Publications by authors named "Steven P Rowe"

273 Publications

Imaging of Cancer Immunotherapy: Response Assessment Methods, Atypical Response Patterns, and Immune-Related Adverse Events, From the Special Series on Imaging of Inflammation.

AJR Am J Roentgenol 2021 Oct 6. Epub 2021 Oct 6.

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

The introduction of immunotherapy with immune-checkpoint inhibitors (ICIs) has revolutionized cancer treatment paradigms. Since the FDA approval of the first ICI in 2011, multiple additional ICIs have been approved and granted marketing authorization, and many promising agents are in early clinical adoption. Due to the distinctive biologic mechanisms of ICIs, the patterns of tumor response and progression differ for immunotherapy from those observed with cytotoxic chemotherapies. With increasing clinical adoption of immunotherapy, it is critical for radiologists to recognize different response patterns and common pitfalls to avoid misinterpretation of imaging studies or prompt premature cessation of potentially effective treatment. This article provides an overview of ICIs and their mechanisms of action and reviews the anatomic and metabolic immune-related response assessment methods, typical and atypical patterns of immunotherapy response (including pseudoprogression, hyper-progression, dissociated response, and durable response), and common imaging features of immune-related adverse events. Future multicenter trials are needed to validate the proposed immune-related response criteria and identify the functional imaging markers of early treatment response and survival.
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http://dx.doi.org/10.2214/AJR.21.26538DOI Listing
October 2021

No major impact of prescribed CAD drugs on myocardial perfusion uptake derived by []rubidium PET.

J Nucl Cardiol 2021 Oct 5. Epub 2021 Oct 5.

Department of Nuclear Medicine, University Hospital Würzburg, Oberdürrbacherstr. 6, 97080, Würzburg, Germany.

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http://dx.doi.org/10.1007/s12350-021-02786-5DOI Listing
October 2021

18F-Fluciclovine-Avid Pulmonary Hamartoma.

Clin Nucl Med 2021 Nov;46(11):919-921

From the Division of Nuclear Medicine and Molecular Imaging, The Russell H. Morgan Department of Radiology and Radiological Science.

Abstract: A 73-year-old man with history of grade group 1/Gleason 3 + 3 = 6 prostate adenocarcinoma status post prostatectomy had subsequent biochemical recurrence with serum prostate-specific antigen level of 2.4 ng/mL. He underwent an 18F-fluciclovine PET/CT scan that demonstrated a left prostate bed recurrence and an incidental 18F-fluciclovine-avid smooth-edged solitary lung nodule with internal fat attenuation. Such uptake of 18F-fluciclovine in a lung hamartoma could be mistaken for prostate cancer metastasis. Given the increasing use of advanced imaging for prostate cancer, there is need for the imaging specialist to know about pitfalls and how to interpret them.
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http://dx.doi.org/10.1097/RLU.0000000000003672DOI Listing
November 2021

F DCFPyL PET Acquisition, Interpretation and Reporting: Suggestions Post Food and Drug Administration Approval.

J Nucl Med 2021 Sep 16. Epub 2021 Sep 16.

Johns Hopkins.

F-DCFPyL was recently approved by the FDA for evaluation prior to definitive therapy and for biochemical recurrence. Here we focus on the key data that justify the clinical use of F-DCFPyL, as well as those aspects of protocol implementation and image interpretation that are important to the nuclear medicine physicians and radiologists who will interpret F-DCFPyL PET/CT and PET/MR scans.
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http://dx.doi.org/10.2967/jnumed.121.262989DOI Listing
September 2021

PET Imaging for Prostate Cancer.

Radiol Clin North Am 2021 Sep;59(5):801-811

Division of Nuclear Medicine and Molecular Imaging, Department of Radiology and Imaging Sciences, Emory University, 1364 Clifton Road NE, Atlanta, GA 30322, USA.

The role of PET imaging with C-choline and F-fluciclovine in evaluating patients with prostate cancer (PCa) has become more important over the years and has been incorporated into the NCCN guidelines. A new generation of PET radiotracers targeting the prostate-specific membrane antigen (PSMA) is widely used outside the United States to evaluate patients with primary PCa and PCa recurrence. PET imaging influences treatment planning and demonstrates a significantly higher disease detection rate than conventional imaging such as computed tomography and MR imaging. Early data indicate that using PET radiotracers such as F-fluciclovine and PSMA improves patient outcomes. 68-Ga-PSMA-11 and 18F-DCFPyL-PET/CT were recently approved by the US Food & Drug Administration (FDA) for clinical use. Other PSMA radiotracers, including fluorinated variants, will likely gain FDA approval in the not-too-distant future.
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http://dx.doi.org/10.1016/j.rcl.2021.05.008DOI Listing
September 2021

Radiology, COVID-19, and the next pandemic.

Diagn Interv Imaging 2021 Oct 6;102(10):583-585. Epub 2021 Aug 6.

