the skeleton followed by the kidneys. Highest mean organ absorbed dose was 3.33 mSv/MBq for osteogenic cells followed by kidneys (0.490 mSv/MBq), red marrow (0.461 mSv/MBq), and urinary bladder wall (0.322 mSv/MBq). The biodistribution and normal organ absorbed doses of [Lu]Lu-DOTA are consistent with preclinical data.

Conclusion: [Lu]Lu-DOTA shows maximum absorbed doses in bone and low kidney doses, making it a promising agent for radionuclide therapy of bone metastasis. Further studies are warranted to evaluate the efficacy and safety of radionuclide therapy with [Lu]Lu-DOTA in the clinical setting.
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http://dx.doi.org/10.1186/s13550-019-0566-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6882969PMC
November 2019

Therapy of Patients with Neuroendocrine Neoplasia-Evidence-Based Approaches and New Horizons.

J Clin Med 2019 Sep 16;8(9). Epub 2019 Sep 16.

Klinik und Poliklinik für Nuklearmedizin, Universitätsklinikum Bonn, 53127 Bonn, Germany.

Neuroendocrine tumors (NETs) show low but increasing incidence and originate in multiple organs, including the pancreas, midgut, caecum, rectum, appendix, colon, and lungs. Due to their stunning genetic, histological, and clinical variability, diagnosis and treatment of NETs are challenging. In addition, low incidence and high variability hamper the implementation of high evidence trials. Therefore, guidelines do not cover the complexity of NETs and, frequently, treatment decisions are taken by interdisciplinary tumor conferences at comprehensive cancer centers. Treatment aims are (i) control of tumor growth, (ii) symptom control, as well as (iii) the improvement of progression-free survival (PFS) and overall survival (OS). Here, we discuss high evidence trials facilitating the achievement of these treatment aims. The majority of the evidence exists for treatment with somatostatin analogue, everolimus, peptide receptor radionuclide therapy (PRRT) with Lu-DOTATATE, sunitinib, and telotristat. Among those, PRRT is the only treatment option that has the potential to control symptoms, stop tumor growth, and to improve PFS and OS. In contrast, only a low level of evidence exists for treatment with cytotoxic drugs such as streptozotocin and doxorubicine. Finally, we discuss novel treatment options by a combination of cytotoxic drugs, Lu-DOTATATE, and tyrosine kinase inhibitors to be tested in randomized prospective trials in the future. In addition, the application of innovative isotopes, such as Ac, for PRRT is discussed.
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http://dx.doi.org/10.3390/jcm8091474DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6780372PMC
September 2019

Semiquantitative Parameters in PSMA-Targeted PET Imaging with [F]DCFPyL: Impact of Tumor Burden on Normal Organ Uptake.

Mol Imaging Biol 2020 02;22(1):190-197

The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA.

Purpose: In this study, we aimed to quantitatively investigate the biodistribution of [F]DCFPyL in patients with prostate cancer (PCa) and to determine whether uptake in normal organs correlates with an increase in tumor burden.

Procedures: Fifty patients who had been imaged with [F]DCFPyL positron emission tomography/computed tomography (PET/CT) were retrospectively included in this study. Forty of 50 (80 %) demonstrated radiotracer uptake on [F]DCFPyL PET/CT compatible with sites of PCa. Volumes of interests (VOIs) were set on normal organs (lacrimal glands, parotid glands, submandibular glands, liver, spleen, and kidneys) and on tumor lesions. Mean standardized uptake values corrected to lean body mass (SUL) and mean standardized uptake values corrected to body weight (SUV) for normal organs were assessed. For the entire tumor burden, SUL, SUV, tumor volume (TV), and the total activity in the VOI were obtained using tumor segmentation. A Spearman's rank correlation coefficient was used to investigate correlations between normal organ uptake and tumor burden.

Results: There was no significant correlation between TV with the vast majority of the investigated organs (lacrimal glands, parotid glands, submandibular glands, spleen, and liver). Only the kidney showed significant correlation: With an isocontour threshold at 50 %, left kidney uptake parameters correlated significantly with TV (SUV, ρ = - 0.214 and SUL, ρ = - 0.176, p < 0.05, respectively).

Conclusions: Only a minimal sink effect with high tumor burden in patients imaged with [F]DCFPyL was observed. Other factors, such as a high intra-patient variability of normal organ uptake, may be a much more important consideration for personalized dosimetry with PSMA-targeted therapeutic agents structurally related to [F]DCFPyL than the tumor burden.
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http://dx.doi.org/10.1007/s11307-019-01375-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7771227PMC
February 2020

Semiquantitative Parameters in PSMA-Targeted PET Imaging with [F]DCFPyL: Intrapatient and Interpatient Variability of Normal Organ Uptake.

