Publications by authors named "Matthijs Cysouw"

MYCN-amplified RB1 wild-type (MYCNRB1) retinoblastoma is a rare and aggressive subtype, often resistant to standard therapies. Identifying unique MRI features is crucial for diagnosing this subtype, as biopsy is not recommended. This study aimed to differentiate MYCNRB1 from the most prevalent RB1 retinoblastoma using pretreatment MRI and radiomics.

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Background: Various risk classification systems (RCSs) are used globally to stratify newly diagnosed patients with prostate cancer (PCa) into prognostic groups.

Objective: To compare the predictive value of different prognostic subgroups (low-, intermediate-, and high-risk disease) within the RCSs for detecting metastatic disease on prostate-specific membrane antigen (PSMA) positron emission tomography (PET)/computed tomography (CT) for primary staging, and to assess whether further subdivision of subgroups would be beneficial.

Design, Setting, And Participants: Patients with newly diagnosed PCa, in whom PSMA-PET/CT was performed between 2017 and 2022, were studied retrospectively.

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Background: Prediction of treatment resistance in schizophrenia (TRS) would be helpful to reduce the duration of ineffective treatment and avoid delays in clozapine initiation. We applied machine learning to identify clinical, sociodemographic, familial, and environmental variables that are associated with TRS and could potentially predict TRS in the future.

Study Design: Baseline and follow-up data on trait(-like) variables from the Genetic Risk and Outcome of Psychosis (GROUP) study were used.

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Article Synopsis
  • The study investigates the use of radiomics from PSMA-PET imaging modeled with machine learning to predict disease risk factors in prostate cancer, focusing on lymph-node involvement (LNI), extracapsular extension (ECE), and postoperative Gleason score (GS).
  • A total of 123 intermediate- to high-risk prostate cancer patients were analyzed using various machine learning methods and a comprehensive dataset, leading to significant predictive performance for Gleason score but not for LNI or ECE.
  • The results indicate that while ML models show promise, especially for GS prediction, further validation is needed, and combat harmonization techniques can enhance performance in external datasets.
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Purpose: Biomarkers that can accurately predict outcome in DLBCL patients are urgently needed. Radiomics features extracted from baseline [F]-FDG PET/CT scans have shown promising results. This study aims to investigate which lesion- and feature-selection approaches/methods resulted in the best prediction of progression after 2 years.

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Targeting the prostate-specific membrane antigen (PSMA) protein has become of great clinical value in prostate cancer (PCa) care. PSMA positron emission tomography/computed tomography (PET/CT) is increasingly used in initial staging and restaging at biochemical recurrence in patients with PCa, where it has shown superior detection rates compared to previous imaging modalities. Apart from targeting PSMA for diagnostic purposes, there is a growing interest in developing ligands to target the PSMA-protein for radioligand therapy (RLT).

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Metastatic tumor deposits in bone marrow elicit differential bone responses that vary with the type of malignancy. This results in either sclerotic, lytic, or mixed bone lesions, which can change in morphology due to treatment effects and/or secondary bone remodeling. Hence, morphological imaging is regarded unsuitable for response assessment of bone metastases and in the current Response Evaluation Criteria In Solid Tumors 1.

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In prostate cancer (PCa) patients, the tumor-to-blood ratio (TBR) has been validated as the preferred simplified method for lesional F-DCFPyL (a radiolabeled prostate-specific membrane antigen ligand) uptake quantification on PET. In contrast to SUVs, the TBR accounts for variability in arterial input functions caused by differences in total tumor burden between patients (the sink effect). However, TBR depends strongly on tracer uptake interval and has worse repeatability and is less applicable in clinical practice than SUVs.

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Purpose: Visual reading of F-florbetapir positron emission tomography (PET) scans is used in the diagnostic process of patients with cognitive disorders for assessment of amyloid-ß (Aß) depositions. However, this can be time-consuming, and difficult in case of borderline amyloid pathology. Computer-aided pattern recognition can be helpful in this process but needs to be validated.

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Purpose: Quantitative prostate-specific membrane antigen (PSMA) PET analysis may provide for non-invasive and objective risk stratification of primary prostate cancer (PCa) patients. We determined the ability of machine learning-based analysis of quantitative [F]DCFPyL PET metrics to predict metastatic disease or high-risk pathological tumor features.

Methods: In a prospective cohort study, 76 patients with intermediate- to high-risk PCa scheduled for robot-assisted radical prostatectomy with extended pelvic lymph node dissection underwent pre-operative [F]DCFPyL PET-CT.

