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Bela Andela S, Amthauer H, Furth C, Rogasch JM, Beck M, Mehrhof F, Ghadjar P, van den Hoff J, Klatte T, Tahbaz R, Zips D, Hofheinz F, Zschaeck S. Quantitative PSMA-PET parameters in localized prostate cancer: prognostic and potential predictive value. Radiat Oncol 2024; 19:97. [PMID: 39080696 PMCID: PMC11288109 DOI: 10.1186/s13014-024-02483-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2024] [Accepted: 06/28/2024] [Indexed: 08/03/2024] Open
Abstract
BACKGROUND PSMA-PET is increasingly used for staging prostate cancer (PCA) patients. However, it is not clear if quantitative imaging parameters of positron emission tomography (PET) have an impact on disease progression and are thus important for the prognosis of localized PCA. METHODS This is a monocenter retrospective analysis of 86 consecutive patients with localized intermediate or high-risk PCA and PSMA-PET before treatment The quantitative PET parameters maximum standardized uptake value (SUVmax), tumor asphericity (ASP), PSMA tumor volume (PSMA-TV), and PSMA total lesion uptake (PSMA-TLU = PSMA-TV × SUVmean) were assessed for their prognostic significance in patients with radiotherapy or surgery. Cox regression analyses were performed for biochemical recurrence-free survival, overall survival (OS), local control, and loco-regional control (LRC). RESULTS 67% of patients had high-risk disease, 51 patients were treated with radiotherapy, and 35 with surgery. Analysis of metric PET parameters in the whole cohort revealed a significant association of PSMA-TV (p = 0.003), PSMA-TLU (p = 0.004), and ASP (p < 0.001) with OS. Upon binarization of PET parameters, several other parameters showed a significant association with clinical outcome. When analyzing high-risk patients according to the primary treatment approach, a previously published cut-off for SUVmax (8.6) showed a significant association with LRC in surgically treated (p = 0.048), but not in primary irradiated (p = 0.34) patients. In addition, PSMA-TLU (p = 0.016) seemed to be a very promising biomarker to stratify surgical patients. CONCLUSION Our data confirm one previous publication on the prognostic impact of SUVmax in surgically treated patients with high-risk PCA. Our exploratory analysis indicates that PSMA-TLU might be even better suited. The missing association with primary irradiated patients needs prospective validation with a larger sample size to conclude a predictive potential. Trial registration Due to the retrospective nature of this research, no registration was carried out.
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Affiliation(s)
- Stephanie Bela Andela
- Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiation Oncology, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany.
| | - Holger Amthauer
- Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Nuclear Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Christian Furth
- Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Nuclear Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Julian M Rogasch
- Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Nuclear Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Marcus Beck
- Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiation Oncology, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Felix Mehrhof
- Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiation Oncology, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Pirus Ghadjar
- Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiation Oncology, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Jörg van den Hoff
- Helmholtz-Zentrum Dresden-Rossendorf, PET Center, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany
| | - Tobias Klatte
- Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Urology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Rana Tahbaz
- Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Urology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Daniel Zips
- Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiation Oncology, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
- Charité - Universitätsmedizin Berlin, Berlin, Germany
- German Cancer Consortium (DKTK), Partner Site Berlin, and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Frank Hofheinz
- Helmholtz-Zentrum Dresden-Rossendorf, PET Center, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany
| | - Sebastian Zschaeck
- Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiation Oncology, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
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2
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Zschaeck S, Klinger B, van den Hoff J, Cegla P, Apostolova I, Kreissl MC, Cholewiński W, Kukuk E, Strobel H, Amthauer H, Blüthgen N, Zips D, Hofheinz F. Combination of tumor asphericity and an extracellular matrix-related prognostic gene signature in non-small cell lung cancer patients. Sci Rep 2023; 13:20840. [PMID: 38012155 PMCID: PMC10681996 DOI: 10.1038/s41598-023-46405-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Accepted: 10/31/2023] [Indexed: 11/29/2023] Open
Abstract
One important aim of precision oncology is a personalized treatment of patients. This can be achieved by various biomarkers, especially imaging parameters and gene expression signatures are commonly used. So far, combination approaches are sparse. The aim of the study was to independently validate the prognostic value of the novel positron emission tomography (PET) parameter tumor asphericity (ASP) in non small cell lung cancer (NSCLC) patients and to investigate associations between published gene expression profiles and ASP. This was a retrospective evaluation of PET imaging and gene expression data from three public databases and two institutional datasets. The whole cohort comprised 253 NSCLC patients, all treated with curative intent surgery. Clinical parameters, standard PET parameters and ASP were evaluated in all patients. Additional gene expression data were available for 120 patients. Univariate Cox regression and Kaplan-Meier analysis was performed for the primary endpoint progression-free survival (PFS) and additional endpoints. Furthermore, multivariate cox regression testing was performed including clinically significant parameters, ASP, and the extracellular matrix-related prognostic gene signature (EPPI). In the whole cohort, a significant association with PFS was observed for ASP (p < 0.001) and EPPI (p = 0.012). Upon multivariate testing, EPPI remained significantly associated with PFS (p = 0.018) in the subgroup of patients with additional gene expression data, while ASP was significantly associated with PFS in the whole cohort (p = 0.012). In stage II patients, ASP was significantly associated with PFS (p = 0.009), and a previously published cutoff value for ASP (19.5%) was successfully validated (p = 0.008). In patients with additional gene expression data, EPPI showed a significant association with PFS, too (p = 0.033). The exploratory combination of ASP and EPPI showed that the combinatory approach has potential to further improve patient stratification compared to the use of only one parameter. We report the first successful validation of EPPI and ASP in stage II NSCLC patients. The combination of both parameters seems to be a very promising approach for improvement of risk stratification in a group of patients with urgent need for a more personalized treatment approach.
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Affiliation(s)
- Sebastian Zschaeck
- Department of Radiation Oncology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
- Berlin Institute of Health (BIH), 10178, Berlin, Germany
| | - Bertram Klinger
- Berlin Institute of Health (BIH), 10178, Berlin, Germany
- Computational Modelling in Medicine, Instiute of Pathology, Charité Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany
- German Cancer Consortium (DKTK), Partner Site Berlin, Berlin, Germany
| | - Jörg van den Hoff
- Helmholtz-Zentrum Dresden-Rossendorf, PET Center, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany
| | - Paulina Cegla
- Department of Nuclear Medicine, Greater Poland Cancer Centre, Poznan, Poland
| | - Ivayla Apostolova
- Department for Diagnostic and Interventional Radiology and Nuclear Medicine, University Hospital Hamburg-Eppendorf, Hamburg, Germany
- Division of Nuclear Medicine, Department of Radiology and Nuclear Medicine, Otto Von Guericke University, Magdeburg, Germany
| | - Michael C Kreissl
- Division of Nuclear Medicine, Department of Radiology and Nuclear Medicine, Otto Von Guericke University, Magdeburg, Germany
| | - Witold Cholewiński
- Department of Nuclear Medicine, Greater Poland Cancer Centre, Poznan, Poland
| | - Emily Kukuk
- Department of Radiation Oncology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Helen Strobel
- Department of Radiation Oncology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Holger Amthauer
- Division of Nuclear Medicine, Department of Radiology and Nuclear Medicine, Otto Von Guericke University, Magdeburg, Germany
- Department of Nuclear Medicine, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Nils Blüthgen
- Berlin Institute of Health (BIH), 10178, Berlin, Germany
- Computational Modelling in Medicine, Instiute of Pathology, Charité Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany
- German Cancer Consortium (DKTK), Partner Site Berlin, Berlin, Germany
| | - Daniel Zips
- Department of Radiation Oncology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
- German Cancer Consortium (DKTK), Partner Site Berlin, Berlin, Germany
| | - Frank Hofheinz
- Helmholtz-Zentrum Dresden-Rossendorf, PET Center, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany.
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Lucchi E, Cercenelli L, Maiolo V, Bortolani B, Marcelli E, Tarsitano A. Pretreatment Tumor Volume and Tumor Sphericity as Prognostic Factors in Patients with Oral Cavity Squamous Cell Carcinoma: A Prospective Clinical Study in 95 Patients. J Pers Med 2023; 13:1601. [PMID: 38003916 PMCID: PMC10672547 DOI: 10.3390/jpm13111601] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Revised: 11/10/2023] [Accepted: 11/11/2023] [Indexed: 11/26/2023] Open
Abstract
The prognostic impact of tumor volume and tumor sphericity was analyzed in 95 patients affected by oral cancer. The pre-operative computed tomography (CT) scans were used to segment the tumor mass with threshold tools, obtaining the corresponding volume and sphericity. Events of recurrence and tumor-related death were detected for each patient. The mean follow-up time was 31 months. A p-value of 0.05 was adopted. Mean tumor volume resulted higher in patients with recurrence or tumor-related death at the Student's t-test (respectively, 19.8 cm3 vs. 11.1 cm3, p = 0.03; 23.3 cm3 vs. 11.7 cm3, p = 0.02). Mean tumor sphericity was higher in disease-free patients (0.65 vs. 0.59, p = 0.04). Recurrence-free survival and disease-specific survival were greater for patients with a tumor volume inferior to the cut-off values of 21.1 cm3 (72 vs. 21 months, p < 0.01) and 22.4 cm3 (85 vs. 32 months, p < 0.01). Recurrence-free survival and disease-specific survival were higher for patients with a tumor sphericity superior to the cut-off value of 0.57 (respectively, 49 vs. 33 months, p < 0.01; 56 vs. 51 months, p = 0.01). To conclude, tumor volume and sphericity, three-dimensional parameters, could add useful information for better stratification of prognosis in oral cancer.
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Affiliation(s)
- Elisabetta Lucchi
- Oral and Maxillofacial Surgery Unit, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Via Albertoni 15, 40138 Bologna, Italy;
| | - Laura Cercenelli
- Laboratory of Bioengineering—eDIMES Lab, Department of Medical and Surgical Sciences (DIMEC), University of Bologna, 40138 Bologna, Italy; (L.C.); (B.B.); (E.M.)
| | - Vincenzo Maiolo
- Radiology Unit, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Via Albertoni 15, 40138 Bologna, Italy;
| | - Barbara Bortolani
- Laboratory of Bioengineering—eDIMES Lab, Department of Medical and Surgical Sciences (DIMEC), University of Bologna, 40138 Bologna, Italy; (L.C.); (B.B.); (E.M.)
| | - Emanuela Marcelli
- Laboratory of Bioengineering—eDIMES Lab, Department of Medical and Surgical Sciences (DIMEC), University of Bologna, 40138 Bologna, Italy; (L.C.); (B.B.); (E.M.)
| | - Achille Tarsitano
- Oral and Maxillofacial Surgery Unit, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Via Albertoni 15, 40138 Bologna, Italy;
- Department of Biomedical and Neuromotor Sciences (DIBINEM), University of Bologna, 40138 Bologna, Italy
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Huynh BN, Groendahl AR, Tomic O, Liland KH, Knudtsen IS, Hoebers F, van Elmpt W, Malinen E, Dale E, Futsaether CM. Head and neck cancer treatment outcome prediction: a comparison between machine learning with conventional radiomics features and deep learning radiomics. Front Med (Lausanne) 2023; 10:1217037. [PMID: 37711738 PMCID: PMC10498924 DOI: 10.3389/fmed.2023.1217037] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Accepted: 07/07/2023] [Indexed: 09/16/2023] Open
Abstract
Background Radiomics can provide in-depth characterization of cancers for treatment outcome prediction. Conventional radiomics rely on extraction of image features within a pre-defined image region of interest (ROI) which are typically fed to a classification algorithm for prediction of a clinical endpoint. Deep learning radiomics allows for a simpler workflow where images can be used directly as input to a convolutional neural network (CNN) with or without a pre-defined ROI. Purpose The purpose of this study was to evaluate (i) conventional radiomics and (ii) deep learning radiomics for predicting overall survival (OS) and disease-free survival (DFS) for patients with head and neck squamous cell carcinoma (HNSCC) using pre-treatment 18F-fluorodeoxuglucose positron emission tomography (FDG PET) and computed tomography (CT) images. Materials and methods FDG PET/CT images and clinical data of patients with HNSCC treated with radio(chemo)therapy at Oslo University Hospital (OUS; n = 139) and Maastricht University Medical Center (MAASTRO; n = 99) were collected retrospectively. OUS data was used for model training and initial evaluation. MAASTRO data was used for external testing to assess cross-institutional generalizability. Models trained on clinical and/or conventional radiomics features, with or without feature selection, were compared to CNNs trained on PET/CT images without or with the gross tumor volume (GTV) included. Model performance was measured using accuracy, area under the receiver operating characteristic curve (AUC), Matthew's correlation coefficient (MCC), and the F1 score calculated for both classes separately. Results CNNs trained directly on images achieved the highest performance on external data for both endpoints. Adding both clinical and radiomics features to these image-based models increased performance further. Conventional radiomics including clinical data could achieve competitive performance. However, feature selection on clinical and radiomics data lead to overfitting and poor cross-institutional generalizability. CNNs without tumor and node contours achieved close to on-par performance with CNNs including contours. Conclusion High performance and cross-institutional generalizability can be achieved by combining clinical data, radiomics features and medical images together with deep learning models. However, deep learning models trained on images without contours can achieve competitive performance and could see potential use as an initial screening tool for high-risk patients.
