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3. Validation of an Artificial Intelligence–Based Prediction Model Using 5 External PET/CT Datasets of Diffuse Large B-Cell Lymphoma.

Author

Ferrández, Maria C., Golla, Sandeep S.V., Eertink, Jakoba J., Wiegers, Sanne E., Zwezerijnen, Gerben J.C., Heymans, Martijn W., Lugtenburg, Pieternella J., Kurch, Lars, Hüttmann, Andreas, Hanoun, Christine, Dührsen, Ulrich, Barrington, Sally F., Mikhaeel, N. George, Ceriani, Luca, Zucca, Emanuele, Czibor, Sándor, Györke, Tamás, Chamuleau, Martine E.D., Zijlstra, Josée M., and Boellaard, Ronald

Published
2024
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4. Whole-Body HER2 Heterogeneity Identified on HER2 PET in HER2-Negative, -Low, and -Positive Metastatic Breast Cancer.

Author

Eisses, Bertha, van Geel, Jasper J.L., Brouwers, Adrienne H., Bensch, Frederike, Elias, Sjoerd G., Kuip, Evelien J.M., Jager, Agnes, van der Vegt, Bert, Lub-de Hooge, Marjolijn N., Emmering, Jasper, Arens, Anne I.J., Zwezerijnen, Gerben J.C., Vugts, Daniëlle J., Menke-van der Houven van Oordt, C. Willemien, de Vries, Elisabeth G.E., Schröder, Carolina P., Bensch, F., van Es, S., van Essen-Eisses, B., and Boers, J.

Published
2024
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5. International Benchmark for Total Metabolic Tumor Volume Measurement in Baseline 18F-FDG PET/CT of Lymphoma Patients: A Milestone Toward Clinical Implementation.

Author

Boellaard, Ronald, Buvat, Irène, Nioche, Christophe, Ceriani, Luca, Cottereau, Anne-Ségolène, Guerra, Luca, Hicks, Rodney J., Kanoun, Salim, Kobe, Carsten, Loft, Annika, Schöder, Heiko, Versari, Annibale, Voltin, Conrad-Amadeus, Zwezerijnen, Gerben J.C., Zijlstra, Josée M., Mikhaeel, N. George, Gallamini, Andrea, El-Galaly, Tarec C., Hanoun, Christine, and Chauvie, Stephane

Published
2024
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6. Baseline radiomics features and MYC rearrangement status predict progression in aggressive B-cell lymphoma

Author

Eertink, Jakoba Johanna, Zwezerijnen, Gerben J.C., Wiegers, Sanne E., Pieplenbosch, Simone, Chamuleau, Martine E.D., Lugtenburg, Pieternella J., de Jong, Daphne, Ylstra, Bauke, Mendeville, Matias, Dührsen, Ulrich, Hanoun, Christine, Hüttmann, Andreas, Richter, Julia, Klapper, Wolfram, Jauw, Yvonne W.S., Hoekstra, Otto S., de Vet, Henrica C.W., Boellaard, Ronald, Zijlstra, Josée M., Radiology and nuclear medicine, Hematology, CCA - Cancer Treatment and quality of life, CCA - Cancer biology and immunology, Pathology, AII - Cancer immunology, CCA - Imaging and biomarkers, Epidemiology and Data Science, APH - Methodology, Amsterdam Neuroscience - Brain Imaging, and AII - Infectious diseases

Subjects
Medizin, Hematology
Abstract

We investigated whether the outcome prediction of patients with aggressive B-cell lymphoma can be improved by combining clinical, molecular genotype, and radiomics features. MYC, BCL2, and BCL6 rearrangements were assessed using fluorescence in situ hybridization. Seventeen radiomics features were extracted from the baseline positron emission tomography–computed tomography of 323 patients, which included maximum standardized uptake value (SUVmax), SUVpeak, SUVmean, metabolic tumor volume (MTV), total lesion glycolysis, and 12 dissemination features pertaining to distance, differences in uptake and volume between lesions, respectively. Logistic regression with backward feature selection was used to predict progression after 2 years. The predictive value of (1) International Prognostic Index (IPI); (2) IPI plus MYC; (3) IPI, MYC, and MTV; (4) radiomics; and (5) MYC plus radiomics models were tested using the cross-validated area under the curve (CV-AUC) and positive predictive values (PPVs). IPI yielded a CV-AUC of 0.65 ± 0.07 with a PPV of 29.6%. The IPI plus MYC model yielded a CV-AUC of 0.68 ± 0.08. IPI, MYC, and MTV yielded a CV-AUC of 0.74 ± 0.08. The highest model performance of the radiomics model was observed for MTV combined with the maximum distance between the largest lesion and another lesion, the maximum difference in SUVpeak between 2 lesions, and the sum of distances between all lesions, yielding an improved CV-AUC of 0.77 ± 0.07. The same radiomics features were retained when adding MYC (CV-AUC, 0.77 ± 0.07). PPV was highest for the MYC plus radiomics model (50.0%) and increased by 20% compared with the IPI (29.6%). Adding radiomics features improved model performance and PPV and can, therefore, aid in identifying poor prognosis patients.