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Quantitative evaluation of radiolabeled prostate-specific membrane antigen (PSMA) PET scans may be used to monitor treatment response in patients with prostate cancer (PCa). To interpret longitudinal differences in PSMA uptake, the intrinsic variability of tracer uptake in PCa lesions needs to be defined. The aim of this study was to investigate the repeatability of quantitative PET/CT measurements using F-DCFPyL ([2-(3-(1-carboxy-5-[(6-F-fluoro-pyridine-3-carbonyl)-amino]-pentyl)-ureido)-pentanedioic acid], a second-generation F-PSMA-ligand) in patients with PCa.

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Objectives: Whole body [F]-fluorodihydrotestosterone positron emission tomography ([F]FDHT PET) imaging directly targets the androgen receptor and is a promising prognostic and predictive biomarker in metastatic castration-resistant cancer (mCRPC). To optimize [F]FDHT PET-CT for diagnostic and response assessment purposes, we assessed how count statistics and reconstruction protocol affect its accuracy, repeatability, and lesion detectability.

Methods: Whole body [F]FDHT PET-CT scans were acquired on an analogue PET-CT on two consecutive days in 14 mCRPC patients harbouring a total of 336 FDHT-avid lesions.

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Radiolabeled prostate-specific membrane antigen (PSMA) PET has demonstrated promising results for prostate cancer (PCa) imaging. Quantification of PSMA radiotracer uptake is desired as it enables reliable interpretation of PET images, use of PSMA uptake as an imaging biomarker for tumor characterization, and evaluation of treatment effects. The aim of this study was to perform a full pharmacokinetic analysis of 2-(3-(1-carboxy-5-[(6-F-fluoro-pyridine-3-carbonyl)-amino]-pentyl)-ureido)-pentanedioic acid (F-DCFPyL), a second-generation F-labeled PSMA ligand.

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PET is increasingly used for prostate cancer (PCa) diagnostics. Important PCa radiotracers include Ga-prostate-specific membrane antigen HBED-CC (Ga-PSMA), F-DCFPyL, F-fluoromethylcholine (F-FCH), and F-dihydrotestosterone (F-FDHT). Knowledge on the variability of tracer uptake in healthy tissues is important for accurate PET interpretation, because malignancy is suspected only if the uptake of a lesion contrasts with its background.

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Purpose: To investigate the predictive value of [F]-fluoromethylcholine positron emission tomography/computed tomography (PET/CT)-derived parameters on progression-free survival (PFS) in oligometastatic prostate cancer patients treated with stereotactic body radiation therapy (SBRT).

Methods And Materials: In [F]-fluoromethylcholine PET/CT scans of 40 consecutive patients with ≤4 metachronous metastases treated with SBRT we retrospectively measured the number of metastases, standardized uptake values (SUV, SUV, SUV), metabolically active tumor volume (MATV), and total lesion choline uptake. Partial-volume correction was applied using the iterative deconvolution Lucy-Richardson algorithm.

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Purpose: Positron-emission tomography can be useful in oncology for diagnosis, (re)staging, determining prognosis, and response assessment. However, partial-volume effects hamper accurate quantification of lesions <2-3× the PET system's spatial resolution, and the clinical impact of this is not evident. This systematic review provides an up-to-date overview of studies investigating the impact of partial-volume correction (PVC) in oncological PET studies.

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Purpose: [F]-fluorothymidine ([F]-FLT) is a PET-tracer enabling in-vivo visualization and quantification of tumor cell proliferation. For qualitative and quantitative analysis, adequate knowledge of normal tissue uptake is indispensable. This study aimed to quantitatively investigate baseline tracer uptake of blood pool, lung, liver and bone marrow and their precision, and to assess the longitudinal effect of systemic treatment on biodistribution.

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Introduction: For patients with oligometastatic recurrence of prostate cancer (PC), stereotactic body radiation therapy (SBRT) represents an attractive treatment option, as it is safe without major side effects. The aim of this study was to investigate the impact of SBRT in delaying the start of androgen deprivation therapy (ADT).

Patients And Methods: Forty-three patients treated with SBRT for oligometastatic recurrence (< 5 metastases) of hormone-sensitive PC, defined with [F]fluoromethylcholine positron emission tomography/computed tomography were included.

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Unlabelled: Accurate quantification of tracer uptake in small tumors using PET is hampered by the partial-volume effect as well as by the method of volume-of-interest (VOI) delineation. This study aimed to investigate the effect of partial-volume correction (PVC) combined with several VOI methods on the accuracy and precision of quantitative PET.

Methods: Four image-based PVC methods and resolution modeling (applied as PVC) were used in combination with several common VOI methods.

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