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Affiliation(s)
- Bao Ngoc Huynh
- Faculty of Science and Technology, Norwegian University of Life Sciences, Ås, Norway
| | | | - Oliver Tomic
- Faculty of Science and Technology, Norwegian University of Life Sciences, Ås, Norway
| | - Kristian Hovde Liland
- Faculty of Science and Technology, Norwegian University of Life Sciences, Ås, Norway
| | - Ingerid Skjei Knudtsen
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Medical Physics, Oslo University Hospital, Oslo, Norway
| | - Frank Hoebers
- Department of Radiation Oncology (MAASTRO), Maastricht University Medical Center, Maastricht, Netherlands
- GROW School for Oncology and Reproduction, Maastricht University Medical Center, Maastricht, Netherlands
| | - Wouter van Elmpt
- Department of Radiation Oncology (MAASTRO), Maastricht University Medical Center, Maastricht, Netherlands
- GROW School for Oncology and Reproduction, Maastricht University Medical Center, Maastricht, Netherlands
| | - Eirik Malinen
- Department of Medical Physics, Oslo University Hospital, Oslo, Norway
- Department of Physics, University of Oslo, Oslo, Norway
| | - Einar Dale
- Department of Oncology, Oslo University Hospital, Oslo, Norway
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Cegla P, Hofheinz F, Burchardt E, Czepczyński R, Kubiak A, van den Hoff J, Nikulin P, Bos-Liedke A, Roszak A, Cholewinski W. Asphericity derived from [ 18F]FDG PET as a new prognostic parameter in cervical cancer patients. Sci Rep 2023; 13:8423. [PMID: 37225735 DOI: 10.1038/s41598-023-35191-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Accepted: 05/14/2023] [Indexed: 05/26/2023] Open
Abstract
The objective of this study was to assess the prognostic value of asphericity (ASP) and standardized uptake ratio (SUR) in cervical cancer patients. Retrospective analysis was performed on a group of 508 (aged 55 ± 12 years) previously untreated cervical cancer patients. All patients underwent a pretreatment [18F]FDG PET/CT study to assess the severity of the disease. The metabolic tumor volume (MTV) of the cervical cancer was delineated with an adaptive threshold method. For the resulting ROIs the maximum standardized uptake value (SUVmax) was measured. In addition, ASP and SUR were determined as previously described. Univariate Cox regression and Kaplan-Meier analysis with respect to event free survival (EFS), overall survival (OS), freedom from distant metastasis (FFDM) and locoregional control (LRC) was performed. Additionally, a multivariate Cox regression including clinically relevant parameters was performed. In the survival analysis, MTV and ASP were shown to be prognostic factors for all investigated endpoints. Tumor metabolism quantified with the SUVmax was not prognostic for any of the endpoints (p > 0.2). The SUR did not reach statistical significance either (p = 0.1, 0.25, 0.066, 0.053, respectively). In the multivariate analysis, the ASP remained a significant factor for EFS and LRC, while MTV was a significant factor for FFDM, indicating their independent prognostic value for the respective endpoints. The alternative parameter ASP has the potential to improve the prognostic value of [18F]FDG PET/CT for event-free survival and locoregional control in radically treated cervical cancer patients.
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Affiliation(s)
- Paulina Cegla
- Department of Nuclear Medicine, Greater Poland Cancer Centre, Garbary 15, 61-866, Poznan, Poland.
| | - Frank Hofheinz
- Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany
| | - Ewa Burchardt
- Department of Electroradiology, Poznan Univeristy of Medical Science, Poznan, Poland
- Department of Radiotherapy and Gynaecological Oncology, Greater Poland Cancer Centre, Poznan, Poland
| | - Rafał Czepczyński
- Department of Endocrinology, Metabolism and Internal Disease, Poznan University of Medical Science, Poznan, Poland
- Department of Nuclear Medicine, Affidea Poznan, Poland
| | - Anna Kubiak
- Greater Poland Cancer Registry, Greater Poland Cancer Centre, Poznan, Poland
| | - Jörg van den Hoff
- Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany
| | - Pavel Nikulin
- Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany
| | | | - Andrzej Roszak
- Department of Electroradiology, Poznan Univeristy of Medical Science, Poznan, Poland
- Department of Radiotherapy and Gynaecological Oncology, Greater Poland Cancer Centre, Poznan, Poland
| | - Witold Cholewinski
- Department of Nuclear Medicine, Greater Poland Cancer Centre, Garbary 15, 61-866, Poznan, Poland
- Department of Electroradiology, Poznan Univeristy of Medical Science, Poznan, Poland
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Noortman WA, Aide N, Vriens D, Arkes LS, Slump CH, Boellaard R, Goeman JJ, Deroose CM, Machiels JP, Licitra LF, Lhommel R, Alessi A, Woff E, Goffin K, Le Tourneau C, Gal J, Temam S, Delord JP, van Velden FHP, de Geus-Oei LF. Development and External Validation of a PET Radiomic Model for Prognostication of Head and Neck Cancer. Cancers (Basel) 2023; 15:2681. [PMID: 37345017 DOI: 10.3390/cancers15102681] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 04/30/2023] [Accepted: 05/03/2023] [Indexed: 06/23/2023] Open
Abstract
AIM To build and externally validate an [18F]FDG PET radiomic model to predict overall survival in patients with head and neck squamous cell carcinoma (HNSCC). METHODS Two multicentre datasets of patients with operable HNSCC treated with preoperative afatinib who underwent a baseline and evaluation [18F]FDG PET/CT scan were included (EORTC: n = 20, Unicancer: n = 34). Tumours were delineated, and radiomic features were extracted. Each cohort served once as a training and once as an external validation set for the prediction of overall survival. Supervised feature selection was performed using variable hunting with variable importance, selecting the top two features. A Cox proportional hazards regression model using selected radiomic features and clinical characteristics was fitted on the training dataset and validated in the external validation set. Model performances are expressed by the concordance index (C-index). RESULTS In both models, the radiomic model surpassed the clinical model with validation C-indices of 0.69 and 0.79 vs. 0.60 and 0.67, respectively. The model that combined the radiomic features and clinical variables performed best, with validation C-indices of 0.71 and 0.82. CONCLUSION Although assessed in two small but independent cohorts, an [18F]FDG-PET radiomic signature based on the evaluation scan seems promising for the prediction of overall survival for HNSSC treated with preoperative afatinib. The robustness and clinical applicability of this radiomic signature should be assessed in a larger cohort.
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Affiliation(s)
- Wyanne A Noortman
- Section of Nuclear Medicine, Department of Radiology, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands
- TechMed Centre, University of Twente, 7522 NB Enschede, The Netherlands
| | - Nicolas Aide
- Nuclear Medicine Department, Centre Hospitalier Universitaire de Caen, 14000 Caen, France
| | - Dennis Vriens
- Section of Nuclear Medicine, Department of Radiology, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands
| | - Lisa S Arkes
- Section of Nuclear Medicine, Department of Radiology, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands
- Technical Medicine, Delft University of Technology, 2628 CD Delft, The Netherlands
| | - Cornelis H Slump
- TechMed Centre, University of Twente, 7522 NB Enschede, The Netherlands
| | - Ronald Boellaard
- Amsterdam University Medical Center, 1081 HV Amsterdam, The Netherlands
| | - Jelle J Goeman
- Department of Biomedical Data Sciences, Leiden University Medical Center, 2300 RC Leiden, The Netherlands
| | - Christophe M Deroose
- Nuclear Medicine and Molecular Imaging, Department of Imaging & Pathology, University Hospitals Leuven, KU Leuven, 3000 Leuven, Belgium
| | - Jean-Pascal Machiels
- Department of Medical Oncology, Institut Roi Albert II, Cliniques Universitaires Saint-Luc, 1200 Brussels, Belgium
- Institute for Experimental and Clinical Research (IREC, pôle MIRO), Université Catholique de Louvain (UCLouvain), 1200 Brussels, Belgium
| | - Lisa F Licitra
- Department of Head and Neck Medical Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, University of Milan, 20133 Milan, Italy
| | - Renaud Lhommel
- Division of Nuclear Medicine, Institut de Recherche Clinique, Cliniques Universitaires Saint Luc, 1200 Brussels, Belgium
| | - Alessandra Alessi
- Department of Nuclear Medicine-PET Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy
| | - Erwin Woff
- Nuclear Medicine Department, Institut Jules Bordet, Université Libre de Bruxelles (ULB), Hôpital Universitaire de Bruxelles (H.U.B.), 1070 Bruxelles, Belgium
| | - Karolien Goffin
- Nuclear Medicine and Molecular Imaging, Department of Imaging & Pathology, University Hospitals Leuven, KU Leuven, 3000 Leuven, Belgium
| | - Christophe Le Tourneau
- Department of Drug Development and Innovation, Institut Curie, Paris-Saclay University, 75005 Paris, France
| | - Jocelyn Gal
- Epidemiology and Biostatistics Department, Centre Antoine Lacassagne, University Côte d'Azur, 06100 Nice, France
| | - Stéphane Temam
- Department of Head and Neck Surgery Gustave Roussy, 94805 Villejuif, France
| | | | - Floris H P van Velden
- Section of Nuclear Medicine, Department of Radiology, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands
| | - Lioe-Fee de Geus-Oei
- Section of Nuclear Medicine, Department of Radiology, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands
- TechMed Centre, University of Twente, 7522 NB Enschede, The Netherlands
- Department of Radiation Science & Technology, Delft University of Technology, 2628 CD Delft, The Netherlands
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Reccia I, Pai M, Kumar J, Spalding D, Frilling A. Tumour Heterogeneity and the Consequent Practical Challenges in the Management of Gastroenteropancreatic Neuroendocrine Neoplasms. Cancers (Basel) 2023; 15:1861. [PMID: 36980746 PMCID: PMC10047148 DOI: 10.3390/cancers15061861] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 03/10/2023] [Accepted: 03/18/2023] [Indexed: 03/22/2023] Open
Abstract
Tumour heterogeneity is a common phenomenon in neuroendocrine neoplasms (NENs) and a significant cause of treatment failure and disease progression. Genetic and epigenetic instability, along with proliferation of cancer stem cells and alterations in the tumour microenvironment, manifest as intra-tumoural variability in tumour biology in primary tumours and metastases. This may change over time, especially under selective pressure during treatment. The gastroenteropancreatic (GEP) tract is the most common site for NENs, and their diagnosis and treatment depends on the specific characteristics of the disease, in particular proliferation activity, expression of somatostatin receptors and grading. Somatostatin receptor expression has a major role in the diagnosis and treatment of GEP-NENs, while Ki-67 is also a valuable prognostic marker. Intra- and inter-tumour heterogeneity in GEP-NENS, however, may lead to inaccurate assessment of the disease and affect the reliability of the available diagnostic, prognostic and predictive tests. In this review, we summarise the current available evidence of the impact of tumour heterogeneity on tumour diagnosis and treatment of GEP-NENs. Understanding and accurately measuring tumour heterogeneity could better inform clinical decision making in NENs.
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Affiliation(s)
- Isabella Reccia
- General Surgical and Oncology Unit, Policlinico San Pietro, Via Carlo Forlanini, 24036 Ponte San Pietro, Italy
| | - Madhava Pai
- Division of Surgery, Department of Surgery & Cancer, Imperial College London, Hammersmith Hospital, Du Cane Road, London W12 0HS, UK
| | - Jayant Kumar
- Division of Surgery, Department of Surgery & Cancer, Imperial College London, Hammersmith Hospital, Du Cane Road, London W12 0HS, UK
| | - Duncan Spalding
- Division of Surgery, Department of Surgery & Cancer, Imperial College London, Hammersmith Hospital, Du Cane Road, London W12 0HS, UK
| | - Andrea Frilling
- Division of Surgery, Department of Surgery & Cancer, Imperial College London, Hammersmith Hospital, Du Cane Road, London W12 0HS, UK
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Quantitative Diffusion-Weighted Imaging Analyses to Predict Response to Neoadjuvant Immunotherapy in Patients with Locally Advanced Head and Neck Carcinoma. Cancers (Basel) 2022; 14:cancers14246235. [PMID: 36551718 PMCID: PMC9776484 DOI: 10.3390/cancers14246235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 12/09/2022] [Accepted: 12/13/2022] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Neoadjuvant immune checkpoint blockade (ICB) prior to surgery may induce early pathological responses in head and neck squamous cell carcinoma (HNSCC) patients. Routine imaging parameters fail to diagnose these responses early on. Magnetic resonance (MR) diffusion-weighted imaging (DWI) has proven to be useful for detecting HNSCC tumor mass after (chemo)radiation therapy. METHODS 32 patients with stage II-IV, resectable HNSCC, treated at a phase Ib/IIa IMCISION trial (NCT03003637), were retrospectively analyzed using MR-imaging before and after two doses of single agent nivolumab (anti-PD-1) (n = 6) or nivolumab with ipilimumab (anti-CTLA-4) ICB (n = 26). The primary tumors were delineated pre- and post-treatment. A total of 32 features were derived from the delineation and correlated with the tumor regression percentage in the surgical specimen. RESULTS MR-DWI data was available for 24 of 32 patients. Smaller baseline tumor diameter (p = 0.01-0.04) and higher sphericity (p = 0.03) were predictive of having a good pathological response to ICB. Post-treatment skewness and the change in skewness between MRIs were negatively correlated with the tumor's regression (p = 0.04, p = 0.02). CONCLUSION Pre-treatment DWI tumor diameter and sphericity may be quantitative biomarkers for the prediction of an early pathological response to ICB. Furthermore, our data indicate that ADC skewness could be a marker for individual response evaluation.