Published
2023
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7. Supplementary Figure S2 from [89Zr]Zr-DFO-girentuximab and [18F]FDG PET/CT to Predict Watchful Waiting Duration in Patients with Metastatic Clear-cell Renal Cell Carcinoma

Author

Verhoeff, Sarah R., primary, Oosting, Sjoukje F., primary, Elias, Sjoerd G., primary, van Es, Suzanne C., primary, Gerritse, Sophie L., primary, Angus, Lindsay, primary, Heskamp, Sandra, primary, Desar, Ingrid M.E., primary, Menke-van der Houven van Oordt, C. Willemien, primary, van der Veldt, Astrid A.M., primary, Arens, Anne I.J., primary, Brouwers, Adrienne H., primary, Eisses, Bertha, primary, Mulders, Peter F.A., primary, Hoekstra, Otto S., primary, Zwezerijnen, Gerben J.C., primary, van der Graaf, Winette T.A., primary, Aarntzen, Erik H.J.G., primary, Oyen, Wim J.G., primary, and van Herpen, Carla M.L., primary

Published
2023
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8. An artificial intelligence method using FDG PET to predict treatment outcome in diffuse large B cell lymphoma patients

Author

Ferrández, Maria C., Golla, Sandeep S.V., Eertink, Jakoba J., de Vries, Bart M., Lugtenburg, Pieternella J., Wiegers, Sanne E., Zwezerijnen, Gerben J.C., Pieplenbosch, Simone, Kurch, Lars, Hüttmann, Andreas, Hanoun, Christine, Dührsen, Ulrich, de Vet, Henrica C.W., Zijlstra, Josée M., Boellaard, Ronald, Ferrández, Maria C., Golla, Sandeep S.V., Eertink, Jakoba J., de Vries, Bart M., Lugtenburg, Pieternella J., Wiegers, Sanne E., Zwezerijnen, Gerben J.C., Pieplenbosch, Simone, Kurch, Lars, Hüttmann, Andreas, Hanoun, Christine, Dührsen, Ulrich, de Vet, Henrica C.W., Zijlstra, Josée M., and Boellaard, Ronald

Abstract

Convolutional neural networks (CNNs) may improve response prediction in diffuse large B-cell lymphoma (DLBCL). The aim of this study was to investigate the feasibility of a CNN using maximum intensity projection (MIP) images from 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) baseline scans to predict the probability of time-to-progression (TTP) within 2 years and compare it with the International Prognostic Index (IPI), i.e. a clinically used score. 296 DLBCL 18F-FDG PET/CT baseline scans collected from a prospective clinical trial (HOVON-84) were analysed. Cross-validation was performed using coronal and sagittal MIPs. An external dataset (340 DLBCL patients) was used to validate the model. Association between the probabilities, metabolic tumour volume and Dmaxbulk was assessed. Probabilities for PET scans with synthetically removed tumors were also assessed. The CNN provided a 2-year TTP prediction with an area under the curve (AUC) of 0.74, outperforming the IPI-based model (AUC = 0.68). Furthermore, high probabilities (> 0.6) of the original MIPs were considerably decreased after removing the tumours (< 0.4, generally). These findings suggest that MIP-based CNNs are able to predict treatment outcome in DLBCL.

Published
2023

9. Supplementary Data from Praluzatamab Ravtansine, a CD166-Targeting Antibody–Drug Conjugate, in Patients with Advanced Solid Tumors: An Open-Label Phase I/II Trial