Department of Radiology, Johns Hopkins Medical Institution, 601 North Caroline Street, Baltimore, MD 21287, USA.

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http://dx.doi.org/10.1016/j.diii.2021.07.004DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8343390PMC
October 2021

The European Association of Urology Biochemical Recurrence Risk Groups Predict Findings on PSMA PET in Patients with Biochemically Recurrent Prostate Cancer after Radical Prostatectomy.

J Nucl Med 2021 Jul 29. Epub 2021 Jul 29.

Johns Hopkins, United States.

To evaluate the association of a new biochemical recurrence (BCR) risk stratification system with PSMA-targeted PET/CT findings. Two prospective studies that included patients with BCR were pooled. Findings on PSMA PET were catalogued. Patients were characterized according to the European Association of Urology (EAU) BCR risk categories. Univariable and multivariable analyses were carried out by logistic regression. 145 patients were included (45 low-risk and 100 high-risk). High-risk BCR patients had a higher positive rate when compared to low-risk (82.0% vs. 48.9%; < 0.001), and reached independent predictor status for positive PSMA PET/CT scan on multivariable logistic regression (OR 6.73, 95% CI 2.41-18.76; < 0.001). The AUC using the combination of BCR risk group and PSA was higher than PSA alone (0.834 vs. 0.759, = 0.015). The EAU BCR risk group defines the best candidates who can benefit from a PSMA PET/CT scan when BCR occurs.
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http://dx.doi.org/10.2967/jnumed.121.262411DOI Listing
July 2021

Applications of artificial intelligence in oncologic F-FDG PET/CT imaging: a systematic review.

Ann Transl Med 2021 May;9(9):823

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

Artificial intelligence (AI) is a growing field of research that is emerging as a promising adjunct to assist physicians in detection and management of patients with cancer. F-FDG PET imaging helps physicians in detection and management of patients with cancer. In this study we discuss the possible applications of AI in F-FDG PET imaging based on the published studies. A systematic literature review was performed in PubMed on early August 2020 to find the relevant studies. A total of 65 studies were available for review against the inclusion criteria which included studies that developed an AI model based on 18F-FDG PET data in cancer to diagnose, differentiate, delineate, stage, assess response to therapy, determine prognosis, or improve image quality. Thirty-two studies met the inclusion criteria and are discussed in this review. The majority of studies are related to lung cancer. Other studied cancers included breast cancer, cervical cancer, head and neck cancer, lymphoma, pancreatic cancer, and sarcoma. All studies were based on human patients except for one which was performed on rats. According to the included studies, machine learning (ML) models can help in detection, differentiation from benign lesions, segmentation, staging, response assessment, and prognosis determination. Despite the potential benefits of AI in cancer imaging and management, the routine implementation of AI-based models and F-FDG PET-derived radiomics in clinical practice is limited at least partially due to lack of standardized, reproducible, generalizable, and precise techniques.
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http://dx.doi.org/10.21037/atm-20-6162DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8246218PMC
May 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

Artificial intelligence in single photon emission computed tomography (SPECT) imaging: a narrative review.

Ann Transl Med 2021 May;9(9):820

Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.

Artificial intelligence (AI) has been widely applied to medical imaging. The use of AI for emission computed tomography, particularly single-photon emission computed tomography (SPECT) emerged nearly 30 years ago but has been accelerated in recent years due to the development of AI technology. In this review, we will describe and discuss the progress of AI technology in SPECT imaging. The applications of AI are dispersed in disease prediction and diagnosis, post-reconstruction image denoising, attenuation map generation, and image reconstruction. These applications are relevant to many disease categories such as the neurological disorders, kidney failure, cancer, heart disease, etc. This review summarizes these applications so that SPECT researchers can have a reference overview of the role of AI in current SPECT studies. For each application, we followed the timeline to present the evolution of AI's usage and offered insights on how AI was combined with the knowledge of underlying physics as well as traditional non-learning techniques. Ultimately, AI applications are critical to the progress of modern SPECT technology because they provide compensations for many deficiencies in conventional SPECT imaging methods and demonstrate unparalleled success. Nonetheless, AI also has its own challenges and limitations in the medical field, including SPECT imaging. These fundamental questions are discussed, and possible future directions and countermeasures are suggested.
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http://dx.doi.org/10.21037/atm-20-5988DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8246162PMC
May 2021

SPECTnet: a deep learning neural network for SPECT image reconstruction.

Ann Transl Med 2021 May;9(9):819

Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.

Background: Single photon emission computed tomography (SPECT) is an important functional tool for clinical diagnosis and scientific research of brain disorders, but suffers from limited spatial resolution and high noise due to hardware design and imaging physics. The present study is to develop a deep learning technique for SPECT image reconstruction that directly converts raw projection data to image with high resolution and low noise, while an efficient training method specifically applicable to medical image reconstruction is presented.