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Dmytriw AA, Ortega C, Anconina R, Metser U, Liu ZA, Liu Z, Li X, Sananmuang T, Yu E, Joshi S, Waldron J, Huang SH, Bratman S, Hope A, Veit-Haibach P. Nasopharyngeal Carcinoma Radiomic Evaluation with Serial PET/CT: Exploring Features Predictive of Survival in Patients with Long-Term Follow-Up. Cancers (Basel) 2022; 14:3105. [PMID: 35804877 PMCID: PMC9264840 DOI: 10.3390/cancers14133105] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 06/09/2022] [Accepted: 06/21/2022] [Indexed: 02/04/2023] Open
Abstract
PURPOSE We aim determine the value of PET and CT radiomic parameters on survival with serial follow-up PET/CT in patients with nasopharyngeal carcinoma (NPC) for which curative intent therapy is undertaken. METHODS Patients with NPC and available pre-treatment as well as follow up PET/CT were included from 2005 to 2006 and were followed to 2021. Baseline demographic, radiological and outcome data were collected. Univariable Cox proportional hazard models were used to evaluate features from baseline and follow-up time points, and landmark analyses were performed for each time point. RESULTS Sixty patients were enrolled, and two-hundred and seventy-eight (278) PET/CT were at baseline and during follow-up. Thirty-eight percent (38%) were female, and sixty-two patients were male. All patients underwent curative radiation or chemoradiation therapy. The median follow-up was 11.72 years (1.26-14.86). Five-year and ten-year overall survivals (OSs) were 80.0% and 66.2%, and progression-free survival (PFS) was 90.0% and 74.4%. Time-dependent modelling suggested that, among others, PET gray-level zone length matrix (GLZLM) gray-level non-uniformity (GLNU) (HR 2.74 95% CI 1.06, 7.05) was significantly associated with OS. Landmark analyses suggested that CT parameters were most predictive at 15 month, whereas PET parameters were most predictive at time points 3, 6, 9 and 15 month. CONCLUSIONS This study with long-term follow up data on NPC suggests that mainly PET-derived radiomic features are predictive for OS but not PFS in a time-dependent evaluation. Furthermore, CT radiomic measures may predict OS and PFS best at initial and long-term follow-up time points and PET measures may be more predictive in the interval. These modalities are commonly used in NPC surveillance, and prospective validation should be considered.
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Affiliation(s)
- Adam A. Dmytriw
- Department of Medical Imaging, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada; (A.A.D.); (R.A.)
- Joint Department of Medical Imaging, Toronto General Hospital, University Health Network, University of Toronto, Toronto, ON M5G 2C4, Canada; (C.O.); (U.M.); (T.S.); (E.Y.); (S.J.)
| | - Claudia Ortega
- Joint Department of Medical Imaging, Toronto General Hospital, University Health Network, University of Toronto, Toronto, ON M5G 2C4, Canada; (C.O.); (U.M.); (T.S.); (E.Y.); (S.J.)
| | - Reut Anconina
- Department of Medical Imaging, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada; (A.A.D.); (R.A.)
| | - Ur Metser
- Joint Department of Medical Imaging, Toronto General Hospital, University Health Network, University of Toronto, Toronto, ON M5G 2C4, Canada; (C.O.); (U.M.); (T.S.); (E.Y.); (S.J.)
| | - Zhihui A. Liu
- Department of Biostatistics, Princess Margaret Cancer Centre, University Health Network, University of Toronto, Toronto, ON M5G 2C1, Canada; (Z.A.L.); (Z.L.); (X.L.)
| | - Zijin Liu
- Department of Biostatistics, Princess Margaret Cancer Centre, University Health Network, University of Toronto, Toronto, ON M5G 2C1, Canada; (Z.A.L.); (Z.L.); (X.L.)
| | - Xuan Li
- Department of Biostatistics, Princess Margaret Cancer Centre, University Health Network, University of Toronto, Toronto, ON M5G 2C1, Canada; (Z.A.L.); (Z.L.); (X.L.)
| | - Thiparom Sananmuang
- Joint Department of Medical Imaging, Toronto General Hospital, University Health Network, University of Toronto, Toronto, ON M5G 2C4, Canada; (C.O.); (U.M.); (T.S.); (E.Y.); (S.J.)
- Department of Diagnostic and Therapeutic Radiology, Faculty of Medicine Ramathibodi Hospital, Mahidol University,270 Rama VI Road, Ratchathewi, Bangkok 10400, Thailand
| | - Eugene Yu
- Joint Department of Medical Imaging, Toronto General Hospital, University Health Network, University of Toronto, Toronto, ON M5G 2C4, Canada; (C.O.); (U.M.); (T.S.); (E.Y.); (S.J.)
| | - Sayali Joshi
- Joint Department of Medical Imaging, Toronto General Hospital, University Health Network, University of Toronto, Toronto, ON M5G 2C4, Canada; (C.O.); (U.M.); (T.S.); (E.Y.); (S.J.)
| | - John Waldron
- Department of Radiation Oncology, Princess Margaret Cancer Centre, University Health Network, University of Toronto, Toronto, ON M5G 2C1, Canada; (J.W.); (S.H.H.); (S.B.); (A.H.)
| | - Shao Hui Huang
- Department of Radiation Oncology, Princess Margaret Cancer Centre, University Health Network, University of Toronto, Toronto, ON M5G 2C1, Canada; (J.W.); (S.H.H.); (S.B.); (A.H.)
| | - Scott Bratman
- Department of Radiation Oncology, Princess Margaret Cancer Centre, University Health Network, University of Toronto, Toronto, ON M5G 2C1, Canada; (J.W.); (S.H.H.); (S.B.); (A.H.)
| | - Andrew Hope
- Department of Radiation Oncology, Princess Margaret Cancer Centre, University Health Network, University of Toronto, Toronto, ON M5G 2C1, Canada; (J.W.); (S.H.H.); (S.B.); (A.H.)
| | - Patrick Veit-Haibach
- Joint Department of Medical Imaging, Toronto General Hospital, University Health Network, University of Toronto, Toronto, ON M5G 2C4, Canada; (C.O.); (U.M.); (T.S.); (E.Y.); (S.J.)
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Zschaeck S, Andela SB, Amthauer H, Furth C, Rogasch JM, Beck M, Hofheinz F, Huang K. Correlation Between Quantitative PSMA PET Parameters and Clinical Risk Factors in Non-Metastatic Primary Prostate Cancer Patients. Front Oncol 2022; 12:879089. [PMID: 35530334 PMCID: PMC9074726 DOI: 10.3389/fonc.2022.879089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Accepted: 03/28/2022] [Indexed: 11/13/2022] Open
Abstract
Background PSMA PET is frequently used for staging of prostate cancer patients. Furthermore, there is increasing interest to use PET information for personalized local treatment approaches in surgery and radiotherapy, especially for focal treatment strategies. However, it is not well established which quantitative imaging parameters show highest correlation with clinical and histological tumor aggressiveness. Methods This is a retrospective analysis of 135 consecutive patients with non-metastatic prostate cancer and PSMA PET before any treatment. Clinical risk parameters (PSA values, Gleason score and D'Amico risk group) were correlated with quantitative PET parameters maximum standardized uptake value (SUVmax), mean SUV (SUVmean), tumor asphericity (ASP) and PSMA tumor volume (PSMA-TV). Results Most of the investigated imaging parameters were highly correlated with each other (correlation coefficients between 0.20 and 0.95). A low to moderate, however significant, correlation of imaging parameters with PSA values (0.19 to 0.45) and with Gleason scores (0.17 to 0.31) was observed for all parameters except ASP which did not show a significant correlation with Gleason score. Receiver operating characteristics for the detection of D'Amico high-risk patients showed poor to fair sensitivity and specificity for all investigated quantitative PSMA PET parameters (Areas under the curve (AUC) between 0.63 and 0.73). Comparison of AUC between quantitative PET parameters by DeLong test showed significant superiority of SUVmax compared to SUVmean for the detection of high-risk patients. None of the investigated imaging parameters significantly outperformed SUVmax. Conclusion Our data confirm prior publications with lower number of patients that reported moderate correlations of PSMA PET parameters with clinical risk factors. With the important limitation that Gleason scores were only biopsy-derived in this study, there is no indication that the investigated additional parameters deliver superior information compared to SUVmax.
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Affiliation(s)
- Sebastian Zschaeck
- Department of Radiation Oncology, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- BIH Charité Clinician Scientist Program, Berlin Institute of Health at Charité – Universitätsmedizin Berlin, BIH Biomedical Innovation Academy, Berlin, Germany
| | - Stephanie Bela Andela
- Department of Radiation Oncology, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Holger Amthauer
- Department of Nuclear Medicine, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Christian Furth
- Department of Nuclear Medicine, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Julian M. Rogasch
- BIH Charité Clinician Scientist Program, Berlin Institute of Health at Charité – Universitätsmedizin Berlin, BIH Biomedical Innovation Academy, Berlin, Germany
- Department of Nuclear Medicine, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Marcus Beck
- Department of Radiation Oncology, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Frank Hofheinz
- PET Center, Institute of Radiopharmaceutical Cancer Research, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany
| | - Kai Huang
- Department of Nuclear Medicine, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
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11
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Fujima N, Shimizu Y, Yoshida D, Kano S, Mizumachi T, Homma A, Yasuda K, Onimaru R, Sakai O, Kudo K, Shirato H. Multiparametric Analysis of Tumor Morphological and Functional MR Parameters Potentially Predicts Local Failure in Pharynx Squamous Cell Carcinoma Patients. THE JOURNAL OF MEDICAL INVESTIGATION 2021; 68:354-361. [PMID: 34759158 DOI: 10.2152/jmi.68.354] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Purpose : To predict local control / failure by a multiparametric approach using magnetic resonance (MR)-derived tumor morphological and functional parameters in pharynx squamous cell carcinoma (SCC) patients. Materials and Methods : Twenty-eight patients with oropharyngeal and hypopharyngeal SCCs were included in this study. Quantitative morphological parameters and intratumoral characteristics on T2-weighted images, tumor blood flow from pseudo-continuous arterial spin labeling, and tumor diffusion parameters of three diffusion models from multi-b-value diffusion-weighted imaging as well as patients' characteristics were analyzed. The patients were divided into local control / failure groups. Univariate and multiparametric analysis were performed for the patient group division. Results : The value of morphological parameter of 'sphericity' and intratumoral characteristic of 'homogeneity' was revealed respectively significant for the prediction of the local control status in univariate analysis. Higher diagnostic performance was obtained with the sensitivity of 0.8, specificity of 0.75, positive predictive value of 0.89, negative predictive value of 0.6 and accuracy of 0.79 by multiparametric diagnostic model compared to results in the univariate analysis. Conclusion : A multiparametric analysis with MR-derived quantitative parameters may be useful to predict local control in pharynx SCC patients. J. Med. Invest. 68 : 354-361, August, 2021.
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Affiliation(s)
- Noriyuki Fujima
- Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan.,The Global Station for Quantum Medical Science and Engineering, Global Institution for collaborative research and education, Sapporo, Japan
| | - Yukie Shimizu
- Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan
| | - Daisuke Yoshida
- Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan
| | - Satoshi Kano
- Department of Otolaryngology-Head and Neck Surgery, Hokkaido University Graduate School of Medicine, Sapporo, Japan
| | - Takatsugu Mizumachi
- Department of Otolaryngology-Head and Neck Surgery, Hokkaido University Graduate School of Medicine, Sapporo, Japan
| | - Akihiro Homma
- Department of Otolaryngology-Head and Neck Surgery, Hokkaido University Graduate School of Medicine, Sapporo, Japan
| | - Koichi Yasuda
- The Global Station for Quantum Medical Science and Engineering, Global Institution for collaborative research and education, Sapporo, Japan.,Department of Radiation Medicine, Hokkaido University Graduate School of Medicine, Sapporo, Japan
| | - Rikiya Onimaru
- Department of Radiation Medicine, Hokkaido University Graduate School of Medicine, Sapporo, Japan
| | - Osamu Sakai
- Departments of Radiology, Otolaryngology-Head and Neck Surgery, and Radiation Oncology, Boston Medical Center, Boston University School of Medicine, Boston, MA, USA
| | - Kohsuke Kudo
- Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan.,The Global Station for Quantum Medical Science and Engineering, Global Institution for collaborative research and education, Sapporo, Japan
| | - Hiroki Shirato
- The Global Station for Quantum Medical Science and Engineering, Global Institution for collaborative research and education, Sapporo, Japan.,Department of Radiation Medicine, Hokkaido University Graduate School of Medicine, Sapporo, Japan
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12
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Gültekin E, Wetz C, Braun J, Geisel D, Furth C, Hamm B, Sack I, Marticorena Garcia SR. Added Value of Tomoelastography for Characterization of Pancreatic Neuroendocrine Tumor Aggressiveness Based on Stiffness. Cancers (Basel) 2021; 13:cancers13205185. [PMID: 34680334 PMCID: PMC8533708 DOI: 10.3390/cancers13205185] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 10/03/2021] [Accepted: 10/13/2021] [Indexed: 12/12/2022] Open
Abstract
Simple Summary The prediction of pancreatic neuroendocrine tumor (PNET) aggressiveness is important for treatment planning. The aim of this study was to evaluate the diagnostic performance of magnetic resonance elastography (MRE) with tomoelastography postprocessing (tomoelastography) in differentiating PNET from healthy pancreatic tissue and to correlate PNET stiffness with aggressiveness using asphericity derived from positron emission tomography (PET) as reference. In this prospective study we showed in a group of 13 patients with PNET that tomoelastography detected PNET by increased stiffness (p < 0.01) with a high diagnostic performance (AUC = 0.96). PNET was positively correlated with PET derived asphericity (r = 0.81). Tomoelastography provides quantitative imaging markers for the detection of PNET and the prediction of greater tumor aggressiveness by increased stiffness. Abstract Purpose: To evaluate the diagnostic performance of tomoelastography in differentiating pancreatic neuroendocrine tumors (PNETs) from healthy pancreatic tissue and to assess the prediction of tumor aggressiveness by correlating PNET stiffness with PET derived asphericity. Methods: 13 patients with PNET were prospectively compared to 13 age-/sex-matched heathy volunteers (CTR). Multifrequency MR elastography was combined with tomoelastography-postprocessing to provide high-resolution maps of shear wave speed (SWS in m/s). SWS of pancreatic neuroendocrine tumor (PNET-T) were compared with nontumorous pancreatic tissue in patients with PNET (PNET-NT) and heathy pancreatic tissue (CTR). The diagnostic performance of tomoelastography was evaluated by ROC-AUC analysis. PNET-SWS correlations were calculated with Pearson’s r. Results: SWS was higher in PNET-T (2.02 ± 0.61 m/s) compared to PNET-NT (1.31 ± 0.18 m/s, p < 0.01) and CTR (1.26 ± 0.09 m/s, p < 0.01). An SWS-cutoff of 1.46 m/s distinguished PNET-T from PNET-NT (AUC = 0.89; sensitivity = 0.85; specificity = 0.92) and a cutoff of 1.49 m/s differentiated pancreatic tissue of CTR from PNET-T (AUC = 0.96; sensitivity = 0.92; specificity = 1.00). The SWS of PNET-T was positively correlated with PET derived asphericity (r = 0.81; p = 0.01). Conclusions: Tomoelastography provides quantitative imaging markers for the detection of PNET and the prediction of greater tumor aggressiveness by increased stiffness.
