Karl Sjöstrand

Supplementary Data and Methods 1 from Automated Imaging as an Adjunct to Serum and Clinical Biomarkers: A New Validated Prediction Tool for Metastatic Castration-Resistant Prostate Cancer

Michael J. Morris, Jessica R. Flynn, Binsheng Zhao, Aseem Anand et autres

Background on statistical methods applied and the results from the bone only cohort analysis.

Data from Automated Imaging as an Adjunct to Serum and Clinical Biomarkers: A New Validated Prediction Tool for Metastatic Castration-Resistant Prostate Cancer

Michael J. Morris, Jessica R. Flynn, Binsheng Zhao, Aseem Anand et autres

AbstractPurpose: Contemporary prostate cancer prognostic models do not include imaging and generally are based on pretreatment parameters. We sought to develop an externally validated model that used novel quantification of soft-tissue and bone disease, integrated with standard clinical and serum biomarkers, at …

Deep learning models built from PSMA PET of the primary tumor can predict synchronous and metachronous prostate cancer metastases

Jesus E. Juarez Casillas, Maryam Nezafat, Cecil Mayra Benitez, Kamil Rzechowski et autres

OBJECTIVE: The objective was to develop prognostic models that included convolutional neural networks (CNN) derived from 18F-DCFPyL (PSMA) PET imaging of the primary tumor uptake patterns to prognose early metastatic progression after curative intent treatment for localized prostate cancer. METHODS: Due to …

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Automated Imaging as an Adjunct to Serum and Clinical Biomarkers: A New Validated Prediction Tool for Metastatic Castration-Resistant Prostate Cancer

Michael J. Morris, Jessica R. Flynn, Binsheng Zhao, Aseem Anand et autres

PURPOSE: Contemporary prostate cancer prognostic models do not include imaging and generally are based on pretreatment parameters. We sought to develop an externally validated model that used novel quantification of soft-tissue and bone disease, integrated with standard clinical and serum biomarkers, at …

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Early detection of recurrent prostate cancer using 18F-DCFPyL PET/CT PET/CT in patients with minimal PSA levels.

Ida Sonni, Nicholas George Nickols, Katelyn Niknam, Gholam Reza Berenji et autres

344 Background: PSMA PET imaging is a highly sensitive and specific imaging tool for detecting prostate cancer, especially in biochemical recurrence (BCR). This has led to growing interest in utilizing PSMA PET for patients with minimally detectable PSA levels following definitive treatment …

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A novel predictive model using changes in clinical and serum biomarkers and automated quantitative imaging for mCRPC patients treated with AR-directed therapy.

Michael J. Morris, Jessica R. Flynn, Binsheng Zhao, Aseem Anand et autres

264 Background: In mCRPC, standard risk models use baseline clinical and blood-based biomarkers, excluding imaging. This study developed a new predictive model incorporating baseline and early on-treatment clinical, blood, and imaging biomarkers to inform overall survival (OS). The training set was derived …

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Artificial Intelligence Model Using PSMA PET Imaging of Primary Prostate Cancer for Analyzing Metastases and Post-Treatment Progression

Jesus Eduardo Juarez, Cecil Mayra Benitez, Kamil Rzechowski, Karl Sjöstrand et autres

1635P Validation of automated bone scan index as a progression endpoint in two phase III studies of metastatic castration resistant prostate cancer (mCRPC) patients

Andrea Knežević, G. Heller, Karl Sjöstrand, Aseem Anand et autres

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Total and anatomically contextualized quantitative 18F-DCFPyL PET at biochemical recurrence to predict subsequent biochemical progression-free survival in patients with prostate cancer.

HONG SUK SONG, Aseem Anand, Karl Sjöstrand, Valentina Ferri et autres

33 Background: PSMA PET has been shown to detect more metastasis and alter management at biochemical recurrence (BCR), but it remains to be determined that it changes oncologic outcome. We assessed the quantitative parameters on 18F-DCFPyL PET at BCR and evaluated their …

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A convolutional neural network model using intraprostatic patterns of [F18]DCFPyL uptake in PSMA PET images to predict synchronous metastases.

Jesus Eduardo Juarez, Cecil Mayra Benitez, Kamil Rzechowski, Karl Sjöstrand et autres

46 Background: [F18]DCFPyL (PyL) is a PSMA targeted imaging agent that provides whole-body staging of prostate cancer. Image analysis of the primary tumor using deep learning algorithms might offer additional insight into disease biology, including co-existing metastatic disease. We developed convolutional neural …

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Total and anatomically contextualized quantitative 18F-DCFPyL PET at biochemical recurrence to predict subsequent biochemical progression free survival in patients with prostate cancer.

HONG SUK SONG, Karl Sjöstrand, Heying Duan, Valentina Ferri et autres

e17015 Background: PSMA PET has been widely adopted in restaging of prostate cancer at biochemical recurrence. We assess the clinical utility of quantitative parameters on 18F-DCFPyL PET/CT at biochemical recurrence and their association with the subsequent biochemical progression free survival (bPFS). Methods: …

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PD35-04 QUANTITATIVE PIFLUFOLASTAT F18 (PSMA) SCAN INDICES AS A RESPONSE IMAGING-BIOMARKER TO ANDROGEN DEPRIVATION THERAPY IN VETERANS WITH NEWLY DIAGNOSED METASTATIC PROSTATE CANCER

Nicholas George Nickols, Gholam Reza Berenji, Nathanael Kane, Karl Sjöstrand et autres

You have accessJournal of UrologyCME1 May 2022PD35-04 QUANTITATIVE PIFLUFOLASTAT F18 (PSMA) SCAN INDICES AS A RESPONSE IMAGING-BIOMARKER TO ANDROGEN DEPRIVATION THERAPY IN VETERANS WITH NEWLY DIAGNOSED METASTATIC PROSTATE CANCER Nicholas Nickols, Gholam Berenji, Nathanael Kane, Karl Sjöstrand, Aseem Anand, Clayton Smith, Jeremie …