Methods: A custom software was developed to generate 20,000 2-D brain phantoms, of which 16,000 were used to train the neural network, 2,000 for validation, and the final 2,000 for testing. To reduce development difficulty, a two-step training strategy for network design was adopted. We first compressed full-size activity image (128×128 pixels) to a one-D vector consisting of 256×1 pixels, accomplished by an autoencoder (AE) consisting of an encoder and a decoder. The vector is a good representation of the full-size image in a lower-dimensional space and was used as a compact label to develop the second network that maps between the projection-data domain and the vector domain. Since the label had 256 pixels only, the second network was compact and easy to converge. The second network, when successfully developed, was connected to the decoder (a portion of AE) to decompress the vector to a regular 128×128 image. Therefore, a complex network was essentially divided into two compact neural networks trained separately in sequence but eventually connectable.

Results: A total of 2,000 test examples, a synthetic brain phantom, and de-identified patient data were used to validate SPECTnet. Results obtained from SPECTnet were compared with those obtained from our clinic OS-EM method. Images with lower noise and more accurate information in the uptake areas were obtained by SPECTnet.

Conclusions: The challenge of developing a complex deep neural network is reduced by training two separate compact connectable networks. The combination of the two networks forms the full version of SPECTnet. Results show that the developed neural network can produce more accurate SPECT images.
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http://dx.doi.org/10.21037/atm-20-3345DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8246183PMC
May 2021

Artificial intelligence in molecular imaging: at the crossroads of revolutions in medical diagnosis.

Authors:
Steven P Rowe

Ann Transl Med 2021 May;9(9):817

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

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http://dx.doi.org/10.21037/atm-2020-mi-09DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8246207PMC
May 2021

Exceptional response to the ALK and ROS1 inhibitor lorlatinib and subsequent mechanism of resistance in relapsed F1174L-mutated neuroblastoma.

Cold Spring Harb Mol Case Stud 2021 08 2;7(4). Epub 2021 Aug 2.

The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Division of Pediatric Oncology, Baltimore, Maryland 21287, USA.

Treatment of high-risk neuroblastoma typically incorporates multiagent chemotherapy, surgery, radiation therapy, autologous stem cell transplantation, immunotherapy, and differentiation therapy. The discovery of activating mutations in ALK receptor tyrosine kinase () in ∼8% of neuroblastomas opens the possibility of further improving outcomes for this subset of patients with the addition of ALK inhibitors. ALK inhibitors have shown efficacy in tumors such as non-small-cell lung cancer and anaplastic large cell lymphoma in which wild-type ALK overexpression is driven by translocation events. In contrast, ALK mutations driving neuroblastomas are missense mutations in the tyrosine kinase domain yielding constitutive activation and differing sensitivity to available ALK inhibitors. We describe a case of a patient with relapsed, refractory, metastatic F1174L-mutated neuroblastoma who showed no response to the first-generation ALK inhibitor crizotinib but had a subsequent complete response to the ALK/ROS1 inhibitor lorlatinib. The patient's disease relapsed after 13 mo of treatment. Sequencing of cell-free DNA at the time of relapse pointed toward a potential mechanism of acquired lorlatinib resistance: amplification of and and a Q61K mutation. We review the literature regarding differing sensitivity of mutations found in neuroblastoma to current FDA-approved ALK inhibitors and known pathways of acquired resistance. Our report adds to the literature of important correlations between neuroblastoma mutation status and clinical responsiveness to ALK inhibitors. It also highlights the importance of understanding acquired mechanisms of resistance.
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http://dx.doi.org/10.1101/mcs.a006064DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8327881PMC
August 2021

Cu-PSMA-BCH: a new radiotracer for delayed PET imaging of prostate cancer.

Eur J Nucl Med Mol Imaging 2021 Jun 25. Epub 2021 Jun 25.

Key Laboratory of Carcinogenesis and Translational Research, Ministry of Education/Beijing), NMPA Key Laboratory for Research and Evaluation of Radiopharmaceuticals (National Medical Products Administration), Department of Nuclear Medicine, Peking University Cancer Hospital & Institute, No. 52 Fu-Cheng Rd, Beijing, 100142, China.

Purpose: Develop a Cu labeled radiopharmaceutical targeting prostate specific membrane antigen (PSMA) and investigate its application for prostate cancer imaging.

Methods: Cu-PSMA-BCH was prepared and investigated for stability, PSMA specificity, and micro-PET imaging. With the approval of Ethics Committee of Beijing Cancer Hospital (No. 2017KT97), PET/CT imaging in 4 patients with suspected prostate cancer was performed and the radiation dosimetry was estimated. Then, PSMA PET-ultrasound image-guided biopsies were performed on 3 patients and the fine needle aspirates were further performed for autoradiography and immunohistochemistry analysis.