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Affiliation(s)
- Emin Gültekin
- Department of Radiology, Campus Virchow Klinikum, Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117 Berlin, Germany; (E.G.); (D.G.); (B.H.)
| | - Christoph Wetz
- Department of Nuclear Medicine, Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 13353 Berlin, Germany; (C.W.); (C.F.)
| | - Jürgen Braun
- Institute for Medical Informatics, Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117 Berlin, Germany;
| | - Dominik Geisel
- Department of Radiology, Campus Virchow Klinikum, Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117 Berlin, Germany; (E.G.); (D.G.); (B.H.)
| | - Christian Furth
- Department of Nuclear Medicine, Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 13353 Berlin, Germany; (C.W.); (C.F.)
| | - Bernd Hamm
- Department of Radiology, Campus Virchow Klinikum, Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117 Berlin, Germany; (E.G.); (D.G.); (B.H.)
- Department of Radiology, Campus Mitte, Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117 Berlin, Germany;
| | - Ingolf Sack
- Department of Radiology, Campus Mitte, Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117 Berlin, Germany;
| | - Stephan R. Marticorena Garcia
- Department of Radiology, Campus Mitte, Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117 Berlin, Germany;
- Correspondence: ; Tel.: +49-30-450-527082; Fax: +49-30-450-7527911
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13
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Fujima N, Andreu-Arasa VC, Meibom SK, Mercier GA, Truong MT, Hirata K, Yasuda K, Kano S, Homma A, Kudo K, Sakai O. Prediction of the local treatment outcome in patients with oropharyngeal squamous cell carcinoma using deep learning analysis of pretreatment FDG-PET images. BMC Cancer 2021; 21:900. [PMID: 34362317 PMCID: PMC8344209 DOI: 10.1186/s12885-021-08599-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Accepted: 07/09/2021] [Indexed: 11/21/2022] Open
Abstract
Background This study aimed to assess the utility of deep learning analysis using pretreatment FDG-PET images to predict local treatment outcome in oropharyngeal squamous cell carcinoma (OPSCC) patients. Methods One hundred fifty-four OPSCC patients who received pretreatment FDG-PET were included and divided into training (n = 102) and test (n = 52) sets. The diagnosis of local failure and local progression-free survival (PFS) rates were obtained from patient medical records. In deep learning analyses, axial and coronal images were assessed by three different architectures (AlexNet, GoogLeNET, and ResNet). In the training set, FDG-PET images were analyzed after the data augmentation process for the diagnostic model creation. A multivariate clinical model was also created using a binomial logistic regression model from a patient’s clinical characteristics. The test data set was subsequently analyzed for confirmation of diagnostic accuracy. Assessment of local PFS rates was also performed. Results Training sessions were successfully performed with an accuracy of 74–89%. ROC curve analyses revealed an AUC of 0.61–0.85 by the deep learning model in the test set, whereas it was 0.62 by T-stage, 0.59 by clinical stage, and 0.74 by a multivariate clinical model. The highest AUC (0.85) was obtained with deep learning analysis of ResNet architecture. Cox proportional hazards regression analysis revealed deep learning-based classification by a multivariate clinical model (P < .05), and ResNet (P < .001) was a significant predictor of the treatment outcome. In the Kaplan-Meier analysis, the deep learning-based classification divided the patient’s local PFS rate better than the T-stage, clinical stage, and a multivariate clinical model. Conclusions Deep learning-based diagnostic model with FDG-PET images indicated its possibility to predict local treatment outcomes in OPSCCs. Supplementary Information The online version contains supplementary material available at 10.1186/s12885-021-08599-6.
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Affiliation(s)
- Noriyuki Fujima
- Departments of Radiology, Boston University School of Medicine, One Boston Medical Center Place, 3rd Floor, 820 Harrison Avenue, Boston, MA, 02118, USA.,Research Center for Cooperative Projects, Hokkaido University Graduate School of Medicine, kita 15, nishi 7, kita-ku, Sapporo, Hokkaido, 060-8638, Japan
| | - V Carlota Andreu-Arasa
- Departments of Radiology, Boston University School of Medicine, One Boston Medical Center Place, 3rd Floor, 820 Harrison Avenue, Boston, MA, 02118, USA
| | - Sara K Meibom
- Departments of Radiology, Boston University School of Medicine, One Boston Medical Center Place, 3rd Floor, 820 Harrison Avenue, Boston, MA, 02118, USA
| | - Gustavo A Mercier
- Departments of Radiology, Boston University School of Medicine, One Boston Medical Center Place, 3rd Floor, 820 Harrison Avenue, Boston, MA, 02118, USA
| | - Minh Tam Truong
- Departments of Radiation Oncology, Boston Medical Center, Boston University School of Medicine, One Boston Medical Center Place, Boston, MA, 02118, USA
| | - Kenji Hirata
- Departments of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, kita 15, nishi 7, kita-ku, Sapporo, Hokkaido, 060-8638, Japan
| | - Koichi Yasuda
- Departments of Radiation Medicine, Hokkaido University Graduate School of Medicine, kita 15, nishi 7, kita-ku, Sapporo, Hokkaido, 060-8638, Japan
| | - Satoshi Kano
- Otolaryngology-Head and Neck Surgery, Hokkaido University Graduate School of Medicine, kita 15, nishi 7, kita-ku, Sapporo, Hokkaido, 060-8638, Japan
| | - Akihiro Homma
- Otolaryngology-Head and Neck Surgery, Hokkaido University Graduate School of Medicine, kita 15, nishi 7, kita-ku, Sapporo, Hokkaido, 060-8638, Japan
| | - Kohsuke Kudo
- Departments of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, kita 15, nishi 7, kita-ku, Sapporo, Hokkaido, 060-8638, Japan.,The Global Station for Quantum Medical Science and Engineering, Global Institution for collaborative research and education, Sapporo, Hokkaido, 060-0808, Japan
| | - Osamu Sakai
- Departments of Radiology, Boston University School of Medicine, One Boston Medical Center Place, 3rd Floor, 820 Harrison Avenue, Boston, MA, 02118, USA. .,Departments of Radiation Oncology, Boston Medical Center, Boston University School of Medicine, One Boston Medical Center Place, Boston, MA, 02118, USA.
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Can 3D pseudo-continuous arterial spin labeling perfusion imaging be applied to predict early response to chemoradiotherapy in patients with advanced nasopharyngeal carcinoma? Radiother Oncol 2021; 160:97-106. [PMID: 33951492 DOI: 10.1016/j.radonc.2021.04.017] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Revised: 04/09/2021] [Accepted: 04/22/2021] [Indexed: 11/22/2022]
Abstract
BACKGROUND AND PURPOSE Chemoradiotherapy (CRT) has been widely applied in patients with advanced nasopharyngeal carcinoma (ANPC). However, limited imaging modality exists on the evaluation of early response to CRT. The purpose of this study was therefore to investigate whether 3D pseudo-continuous arterial spin labeling (3D pCASL) perfusion imaging could predict early response to CRT in ANPC patients. MATERIALS AND METHODS Seventy ANPC patients who received CRT underwent pre-treatment MRI including 3D pCASL perfusion measurements, and were categorized into response group (RG) and no-response group (NRG) according to RECIST 1.1. Pre-treatment 3D pCASL derived cerebral blood flow (CBF) values in tumors were compared between RG and NRG patients. Receiver-operating characteristic (ROC) analysis was performed to determine the optimal diagnostic cutoff value for CBF in predicting tumor response to CRT. Clinicopathological variables were also analyzed by using univariate and binary logistic regression. The corresponding obtained variables with statistical significance were further applied to create a nomogram in which the bootstrap resampling method was used for calibration. RESULTS Forty-eight patients in RG had significantly higher pre-treatment CBF values in tumors compared with 22 patients in NRG (P < 0.001). CBF showed the high area under the ROC curve (AUC = 0.843) in distinguishing RG from NRG patients. The corresponding cutoff value for CBF was 103.68 ml/100 g/min, with respective accuracy, sensitivity and specificity of 82.86%, 87.50% and 72.73%. The nomogram was generated by binary logistic regression results, incorporating three variables: CBF value, clinical stage and pathological type. The AUC, accuracy, sensitivity and specificity of the nomogram was respectively 0.893, 84.28%, 81.25% and 90.91% in predicting tumor response to CRT. Moreover, as shown in the calibration curve, a strong agreement was observed between nomogram prediction probability and actual clinical findings (P = 0.309). CONCLUSIONS 3D pCASL derived CBF in tumor could act as a noninvasive effective biomarker to predict tumor response to CRT in ANPC patients before clinical treatment. Furthermore, the nomogram combining CBF and clinicopathological variables could serve as a novel clinical analysis tool for treatment response prediction.
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15
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Fujima N, Andreu-Arasa VC, Meibom SK, Mercier GA, Salama AR, Truong MT, Sakai O. Prediction of the treatment outcome using machine learning with FDG-PET image-based multiparametric approach in patients with oral cavity squamous cell carcinoma. Clin Radiol 2021; 76:711.e1-711.e7. [PMID: 33934877 DOI: 10.1016/j.crad.2021.03.017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2020] [Accepted: 03/26/2021] [Indexed: 12/15/2022]
Abstract
AIM To investigate the value of machine learning-based multiparametric analysis using 2-[18F]-fluoro-2-deoxy-d-glucose positron-emission tomography (FDG-PET) images to predict treatment outcome in patients with oral cavity squamous cell carcinoma (OCSCC). MATERIALS AND METHODS Ninety-nine patients with OCSCC who received pretreatment integrated FDG-PET/computed tomography (CT) were included. They were divided into the training (66 patients) and validation (33 patients) cohorts. The diagnosis of local control or local failure was obtained from patient's medical records. Conventional FDG-PET parameters, including the maximum and mean standardised uptake values (SUVmax and SUVmean), metabolic tumour volume (MTV), and total lesion glycolysis (TLG), quantitative tumour morphological parameters, intratumoural histogram, and texture parameters, as well as T-stage and clinical stage, were evaluated by a machine learning analysis. The diagnostic ability of T-stage, clinical stage, and conventional FDG-PET parameters (SUVmax, SUVmean, MTV, and TLG) was also assessed separately. RESULTS In support-vector machine analysis of the training dataset, the final selected parameters were T-stage, SUVmax, TLG, morphological irregularity, entropy, and run-length non-uniformity. In the validation dataset, the diagnostic performance of the created algorithm was as follows: sensitivity 0.82, specificity 0.7, positive predictive value 0.86, negative predictive value 0.64, and accuracy 0.79. In a univariate analysis using conventional FDG-PET parameters, T-stage and clinical stage, diagnostic accuracy of each variable was revealed as follows: 0.61 in T-stage, 0.61 in clinical stage, 0.64 in SUVmax, 0.61 in SUVmean, 0.64 in MTV, and 0.7 in TLG. CONCLUSION A machine-learning-based approach to analysing FDG-PET images by multiparametric analysis might help predict local control or failure in patients with OCSCC.
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Affiliation(s)
- N Fujima
- Department of Radiology, Boston Medical Center, Boston University School of Medicine, USA; Research Center for Cooperative Projects, Hokkaido University Graduate School of Medicine, Japan
| | - V C Andreu-Arasa
- Department of Radiology, Boston Medical Center, Boston University School of Medicine, USA
| | - S K Meibom
- Department of Radiology, Boston Medical Center, Boston University School of Medicine, USA
| | - G A Mercier
- Department of Radiology, Boston Medical Center, Boston University School of Medicine, USA
| | - A R Salama
- Department of Otolaryngology - Head and Neck Surgery, Boston Medical Center, Boston University School of Medicine, USA; Department of Oral & Maxillofacial Surgery, Boston Medical Center, Boston University Henry M. Goldman School of Dental Medicine, USA
| | - M T Truong
- Department of Radiation Oncology, Boston Medical Center, Boston University School of Medicine, USA
| | - O Sakai
- Department of Radiology, Boston Medical Center, Boston University School of Medicine, USA; Department of Otolaryngology - Head and Neck Surgery, Boston Medical Center, Boston University School of Medicine, USA; Department of Radiation Oncology, Boston Medical Center, Boston University School of Medicine, USA.
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16
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Zeng T, Xu Z, Yan J. The value of asphericity derived from T1-weighted MR in differentiating intraparenchymal ring-enhancing lesions-comparison of glioblastomas and brain abscesses. Neurol Sci 2021; 42:5171-5175. [PMID: 33796946 DOI: 10.1007/s10072-021-05226-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Accepted: 03/25/2021] [Indexed: 11/28/2022]
Abstract
BACKGROUND Both brain abscess(BA)and glioblastoma (GBM) are common causative pathologies of intraparenchymal ring-enhancing lesions. Advanced MR sequences such as diffusion weighted image (DWI) were often used to increase distinguishability of both entities. PURPOSE To evaluate the value of asphericity (ASP) from conventional T1-weighted MR images in differentiating BA from morphologically similar ring-enhancing GBM. MATERIAL AND METHODS Twenty-one BA and twenty-nine GBM were retrospectively included in this study. Each region of interest (ROI) was delineated twice with the software of ITK-SNAP on the contrast-enhanced T1 images by two observers. ASP was calculated to define the relative deviation of the ROI's shape from a sphere. Intraclass correlation coefficients (ICC) for inter-observer and intra-observer were calculated. The diagnostic capabilities of ASP and conventional volume (VOL) of ROI were evaluated with receiver operating characteristic (ROC) curve analysis. In addition, areas under the ROC curves of ASP and VOL were compared. RESULTS ICC of intra-observer and inter-observer were 0.99 (95% confidence interval, [CI] 0.97-0.99) and 0.98 (0.95-0.99), respectively. Both ASP and VOL showed significant difference between BA and GBM. The mean ASP values for BA and GBM were 66.3±7.8 and 14.7±1.8, respectively. The mean VOL value of BA was also larger than that of GBM (47.2±7.4 vs. 20.7±1.5 mm3). The mean AUC of ASP and VOL were 0.977 (95% CI 0.944-1) and 0.86 (95% CI 0.746-0.974), respectively. The AUC of ASP was significantly higher than that of VOL (p=0.04). The optimal cut point values of ASP and VOL were 24.39 and 24.86 mm3, respectively. CONCLUSIONS ASP derived from routine MRI is useful in differentiating BA from GBM.