Mol Imaging Biol 2020 02;22(1):181-189

The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA.

Purpose: Prostate-specific membrane antigen (PSMA)-targeted positron emission tomography (PET) imaging has impacted the management of patients with prostate cancer (PCa) in many parts of the world. PSMA-targeted endoradiotherapies are also being increasingly utilized and for these applications, the radiopharmaceutical distribution in normal organs is particularly important because it may limit the dose that can be delivered to tumors. In this study, we measured both interpatient and intrapatient variability of [F]DCFPyL uptake in the most relevant normal organs.

Procedures: Baseline and 6-month follow-up PSMA-targeted [F]DCFPyL PET/computed tomography (CT) scans from 39 patients with PCa were reviewed. Volumes of interest were manually drawn using the best visual approximation of the organ edge for both lacrimal glands, all four major salivary glands, the liver, the spleen, and both kidneys for all patients. The average SUV, the COVs, and intraclass correlation coefficients (ICCs) across scans were calculated. Bland-Altman analyses were performed for all organs to derive repeatability coefficients (RCs).

Results: The liver demonstrated the lowest interpatient variability (13.0 and 16.6 % at baseline and follow-up, respectively), while the spleen demonstrated the largest interpatient variability (44.6 and 51.0 % at baseline and follow-up, respectively). The lowest intrapatient variability was found in the spleen (ICC 0.86) while the highest intrapatient variability was in the kidneys (ICCs 0.40-0.50). Bland-Altman analyses showed 95 % repeatability coefficients for mean uptake > 40 % for multiple organs and were highest for the lacrimal glands, kidneys, and spleen.

Conclusions: Normal organs demonstrate significant variability in uptake of the PSMA-targeted radiotracer [F]DCFPyL. Depending on the organ, different contributions of interpatient and intrapatient factors affect the intrinsic variability. The RCs also vary significantly among the different organs were highest for the lacrimal glands, kidneys, and spleen. These findings may have important implications for the design of clinical protocols and personalized dosimetry for PSMA-targeted endoradiotherapies.
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http://dx.doi.org/10.1007/s11307-019-01376-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7955793PMC
February 2020

4D-CT-based motion correction of PET images using 3D iterative deconvolution.

Oncotarget 2019 Apr 26;10(31):2987-2995. Epub 2019 Apr 26.

Klinik und Poliklinik für Nuklearmedizin, Universitaetsklinikum Bonn, Bonn, Germany.

Objectives: Positron emission tomography acquisition takes several minutes representing an image averaged over multiple breathing cycles. Therefore, in areas influenced by respiratory movement, PET-positive lesions occur larger, but less intensive than they actually are, resulting in false quantitative assessment. We developed a motion-correction algorithm based on 4D-CT without the need to adapt PET-acquisition.

Methods: The algorithm is based on a full 3D iterative Richardson-Lucy-Deconvolution using a point-spread-function constructed using the motion information obtained from the 4D-CT. In a motion phantom study (3 different hot spheres in background activity), optimal parameters for the algorithm in terms of number of iterations and start image were estimated. Finally, the correction method was applied to 3 patient data sets. In phantom and patient data sets lesions were delineated and compared between motion corrected and uncorrected images for activity uptake and volume.

Results: Phantom studies showed best results for motion correction after 6 deconvolution steps or higher. In phantom studies, lesion volume improved up to 23% for the largest, 43% for the medium and 49% for the smallest sphere due to the correction algorithm. In patient data the correction resulted in a significant reduction of the tumor volume up to 33.3 % and an increase of the maximum and mean uptake of the lesion up to 62.1 and 19.8 % respectively.

Conclusion: In conclusion, the proposed motion correction method showed good results in phantom data and a promising reduction of detected lesion volume and a consequently increasing activity uptake in three patients with lung lesions.
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http://dx.doi.org/10.18632/oncotarget.26862DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6508203PMC
April 2019

Preliminary results of biodistribution and dosimetric analysis of [Ga]Ga-DOTA: a new zoledronate-based bisphosphonate for PET/CT diagnosis of bone diseases.

Ann Nucl Med 2019 Jun 15;33(6):404-413. Epub 2019 Mar 15.

Department of Nuclear Medicine, University Medical Center Bonn, Bonn, Germany.

Objective: Pre-clinical studies with gallium-68 zoledronate ([Ga]Ga-DOTA) have proposed it to be a potent bisphosphonate for PET/CT diagnosis of bone diseases and diagnostic counterpart to [Lu]Lu-DOTA and [Ac]Ac-DOTA. This study aims to be the first human biodistribution and dosimetric analysis of [Ga]Ga-DOTA.