Results: Cu-PSMA-BCH was prepared with high radiochemical yield and stability. In vivo study showed higher uptake in PSMA ( +) 22Rv1 cells than PSMA ( -) PC-3 cells (5.59 ± 0.36 and 1.97 ± 0.22 IA%/10 cells at 1 h). It accumulated in 22Rv1 tumor with increasing radioactivity uptake and T/N ratios from 1 to 24 h post-injection. In patients with suspected prostate cancer, SUVmax and T/N ratios increased within 24 h post-injection. Compared with image at 1 h post-injection, more tumor lesions were detected at 6 h and 24 h post-injection. The human organ radiation dosimetry showed gallbladder wall was most critical, liver and kidneys were followed, and the whole-body effective dose was 0.0292 mSv/MBq. Two fine needle aspirates obtained by PET-ultrasound-guided targeted biopsy showed high radioactive signal by autoradiography, with 100% PSMA expression in cytoplasm and 30% expression in nucleus.

Conclusion: Cu-PSMA-BCH was PSMA specific and showed high stability in vivo with lower uptake in liver than Cu-PSMA-617. Biodistribution in mice and PCa patients showed similar profile compared with other PSMA ligands and it was safe with moderate effective dosimetry. The increased tumor uptake and T/N ratios by delayed imaging may facilitate the detection of small lesions and guiding targeted biopsies.
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http://dx.doi.org/10.1007/s00259-021-05426-9DOI Listing
June 2021

New imaging modalities to consider for men with prostate cancer on active surveillance.

World J Urol 2021 Jun 19. Epub 2021 Jun 19.

The Brady Urological Institute, The Johns Hopkins School of Medicine, Baltimore, MD, 21287, USA.

Purpose: To discuss the potential utility of newer imaging modalities including micro-ultrasound and PSMA-PET for the detection of clinically significant prostate cancer, technologies that may gain roles as adjuncts to multiparametric magnetic resonance imaging (mpMRI) in the active surveillance (AS) setting.

Methods: Narrative review of two new imaging modalities used for primary prostate cancer through April 2021. A targeted search was performed to identify current relevant literature on the role of new imaging modalities for primary prostate cancer using search terms "micro-ultrasound," "molecular imaging," "prostate cancer," "active surveillance," "multiparametric MRI," "PI-RADS," "PRI-MUS," and "detection rate." In addition, references of included articles were screened for further relevant publications.

Results: Micro-ultrasound (micro-US) and prostate-specific membrane antigen-positron emission tomography (PSMA-PET) are increasing in their use and applicability to prostate cancer imaging. Micro-US is used for cancer detection and may identify higher grade cancers more accurately than conventional ultrasound, despite technical hurdles in its initial launch. PSMA-PET is highly sensitive and specific for high-grade and metastatic prostate cancer, though costly and not easily available. Though data are sparse, it may have an emerging role in cancer diagnosis in select localized cases, and in some men considering (or currently on) AS who have indications of more aggressive disease.

Conclusion: There are very limited data on micro-US and PSMA-PET in AS patients. However, given the ability of these modalities to identify high-grade cancer, their judicious use in AS patients may be of utility in the future.
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http://dx.doi.org/10.1007/s00345-021-03762-xDOI Listing
June 2021

A three-stage, deep learning, ensemble approach for prognosis in patients with Parkinson's disease.

EJNMMI Res 2021 Jun 7;11(1):52. Epub 2021 Jun 7.

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

Background: Diagnosis of Parkinson's disease (PD) is informed by the presence of progressive motor and non-motor symptoms and by imaging dopamine transporter with [I]ioflupane (DaTscan). Deep learning and ensemble methods have recently shown promise in medical image analysis. Therefore, this study aimed to develop a three-stage, deep learning, ensemble approach for prognosis in patients with PD.

Methods: Retrospective data of 198 patients with PD were retrieved from the Parkinson's Progression Markers Initiative database and randomly partitioned into the training, validation, and test sets with 118, 40, and 40 patients, respectively. The first and second stages of the approach extracted features from DaTscan and clinical measures of motor symptoms, respectively. The third stage trained an ensemble of deep neural networks on different subsets of the extracted features to predict patient outcome 4 years after initial baseline screening. The approach was evaluated by assessing mean absolute percentage error (MAPE), mean absolute error (MAE), Pearson's correlation coefficient, and bias between the predicted and observed motor outcome scores. The approach was compared to individual networks given different data subsets as inputs.

Results: The ensemble approach yielded a MAPE of 18.36%, MAE of 4.70, a Pearson's correlation coefficient of 0.84, and had no significant bias indicating accurate outcome prediction. The approach outperformed individual networks not given DaTscan imaging or clinical measures of motor symptoms as inputs, respectively.

Conclusion: The approach showed promise for longitudinal prognostication in PD and demonstrated the synergy of imaging and non-imaging information for the prediction task.
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http://dx.doi.org/10.1186/s13550-021-00795-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8184905PMC
June 2021

A bicentric retrospective analysis of clinical utility of F-fluciclovine PET in biochemically recurrent prostate cancer following primary radiation therapy: is it helpful in patients with a PSA rise less than the Phoenix criteria?