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Affiliation(s)
- Tao Zeng
- Department of Neurosurgery, Shanghai Tenth People's Hospital, Tongji University School of Medicine, No. 301 Middle Yanchang Road, Shanghai, 200072, China
| | - Zijun Xu
- Department of Radiology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, No. 301 Middle Yanchang Road, Shanghai, 200072, China
| | - Jianhua Yan
- Shanghai Key Laboratory of Molecular Imaging, Shanghai University of Medicine and Health Sciences, Shanghai, 201318, China. .,Molecular Imaging Precision Medicine Collaborative Innovation Center, Shanxi Medical University, Taiyuan, 030001, Shanxi, China.
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17
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Creff G, Devillers A, Depeursinge A, Palard-Novello X, Acosta O, Jegoux F, Castelli J. Evaluation of the Prognostic Value of FDG PET/CT Parameters for Patients With Surgically Treated Head and Neck Cancer: A Systematic Review. JAMA Otolaryngol Head Neck Surg 2021; 146:471-479. [PMID: 32215611 DOI: 10.1001/jamaoto.2020.0014] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Importance Head and neck squamous cell cancer (HNSCC) represents the seventh most frequent cancer worldwide. More than half of the patients diagnosed with HNSCC are treated with primary surgery. Objective To report the available evidence on the value of quantitative parameters of fluorodeoxyglucose F 18-labeled positron emission tomography and computed tomography (FDG-PET/CT) performed before surgical treatment of HNSCC to estimate overall survival (OS), disease-free survival (DFS), and distant metastasis (DM) and to discuss their limitations. Evidence Review A systematic review of the English-language literature in PubMed/MEDLINE and ScienceDirect published between January 2003 and February 15, 2019, was performed between March 1 and July 27, 2019, to identify articles addressing the association between preoperative FDG-PET/CT parameters and oncological outcomes among patients with HNSCC. Articles included those that addressed the following: (1) cancer of the oral cavity, oropharynx, hypopharynx, or larynx; (2) surgically treated (primary or for salvage); (3) pretreatment FDG-PET/CT; (4) quantitative or semiquantitative evaluation of the FDG-PET/CT parameters; and (5) the association between the value of FDG-PET/CT parameters and clinical outcomes. Quality assessment was performed using the Oxford Centre for Evidence-Based Medicine level of evidence. Findings A total of 128 studies were retrieved from the databases, and 36 studies met the inclusion criteria; these studies comprised 3585 unique patients with a median follow-up of 30.6 months (range, 16-53 months). Of these 36 studies, 32 showed an association between at least 1 FDG-PET/CT parameter and oncological outcomes (OS, DFS, and DM). The FDG-PET/CT volumetric parameters (metabolic tumor volume [MTV] and total lesion glycolysis [TLG]) were independent prognostic factors in most of the data, with a higher prognostic value than the maximum standard uptake value (SUVmax). For example, in univariate analysis of OS, the SUVmax was correlated with OS in 5 of 11 studies, MTV in 11 of 12 studies, and TLG in 6 of 9 studies. The spatial distribution of metabolism via textural indices seemed promising, although that factor is currently poorly evaluated: only 3 studies analyzed data from radiomics indices. Conclusions and Relevance The findings of this study suggest that the prognostic effectiveness of FDG-PET/CT parameters as biomarkers of OS, DFS, and DM among patients with HNSCC treated with surgery may be valuable. The volumetric parameters (MTV and TLG) seemed relevant for identifying patients with a higher risk of postsurgical disease progression who could receive early therapeutic intervention to improve their prognosis. However, further large-scale studies including exclusively surgery-treated patients stratified according to localization and further analysis of the textural indices are required to define a reliable FDG-PET/CT-based prognostic model of mortality and recurrence risk for these patients.
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Affiliation(s)
- Gwenaelle Creff
- Department of Otolaryngology-Head and Neck Surgery, Rennes University Hospital, Rennes, France
| | - Anne Devillers
- Department of Nuclear Medicine, Centre Eugène Marquis, Rennes, France
| | - Adrien Depeursinge
- University of Applied Sciences and Arts Western Switzerland, Lausanne, Switzerland
| | | | - Oscar Acosta
- LTSI (Image and Signal Processing Laboratory), INSERM, U1099, Rennes, France
| | - Franck Jegoux
- Department of Otolaryngology-Head and Neck Surgery, Rennes University Hospital, Rennes, France
| | - Joel Castelli
- Department of Radiation Oncology, Cancer Institute Eugène Marquis, Rennes, France
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18
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Belgioia L, Morbelli SD, Corvò R. Prediction of Response in Head and Neck Tumor: Focus on Main Hot Topics in Research. Front Oncol 2021; 10:604965. [PMID: 33489911 PMCID: PMC7821385 DOI: 10.3389/fonc.2020.604965] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Accepted: 11/26/2020] [Indexed: 11/13/2022] Open
Abstract
Radiation therapy is a cornerstone in the treatment of head and neck cancer patients; actually, their management is based on clinical and radiological staging with all patients at the same stage treated in the same way. Recently the increasing knowledge in molecular characterization of head and neck cancer opens the way for a more tailored treatment. Patient outcomes could be improved by a personalized radiotherapy beyond technological and anatomical precision. Several tumor markers are under evaluation to understand their possible prognostic or predictive value. In this paper we discuss those markers specific for evaluate response to radiation therapy in head and neck cancer for a shift toward a biological personalization of radiotherapy.
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Affiliation(s)
- Liliana Belgioia
- Radiation Oncology Department, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.,Health Science Department (DISSAL), University of Genoa, Genoa, Italy
| | - Silvia Daniela Morbelli
- Health Science Department (DISSAL), University of Genoa, Genoa, Italy.,Nuclear Medicine Department, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Renzo Corvò
- Radiation Oncology Department, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.,Health Science Department (DISSAL), University of Genoa, Genoa, Italy
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19
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Briest F, Koziolek EJ, Albrecht J, Schmidt F, Bernsen MR, Haeck J, Kühl AA, Sedding D, Hartung T, Exner S, Welzel M, Fischer C, Grötzinger C, Brenner W, Baum RP, Grabowski P. Does the proteasome inhibitor bortezomib sensitize to DNA-damaging therapy in gastroenteropancreatic neuroendocrine neoplasms? - A preclinical assessment in vitro and in vivo. Neoplasia 2020; 23:80-98. [PMID: 33246310 PMCID: PMC7701025 DOI: 10.1016/j.neo.2020.11.004] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Revised: 11/01/2020] [Accepted: 11/03/2020] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND Well-differentiated gastroenteropancreatic neuroendocrine neoplasms are rare tumors with a slow proliferation. They are virtually resistant to many DNA-damaging therapeutic approaches, such as chemo- and external beam therapy, which might be overcome by DNA damage inhibition induced by proteasome inhibitors such as bortezomib. METHODS AND RESULTS In this study, we assessed several combined treatment modalities in vitro and in vivo. By cell-based functional analyses, in a 3D in ovo and an orthotopic mouse model, we demonstrated sensitizing effects of bortezomib combined with cisplatin, radiation and peptide receptor radionuclide therapy (PRRT). By gene expression profiling and western blot, we explored the underlying mechanisms, which resulted in an impaired DNA damage repair. Therapy-induced DNA damage triggered extrinsic proapoptotic signaling as well as the induction of cell cycle arrest, leading to a decreased vital tumor volume and altered tissue composition shown by magnetic resonance imaging and F-18-FDG-PET in vivo, however with no significant additional benefit related to PRRT alone. CONCLUSIONS We demonstrated that bortezomib has short-term sensitizing effects when combined with DNA damaging therapy by interfering with DNA repair in vitro and in ovo. Nevertheless, due to high tumor heterogeneity after PRRT in long-term observations, we were not able to prove a therapeutic advantage of bortezomib-combined PRRT in an in vivo mouse model.
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Affiliation(s)
- Franziska Briest
- Department of Hematology, Oncology and Tumor Immunology, Charité-Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany; Department of Biology, Chemistry, and Pharmacy, Institute of Chemistry and Biochemistry, Freie Universität (FU) Berlin, Berlin, Germany.
| | - Eva J Koziolek
- German Cancer Consortium (DKTK), Germany; Department of Nuclear Medicine, Charité Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin Germany; German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Jakob Albrecht
- Department of Nuclear Medicine, Charité Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin Germany
| | - Fränze Schmidt
- German Cancer Consortium (DKTK), Germany; Department of Nuclear Medicine, Charité Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin Germany; German Cancer Research Center (DKFZ), Heidelberg, Germany; Institute for Biochemistry and Biotechnology, Martin-Luther-University (MLU) Halle-Wittenberg, Halle (Saale), Germany
| | | | - Joost Haeck
- Department of Radiology, Erasmus MC, Rotterdam, The Netherlands
| | - Anja A Kühl
- iPATH.Berlin, Campus Benjamin Franklin, Charité - Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin
| | - Dagmar Sedding
- Department of Hematology, Oncology and Tumor Immunology, Charité-Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany; Institute of Biology, Humboldt-Universität (HU) Berlin, Berlin, Germany
| | - Teresa Hartung
- Department of Hematology, Oncology and Tumor Immunology, Charité-Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Samantha Exner
- Department of Hepatology and Gastroenterology and Molecular Cancer Research Center, Tumor Targeting Laboratory, Charité-Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Martina Welzel
- Experimental and Clinical Research Center, a joint cooperation between the Charité Medical Faculty and the Max-Delbrück Center (MDC) for Molecular Medicine, Berlin, Germany
| | - Christian Fischer
- Experimental and Clinical Research Center, a joint cooperation between the Charité Medical Faculty and the Max-Delbrück Center (MDC) for Molecular Medicine, Berlin, Germany
| | - Carsten Grötzinger
- German Cancer Consortium (DKTK), Germany; Department of Hepatology and Gastroenterology and Molecular Cancer Research Center, Tumor Targeting Laboratory, Charité-Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Winfried Brenner
- German Cancer Consortium (DKTK), Germany; Department of Nuclear Medicine, Charité Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin Germany; Berlin Experimental Radionuclide Imaging Center (BERIC), Charité Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Richard P Baum
- Department of Nuclear Medicine, Zentralklinik Bad Berka GmbH, Bad Berka, Germany; CURANOSTICUM Wiesbaden-Frankfurt, DKD Helios Clinic, Wiesbaden, Germany
| | - Patricia Grabowski
- Department of Hematology, Oncology and Tumor Immunology, Charité-Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany; Department of Gastroenterology and Endocrinology, Zentralklinik Bad Berka GmbH, Bad Berka, Germany; Department of Medical Immunology, Charité Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
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20
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Rogasch JMM, Furth C, Bluemel S, Radojewski P, Amthauer H, Hofheinz F. Asphericity of tumor FDG uptake in non-small cell lung cancer: reproducibility and implications for harmonization in multicenter studies. EJNMMI Res 2020; 10:134. [PMID: 33140213 PMCID: PMC7606415 DOI: 10.1186/s13550-020-00725-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Accepted: 10/21/2020] [Indexed: 11/15/2022] Open
Abstract
Background Asphericity (ASP) of the primary tumor’s metabolic tumor volume (MTV) in FDG-PET/CT is independently predictive for survival in patients with non-small cell lung cancer (NSCLC). However, comparability between PET systems may be limited. Therefore, reproducibility of ASP was evaluated at varying image reconstruction and acquisition times to assess feasibility of ASP assessment in multicenter studies.
Methods This is a retrospective study of 50 patients with NSCLC (female 20; median age 69 years) undergoing pretherapeutic FDG-PET/CT (median 3.7 MBq/kg; 180 s/bed position). Reconstruction used OSEM with TOF4/16 (iterations 4; subsets 16; in-plane filter 2.0, 6.4 or 9.5 mm), TOF4/8 (4 it; 8 ss; filter 2.0/6.0/9.5 mm), PSF + TOF2/17 (2 it; 17 ss; filter 2.0/7.0/10.0 mm) or Bayesian-penalized likelihood (Q.Clear; beta, 600/1750/4000). Resulting reconstructed spatial resolution (FWHM) was determined from hot sphere inserts of a NEMA IEC phantom. Data with approx. 5-mm FWHM were retrospectively smoothed to achieve 7-mm FWHM. List mode data were rebinned for acquisition times of 120/90/60 s. Threshold-based delineation of primary tumor MTV was followed by evaluation of relative ASP/SUVmax/MTV differences between datasets and resulting proportions of discordantly classified cases.