Author

Boni, Valentina, primary, Fidler, Mary J., primary, Arkenau, Hendrik-Tobias, primary, Spira, Alexander, primary, Meric-Bernstam, Funda, primary, Uboha, Nataliya, primary, Sanborn, Rachel E., primary, Sweis, Randy F., primary, LoRusso, Patricia, primary, Nagasaka, Misako, primary, Garcia-Corbacho, Javier, primary, Jalal, Shadia, primary, Harding, James J., primary, Kim, Stella K., primary, Miedema, Iris H.C., primary, Vugts, Danielle J., primary, Huisman, Marc C., primary, Zwezerijnen, Gerben J.C., primary, van Dongen, Guus A.M.S., primary, Menke van der Houven van Oordt, C. Willemien, primary, Wang, Song, primary, Dang, Tam, primary, Zein, Ivan A., primary, Vasiljeva, Olga, primary, Lyman, Susan K., primary, Paton, Virginia, primary, Hannah, Alison, primary, and Liu, Joyce F., primary

Published
2023
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10. [89Zr]Zr-DFO-girentuximab and [18F]FDG PET/CT to Predict Watchful Waiting Duration in Patients with Metastatic Clear-cell Renal Cell Carcinoma

Author

Verhoeff, Sarah R., primary, Oosting, Sjoukje F., additional, Elias, Sjoerd G., additional, van Es, Suzanne C., additional, Gerritse, Sophie L., additional, Angus, Lindsay, additional, Heskamp, Sandra, additional, Desar, Ingrid M.E., additional, Menke-van der Houven van Oordt, C. Willemien, additional, van der Veldt, Astrid A.M., additional, Arens, Anne I.J., additional, Brouwers, Adrienne H., additional, Eisses, Bertha, additional, Mulders, Peter F.A., additional, Hoekstra, Otto S., additional, Zwezerijnen, Gerben J.C., additional, van der Graaf, Winette T.A., additional, Aarntzen, Erik H.J.G., additional, Oyen, Wim J.G., additional, and van Herpen, Carla M.L., additional

Published
2022
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11. Comment on: Effects of Anti‐Tumor Necrosis Factor therapy on Osteoblastic Activity at Sites of Inflammatory and Structural Lesions in Radiographic Axial Spondyloarthritis – A Prospective Proof‐of‐Concept Study using Positron Emission Tomography/Magnetic Resonance Imaging of the Sacroiliac Joints and Spine

Author

de Jongh, Jerney, primary, Zwezerijnen, Gerben J.C., additional, Yaqub, Maqsood, additional, and van der Laken, Conny J., additional

Published
2022
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12. Proposed New Dynamic Prognostic Index for Diffuse Large B-Cell Lymphoma: International Metabolic Prognostic Index

Author

Mikhaeel, N. George, primary, Heymans, Martijn W., additional, Eertink, Jakoba J., additional, de Vet, Henrica C.W., additional, Boellaard, Ronald, additional, Dührsen, Ulrich, additional, Ceriani, Luca, additional, Schmitz, Christine, additional, Wiegers, Sanne E., additional, Hüttmann, Andreas, additional, Lugtenburg, Pieternella J., additional, Zucca, Emanuele, additional, Zwezerijnen, Gerben J.C., additional, Hoekstra, Otto S., additional, Zijlstra, Josée M., additional, and Barrington, Sally F., additional

Published
2022
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13. Positron Emission Tomography to Improve Assessment of Interstitial Lung Disease in Patients With Systemic Sclerosis Eligible for Autologous Stem Cell Transplantation

Author

Broens, Bo, primary, van der Laken, Conny J., additional, Zwezerijnen, Gerben J.C., additional, Nossent, Esther J., additional, Meijboom, Lilian J., additional, Spierings, Julia, additional, de Vries-Bouwstra, Jeska K., additional, van Laar, Jacob M., additional, and Voskuyl, Alexandre E., additional

Published
2022
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14. 18F-FDG PET baseline radiomics features improve the prediction of treatment outcome in diffuse large B-cell lymphoma

Author

Eertink, Jakoba J., van de Brug, Tim, Wiegers, Sanne E., Zwezerijnen, Gerben J.C., Pfaehler, Elisabeth A.G., Lugtenburg, Pieternella J., van der Holt, Bronno, de Vet, Henrica C.W., Hoekstra, Otto S., Boellaard, Ronald, Zijlstra, Josée M., Eertink, Jakoba J., van de Brug, Tim, Wiegers, Sanne E., Zwezerijnen, Gerben J.C., Pfaehler, Elisabeth A.G., Lugtenburg, Pieternella J., van der Holt, Bronno, de Vet, Henrica C.W., Hoekstra, Otto S., Boellaard, Ronald, and Zijlstra, Josée M.