Methods: Five metastatic skeletal disease patients (mean age: 72 years, M: F; 4:1) were injected with 150-190 MBq (4.05-5.14 mCi) of [Ga]Ga-DOTA i.v. Biodistribution of [Ga]Ga-DOTA was studied with PET/CT initial dynamic imaging for 30 min; list mode over abdomen (reconstructed as six images of 300 s) followed by static (skull to mid-thigh) imaging at 45 min and 2.5 h with Siemens Biograph 2 PET/CT camera. Also, blood samples (8 time points) and urine samples (2 time points) were collected over a period of 2.5 h. Total activity (MBq) in source organs was determined using interview fusion software (MEDISO Medical Imaging Systems, Budapest, Hungary). A blood-based method for bone marrow self-dose determination and a trapezoidal method for urinary bladder contents residence time calculation were used. OLINDA/EXM version 2.0 software (Hermes Medical Solutions, Stockholm, Sweden) was used to generate residence times for source organs, organ absorbed doses and effective doses.

Results: High uptake in skeleton as target organ, kidneys and urinary bladder as organs of excretion and faint uptake in liver, spleen and salivary glands were seen. Qualitative and quantitative analysis supported fast blood clearance, high bone to soft tissue and lesion to normal bone uptake with [Ga]Ga-DOTA. Urinary bladder with the highest absorbed dose of 0.368 mSv/MBq presented the critical organ, followed by osteogenic cells, kidneys and red marrow receiving doses of 0.040, 0.031 and 0.027 mSv/MBq, respectively. The mean effective dose was found to be 0.0174 mSv/MBq which results in an effective dose of 2.61 mSv from 150 MBq.

Conclusions: Biodistribution of [Ga]Ga-DOTA was comparable to [F]NaF, [Tc]Tc-MDP and [Ga]Ga-PSMA-617. With proper hydration and diuresis to reduce urinary bladder and kidney absorbed doses, it has clear advantages over [F]NaF owing to its onsite, low-cost production and theranostic potential of personalized dosimetry for treatment with [Lu]Lu-DOTA and [Ac]Ac-DOTA.
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http://dx.doi.org/10.1007/s12149-019-01348-7DOI Listing
June 2019

Novel Structured Reporting Systems for Theranostic Radiotracers.

J Nucl Med 2019 05 22;60(5):577-584. Epub 2019 Feb 22.

Division of Nuclear Medicine and Molecular Imaging, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland

Standardized reporting is more and more routinely implemented in clinical practice, and such structured reports have a major impact on a large variety of medical fields, such as laboratory medicine, pathology, and, recently, radiology. Notably, the field of nuclear medicine is constantly evolving as novel radiotracers for numerous clinical applications are developed. Thus, framework systems for standardized reporting in this field may increase clinical acceptance of new radiotracers, allow for inter- and intracenter comparisons for quality assurance, and be used in global multicenter studies to ensure comparable results and enable efficient data abstraction. In the last couple of years, several standardized framework systems for PET radiotracers with potential theranostic applications have been proposed. These include systems for prostate-specific membrane antigen-targeted PET agents to diagnose and treat prostate cancer, and systems for somatostatin receptor-targeted PET agents to diagnose and treat neuroendocrine neoplasia. In the present review, the framework systems for these 2 types of cancer will be briefly introduced, followed by an overview of their advantages and limitations. In addition, potential applications will be defined, approaches to validate such concepts will be proposed, and future perspectives will be discussed.
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http://dx.doi.org/10.2967/jnumed.118.223537DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6495242PMC
May 2019

Radionuclide intake risks in the clinical administration of RaCl.

J Radiol Prot 2019 Jun 4;39(2):387-398. Epub 2019 Feb 4.

Radiation Protection Department, Institute for Work Design of North-Rhine Westphalia, Gesundheitscampus 10, 44801 Bochum, Germany.

An intake monitoring program covering more than half a year of clinical administration of Radium-223-dichloride for the palliative treatment of castration-resistant prostate cancer was carried out in the nuclear medicine department of the university hospital Bonn. Radioactivity in a total of 87 samples of gloves, air filters, faecal bioassays and face masks was measured and evaluated to assess the need for radiation protection measures for the medical staff. The main aim was to quantify or obtain an upper limit for the intake factor. An intake factor of 10 was measured when the preparation of patient doses took place in part in a laminar flow cabinet, which indicates an intake factor of 10 in more commonplace practice without a cabinet. The intake factor is therefore at the same level as other standard applications of unsealed sources in nuclear medicine. Our findings confirmed that masks are not required under any circumstances. However, the investigation also revealed that contamination risks, especially during the preparation of doses in syringes, should not be neglected.
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http://dx.doi.org/10.1088/1361-6498/ab044dDOI Listing
June 2019

Role of textural heterogeneity parameters in patient selection for 177Lu-PSMA therapy via response prediction.