Results Reconstructed resolution for narrow/medium/wide in-plane filter (or low/medium/high beta) was approx. 5/7/9 mm FWHM. Comparing different pairs of reconstructed resolution between TOF4/8, PSF + TOF2/17, Q.Clear and the reference algorithm TOF4/16, ASP differences was lowest at FWHM of 7 versus 7 mm. Proportions of discordant cases (ASP > 19.5% vs. ≤ 19.5%) were also lowest at 7 mm (TOF4/8, 2%; PSF + TOF2/17, 4%; Q.Clear, 10%). Smoothing of 5-mm data to 7-mm FWHM significantly reduced discordant cases (TOF4/8, 38% reduced to 2%; PSF + TOF2/17, 12% to 4%; Q.Clear, 10% to 6%), resulting in proportions comparable to original 7-mm data. Shorter acquisition time only increased proportions of discordant cases at < 90 s. Conclusions ASP differences were mainly determined by reconstructed spatial resolution, and multicenter studies should aim at comparable FWHM (e.g., 7 mm; determined by in-plane filter width). This reduces discordant cases (high vs. low ASP) to an acceptable proportion for TOF and PSF + TOF of < 5% (Q.Clear: 10%). Data with better resolution (i.e., lower FWHM) could be retrospectively smoothed to the desired FWHM, resulting in a comparable number of discordant cases.
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Affiliation(s)
- Julian M M Rogasch
- Department of Nuclear Medicine, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität Zu Berlin, and Berlin Institute of Health, Augustenburger Platz 1, 13353, Berlin, Germany.
| | - Christian Furth
- Department of Nuclear Medicine, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität Zu Berlin, and Berlin Institute of Health, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Stephanie Bluemel
- Department of Nuclear Medicine, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität Zu Berlin, and Berlin Institute of Health, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Piotr Radojewski
- Department of Nuclear Medicine, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität Zu Berlin, and Berlin Institute of Health, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Holger Amthauer
- Department of Nuclear Medicine, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität Zu Berlin, and Berlin Institute of Health, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Frank Hofheinz
- Institute for Radiopharmaceutical Cancer Research, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany
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21
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Du D, Gu J, Chen X, Lv W, Feng Q, Rahmim A, Wu H, Lu L. Integration of PET/CT Radiomics and Semantic Features for Differentiation between Active Pulmonary Tuberculosis and Lung Cancer. Mol Imaging Biol 2020; 23:287-298. [PMID: 33030709 DOI: 10.1007/s11307-020-01550-4] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Revised: 09/25/2020] [Accepted: 09/29/2020] [Indexed: 10/23/2022]
Abstract
PURPOSE We aim to accurately differentiate between active pulmonary tuberculosis (TB) and lung cancer (LC) based on radiomics and semantic features as extracted from pre-treatment positron emission tomography/X-ray computed tomography (PET/CT) images. PROCEDURES A total of 174 patients (77/97 pulmonary TB/LC as confirmed by pathology) were retrospectively selected, with 122 in the training cohort and 52 in the validation cohort. Four hundred eighty-seven radiomics features were initially extracted to quantify phenotypic characteristics of the lesion region in both PET and CT images. Eleven semantic features were additionally defined by two experienced nuclear medicine physicians. Feature selection was performed in 5 steps to enable derivation of robust and effective signatures. Multivariable logistic regression analysis was subsequently used to develop a radiomics nomogram. The calibration, discrimination, and clinical usefulness of the nomogram were evaluated in both the training and independent validation cohorts. RESULTS The individualized radiomics nomogram, which combined PET/CT radiomics signature with semantic features, demonstrated good calibration and significantly improved the diagnostic performance with respect to the semantic model alone or PET/CT signature alone in training cohort (AUC 0.97 vs. 0.94 or 0.91, p = 0.0392 or 0.0056), whereas did not significantly improve the performance in validation cohort (AUC 0.93 vs. 0.89 or 0.91, p = 0.3098 or 0.3323). CONCLUSION The radiomics nomogram showed potential for individualized differential diagnosis between solid active pulmonary TB and solid LC, although the improvement of performance was not significant relative to semantic model.
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Affiliation(s)
- Dongyang Du
- School of Biomedical Engineering and Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, 510515, Guangdong, China
| | - Jiamei Gu
- Nanfang PET Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, China
| | - Xiaohui Chen
- Nanfang PET Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, China
| | - Wenbing Lv
- School of Biomedical Engineering and Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, 510515, Guangdong, China
| | - Qianjin Feng
- School of Biomedical Engineering and Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, 510515, Guangdong, China
| | - Arman Rahmim
- Departments of Radiology and Physics, University of British Columbia, Vancouver, BC, V6T 1Z1, Canada.,Department of Integrative Oncology, BC Cancer Research Centre, Vancouver, BC, V5Z 1L3, Canada
| | - Hubing Wu
- Nanfang PET Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, China.
| | - Lijun Lu
- School of Biomedical Engineering and Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, 510515, Guangdong, China.
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22
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Choi Y, Nam Y, Jang J, Shin NY, Ahn KJ, Kim BS, Lee YS, Kim MS. Prediction of Human Papillomavirus Status and Overall Survival in Patients with Untreated Oropharyngeal Squamous Cell Carcinoma: Development and Validation of CT-Based Radiomics. AJNR Am J Neuroradiol 2020; 41:1897-1904. [PMID: 32943420 DOI: 10.3174/ajnr.a6756] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2020] [Accepted: 07/03/2020] [Indexed: 12/14/2022]
Abstract
BACKGROUND AND PURPOSE Human papillomavirus is a prognostic marker for oropharyngeal squamous cell carcinoma. We aimed to determine the value of CT-based radiomics for predicting the human papillomavirus status and overall survival in patients with oropharyngeal squamous cell carcinoma. MATERIALS AND METHODS Eighty-six patients with oropharyngeal squamous cell carcinoma were retrospectively collected and grouped into training (n = 61) and test (n = 25) sets. For human papillomavirus status and overall survival prediction, radiomics features were selected via a random forest-based algorithm and Cox regression analysis, respectively. Relevant features were used to build multivariate Cox regression models and calculate the radiomics score. Human papillomavirus status and overall survival prediction were assessed via the area under the curve and concordance index, respectively. The models were validated in the test and The Cancer Imaging Archive cohorts (n = 78). RESULTS For prediction of human papillomavirus status, radiomics features yielded areas under the curve of 0.865, 0.747, and 0.834 in the training, test, and validation sets, respectively. In the univariate Cox regression, the human papillomavirus status (positive: hazard ratio, 0.257; 95% CI, 0.09-0.7; P = .008), T-stage (≥III: hazard ratio, 3.66; 95% CI, 1.34-9.99; P = .011), and radiomics score (high-risk: hazard ratio, 3.72; 95% CI, 1.21-11.46; P = .022) were associated with overall survival. The addition of the radiomics score to the clinical Cox model increased the concordance index from 0.702 to 0.733 (P = .01). Validation yielded concordance indices of 0.866 and 0.720. CONCLUSIONS CT-based radiomics may be useful in predicting human papillomavirus status and overall survival in patients with oropharyngeal squamous cell carcinoma.
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Affiliation(s)
- Y Choi
- Department of Radiology (Y.C., Y.N., J.J., N.-Y.S, K.-J.A., B.-S.K.), Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Y Nam
- Department of Radiology (Y.C., Y.N., J.J., N.-Y.S, K.-J.A., B.-S.K.), Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
- Division of Biomedical Engineering (Y.N.), Hankuk University of Foreign Studies, Yongin-Si, Gyeonggi-do, Republic of Korea
| | - J Jang
- Department of Radiology (Y.C., Y.N., J.J., N.-Y.S, K.-J.A., B.-S.K.), Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - N-Y Shin
- Department of Radiology (Y.C., Y.N., J.J., N.-Y.S, K.-J.A., B.-S.K.), Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - K-J Ahn
- Department of Radiology (Y.C., Y.N., J.J., N.-Y.S, K.-J.A., B.-S.K.), Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - B-S Kim
- Department of Radiology (Y.C., Y.N., J.J., N.-Y.S, K.-J.A., B.-S.K.), Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Y-S Lee
- Department of Hospital Pathology (Y.-S.L.), Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - M-S Kim
- Department of Otolaryngology-Head and Neck Surgery (M.S.K.), Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
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23
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Zschaeck S, Li Y, Lin Q, Beck M, Amthauer H, Bauersachs L, Hajiyianni M, Rogasch J, Ehrhardt VH, Kalinauskaite G, Weingärtner J, Hartmann V, van den Hoff J, Budach V, Stromberger C, Hofheinz F. Prognostic value of baseline [18F]-fluorodeoxyglucose positron emission tomography parameters MTV, TLG and asphericity in an international multicenter cohort of nasopharyngeal carcinoma patients. PLoS One 2020; 15:e0236841. [PMID: 32730364 PMCID: PMC7392321 DOI: 10.1371/journal.pone.0236841] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Accepted: 07/14/2020] [Indexed: 01/02/2023] Open
Abstract
Purpose [18F]-fluorodeoxyglucose (FDG) positron emission tomography (PET) parameters have shown prognostic value in nasopharyngeal carcinomas (NPC), mostly in monocenter studies. The aim of this study was to assess the prognostic impact of standard and novel PET parameters in a multicenter cohort of patients. Methods The established PET parameters metabolic tumor volume (MTV), total lesion glycolysis (TLG) and maximal standardized uptake value (SUVmax) as well as the novel parameter tumor asphericity (ASP) were evaluated in a retrospective multicenter cohort of 114 NPC patients with FDG-PET staging, treated with (chemo)radiation at 8 international institutions. Uni- and multivariable Cox regression and Kaplan-Meier analysis with respect to overall survival (OS), event-free survival (EFS), distant metastases-free survival (FFDM), and locoregional control (LRC) was performed for clinical and PET parameters. Results When analyzing metric PET parameters, ASP showed a significant association with EFS (p = 0.035) and a trend for OS (p = 0.058). MTV was significantly associated with EFS (p = 0.026), OS (p = 0.008) and LRC (p = 0.012) and TLG with LRC (p = 0.019). TLG and MTV showed a very high correlation (Spearman’s rho = 0.95), therefore TLG was subesequently not further analysed. Optimal cutoff values for defining high and low risk groups were determined by maximization of the p-value in univariate Cox regression considering all possible cutoff values. Generation of stable cutoff values was feasible for MTV (p<0.001), ASP (p = 0.023) and combination of both (MTV+ASP = occurrence of one or both risk factors, p<0.001) for OS and for MTV regarding the endpoints OS (p<0.001) and LRC (p<0.001). In multivariable Cox (age >55 years + one binarized PET parameter), MTV >11.1ml (hazard ratio (HR): 3.57, p<0.001) and ASP > 14.4% (HR: 3.2, p = 0.031) remained prognostic for OS. MTV additionally remained prognostic for LRC (HR: 4.86 p<0.001) and EFS (HR: 2.51 p = 0.004). Bootstrapping analyses showed that a combination of high MTV and ASP improved prognostic value for OS compared to each single variable significantly (p = 0.005 and p = 0.04, respectively). When using the cohort from China (n = 57 patients) for establishment of prognostic parameters and all other patients for validation (n = 57 patients), MTV could be successfully validated as prognostic parameter regarding OS, EFS and LRC (all p-values <0.05 for both cohorts). Conclusions In this analysis, PET parameters were associated with outcome of NPC patients. MTV showed a robust association with OS, EFS and LRC. Our data suggest that combination of MTV and ASP may potentially further improve the risk stratification of NPC patients.
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Affiliation(s)
- Sebastian Zschaeck
- Charité –Universitätsmedizin Berlin, Berlin, Germany
- Freie Universität Berlin, Berlin, Germany
- Humboldt-Universität zu Berlin, Berlin, Germany
- Department of Radiation Oncology, Berlin Institute of Health, Berlin, Germany
- Berlin Institute of Health (BIH), Berlin, Germany
| | - Yimin Li
- Department of Radiation Oncology, Xiamen Cancer Center, The First Affiliated Hospital of Xiamen University, Xiamen, China
| | - Qin Lin
- Department of Radiation Oncology, Xiamen Cancer Center, The First Affiliated Hospital of Xiamen University, Xiamen, China
- * E-mail:
| | - Marcus Beck
- Charité –Universitätsmedizin Berlin, Berlin, Germany
- Freie Universität Berlin, Berlin, Germany
- Humboldt-Universität zu Berlin, Berlin, Germany
- Department of Radiation Oncology, Berlin Institute of Health, Berlin, Germany
| | - Holger Amthauer
- Department of Nuclear Medicine, Charité—Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany
| | - Laura Bauersachs
- Charité –Universitätsmedizin Berlin, Berlin, Germany
- Freie Universität Berlin, Berlin, Germany
- Humboldt-Universität zu Berlin, Berlin, Germany
- Department of Radiation Oncology, Berlin Institute of Health, Berlin, Germany
| | - Marina Hajiyianni
- Charité –Universitätsmedizin Berlin, Berlin, Germany
- Freie Universität Berlin, Berlin, Germany
- Humboldt-Universität zu Berlin, Berlin, Germany
- Department of Radiation Oncology, Berlin Institute of Health, Berlin, Germany
| | - Julian Rogasch
- Department of Nuclear Medicine, Charité—Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany
| | - Vincent H. Ehrhardt
- Charité –Universitätsmedizin Berlin, Berlin, Germany
- Freie Universität Berlin, Berlin, Germany
- Humboldt-Universität zu Berlin, Berlin, Germany
- Department of Radiation Oncology, Berlin Institute of Health, Berlin, Germany
| | - Goda Kalinauskaite
- Charité –Universitätsmedizin Berlin, Berlin, Germany
- Freie Universität Berlin, Berlin, Germany
- Humboldt-Universität zu Berlin, Berlin, Germany
- Department of Radiation Oncology, Berlin Institute of Health, Berlin, Germany
| | - Julian Weingärtner
- Charité –Universitätsmedizin Berlin, Berlin, Germany
- Freie Universität Berlin, Berlin, Germany
- Humboldt-Universität zu Berlin, Berlin, Germany
- Department of Radiation Oncology, Berlin Institute of Health, Berlin, Germany
| | - Vivian Hartmann
- Charité –Universitätsmedizin Berlin, Berlin, Germany
- Freie Universität Berlin, Berlin, Germany
- Humboldt-Universität zu Berlin, Berlin, Germany
- Department of Radiation Oncology, Berlin Institute of Health, Berlin, Germany
| | - Jörg van den Hoff
- Department of Positron Emission Tomography, Institute of Radiopharmaceutical Cancer Research, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany
| | - Volker Budach
- Charité –Universitätsmedizin Berlin, Berlin, Germany
- Freie Universität Berlin, Berlin, Germany
- Humboldt-Universität zu Berlin, Berlin, Germany
- Department of Radiation Oncology, Berlin Institute of Health, Berlin, Germany
| | - Carmen Stromberger
- Charité –Universitätsmedizin Berlin, Berlin, Germany
- Freie Universität Berlin, Berlin, Germany
- Humboldt-Universität zu Berlin, Berlin, Germany
- Department of Radiation Oncology, Berlin Institute of Health, Berlin, Germany
| | - Frank Hofheinz
- Department of Positron Emission Tomography, Institute of Radiopharmaceutical Cancer Research, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany
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24
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Whi W, Ha S, Bae S, Choi H, Paeng JC, Cheon GJ, Kang KW, Lee DS. Relationship of EGFR Mutation to Glucose Metabolic Activity and Asphericity of Metabolic Tumor Volume in Lung Adenocarcinoma. Nucl Med Mol Imaging 2020; 54:175-182. [PMID: 32831963 DOI: 10.1007/s13139-020-00646-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Revised: 06/01/2020] [Accepted: 06/04/2020] [Indexed: 12/31/2022] Open
Abstract
Purpose EGFR-mutation (EGFR-mt) is a major oncogenic driver mutation in lung adenocarcinoma (ADC) and is more often observed in Asian population. In lung ADC, some radiomics parameters of FDG PET have been reported to be associated with EGFR-mt. Here, the associations between EGFR-mt and PET parameters, particularly asphericity (ASP), were evaluated in Asian population. Methods Lung ADC patients who underwent curative surgical resection as the first treatment were retrospectively enrolled. EGFR mutation was defined as exon 19 deletion and exon 21 point mutation and was evaluated using surgical specimens. On FDG PET, image parameters of maximal standardized uptake value (SUVmax), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and ASP were obtained. The parameters were compared between EGFR-mt and wild type (EGFR-wt) groups, and the relationships between these PET parameters and EGFR-mt were evaluated. Results A total of 64 patients (median age 66 years, M:F = 34:30) were included in the analysis, and 29 (45%) patients showed EGFR-mt. In EGFR-mt group, all the image parameters of SUVmax, MTV, TLG, and ASP were significantly lower than in EGFR-wt group (all adjusted P < 0.050). In univariable logistic regression, SUVmax (P = 0.003) and ASP (P = 0.010) were significant determinants for EGFR-mt, whereas MTV was not (P = 0.690). Multivariate analysis revealed that SUVmax and ASP are independent determinants for EGFR-mt, regardless of inclusion of MTV in the analysis (P < 0.05). Conclusion In Asian NSCLC/ADC patients, SUVmax, MTV, and ASP on FDG PET are significantly related to EGFR mutation status. Particularly, low SUVmax and ASP are independent determinants for EGFR-mt.