Abstract

Purpose: Accurate prognostic markers are urgently needed to identify diffuse large B-Cell lymphoma (DLBCL) patients at high risk of progression or relapse. Our purpose was to investigate the potential added value of baseline radiomics features to the international prognostic index (IPI) in predicting outcome after first-line treatment. Methods: Three hundred seventeen newly diagnosed DLBCL patients were included. Lesions were delineated using a semi-automated segmentation method (standardized uptake value ≥ 4.0), and 490 radiomics features were extracted. We used logistic regression with backward feature selection to predict 2-year time to progression (TTP). The area under the curve (AUC) of the receiver operator characteristic curve was calculated to assess model performance. High-risk groups were defined based on prevalence of events; diagnostic performance was assessed using positive and negative predictive values. Results: The IPI model yielded an AUC of 0.68. The optimal radiomics model comprised the natural logarithms of metabolic tumor volume (MTV) and of SUVpeak and the maximal distance between the largest lesion and any other lesion (Dmaxbulk, AUC 0.76). Combining radiomics and clinical features showed that a combination of tumor- (MTV, SUVpeak and Dmaxbulk) and patient-related parameters (WHO performance status and age > 60 years) performed best (AUC 0.79). Adding radiomics features to clinical predictors increased PPV with 15%, with more accurate selection of high-risk patients compared to the IPI model (progression at 2-year TTP, 44% vs 28%, respectively). Conclusion: Prediction models using baseline radiomics combined with currently used clinical predictors identify patients at risk of relapse at baseline and significantly improved model performance.

Published
2022

15. PET-CT Imaging of Polymeric Nanoparticle Tumor Accumulation in Patients

Author

Miedema, Iris H.C., Zwezerijnen, Gerben J.C., Huisman, Marc C., Doeleman, Ellen, Mathijssen, Ron H.J., Lammers, Twan, Hu, Qizhi, van Dongen, Guus A.M.S., Rijcken, Cristianne J.F., Vugts, Danielle J., Menke-van der Houven van Oordt, C. Willemien, Miedema, Iris H.C., Zwezerijnen, Gerben J.C., Huisman, Marc C., Doeleman, Ellen, Mathijssen, Ron H.J., Lammers, Twan, Hu, Qizhi, van Dongen, Guus A.M.S., Rijcken, Cristianne J.F., Vugts, Danielle J., and Menke-van der Houven van Oordt, C. Willemien

Abstract

Several FDA/EMA-approved nanomedicines have demonstrated improved pharmacokinetics and toxicity profiles compared to their conventional chemotherapeutic counterparts. The next step to increase therapeutic efficacy depends on tumor accumulation, which can be highly heterogeneous. A clinical tool for patient stratification is urgently awaited. Therefore, a docetaxel-entrapping polymeric nanoparticle (89Zr-CPC634) is radiolabeled, and positron emission tomography/computed tomography (PET/CT) imaging is performed in seven patients with solid tumors with two different doses of CPC634: an on-treatment (containing 60 mg m−2 docetaxel) and a diagnostic (1–2 mg docetaxel) dose (NCT03712423). Pharmacokinetic half-life for 89Zr-CPC634 is mean 97.0 ± 14.4 h on-treatment, and 62.4 ± 12.9 h for the diagnostic dose (p = 0.003). At these doses accumulation is observed in 46% and 41% of tumor lesions with a median accumulation in positive lesions 96 h post-injection of 4.94 and 4.45%IA kg−1 (p = 0.91), respectively. In conclusion, PET/CT imaging with a diagnostic dose of 89Zr-CPC634 accurately reflects on-treatment tumor accumulation and thus opens the possibility for patient stratification in cancer nanomedicine with polymeric nanoparticles.

Published
2022

16. 89Zr-immuno-PET using the anti-LAG-3 tracer [89Zr]Zr-BI 754111: demonstrating target specific binding in NSCLC and HNSCC.

Author

Miedema, Iris H.C., Huisman, Marc C., Zwezerijnen, Gerben J.C., Grempler, Rolf, Pitarch, Alejandro Perez, Thiele, Andrea, Hesse, Raphael, Elgadi, Mabrouk, Peltzer, Alexander, Vugts, Danielle J., van Dongen, Guus A.M.S., de Gruijl, Tanja D., Menke-van der Houven van Oordt, C. Willemien, and Bahce, Idris

Subjects
POSITRON emission tomography, LYMPHOCYTE transformation, NON-small-cell lung carcinoma, RNA sequencing, ANTINEOPLASTIC agents, PROGRAMMED cell death 1 receptors
Abstract