Oncotarget 2018 Sep 7;9(70):33312-33321. Epub 2018 Sep 7.

Department of Nuclear Medicine, University Hospital Bonn, Bonn, Germany.

Purpose: Prostate cancer is most common tumor in men causing significant patient mortality and morbidity. In newer diagnostic/therapeutic agents PSMA linked ones are specifically important. Analysis of textural heterogeneity parameters is associated with determination of innately aggressive and therapy resistant cell lines thus emphasizing their importance in therapy planning. The objective of current study was to assess predictive ability of tumor textural heterogeneity parameters from baseline Ga-PSMA PET prior to Lu-PSMA therapy.

Results: Entropy showed a negative correlation (r = -0.327, = 0.006, AUC = 0.695) and homogeneity showed a positive correlation (r = 0.315, = 0.008, AUC = 0.683) with change in pre and post therapy PSA levels.

Conclusions: Study showed potential for response prediction through baseline PET scan using textural features. It suggested that increase in heterogeneity of PSMA expression seems to be associated with an increased response to PSMA radionuclide therapy.

Materials And Methods: Retrospective analysis of 70 patients was performed. All patients had metastatic prostate cancer and were planned to undergo Lu-PSMA therapy. Pre-therapeutic Ga- PSMA PET scans were used for analysis. 3D volumes (VOIs) of 3 lesions each in bones and lymph nodes were manually delineated in static PET images. Five PET based textural heterogeneity parameters (COV, entropy, homogeneity, contrast, size variation) were determined. Results obtained were then compared with clinical parameters including pre and post therapy PSA, alkaline phosphate, bone specific alkaline phosphate levels and ECOG criteria. Spearman correlation was used to determine statistical dependence among variables. ROC analysis was performed to estimate the optimal cutoff value and AUC.
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http://dx.doi.org/10.18632/oncotarget.26051DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6161784PMC
September 2018

Volumetric and texture analysis of pretherapeutic F-FDG PET can predict overall survival in medullary thyroid cancer patients treated with Vandetanib.

Endocrine 2019 02 11;63(2):293-300. Epub 2018 Sep 11.

Department of Nuclear Medicine, University Hospital Wuerzburg, Wuerzburg, Germany.

Purpose: The metabolically most active lesion in 2-deoxy-2-(F)fluoro-D-glucose (F-FDG) PET/CT can predict progression-free survival (PFS) in patients with medullary thyroid carcinoma (MTC) starting treatment with the tyrosine kinase inhibitor (TKI) vandetanib. However, this metric failed in overall survival (OS) prediction. In the present proof of concept study, we aimed to explore the prognostic value of intratumoral textural features (TF) as well as volumetric parameters (total lesion glycolysis, TLG) derived by pre-therapeutic F-FDG PET.

Methods: Eighteen patients with progressive MTC underwent baseline F-FDG PET/CT prior to and 3 months after vandetanib initiation. By manual segmentation of the tumor burden at baseline and follow-up PET, intratumoral TF and TLG were computed. The ability of TLG, imaging-based TF, and clinical parameters (including age, tumor marker doubling times, prior therapies and RET (rearranged during transfection) mutational status) for prediction of both PFS and OS were evaluated.

Results: The TF Complexity and the volumetric parameter TLG obtained at baseline prior to TKI initiation successfully differentiated between low- and high-risk patients. Complexity allocated 10/18 patients to the high-risk group with an OS of 3.3 y (vs. low-risk group, OS = 5.3 y, 8/18, AUC = 0.78, P = 0.03). Baseline TLG designated 11/18 patients to the high-risk group (OS = 3.5 y vs. low-risk group, OS = 5 y, 7/18, AUC = 0.83, P = 0.005). The Hazard Ratio for cancer-related death was 6.1 for Complexity (TLG, 9.5). Among investigated clinical parameters, the age at initiation of TKI treatment reached significance for PFS prediction (P = 0.02, OS, n.s.).

Conclusions: The TF Complexity and the volumetric parameter TLG are both independent parameters for OS prediction.
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http://dx.doi.org/10.1007/s12020-018-1749-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6394453PMC
February 2019

Interobserver Agreement for the Standardized Reporting System PSMA-RADS 1.0 on F-DCFPyL PET/CT Imaging.

J Nucl Med 2018 12 6;59(12):1857-1864. Epub 2018 Sep 6.