Eur J Nucl Med Mol Imaging 2021 Jun 6. Epub 2021 Jun 6.

Department of Radiology, University of Minnesota, Minneapolis, MN, USA.

Purpose: F-Fluciclovine PET imaging has been increasingly used in the restaging of prostate cancer patients with biochemical recurrence (BCR); however, its clinical utility in patients with low prostate-specific antigen (PSA) levels following primary radiation therapy has not been well-studied. This study aims to determine the detection rate and diagnostic accuracy of F-fluciclovine PET and the patterns of prostate cancer recurrence in patients with rising PSA after initial radiation therapy, particularly in patients with PSA levels below the accepted Phoenix definition of BCR (PSA nadir +2 ng/mL).

Methods: This retrospective study included patients from two tertiary institutions who underwent F-fluciclovine PET scans for elevated PSA level following initial external beam radiation therapy, brachytherapy, and/or proton therapy. Logistic regression and receiver operating characteristic (ROC) curve analyses were performed to determine the diagnostic accuracy of F-fluciclovine PET and associations of PSA kinetic parameters with F-fluciclovine PET outcome.

Results: One hundred patients were included in this study. The overall detection rate on a patient-level was 79% (79/100). F-Fluciclovine PET was positive in 62% (23/37) of cases with PSA below the Phoenix criteria. The positive predictive value of F-fluciclovine PET was 89% (95% CI: 80-94%). In patients with PSA below the Phoenix criteria, the PSA velocity had the highest predictive value of F-fluciclovine PET outcome. PSA doubling time (PSADT) and PSA velocity were associated with the presence of extra-pelvic metastatic disease.

Conclusion: F-Fluciclovine PET can identify recurrent disease at low PSA level and PSA rise below accepted Phoenix criteria in patients with suspected BCR after primary radiation therapy, particularly in patients with low PSADT or high PSA velocity. In patients with low PSADT or high PSA velocity, there is an increased probability of extra-pelvic metastases. Therefore, these patients are more likely to benefit from PET/CT or PET/MRI than pelvic MRI alone.
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http://dx.doi.org/10.1007/s00259-021-05415-yDOI Listing
June 2021

Neuroendocrine Tumor Theranostics: An Update and Emerging Applications in Clinical Practice.

AJR Am J Roentgenol 2021 08 2;217(2):495-506. Epub 2021 Jun 2.

Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Johns Hopkins Hospital, Johns Hopkins Outpatient Center, 601 N Caroline St, JHOC 3009, Baltimore, MD 21287.

Theranostics have shown great promise for delivering precision medicine, particularly in neuroendocrine tumors (NETs). The clinical applications of radiolabeled somatostatin analogues in imaging and radionuclide therapy have been rapidly increasing over the past 2 decades and are currently integrated into the management guidelines of NETs. This article summarizes the available literature on different somatostatin receptor-targeting radiopharmaceuticals with theranostic potential in NETs, pheochromocytomas, and paragangliomas. We discuss the clinical application, administration, and toxicity of recent FDA-approved radionuclide therapies, including Lu-DOTATATE in advanced gastroenteropancreatic NETs and I-MIBG in advanced paragangliomas and pheochromocytomas. Several studies support the safety and clinical efficacy of peptide receptor radionuclide therapies in disease control and quality-of-life improvement in patients with NETs and report potential benefits of combined radionuclide treatment approaches. The utility and pitfalls of functional imaging in therapy response assessment and surveillance of NETs remain to be established.
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http://dx.doi.org/10.2214/AJR.20.23349DOI Listing
August 2021

Neoadjuvant Nivolumab in Patients with High-risk Nonmetastatic Renal Cell Carcinoma.

Eur Urol Oncol 2021 May 25. Epub 2021 May 25.

The James Buchanan Brady Urological Institute and Department of Urology, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA. Electronic address:

Neoadjuvant immune checkpoint blockade represents a novel approach for potentially decreasing the risk of recurrence in patients with nonmetastatic renal cell carcinoma (RCC). In this early phase clincal tiral, we evaluated the safety and tolerability of neoadjuvant treatment with the programmed cell death protein 1 (PD-1) inhibitor nivolumab in patients with nonmetastatic high-risk RCC. Nonprimary endpoints included objective radiographic tumor response rate, immune-related pathologic response rate, quality of life alterations, and metastasis-free and overall survival. In total, 17 patients were enrolled in this study and underwent surgery without a delay after receiving three every-2-wk doses of neoadjuvant nivolumab. Adverse events (AEs) of any grade occurred in 14 (82.4%) patients, with two (11.8%) experiencing grade 3 events. Ten (58.8%) patients experienced an AE of any grade potentially attributable to nivolumab (all grade 1-2), and no grade 4-5 AEs occurred regardless of treatment attribution. The most common AEs were grade 1 fatigue (41.2%), grade 1 pruritis (29.4%), and grade 1 rash (29.4%). All evaluable patients had stable disease as per established radiographic criteria, with one (6.7%) demonstrating features of an immune-related pathologic response. Quality of life remained stable during treatment, with improvements relative to baseline noted at ≥6 mo postoperatively. Metastasis-free survival and overall survival were 85.1% and 100% at 2 yr, respectively. PATIENT SUMMARY: In this study, we evaluated the safety and tolerability of preoperative administration of three doses of the immune checkpoint inhibitor nivolumab in patients with clinically localized high-risk renal cell carcinoma. We demonstrated the safety of this approach and found that, although most patients will not experience a radiographic response to treatment, a subset may have features of an immune-related pathologic response.
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http://dx.doi.org/10.1016/j.euo.2021.04.002DOI Listing
May 2021

[18F]FDG-labelled stem cell PET imaging in different route of administrations and multiple animal species.

Sci Rep 2021 05 25;11(1):10896. Epub 2021 May 25.

Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama, Japan.

Stem cell therapy holds great promise for tissue regeneration and cancer treatment, although its efficacy is still inconclusive and requires further understanding and optimization of the procedures. Non-invasive cell tracking can provide an important opportunity to monitor in vivo cell distribution in living subjects. Here, using a combination of positron emission tomography (PET) and in vitro 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) direct cell labelling, the feasibility of engrafted stem cell monitoring was tested in multiple animal species. Human mesenchymal stem cells (MSCs) were incubated with phosphate-buffered saline containing [18F]FDG for in vitro cell radiolabelling. The pre-labelled MSCs were administrated via peripheral vein in a mouse (n = 1), rats (n = 4), rabbits (n = 4) and non-human primates (n = 3), via carotid artery in rats (n = 4) and non-human primates (n = 3), and via intra-myocardial injection in rats (n = 5). PET imaging was started 10 min after cell administration using a dedicated small animal PET system for a mouse and rats. A clinical PET system was used for the imaging of rabbits and non-human primates. After MSC administration via peripheral vein, PET imaging revealed intense radiotracer signal from the lung in all tested animal species including mouse, rat, rabbit, and non-human primate, suggesting administrated MSCs were trapped in the lung tissue. Furthermore, the distribution of the PET signal significantly differed based on the route of cell administration. Administration via carotid artery showed the highest activity in the head, and intra-myocardial injection increased signal from the heart. In vitro [18F]FDG MSC pre-labelling for PET imaging is feasible and allows non-invasive visualization of initial cell distribution after different routes of cell administration in multiple animal models. Those results highlight the potential use of that imaging approach for the understanding and optimization of stem cell therapy in translational research.
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http://dx.doi.org/10.1038/s41598-021-90383-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8149709PMC
May 2021

Re: Patrick D. McGillivray, Daiki Ueno, Aydin Pooli, et al. Distinguishing Benign Renal Tumors with an Oncocytic Gene Expression (ONEX) Classifier. Eur Urol 2021;79:107-11: Integrating Tc-sestamibi and ONEX to Optimize Risk Stratification for Renal Masses.

Eur Urol 2021 07 2;80(1):e20-e21. Epub 2021 May 2.

Department of Urology, The James Buchanan Brady Urological Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA. Electronic address:

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http://dx.doi.org/10.1016/j.eururo.2021.04.020DOI Listing
July 2021

Theranostics in Oncology-Thriving, Now More than Ever.

Diagnostics (Basel) 2021 Apr 29;11(5). Epub 2021 Apr 29.

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

Tracing its roots back to the 1940s, theranostics in nuclear oncology has proved successful mainly due to the beneficial effects of image-guided therapeutic concepts for patients afflicted with a variety of different cancers. The majority of these treatments are not only characterized by substantial prolongation of progression-free and overall survival, but are also generally safe, rendering theranostic agents as an attractive treatment option in various clinical scenarios in oncology. In this Special Issue , nine original articles from around the globe provide further evidence on the use of the theranostic concept for neuroendocrine neoplasm (NEN), prostate cancer (PC), meningioma, and neuroblastoma. The investigated diagnostic and therapeutic radiotracers target not only established structures, such as somatostatin receptor, prostate-specific membrane antigen or norepinephrine transporter, but also recently emerging targets such as the C-X-C motif chemokine receptor 4. Moreover, the presented original articles also combine the concept of theranostics with in-depth read-out techniques such as radiomics or novel reconstruction algorithms on pretherapeutic scans, e.g., for outcome prediction. Even 80 years after its initial clinical introduction, theranostics in oncology continues to thrive, now more than ever.
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http://dx.doi.org/10.3390/diagnostics11050805DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8146294PMC
April 2021

"Brother, Can You Spare a Dime?" An Introduction to Philanthropy and Fundraising.