Purpose: Although lymphocyte activation gene-3 (LAG-3) directed therapies demonstrate promising clinical anti-cancer activity, only a subset of patients seems to benefit and predictive biomarkers are lacking. Here, we explored the potential use of the anti-LAG-3 antibody tracer [89Zr]Zr-BI 754111 as a predictive imaging biomarker and investigated its target specific uptake as well as the correlation of its tumor uptake and the tumor immune infiltration. Methods: Patients with head and neck (N = 2) or lung cancer (N = 4) were included in an imaging substudy of a phase 1 trial with BI 754091 (anti-PD-1) and BI 754111 (anti-LAG-3). After baseline tumor biopsy and [18F]FDG-PET, patients were given 240 mg of BI 754091, followed 8 days later by administration of [89Zr]Zr-BI 754111 (37 MBq, 4 mg). PET scans were performed 2 h, 96 h, and 144 h post-injection. To investigate target specificity, a second tracer administration was given two weeks later, this time with pre-administration of 40 (N = 3) or 600 mg (N = 3) unlabeled BI 754111, followed by PET scans at 96 h and 144 h post-injection. Tumor immune cell infiltration was assessed by immunohistochemistry and RNA sequencing. Results: Tracer uptake in tumors was clearly visible at the 4-mg mass dose (tumor-to-plasma ratio 1.63 [IQR 0.37-2.89]) and could be saturated by increasing mass doses (44 mg: 0.67 [IQR 0.50–0.85]; 604 mg: 0.56 [IQR 0.42–0.75]), demonstrating target specificity. Tumor uptake correlated to immune cell-derived RNA signatures. Conclusions: [89Zr]Zr-BI-754111 PET imaging shows favorable technical and biological characteristics for developing a potential predictive imaging biomarker for LAG-3-directed therapies. Trial registration: ClinicalTrials.gov, NCT03780725. Registered 19 December 2018 [ABSTRACT FROM AUTHOR]

Published
2023
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17. Whole-Body Macrophage Positron Emission Tomography Imaging for Disease Activity Assessment in Early Rheumatoid Arthritis

Author

Verweij, Nicki J.F., primary, de Jongh, Jerney, additional, Wee, Marieke M. ter, additional, Zwezerijnen, Gerben J.C., additional, Yaqub, Maqsood, additional, Voskuyl, Alexandre E., additional, Lammertsma, Adriaan A., additional, van Schaardenburg, Dirkjan, additional, Boers, Maarten, additional, Lems, Willem F., additional, and van der Laken, Conny J., additional

Published
2022
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18. Praluzatamab Ravtansine, a CD166-Targeting Antibody–Drug Conjugate, in Patients with Advanced Solid Tumors: An Open-Label Phase I/II Trial

Author

Boni, Valentina, primary, Fidler, Mary J., additional, Arkenau, Hendrik-Tobias, additional, Spira, Alexander, additional, Meric-Bernstam, Funda, additional, Uboha, Nataliya, additional, Sanborn, Rachel E., additional, Sweis, Randy F., additional, LoRusso, Patricia, additional, Nagasaka, Misako, additional, Garcia-Corbacho, Javier, additional, Jalal, Shadia, additional, Harding, James J., additional, Kim, Stella K., additional, Miedema, Iris H.C., additional, Vugts, Danielle J., additional, Huisman, Marc C., additional, Zwezerijnen, Gerben J.C., additional, van Dongen, Guus A.M.S., additional, Menke van der Houven van Oordt, C. Willemien, additional, Wang, Song, additional, Dang, Tam, additional, Zein, Ivan A., additional, Vasiljeva, Olga, additional, Lyman, Susan K., additional, Paton, Virginia, additional, Hannah, Alison, additional, and Liu, Joyce F., additional

Published
2022
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19. The Impact of Semiautomatic Segmentation Methods on Metabolic Tumor Volume, Intensity, and Dissemination Radiomics in 18F-FDG PET Scans of Patients with Classical Hodgkin Lymphoma

Author

Driessen, Julia, primary, Zwezerijnen, Gerben J.C., additional, Schöder, Heiko, additional, Drees, Esther E.E., additional, Kersten, Marie José, additional, Moskowitz, Alison J., additional, Moskowitz, Craig H., additional, Eertink, Jakoba J., additional, Vet, Henrica C.W. de, additional, Hoekstra, Otto S., additional, Zijlstra, Josée M., additional, and Boellaard, Ronald, additional

Published
2022
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20. Interobserver agreement in automated metabolic tumor volume measurements of Deauville score 4 and 5 lesions at interim 18F-FDG PET in DLBCL