The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland

Recently, the standardized reporting and data system for prostate-specific membrane antigen (PSMA)-targeted PET imaging studies, termed PSMA-RADS version 1.0, was introduced. We aimed to determine the interobserver agreement for applying PSMA-RADS to imaging interpretation of F-DCFPyL (2-(3-{1-carboxy-5-[(6-F-fluoro-pyridine-3-carbonyl)-amino]-pentyl}-ureido)-pentanedioic acid) PET examinations in a prospective setting mimicking the typical clinical workflow at a prostate cancer referral center. Four readers (2 experienced readers (ERs, >3 y of PSMA-targeted PET interpretation experience) and 2 inexperienced readers (IRs, <1 y of experience)), who had all read the initial publication on PSMA-RADS 1.0, assessed 50 F-DCFPyL PET/CT studies independently. Per scan, a maximum of 5 target lesions was selected by the observers, and a PSMA-RADS score for every target lesion was recorded. No specific preexisting conditions were placed on the selection of the target lesions, although PSMA-RADS 1.0 suggests that readers focus on the most avid or largest lesions. An overall scan impression based on PSMA-RADS was indicated, and interobserver agreement rates on a target lesion-based, on an organ-based, and on an overall PSMA-RADS score-based level were computed. The number of target lesions identified by each observer was as follows: ER 1, 123; ER 2, 134; IR 1, 123; and IR 2, 120. Among those selected target lesions, 125 were chosen by at least 2 individual observers (all 4 readers selected the same target lesion in 58 of 125 [46.4%] instances, 3 readers in 40 of 125 [32%], and 2 observers in 27 of 125 [21.6%]). The interobserver agreement for PSMA-RADS scoring among identical target lesions was good (intraclass correlation coefficient [ICC] for 4, 3, and 2 identical target lesions, ≥0.60, respectively). For lymph nodes, an excellent interobserver agreement was derived (ICC, 0.79). The interobserver agreement for an overall scan impression based on PSMA-RADS was also excellent (ICC, 0.84), with a significant difference for ER (ICC, 0.97) vs. IR (ICC, 0.74) ( = 0.005). PSMA-RADS demonstrated a high concordance rate in this study, even among readers with different levels of experience. This finding suggests that PSMA-RADS can be effectively used for communication with clinicians and can be implemented in the collection of data for large prospective trials.
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http://dx.doi.org/10.2967/jnumed.118.217588DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6278904PMC
December 2018

Molecular imaging reporting and data systems (MI-RADS): a generalizable framework for targeted radiotracers with theranostic implications.

Ann Nucl Med 2018 Oct 14;32(8):512-522. Epub 2018 Aug 14.

The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, 601 N. Caroline St., Baltimore, MD, 21287, USA.

Both prostate-specific membrane antigen (PSMA)- and somatostatin receptor (SSTR)-targeted positron emission tomography (PET)-based imaging agents for prostate carcinoma and neuroendocrine tumors, respectively, are seeing rapidly expanding use. In addition to diagnostic applications, both classes of radiotracers can be used to triage patients for theranostic endoradiotherapy. While interpreting PSMA- or SSTR-targeted PET/computed tomography (CT) scans, the reader has to be aware of certain pitfalls. Adding to the complexity of the interpretation of those imaging agents, both normal biodistribution, and also false-positive and -negative findings differ between PSMA- and SSTR-targeted PET radiotracers. Herein summarized under the umbrella term molecular imaging reporting and data systems (MI-RADS), two novel RADS classifications for PSMA- and SSTR-targeted PET imaging are described (PSMA- and SSTR-RADS). Notably, PSMA- and SSTR-RADS are structured in a reciprocal fashion, i.e., if the reader is familiar with one system, the other system can readily be applied, as well. In the present review, we will discuss the most common pitfalls on PSMA- and SSTR-targeted PET/CT, briefly introduce PSMA- and SSTR-RADS, and define a potential future role of the umbrella framework MI-RADS compared to other classification systems.
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http://dx.doi.org/10.1007/s12149-018-1291-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6182628PMC
October 2018

Correction to: Pre-therapy Somatostatin Receptor-Based Heterogeneity Predicts Overall Survival in Pancreatic Neuroendocrine Tumor Patients Undergoing Peptide Receptor Radionuclide Therapy.

Mol Imaging Biol 2018 12;20(6):1068

Department of Nuclear Medicine, University Hospital Bonn, Sigmund-Freud-Str. 25, 53127, Bonn, Germany.

The article "Pre-therapy Somatostatin Receptor-Based Heterogeneity Predicts Overall Survival in Pancreatic Neuroendocrine Tumor Patients Undergoing Peptide Receptor Radionuclide Therapy," was originally published electronically on the publisher's internet portal without open access.
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http://dx.doi.org/10.1007/s11307-018-1261-4DOI Listing
December 2018

Pre-therapy Somatostatin Receptor-Based Heterogeneity Predicts Overall Survival in Pancreatic Neuroendocrine Tumor Patients Undergoing Peptide Receptor Radionuclide Therapy.