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Affiliation(s)
- Wonseok Whi
- Department of Nuclear Medicine, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, 03080 South Korea.,Molecular Medicine and Biopharmaceutical Science, Graduate School of Convergence Science and Technology Seoul National University, Seoul, South Korea
| | - Seunggyun Ha
- Department of Nuclear Medicine, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, 03080 South Korea.,Division of Nuclear Medicine Department of Radiology, Seoul St. Mary's Hospital, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul, 06591 South Korea
| | - Sungwoo Bae
- Department of Nuclear Medicine, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, 03080 South Korea.,Molecular Medicine and Biopharmaceutical Science, Graduate School of Convergence Science and Technology Seoul National University, Seoul, South Korea
| | - Hongyoon Choi
- Department of Nuclear Medicine, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, 03080 South Korea
| | - Jin Chul Paeng
- Department of Nuclear Medicine, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, 03080 South Korea
| | - Gi Jeong Cheon
- Department of Nuclear Medicine, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, 03080 South Korea.,Cancer Research Institute, Seoul National University, Seoul, South Korea
| | - Keon Wook Kang
- Department of Nuclear Medicine, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, 03080 South Korea.,Cancer Research Institute, Seoul National University, Seoul, South Korea
| | - Dong Soo Lee
- Department of Nuclear Medicine, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, 03080 South Korea
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25
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Fujima N, Andreu-Arasa VC, Meibom SK, Mercier GA, Salama AR, Truong MT, Sakai O. Deep learning analysis using FDG-PET to predict treatment outcome in patients with oral cavity squamous cell carcinoma. Eur Radiol 2020; 30:6322-6330. [PMID: 32524219 DOI: 10.1007/s00330-020-06982-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2020] [Revised: 04/20/2020] [Accepted: 05/26/2020] [Indexed: 12/15/2022]
Abstract
OBJECTIVE To assess the utility of deep learning analysis using 18F-fluorodeoxyglucose (FDG) uptake by positron emission tomography (PET/CT) to predict disease-free survival (DFS) in patients with oral cavity squamous cell carcinoma (OCSCC). METHODS One hundred thirteen patients with OCSCC who received pretreatment FDG-PET/CT were included. They were divided into training (83 patients) and test (30 patients) sets. The diagnosis of treatment control/failure and the DFS rate were obtained from patients' medical records. In deep learning analyses, three planes of axial, coronal, and sagittal FDG-PET images were assessed by ResNet-101 architecture. In the training set, image analysis was performed for the diagnostic model creation. The test data set was subsequently analyzed for confirmation of diagnostic accuracy. T-stage, clinical stage, and conventional FDG-PET parameters (the maximum and mean standardized uptake value (SUVmax and SUVmean), heterogeneity index, metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were also assessed with determining the optimal cutoff from training dataset and then validated their diagnostic ability from test dataset. RESULTS In dividing into patients with treatment control and failure, the highest diagnostic accuracy of 0.8 was obtained using deep learning classification, with a sensitivity of 0.8, specificity of 0.8, positive predictive value of 0.89, and negative predictive value of 0.67. In the Kaplan-Meier analysis, the DFS rate was significantly different only with the analysis of deep learning-based classification (p < .01). CONCLUSIONS Deep learning-based diagnosis with FDG-PET images may predict treatment outcome in patients with OCSCC. KEY POINTS • Deep learning-based diagnosis of FDG-PET images showed the highest diagnostic accuracy to predict the treatment outcome in patients with oral cavity squamous cell carcinoma. • Deep learning-based diagnosis was shown to differentiate patients between good and poor disease-free survival more clearly than conventional T-stage, clinical stage, and conventional FDG-PET-based parameters.
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Affiliation(s)
- Noriyuki Fujima
- Department of Radiology, Boston Medical Center, Boston University School of Medicine, FGH Building, 3rd Floor, 820 Harrison Avenue, Boston, MA, 02118, USA.,Research Center for Cooperative Projects, Hokkaido University Graduate School of Medicine, Sapporo, Japan
| | - V Carlota Andreu-Arasa
- Department of Radiology, Boston Medical Center, Boston University School of Medicine, FGH Building, 3rd Floor, 820 Harrison Avenue, Boston, MA, 02118, USA
| | - Sara K Meibom
- Department of Radiology, Boston Medical Center, Boston University School of Medicine, FGH Building, 3rd Floor, 820 Harrison Avenue, Boston, MA, 02118, USA
| | - Gustavo A Mercier
- Department of Radiology, Boston Medical Center, Boston University School of Medicine, FGH Building, 3rd Floor, 820 Harrison Avenue, Boston, MA, 02118, USA
| | - Andrew R Salama
- Department of Otolaryngology - Head and Neck Surgery, Boston Medical Center, Boston University School of Medicine, Boston, USA.,Department of Oral & Maxillofacial Surgery, Boston Medical Center, Boston University Henry M. Goldman School of Dental Medicine, Boston, USA
| | - Minh Tam Truong
- Department of Radiation Oncology, Boston Medical Center, Boston University School of Medicine, Boston, USA
| | - Osamu Sakai
- Department of Radiology, Boston Medical Center, Boston University School of Medicine, FGH Building, 3rd Floor, 820 Harrison Avenue, Boston, MA, 02118, USA. .,Department of Otolaryngology - Head and Neck Surgery, Boston Medical Center, Boston University School of Medicine, Boston, USA. .,Department of Radiation Oncology, Boston Medical Center, Boston University School of Medicine, Boston, USA.
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26
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Tixier F, Cheze-le-Rest C, Schick U, Simon B, Dufour X, Key S, Pradier O, Aubry M, Hatt M, Corcos L, Visvikis D. Transcriptomics in cancer revealed by Positron Emission Tomography radiomics. Sci Rep 2020; 10:5660. [PMID: 32221360 PMCID: PMC7101432 DOI: 10.1038/s41598-020-62414-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2019] [Accepted: 03/13/2020] [Indexed: 11/09/2022] Open
Abstract
Metabolic images from Positron Emission Tomography (PET) are used routinely for diagnosis, follow-up or treatment planning purposes of cancer patients. In this study we aimed at determining if radiomic features extracted from 18F-Fluoro Deoxy Glucose (FDG) PET images could mirror tumor transcriptomics. In this study we analyzed 45 patients with locally advanced head and neck cancer (H&N) that underwent FDG-PET scans at the time of diagnosis and transcriptome analysis using RNAs from both cancer and healthy tissues on microarrays. Association between PET radiomics and transcriptomics was carried out with the Genomica software and a functional annotation was used to associate PET radiomics, gene expression and altered biological pathways. We identified relationships between PET radiomics and genes involved in cell-cycle, disease, DNA repair, extracellular matrix organization, immune system, metabolism or signal transduction pathways, according to the Reactome classification. Our results suggest that these FDG PET radiomic features could be used to infer tissue gene expression and cellular pathway activity in H&N cancers. These observations strengthen the value of radiomics as a promising approach to personalize treatments through targeting tumor-specific molecular processes.
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Affiliation(s)
- Florent Tixier
- Department of Nuclear Medicine, Poitiers University Hospital, Poitiers, France.
- LaTIM, INSERM, UMR 1101, Univ Brest, Brest, France.
| | - Catherine Cheze-le-Rest
- Department of Nuclear Medicine, Poitiers University Hospital, Poitiers, France
- LaTIM, INSERM, UMR 1101, Univ Brest, Brest, France
| | - Ulrike Schick
- LaTIM, INSERM, UMR 1101, Univ Brest, Brest, France
- Radiation Oncology Department, University Hospital, Brest, France
| | - Brigitte Simon
- INSERM, UMR 1078, Université de Brest, Génétique Génomique Fonctionnelle et Biotechnologies, Etablissement Français du Sang, Brest, France
| | - Xavier Dufour
- Head and Neck Department, Poitiers University Hospital, Poitiers, France
| | - Stéphane Key
- Radiation Oncology Department, University Hospital, Brest, France
| | - Olivier Pradier
- Radiation Oncology Department, University Hospital, Brest, France
| | - Marc Aubry
- CNRS, UMR 6290, IGDR, Université de Rennes 1, Rennes, France
| | - Mathieu Hatt
- LaTIM, INSERM, UMR 1101, Univ Brest, Brest, France
| | - Laurent Corcos
- INSERM, UMR 1078, Université de Brest, Génétique Génomique Fonctionnelle et Biotechnologies, Etablissement Français du Sang, Brest, France
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27
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Krarup MMK, Nygård L, Vogelius IR, Andersen FL, Cook G, Goh V, Fischer BM. Heterogeneity in tumours: Validating the use of radiomic features on 18F-FDG PET/CT scans of lung cancer patients as a prognostic tool. Radiother Oncol 2020; 144:72-78. [PMID: 31733491 DOI: 10.1016/j.radonc.2019.10.012] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2019] [Revised: 10/01/2019] [Accepted: 10/17/2019] [Indexed: 02/06/2023]
Abstract
AIM The aim was to validate promising radiomic features (RFs)1 on 18F-flourodeoxyglucose positron emission tomography/computed tomography-scans (18F-FDG PET/CT) of non-small cell lung cancer (NSCLC) patients undergoing definitive chemo-radiotherapy. METHODS 18F-FDG PET/CT scans performed for radiotherapy (RT) planning were retrieved. Auto-segmentation with visual adaption was used to define the primary tumour on PET images. Six pre-selected prognostic and reproducible PET texture -and shape-features were calculated using texture respectively shape analysis. The correlation between these RFs and metabolic active tumour volume (MTV)3, gross tumour volume (GTV)4 and maximum and mean of standardized uptake value (SUV)5 was tested with a Spearman's Rank test. The prognostic value of RFs was tested in a univariate cox regression analysis and a multivariate cox regression analysis with GTV, clinical stage and histology. P-value ≤ 0.05 were considered significant. RESULTS Image analysis was performed for 233 patients: 145 males and 88 females, mean age of 65.7 and clinical stage II-IV. Mean GTV was 129.87 cm3 (SD 130.30 cm3). Texture and shape-features correlated more strongly to MTV and GTV compared to SUV-measurements. Four RFs predicted PFS in the univariate analysis. No RFs predicted PFS in the multivariate analysis, whereas GTV and clinical stage predicted PFS (p = 0.001 and p = 0.008 respectively). CONCLUSION The pre-selected RFs were insignificant in predicting PFS in combination with GTV, clinical stage and histology. These results might be due to variations in technical parameters. However, it is relevant to question whether RFs are stable enough to provide clinically useful information.
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Affiliation(s)
- Marie Manon Krebs Krarup
- Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, Copenhagen University Hospital, Denmark.
| | - Lotte Nygård
- Department of Oncology, Rigshospitalet, Copenhagen University Hospital, Denmark.
| | - Ivan Richter Vogelius
- Department of Oncology, Rigshospitalet, Copenhagen University Hospital, Denmark; Faculty of Health and Medical Sciences, Copenhagen University, Denmark.
| | - Flemming Littrup Andersen
- Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, Copenhagen University Hospital, Denmark.
| | - Gary Cook
- PET Centre, School of Biomedical Engineering and Imaging Sciences, King's College London, St. Thomas' Hospital, United Kingdom.
| | - Vicky Goh
- PET Centre, School of Biomedical Engineering and Imaging Sciences, King's College London, St. Thomas' Hospital, United Kingdom.
| | - Barbara Malene Fischer
- Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, Copenhagen University Hospital, Denmark; PET Centre, School of Biomedical Engineering and Imaging Sciences, King's College London, St. Thomas' Hospital, United Kingdom.