Author

Zwezerijnen, Gerben J.C., Eertink, Jakoba J., Burggraaff, Coreline N., Wiegers, Sanne E., Shaban, Ekhlas A.I.N., Pieplenbosch, Simone, Oprea-Lager, Daniela E., Lugtenburg, Pieternella J., Hoekstra, Otto S., de Vet, Henrica C.W., Zijlstra, Josee M., Boellaard, Ronald, and Hematology

Abstract

Metabolic tumor volume (MTV) on interim-PET (I-PET) is a potential prognostic biomarker for diffuse large B-cell lymphoma (DLBCL). Implementation of MTV on I-PET requires consensus which semi-automated segmentation method delineates lesions most successfully with least user interaction. Methods used for baseline PET are not necessarily optimal for I-PET due to lower lesional standardized uptake values (SUV) at I-PET. Therefore, we aimed to evaluate which method provides the best delineation quality of Deauville-score (DS) 4-5 DLBCL lesions on I-PET at best interobserver agreement on delineation quality and, secondly, to assess the effect of lesional SUVmax on delineation quality and performance agreements. Methods: DS4-5 lesions from 45 I-PET scans were delineated using six semi-automated methods i) SUV 2.5, ii) SUV 4.0, iii) adaptive threshold [A50%peak], iv) 41% of maximum SUV [41%max], v) majority vote including voxels detected by ≥2 methods [MV2] and vi) detected by ≥3 methods [MV3]. Delineation quality per MTV was rated by three independent observers as acceptable or non-acceptable. For each method, observer scores on delineation quality, specific agreements and MTV were assessed for all lesions, and per category of lesional SUVmax (10). Results: In 60 DS4-5 lesions on I-PET, MV3 performed best, with acceptable delineation in 90% of lesions, with a positive agreement (PA) of 93%. Delineation quality scores and agreements per method strongly depended on lesional SUV: the best delineation quality scores were obtained using MV3 in lesions with SUVmax10, were comparable after excluding visually failed MV3 contouring. For lesions with SUVmax

Published
2021

22. Combining PET Radiomic Features with MYC Gene Rearrangement Results in High Prediction of Outcome in Diffuse Large B-Cell Lymphoma

Author

Eertink, Jakoba J, primary, Zwezerijnen, Gerben J.C, additional, Wiegers, Sanne E, additional, Chamuleau, Martine E.D, additional, Lugtenburg, Pieternella, additional, De Jong, Daphne, additional, Ylstra, Bauke, additional, Mendeville, Matias, additional, Dührsen, Ulrich, additional, Hüttmann, Andreas, additional, Schmitz, Christine, additional, Richter, Julia, additional, Klapper, Wolfram, additional, Hoekstra, Otto S, additional, de Vet, Henrica C.W, additional, Boellaard, Ronald, additional, and Zijlstra, Josée M, additional

Published
2021
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23. Interobserver Agreement on Automated Metabolic Tumor Volume Measurements of Deauville Score 4 and 5 Lesions at Interim 18F-FDG PET in Diffuse Large B-Cell Lymphoma

Author

Zwezerijnen, Gerben J.C., primary, Eertink, Jakoba J., additional, Burggraaff, Coreline N., additional, Wiegers, Sanne E., additional, Shaban, Ekhlas A.I.N., additional, Pieplenbosch, Simone, additional, Oprea-Lager, Daniela E., additional, Lugtenburg, Pieternella J., additional, Hoekstra, Otto S., additional, de Vet, Henrica C.W., additional, Zijlstra, Josee M., additional, and Boellaard, Ronald, additional

Published
2021
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25. 18f-FDG PET/CT Baseline Rdiomics Features Improve the Prediction of Treatment Outcome in Diffuse Large B-Cell Lymphoma Patients

Author

Eertink, Jakoba J, primary, van de Brug, Tim, additional, Wiegers, Sanne E, additional, Zwezerijnen, Gerben J.C., additional, Pfaehler, Elisabeth, additional, Lugtenburg, Pieternella J., additional, van der Holt, Bronno, additional, de Vet, Henrica C.W., additional, Hoekstra, Otto S, additional, Boellaard, Ronald, additional, and Zijlstra, Josée M, additional

Published
2020
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26. Prediction of watchful waiting in newly diagnosed metastatic clear cell renal cell carcinoma patients with a good or intermediate prognosis.