Mol Imaging Biol 2019 06;21(3):582-590

Department of Nuclear Medicine, University Hospital Bonn, Sigmund-Freud-Str. 25, 53127, Bonn, Germany.

Purpose: Early identification of aggressive disease could improve decision support in pancreatic neuroendocrine tumor (pNET) patients prior to peptide receptor radionuclide therapy (PRRT). The prognostic value of intratumoral textural features (TF) determined by baseline somatostatin receptor (SSTR)-positron emission tomography (PET) before PRRT was analyzed.

Procedures: Thirty-one patients with G1/G2 pNET were enrolled (G2, n = 23/31). Prior to PRRT with [Lu]DOTATATE (mean, 3.6 cycles), baseline SSTR-PET computed tomography was performed. By segmentation of 162 (median per patient, 5) metastases, intratumoral TF were computed. The impact of conventional PET parameters (SUV), imaging-based TF, and clinical parameters (Ki67, CgA) for prediction of both progression-free survival (PFS) and overall survival (OS) after PRRT were evaluated.

Results: Within a median follow-up of 3.7 years, tumor progression was detected in 21 patients (median, 1.5 years) and 13/31 deceased (median, 1.9 years). In ROC analysis, the TF entropy, reflecting derangement on a voxel-by-voxel level, demonstrated predictive capability for OS (cutoff = 6.7, AUC = 0.71, p = 0.02). Of note, increasing entropy could predict a longer survival (> 6.7, OS = 2.5 years, 17/31), whereas less voxel-based derangement portended inferior outcome (< 6.7, OS = 1.9 years, 14/31). These findings were supported in a G2 subanalysis (> 6.9, OS = 2.8 years, 9/23 vs. < 6.9, OS = 1.9 years, 14/23). Kaplan-Meier analysis revealed a significant distinction between high- and low-risk groups using entropy (n = 31, p < 0.05). For those patients below the ROC-derived threshold, the relative risk of death after PRRT was 2.73 (n = 31, p = 0.04). Ki67 was negatively associated with PFS (p = 0.002); however, SUV failed in prognostication (n.s.).

Conclusions: In contrast to conventional PET parameters, assessment of intratumoral heterogeneity demonstrated superior prognostic performance in pNET patients undergoing PRRT. This novel PET-based strategy of outcome prediction prior to PRRT might be useful for patient risk stratification.
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http://dx.doi.org/10.1007/s11307-018-1252-5DOI Listing
June 2019

Prediction of Normal Organ Absorbed Doses for [177Lu]Lu-PSMA-617 Using [44Sc]Sc-PSMA-617 Pharmacokinetics in Patients With Metastatic Castration Resistant Prostate Carcinoma.

Clin Nucl Med 2018 Jul;43(7):486-491

Institute of Nuclear Chemistry, Johannes Gutenberg University Mainz, Mainz, Germany.

In vivo pharmacokinetic analysis of [Sc]Sc-PSMA-617 was used to determine the normal organ-absorbed doses that may result from therapeutic activity of [Lu]Lu-PSMA-617 and to predict the maximum permissible activity of [Lu]Lu-PSMA-617 for patients with metastatic castration-resistant prostate carcinoma.

Methods: Pharmacokinetics of [Sc]Sc-PSMA-617 was evaluated in 5 patients with metastatic castration-resistant prostate carcinoma using dynamic PET/CT, followed by 3 static PET/CT acquisitions and blood sample collection over 19.5 hours, as well as urine sample collection at 2 time points. Total activity measured in source organs by PET imaging, as well as counts per milliliter measured in blood and urine samples, was decay corrected back to the time of injection using the half-life of Sc. Afterward, forward decay correction using the half-life of Lu was performed, extrapolating the pharmacokinetics of [Sc]Sc-PSMA-617 to that of [Lu]Lu-PSMA-617. Source organs residence times and organ-absorbed doses for [Lu]Lu-PSMA-617 were calculated using OLINDA/EXM software. Bone marrow self-dose was determined with indirect blood-based method, and urinary bladder contents residence time was estimated by trapezoidal approximation. The maximum permissible activity of [Lu]Lu-PSMA-617 was calculated for each patient considering external beam radiotherapy toxicity limits for radiation absorbed doses to kidneys, bone marrow, salivary glands, and whole body.

Results: The predicted mean organ-absorbed doses were highest in the kidneys (0.44 mSv/MBq), followed by the salivary glands (0.23 mSv/MBq). The maximum permissible activity was highly variable among patients; limited by whole body-absorbed dose (1 patient), marrow-absorbed dose (1 patient), and kidney-absorbed dose (3 patients).