J Am Coll Radiol 2021 10 28;18(10):1466-1468. Epub 2021 Apr 28.

Associate Professors from The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland. Electronic address:

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http://dx.doi.org/10.1016/j.jacr.2021.04.003DOI Listing
October 2021

Cellular and Molecular Imaging with SPECT and PET in Brain Tumors.

Radiol Clin North Am 2021 May;59(3):363-375

The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, 601 North Caroline Street, JHOC 3150, Baltimore, MD 21287, USA. Electronic address:

This review highlights the 2 major molecular imaging modalities that are used in clinics, namely single-photon emission computed tomography (SPECT) and positron emission tomography (PET), and their added value in management of patients with brain tumors. There are a variety of SPECT and PET radiotracers that can allow imaging of different molecular processes. Those radiotracers target specific molecular features of tumors, resulting in improved specificity of these agents. Potential applications include staging of brain tumors and evaluating post-therapeutic changes.
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http://dx.doi.org/10.1016/j.rcl.2021.01.005DOI Listing
May 2021

Effect of Point-Spread Function Reconstruction for Indeterminate PSMA-RADS-3A Lesions on PSMA-Targeted PET Imaging of Men with Prostate Cancer.

Diagnostics (Basel) 2021 Apr 7;11(4). Epub 2021 Apr 7.

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

Purpose: Prostate-specific membrane antigen (PSMA) positron emission tomography (PET) is emerging as an important modality for imaging patients with prostate cancer (PCa). As with any imaging modality, indeterminate findings will arise. The PSMA reporting and data system (PSMA-RADS) version 1.0 codifies indeterminate soft tissue findings with the PSMA-RADS-3A moniker. We investigated the role of point-spread function (PSF) reconstructions on categorization of PSMA-RADS-3A lesions.

Methods: This was a post hoc analysis of an institutional review board approved prospective trial. Around 60 min after the administration of 333 MBq (9 mCi) of PSMA-targeted F-DCFPyL, patients underwent PET/computed tomography (CT) acquisitions from the mid-thighs to the skull vertex. The PET data were reconstructed with and without PSF. Scans were categorized according to PSMA-RADS version 1.0, and all PSMA-RADS-3A lesions on non-PSF images were re-evaluated to determine if any could be re-categorized as PSMA-RADS-4. The maximum standardized uptake values (SUVs) of the lesions, mean SUVs of blood pool, and the ratios of those values were determined.

Results: A total of 171 PSMA-RADS-3A lesions were identified in 30 patients for whom both PSF reconstructions and cross-sectional imaging follow-up were available. A total of 13/171 (7.6%) were re-categorized as PSMA-RADS-4 lesions with PSF reconstructions. A total of 112/171 (65.5%) were found on follow-up to be true positive for PCa, with all 13 of the re-categorized lesions being true positive on follow-up. The lesions that were re-categorized trended towards having higher SUV-lesion and SUV-lesion/SUV-blood-pool metrics, although these relationships were not statistically significant.

Conclusions: The use of PSF reconstructions for F-DCFPyL PET can allow the appropriate re-categorization of a small number of indeterminate PSMA-RADS-3A soft tissue lesions as more definitive PSMA-RADS-4 lesions. The routine use of PSF reconstructions for PSMA-targeted PET may be of value at those sites that utilize this technology.
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http://dx.doi.org/10.3390/diagnostics11040665DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8067967PMC
April 2021

Learning fuzzy clustering for SPECT/CT segmentation via convolutional neural networks.

Med Phys 2021 Jul 28;48(7):3860-3877. Epub 2021 May 28.

Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA.

Purpose: Quantitative bone single-photon emission computed tomography (QBSPECT) has the potential to provide a better quantitative assessment of bone metastasis than planar bone scintigraphy due to its ability to better quantify activity in overlapping structures. An important element of assessing the response of bone metastasis is accurate image segmentation. However, limited by the properties of QBSPECT images, the segmentation of anatomical regions-of-interests (ROIs) still relies heavily on the manual delineation by experts. This work proposes a fast and robust automated segmentation method for partitioning a QBSPECT image into lesion, bone, and background.

Methods: We present a new unsupervised segmentation loss function and its semi- and supervised variants for training a convolutional neural network (ConvNet). The loss functions were developed based on the objective function of the classical Fuzzy C-means (FCM) algorithm. The first proposed loss function can be computed within the input image itself without any ground truth labels, and is thus unsupervised; the proposed supervised loss function follows the traditional paradigm of the deep learning-based segmentation methods and leverages ground truth labels during training. The last loss function is a combination of the first and the second and includes a weighting parameter, which enables semi-supervised segmentation using deep learning neural network.