Author

Verhoeff, Sarah, primary, van Es, Suzanne C, additional, Elias, Sjoerd G., additional, Gerritse, Sophie, additional, Angus, Lindsay, additional, Oosting, Sjoukje, additional, Heskamp, Sandra, additional, Brouwers, Adrienne H., additional, Arens, Anne I.J., additional, Menke, Catharina Wilhelmina, additional, Hoekstra, Otto S., additional, Zwezerijnen, Gerben J.C., additional, Van Der Veldt, Astrid Aplonia Maria, additional, Mulders, Peter, additional, Van Der Graaf, Winette T.A., additional, De Vries, Elisabeth, additional, Oyen, Wim J.G., additional, Aarntzen, Erik H.J.G., additional, and Van Herpen, Carla M.L.-, additional

Published
2020
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28. First-in-human imaging of nanoparticle entrapped docetaxel (CPC634) in patients with advanced solid tumors using 89Zr-Df-CPC634 PET/CT.

Author

Miedema, Iris H.C., primary, Zwezerijnen, Gerben J.C., additional, Oprea-Lager, Daniela E., additional, Verheul, Henk M.W., additional, Vugts, Danielle J., additional, Huisman, Marc C., additional, Mathijssen, Ron H.J., additional, Rijcken, Cristianne J.F., additional, Hu, Qizhi, additional, Dongen, G.a.M.S. van, additional, and Menke, Catharina Wilhelmina, additional

Published
2019
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29. Optimizing Workflows for Fast and Reliable Metabolic Tumor Volume Measurements in Diffuse Large B Cell Lymphoma.

Author

Burggraaff, Coreline N., Rahman, Fareen, Kaßner, Isabelle, Pieplenbosch, Simone, Barrington, Sally F., Jauw, Yvonne W.S., Zwezerijnen, Gerben J.C., Müller, Stefan, Hoekstra, Otto S., Zijlstra, Josée M., De Vet, Henrica C.W., and Boellaard, Ronald

Subjects
RITUXIMAB, FLUORODEOXYGLUCOSE F18, B cells, VOLUME measurements, NUCLEAR medicine, INTRACLASS correlation, MEMORY bias
Abstract

Purpose: This pilot study aimed to determine interobserver reliability and ease of use of three workflows for measuring metabolic tumor volume (MTV) and total lesion glycolysis (TLG) in diffuse large B cell lymphoma (DLBCL). Procedures: Twelve baseline [18F]FDG PET/CT scans from DLBCL patients with wide variation in number and size of involved organs and lymph nodes were selected from the international PETRA consortium database. Three observers analyzed scans using three workflows. Workflow A: user-defined selection of individual lesions followed by four automated segmentations (41%SUVmax, A50%SUVpeak, SUV≥2.5, SUV≥4.0). For each lesion, observers indicated their "preferred segmentation." Individually selected lesions were summed to yield total MTV and TLG. Workflow B: fully automated preselection of [18F]FDG-avid structures (SUV≥4.0 and volume≥3ml), followed by removing non-tumor regions with single mouse clicks. Workflow C: preselected volumes based on Workflow B modified by manually adding lesions or removing physiological uptake, subsequently checked by experienced nuclear medicine physicians. Workflow C was performed 3 months later to avoid recall bias from the initial Workflow B analysis. Interobserver reliability was expressed as intraclass correlation coefficients (ICC). Results: Highest interobserver reliability in Workflow A was found for SUV≥2.5 and SUV≥4.0 methods (ICCs for MTV 0.96 and 0.94, respectively). SUV≥4.0 and A50%Peak were most and SUV≥2.5 was the least preferred segmentation method. Workflow B had an excellent interobserver reliability (ICC = 1.00) for MTV and TLG. Workflow C reduced the ICC for MTV and TLG to 0.92 and 0.97, respectively. Mean workflow analysis time per scan was 29, 7, and 22 min for A, B, and C, respectively. Conclusions: Improved interobserver reliability and ease of use occurred using fully automated preselection (using SUV≥4.0 and volume≥3ml, Workflow B) compared with individual lesion selection by observers (Workflow A). Subsequent manual modification was necessary for some patients but reduced interobserver reliability which may need to be balanced against potential improvement on prognostic accuracy. [ABSTRACT FROM AUTHOR]

Published
2020
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30. 18F-FDG PET scanning in graft-versus-host disease after allogeneic stem cell transplantation

Author

Zwezerijnen, Gerben J.C., M., Arpinati, M., Celli, V., Ambrosini, F., Bonifazi, G., Bandini, J.J.W.M., Janssen, S., Fanti, O., Visser, Radiology and nuclear medicine, and CCA - Imaging and biomarkers

Subjects
surgical procedures, operative, immune system diseases, chemical and pharmacologic phenomena
Abstract