Conclusions: [Sc]Sc-PSMA-617 PET/CT imaging is feasible and allows theoretical extrapolation of the pharmacokinetics of [Sc]Sc-PSMA-617 to that of [Lu]Lu-PSMA-617, with the intent of predicting normal organ-absorbed doses and maximum permissible activity in patients scheduled for therapy with [Lu]Lu-PSMA-617.
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http://dx.doi.org/10.1097/RLU.0000000000002102DOI Listing
July 2018

[44Sc]Sc-PSMA-617 Biodistribution and Dosimetry in Patients With Metastatic Castration-Resistant Prostate Carcinoma.

Clin Nucl Med 2018 May;43(5):323-330

Aim: [Sc]Sc-PSMA-617 with 3.9-hour half-life, in vitro and in vivo characteristics similar to [Lu]Lu-PSMA-617 and possibility of delayed imaging after 24 hours or later, implies it to be advantageous than [ Ga]Ga-PSMA-617 for pretherapeutic dosimetric assessment for [Lu]Lu-PSMA-617 in metastatic castration-resistant prostate carcinoma (mCRPC) patients. In this study, we investigated biodistribution and radiation exposure to normal organs with [Sc]Sc-PSMA-617 in mCRPC patients.

Methods: Five mCRPC patients (mean age, 69 years) enrolled for [Lu]Lu-PSMA-617 therapy were injected with 40-62 MBq [Sc]Sc-PSMA-617 intravenously; Siemens Biograph 2 PET/CT system was used to acquire dynamic PET data (30 minutes) in list mode over the abdomen, followed by the collection of static PET/CT images (skull to mid-thigh) at 45 minutes, 2 and approximately 20 hours postinjection. Time-dependent changes in percentage activity in source organs (kidneys, bladder, salivary glands, small intestine, liver, spleen, and whole body) were determined. Bone marrow and urinary bladder contents residence time were also calculated. Source organs residence time, organ-absorbed doses, and effective doses were determined using OLINDA/EXM software.

Results: Physiological tracer uptake was seen in kidneys, liver, spleen, small intestine, urinary bladder, and salivary glands and in metastases. Kidneys with highest radiation absorbed dose of 3.19E-01 mSv/MBq were the critical organs, followed by urinary bladder wall (2.24E-01 mSv/MBq, spleen [1.85E-01], salivary glands [1.11E-01], and liver [1.07E-01] mSv/MBq). Red marrow dose was found to be 3.31E-02 mSv/MBq. The mean effective dose of 3.89E-02 mSv/MBq and effective dose of 1.95 mSv was estimated from 50 MBq (treatment planning dose) of [Sc]Sc-PSMA-617.

Conclusions: [Sc]Sc-PSMA-617 is found to be a very promising radiopharmaceutical that can be used for pre [Lu]Lu-PSMA-617 therapeutic dosimetric assessment.
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http://dx.doi.org/10.1097/RLU.0000000000002003DOI Listing
May 2018

Ga-PSMA-PET/CT imaging of localized primary prostate cancer patients for intensity modulated radiation therapy treatment planning with integrated boost.

Eur J Nucl Med Mol Imaging 2018 07 21;45(7):1170-1178. Epub 2018 Feb 21.

Klinik und Poliklinik für Nuklearmedizin, Universitätsklinikum Bonn, Sigmund-Freud-Str. 25, 53127, Bonn, Germany.

Purpose: The purpose of our study was to show the feasibility and potential benefits of using Ga-PSMA-PET/CT imaging for radiation therapy treatment planning of patients with primary prostate cancer using either integrated boost on the PET-positive volume or localized treatment of the PET-positive volume. The potential gain of such an approach, the improvement of tumor control, and reduction of the dose to organs-at-risk at the same time was analyzed using the QUANTEC biological model.

Methods: Twenty-one prostate cancer patients (70 years average) without previous local therapy received Ga-PSMA-PET/CT imaging. Organs-at-risk and standard prostate target volumes were manually defined on the obtained datasets. A PET active volume (PTV_PET) was segmented with a 40% of the maximum activity uptake in the lesion as threshold followed by manual adaption. Five different treatment plan variations were calculated for each patient. Analysis of derived treatment plans was done according to QUANTEC with in-house developed software. Tumor control probability (TCP) and normal tissue complication probability (NTCP) was calculated for all plan variations.

Results: Comparing the conventional plans to the plans with integrated boost and plans just treating the PET-positive tumor volume, we found that TCP increased to (95.2 ± 0.5%) for an integrated boost with 75.6 Gy, (98.1 ± 0.3%) for an integrated boost with 80 Gy, (94.7 ± 0.8%) for treatment of PET-positive volume with 75 Gy, and to (99.4 ± 0.1%) for treating PET-positive volume with 95 Gy (all p < 0.0001). For the integrated boost with 80 Gy, a significant increase of the median NTCP of the rectum was found, for all other plans no statistical significant increase in the NTCP neither of the rectum nor the bladder was found.