Experiments And Results: We conducted a comprehensive study to compare our proposed methods with ConvNets trained using supervised, cross-entropy and Dice loss functions, and conventional clustering methods. The Dice similarity coefficient (DSC) and several other metrics were used as figures of merit as applied to the task of delineating lesion and bone in both simulated and clinical SPECT/CT images. We experimentally demonstrated that the proposed methods yielded good segmentation results on a clinical dataset even though the training was done using realistic simulated images. On simulated SPECT/CT, the proposed unsupervised model's accuracy was greater than the conventional clustering methods while reducing computation time by 200-fold. For the clinical QBSPECT/CT, the proposed semi-supervised ConvNet model, trained using simulated images, produced DSCs of and for lesion and bone segmentation in SPECT, and a DSC of bone segmentation of CT images. These DSCs were larger than that for standard segmentation loss functions by for SPECT segmentation, and for CT segmentation with P-values from a paired t-test.

Conclusions: A ConvNet-based image segmentation method that uses novel loss functions was developed and evaluated. The method can operate in unsupervised, semi-supervised, or fully-supervised modes depending on the availability of annotated training data. The results demonstrated that the proposed method provides fast and robust lesion and bone segmentation for QBSPECT/CT. The method can potentially be applied to other medical image segmentation applications.
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http://dx.doi.org/10.1002/mp.14903DOI Listing
July 2021

Current and future perspectives on functional molecular imaging in nephro-urology: theranostics on the horizon.

Theranostics 2021 7;11(12):6105-6119. Epub 2021 Apr 7.

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

In recent years, a paradigm shift from single-photon-emitting radionuclide radiotracers toward positron-emission tomography (PET) radiotracers has occurred in nuclear oncology. Although PET-based molecular imaging of the kidneys is still in its infancy, such a trend has emerged in the field of functional renal radionuclide imaging. Potentially allowing for precise and thorough evaluation of renal radiotracer urodynamics, PET radionuclide imaging has numerous advantages including precise anatomical co-registration with CT images and dynamic three-dimensional imaging capability. In addition, relative to scintigraphic approaches, PET can allow for significantly reduced scan time enabling high-throughput in a busy PET practice and further reduces radiation exposure, which may have a clinical impact in pediatric populations. In recent years, multiple renal PET radiotracers labeled with C, Ga, and F have been utilized in clinical studies. Beyond providing a precise non-invasive read-out of renal function, such radiotracers may also be used to assess renal inflammation. This manuscript will provide an overview of renal molecular PET imaging and will highlight the transformation of conventional scintigraphy of the kidneys toward novel, high-resolution PET imaging for assessing renal function. In addition, future applications will be introduced, e.g. by transferring the concept of molecular image-guided diagnostics and therapy (theranostics) to the field of nephrology.
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http://dx.doi.org/10.7150/thno.58682DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8058716PMC
July 2021

Surviving and Thriving in a Black Swan Event.

J Am Coll Radiol 2021 09 1;18(9):1369-1370. Epub 2021 May 1.

Associate Professor, The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland. Electronic address:

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http://dx.doi.org/10.1016/j.jacr.2021.03.012DOI Listing
September 2021

Imaging infections in patients using pathogen-specific positron emission tomography.

Sci Transl Med 2021 04;13(589)

Center for Infection and Inflammation Imaging Research, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.

represent the largest group of bacterial pathogens in humans and are responsible for severe, deep-seated infections, often resulting in sepsis or death. They are also a prominent cause of multidrug-resistant (MDR) infections, and some species are recognized as biothreat pathogens. Tools for noninvasive, whole-body analysis that can localize a pathogen with specificity are needed, but no such technology currently exists. We previously demonstrated that positron emission tomography (PET) with 2-deoxy-2-[F]fluoro-d-sorbitol (F-FDS) can selectively detect infections in murine models. Here, we demonstrate that uptake of F-FDS by bacteria occurs via a metabolically conserved sorbitol-specific pathway with rapid in vitro F-FDS uptake noted in clinical strains, including MDR isolates. Whole-body F-FDS PET/computerized tomography (CT) in 26 prospectively enrolled patients with either microbiologically confirmed infection or other pathologies demonstrated that F-FDS PET/CT was safe, could rapidly detect and localize infections due to drug-susceptible or MDR strains, and differentiated them from sterile inflammation or cancerous lesions. Repeat imaging in the same patients monitored antibiotic efficacy with decreases in PET signal correlating with clinical improvement. To facilitate the use of F-FDS, we developed a self-contained, solid-phase cartridge to rapidly (<10 min) formulate ready-to-use F-FDS from commercially available 2-deoxy-2-[F]fluoro-d-glucose (F-FDG) at room temperature. In a hamster model, F-FDS PET/CT also differentiated severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pneumonia from secondary pneumonia-a leading cause of complications in hospitalized patients with COVID-19. These data support F-FDS as an innovative and readily available, pathogen-specific PET technology with clinical applications.
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http://dx.doi.org/10.1126/scitranslmed.abe9805DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8120649PMC
April 2021
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