Background: diagnosis and onset prediction of Graft-versus-host disease (GvHD) after hematopoietic stem cell transplantation (HSCT) as well as therapy monitoring is still an open issue. Aim: to evaluate the role of FDG PET for the assessment of GvHD in patients after HSCT. Methods: we retrospectively studied patients with malignant lymphoma and multiple myeloma who underwent FDG PET between 2004 and 2009. We included patients who underwent HSCT and performed PET scan before transplant and at least three follow up PET scans. Overall 36 patients (8 non-Hodgkin lymphoma, 20 Hodgkin's disease, 8 multiple myeloma) were included. GvHD diagnosis was based on clinical data and, when available, on biopsy results. PET scans were evaluated by two experienced nuclear medicine physicians unaware of clinical data: findings of scans acquired at the time of GvHD clinical manifestation were compared with scans obtained before transplant and with scans during clinical remission, as well as with PET scans carried out in patients without GvHD. Results: overall 25/36 patients developed GvHD (22 acute, 9 chronic) while 11 remained GvHD clinically-free during the time of follow up. In 8/25 patients one or more PET scans were performed during clinical GvHD, and PET was positive in 8/8 cases. Pathological FDG uptake was evident at intestinal and/or liver and/or mouth level. Intestinal GvHD was clinically observed in 6/8 patients. PET corresponding images showed intense uptake in the bowel in comparison to the scans obtained in the same patients in the GvHD clinically-free period. A strong decrease in bowel FDG uptake was observed in patients responding to therapy. In 2 cases in which liver GvHD was pathologically confirmed, PET was positive in one case. Among 6 patients with mouth GvHD, only 1 showed intense FDG uptake as compared to scans obtained in the GvHD clinically-free group. Among the 11 patients who did not develop GvHD clinical manifestation, only one showed a faint intestinal FDG uptake. Overall considering sites of documented GvHD, PET was true positive in all cases presenting intestinal GvHD (6), false negative at liver in 1/2 cases, false negative at mouth in 5/6 cases and false positive in 1 patient not presenting GvHD. Conclusion: our preliminary data show that together with clinical findings, FDG PET could be useful in diagnosing and monitoring GvHD, especially at bowel level.

Published
2010
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31. Baseline radiomics features and MYCrearrangement status predict progression in aggressive B-cell lymphoma

Author

Eertink, Jakoba J., Zwezerijnen, Gerben J.C., Wiegers, Sanne E., Pieplenbosch, Simone, Chamuleau, Martine E.D., Lugtenburg, Pieternella J., de Jong, Daphne, Ylstra, Bauke, Mendeville, Matias, Dührsen, Ulrich, Hanoun, Christine, Hüttmann, Andreas, Richter, Julia, Klapper, Wolfram, Jauw, Yvonne W.S., Hoekstra, Otto S., de Vet, Henrica C.W., Boellaard, Ronald, and Zijlstra, Josée M.

Abstract

We investigated whether the outcome prediction of patients with aggressive B-cell lymphoma can be improved by combining clinical, molecular genotype, and radiomics features. MYC, BCL2, and BCL6rearrangements were assessed using fluorescence in situ hybridization. Seventeen radiomics features were extracted from the baseline positron emission tomography–computed tomography of 323 patients, which included maximum standardized uptake value (SUVmax), SUVpeak, SUVmean, metabolic tumor volume (MTV), total lesion glycolysis, and 12 dissemination features pertaining to distance, differences in uptake and volume between lesions, respectively. Logistic regression with backward feature selection was used to predict progression after 2 years. The predictive value of (1) International Prognostic Index (IPI); (2) IPI plus MYC; (3) IPI, MYC, and MTV; (4) radiomics; and (5) MYCplus radiomics models were tested using the cross-validated area under the curve (CV-AUC) and positive predictive values (PPVs). IPI yielded a CV-AUC of 0.65 ± 0.07 with a PPV of 29.6%. The IPI plus MYCmodel yielded a CV-AUC of 0.68 ± 0.08. IPI, MYC, and MTV yielded a CV-AUC of 0.74 ± 0.08. The highest model performance of the radiomics model was observed for MTV combined with the maximum distance between the largest lesion and another lesion, the maximum difference in SUVpeakbetween 2 lesions, and the sum of distances between all lesions, yielding an improved CV-AUC of 0.77 ± 0.07. The same radiomics features were retained when adding MYC(CV-AUC, 0.77 ± 0.07). PPV was highest for the MYCplus radiomics model (50.0%) and increased by 20% compared with the IPI (29.6%). Adding radiomics features improved model performance and PPV and can, therefore, aid in identifying poor prognosis patients.

Published
2023
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