Conclusions: Our study demonstrates that the use of Ga-PSMA-PET/CT image information allows for more individualized prostate treatment planning. TCP values of identified active tumor volumes were increased, while rectum and bladder NTCP values either remained the same or were even lower. However, further studies need to clarify the clinical benefit for the patients applying these techniques.
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http://dx.doi.org/10.1007/s00259-018-3954-yDOI Listing
July 2018

Clinical Translation and First In-Human Use of [Sc]Sc-PSMA-617 for PET Imaging of Metastasized Castrate-Resistant Prostate Cancer.

Theranostics 2017 26;7(18):4359-4369. Epub 2017 Sep 26.

Institute of Nuclear Chemistry, Johannes Gutenberg University, 55128 Mainz, Germany.

Background: Various trivalent radiometals are well suited for labeling of DOTA-conjugated variants of Glu-ureido-based prostate-specific membrane antigen (PSMA) inhibitors. The DOTA-conjugate PSMA-617 has proven high potential in PSMA radioligand therapy (PSMA-RLT) of prostate cancer as well as PET imaging when labeled with lutetium-177 and gallium-68 respectively. Considering the relatively short physical half-life of gallium-68 this positron emitter precludes prolonged acquisition periods, as required for pre-therapeutic dosimetry or intraoperative applications. In this context, the positron emitter scandium-44 is an attractive alternative for PET imaging. We report the synthesis of [Sc]Sc-PSMA-617 as radiopharmaceutical with generator produced scandium-44, its characterization and clinical translation as part of a first in-human study.

Methods: Scandium-44 was obtained from a Ti/Sc radionuclide generator. PSMA-617 was labeled with 142.4±12.7 MBq of scandium-44 in analogy to [Ga]Ga-PSMA-617 and evaluated and in cell studies using PSMA+ LNCaP cells. A first-in-human investigation was subsequently carried out in a cohort of 4 patients (mean age 70±1.8 a) registered for [Lu]Lu-PSMA-617 therapy. 50.5±9.3 MBq (40 µg, 38.4 nmol) [Sc]Sc-PSMA-617 were applied via intravenous injection (i.v.), respectively. A Siemens Biograph 2 PET/CT system was used to acquire initial dynamic PET data (30 min) of abdomen in list mode followed by static PET/CT data (skull to mid-thigh) at 45 min, 2 and 18 h post-injection (p.i.). For quantitative analysis, dynamic images were reconstructed as 6 data sets of 300 s each. The noise ratio was measured in liver, lung and an additional region outside the body. SUV values in different organs and lesions were measured and compared to [Ga]Ga-PSMA-11 data of the same patients. Residence times and organ absorbed doses were calculated using OLINDA/EXM software.

Results: Quantitative radiochemical yields of ≥98 % were achieved using 18 nmol of PSMA-617 after 20 min at 95 °C with apparent molar activity of 6.69±0.78 MBq/nmol. Following purification, >99 % radiochemical purity was obtained. [Sc]Sc-PSMA-617 showed high stability (>95 %) in serum for 24 h. The binding affinity and internalization fraction were determined in PSMA+ LNCaP cells (IC = 4.72±0.7 nM and internalization fraction: 15.78±2.14 % IA/10 LNCaP cells) and compared to [Ga]Ga-PSMA-11 (12.0±2.8 nM and 9.47±2.56 % IA/10 LNCaP cells). Physiological tracer uptake was observed in kidneys, liver, spleen, small intestine, urinary bladder, and salivary glands and pathological uptake in both soft and skeletal metastases. SUV values were significantly lower in the kidneys (14.0) compared to [Ga]Ga-PSMA-11 OET (30.5). All other measured SUV values did not show a statistically significant difference. Tumor to liver ratios were found to lie between 1.9 and 8.3 for [Ga]Ga-PSMA-11 and between 2.5 and 8.8 for [Sc]Sc-PSMA-617 after 120 min. For [Sc]Sc-PSMA-617 the ratios were higher and no statistically significant differences were observed. Total and % activity were highest in liver followed by kidneys, spleen, small intestine and salivary glands. Rapid wash out was seen in liver and spleen and gradually over time in kidneys. Kidneys received the highest radiation absorbed dose of 0.354 (0.180-0.488) mSv/MBq. No adverse pharmacological effects were observed.

Conclusion: In conclusion [Sc]Sc-PSMA-617 PET is suitable for PET imaging of prostate cancer tissue. [Sc]Sc-PSMA-617 shows promise to enable pre-therapeutic dosimetry in clinical settings. However, the clinical advantages for individual dosimetry or other applications like intraoperative applications have to be investigated in further studies.
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http://dx.doi.org/10.7150/thno.20586DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5695136PMC
March 2018
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