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28
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Tello Galán MJ, García Vicente AM, Pérez Beteta J, Amo Salas M, Jiménez Londoño GA, Pena Pardo FJ, Soriano Castrejón ÁM, Pérez García VM. Global heterogeneity assessed with 18F-FDG PET/CT. Relation with biological variables and prognosis in locally advanced breast cancer. Rev Esp Med Nucl Imagen Mol 2019. [DOI: 10.1016/j.remnie.2019.03.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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29
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Tello Galán MJ, García Vicente AM, Pérez Beteta J, Amo Salas M, Jiménez Londoño GA, Pena Pardo FJ, Soriano Castrejón ÁM, Pérez García VM. Global heterogeneity assessed with 18F-FDG PET/CT. Relation with biological variables and prognosis in locally advanced breast cancer. Rev Esp Med Nucl Imagen Mol 2019; 38:290-297. [PMID: 31427247 DOI: 10.1016/j.remn.2019.02.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2018] [Revised: 02/07/2019] [Accepted: 02/26/2019] [Indexed: 02/07/2023]
Abstract
AIM To analyze the relationship between measurements of global heterogeneity, obtained from 18F-FDG PET/CT, with biological variables, and their predictive and prognostic role in patients with locally advanced breast cancer (LABC). MATERIAL AND METHODS 68 patients from a multicenter and prospective study, with LABC and a baseline 18F-FDG PET/CT were included. Immunohistochemical profile [estrogen receptors (ER) and progesterone receptors (PR), expression of the HER-2 oncogene, Ki-67 proliferation index and tumor histological grade], response to neoadjuvant chemotherapy (NC), overall survival (OS) and disease-free survival (DFS) were obtained as clinical variables. Three-dimensional segmentation of the lesions, providing SUV, volumetric [metabolic tumor volume (MTV) and total lesion glycolysis (TLG)] and global heterogeneity variables [coefficient of variation (COV) and SUVmean/SUVmax ratio], as well as sphericity was performed. The correlation between the results obtained with the immunohistochemical profile, the response to NC and survival was also analyzed. RESULTS Of the patients included, 62 received NC. Only 18 responded. 13 patients relapsed and 11 died during follow-up. ER negative tumors had a lower COV (p=0.018) as well as those with high Ki-67 (p=0.001) and high risk phenotype (p=0.033) compared to the rest. No PET variable showed association with the response to NC nor OS. There was an inverse relationship between sphericity with DFS (p=0.041), so, for every tenth that sphericity increases, the risk of recurrence decreases by 37%. CONCLUSIONS Breast tumors in our LABC dataset behaved as homogeneous and spherical lesions. Larger volumes were associated with a lower sphericity. Global heterogeneity variables and sphericity do not seem to have a predictive role in response to NC nor in OS. More spherical tumors with less variation in gray intensity between voxels showed a lower risk of recurrence.
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Affiliation(s)
- M J Tello Galán
- Servicio de Medicina Nuclear. Hospital General Universitario de Ciudad Real, España.
| | - A M García Vicente
- Servicio de Medicina Nuclear. Hospital General Universitario de Ciudad Real, España
| | - J Pérez Beteta
- Instituto de Matemática Aplicada a la Ciencia y la Ingeniería. Universidad de Castilla La Mancha, Ciudad Real, España
| | - M Amo Salas
- Departamento de Matemáticas. Universidad de Castilla La Mancha, Ciudad Real, España
| | - G A Jiménez Londoño
- Servicio de Medicina Nuclear. Hospital General Universitario de Ciudad Real, España
| | - F J Pena Pardo
- Servicio de Medicina Nuclear. Hospital General Universitario de Ciudad Real, España
| | | | - V M Pérez García
- Instituto de Matemática Aplicada a la Ciencia y la Ingeniería. Universidad de Castilla La Mancha, Ciudad Real, España
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30
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Fujima N, Shimizu Y, Yoshida D, Kano S, Mizumachi T, Homma A, Yasuda K, Onimaru R, Sakai O, Kudo K, Shirato H. Machine-Learning-Based Prediction of Treatment Outcomes Using MR Imaging-Derived Quantitative Tumor Information in Patients with Sinonasal Squamous Cell Carcinomas: A Preliminary Study. Cancers (Basel) 2019; 11:cancers11060800. [PMID: 31185611 PMCID: PMC6627127 DOI: 10.3390/cancers11060800] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2019] [Revised: 06/02/2019] [Accepted: 06/06/2019] [Indexed: 02/06/2023] Open
Abstract
The purpose of this study was to determine the predictive power for treatment outcome of a machine-learning algorithm combining magnetic resonance imaging (MRI)-derived data in patients with sinonasal squamous cell carcinomas (SCCs). Thirty-six primary lesions in 36 patients were evaluated. Quantitative morphological parameters and intratumoral characteristics from T2-weighted images, tumor perfusion parameters from arterial spin labeling (ASL) and tumor diffusion parameters of five diffusion models from multi-b-value diffusion-weighted imaging (DWI) were obtained. Machine learning by a non-linear support vector machine (SVM) was used to construct the best diagnostic algorithm for the prediction of local control and failure. The diagnostic accuracy was evaluated using a 9-fold cross-validation scheme, dividing patients into training and validation sets. Classification criteria for the division of local control and failure in nine training sets could be constructed with a mean sensitivity of 0.98, specificity of 0.91, positive predictive value (PPV) of 0.94, negative predictive value (NPV) of 0.97, and accuracy of 0.96. The nine validation data sets showed a mean sensitivity of 1.0, specificity of 0.82, PPV of 0.86, NPV of 1.0, and accuracy of 0.92. In conclusion, a machine-learning algorithm using various MR imaging-derived data can be helpful for the prediction of treatment outcomes in patients with sinonasal SCCs.
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Affiliation(s)
- Noriyuki Fujima
- Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo 060-8638, Hokkaido, Japan.
| | - Yukie Shimizu
- Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo 060-8638, Hokkaido, Japan.
| | - Daisuke Yoshida
- Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo 060-8638, Hokkaido, Japan.
| | - Satoshi Kano
- Department of Otolaryngology-Head and Neck Surgery, Hokkaido University Graduate School of Medicine, Sapporo 060-8638, Hokkaido, Japan.
| | - Takatsugu Mizumachi
- Department of Otolaryngology-Head and Neck Surgery, Hokkaido University Graduate School of Medicine, Sapporo 060-8638, Hokkaido, Japan.
| | - Akihiro Homma
- Department of Otolaryngology-Head and Neck Surgery, Hokkaido University Graduate School of Medicine, Sapporo 060-8638, Hokkaido, Japan.
| | - Koichi Yasuda
- Department of Radiation Medicine, Hokkaido University Graduate School of Medicine, Sapporo 060-8638, Hokkaido, Japan.
| | - Rikiya Onimaru
- Department of Radiation Medicine, Hokkaido University Graduate School of Medicine, Sapporo 060-8638, Hokkaido, Japan.
| | - Osamu Sakai
- Departments of Radiology, Otolaryngology-Head and Neck Surgery, and Radiation Oncology, Boston Medical Center, Boston University School of Medicine, Boston, MA 02118, USA.
| | - Kohsuke Kudo
- Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo 060-8638, Hokkaido, Japan.
| | - Hiroki Shirato
- Department of Radiation Medicine, Hokkaido University Graduate School of Medicine, Sapporo 060-8638, Hokkaido, Japan.
- The Global Station for Quantum Medical Science and Engineering, Global Institution for Collaborative Research and Education, Sapporo 060-0808, Hokkaido, Japan.
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Wetz C, Genseke P, Apostolova I, Furth C, Ghazzawi S, Rogasch JMM, Schatka I, Kreissl MC, Hofheinz F, Grosser OS, Amthauer H. The association of intra-therapeutic heterogeneity of somatostatin receptor expression with morphological treatment response in patients undergoing PRRT with [177Lu]-DOTATATE. PLoS One 2019; 14:e0216781. [PMID: 31091247 PMCID: PMC6519899 DOI: 10.1371/journal.pone.0216781] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2018] [Accepted: 04/29/2019] [Indexed: 12/11/2022] Open
Abstract
Aim Purpose of this study was to evaluate the association of the spatial heterogeneity (asphericity, ASP) in intra-therapeutic SPECT/ CT imaging of somatostatin receptor (SSR) positive metastatic gastroenteropancreatic neuroendocrine neoplasms (GEP-NEN) for morphological treatment response to peptide receptor radionuclide therapy (PRRT). Secondly, we correlated ASP derived form a pre-therapeutic OctreoScan (ASP[In]) and an intra-therapeutic [177Lu]-SPECT/CT (ASP[Lu]). Materials and methods Data from first therapy cycle [177Lu-DOTA0-Tyr3]octreotate ([177Lu]-DOTATATE)-PRRT was retrospectively analyzed in 33 patients (m = 20; w = 13; median age, 72 [46–88] years). The evaluation of response to PRRT was performed according to RECIST 1.1 in responding lesions [RL (SD, PR, CR), n = 104] and non-responding lesions [NRL (PD), n = 27]. The association of SSR tumor heterogeneity with morphological response was evaluated by Kruskal-Wallis test and receiver operating characteristic curve (ROC). The optimal threshold for separation (RL vs. NRL) was calculated using the Youden-index. Relationship between pre- and intra-therapeutic ASP was determined with Spearman’s rank correlation coefficient (ρ) and Bland-Altman plots. Results A total of 131 lesions (liver: n = 59, lymph nodes: n = 48, bone: n = 19, pancreas: n = 5) were analyzed. Lesions with higher ASP values showed a significantly poorer response to PRRT (PD, median: 11.3, IQR: 8.5–15.5; SD, median: 3.4, IQR: 2.1–4.5; PR, median 1.7, IQR: 0.9–2.8; CR, median: 0.5, IQR: 0.0–1.3); Kruskal-Wallis, p<0.001). ROC analyses revealed a significant separation between RL and NRL for ASP after 4 months (AUC 0.85, p<0.001) and after 12 months (AUC 0.94, p<0.001). The optimal threshold for ASP was >5.45% (sensitivity 96% and specificity 82%). The correlation coefficient of pre- and intra-therapeutic ASP revealed ρ = 0.72 (p <0.01). The mean absolute difference between ASP[In] and ASP[Lu] was -0.04 (95% Limits of Agreement, -6.1–6.0). Conclusion Pre- and intra-therapeutic ASP shows a strong correlation and might be an useful tool for therapy monitoring.
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Affiliation(s)
- Christoph Wetz
- Department of Radiology and Nuclear Medicine; University Hospital Magdeburg A.ö.R., Otto-von-Guericke University Magdeburg, Magdeburg, Germany
- Department of Nuclear Medicine, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Philipp Genseke
- Department of Radiology and Nuclear Medicine; University Hospital Magdeburg A.ö.R., Otto-von-Guericke University Magdeburg, Magdeburg, Germany
| | - Ivayla Apostolova
- Department of Nuclear Medicine, University Medical Center Hamburg UKE, Hamburg, Germany
| | - Christian Furth
- Department of Nuclear Medicine, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Sammy Ghazzawi
- Department of Radiology and Nuclear Medicine; University Hospital Magdeburg A.ö.R., Otto-von-Guericke University Magdeburg, Magdeburg, Germany
| | - Julian M. M. Rogasch
- Department of Nuclear Medicine, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Imke Schatka
- Department of Nuclear Medicine, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Michael C. Kreissl
- Department of Radiology and Nuclear Medicine; University Hospital Magdeburg A.ö.R., Otto-von-Guericke University Magdeburg, Magdeburg, Germany
| | - Frank Hofheinz
- Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical Cancer Research, PET Center, Dresden, Germany
| | - Oliver S. Grosser
- Department of Radiology and Nuclear Medicine; University Hospital Magdeburg A.ö.R., Otto-von-Guericke University Magdeburg, Magdeburg, Germany
| | - Holger Amthauer
- Department of Nuclear Medicine, Charité-Universitätsmedizin Berlin, Berlin, Germany
- * E-mail:
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Prognostic value of 18F-FDG PET/CT functional parameters in patients with head and neck cancer. Nucl Med Commun 2019; 40:361-369. [DOI: 10.1097/mnm.0000000000000974] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Finocchiaro D, Berenato S, Grassi E, Bertolini V, Castellani G, Lanconelli N, Versari A, Spezi E, Iori M, Fioroni F. Partial volume effect of SPECT images in PRRT with 177Lu labelled somatostatin analogues: A practical solution. Phys Med 2019; 57:153-159. [PMID: 30738519 DOI: 10.1016/j.ejmp.2018.12.029] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2018] [Revised: 11/26/2018] [Accepted: 12/20/2018] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND At present activity quantification is one of the most critical step in dosimetry calculation, and Partial Volume Effect (PVE) one of the most important source of error. In recent years models based upon phantoms that incorporate hot spheres have been used to establish recovery models. In this context the goal of this study was to point out the most critical issues related to PVE and to establish a model closer to a biological imaging environment. METHODS Two different phantoms, filled with a 177Lu solution, were used to obtain the PVE Recovery Coefficients (RCs): a phantom with spherical inserts and a phantom with organ-shaped inserts. Two additional phantoms with inserts of various geometrical shapes and an anthropomorphic phantom were acquired to compare the real activities to predicted values after PVE correction. RESULTS The RCs versus volume of the inserts produced two different curves, one for the spheres and one for the organs. After PVE correction, accuracy on activity quantification averaged over all inserts of three test phantoms passed from -26% to 1.3% (from 26% to 10% for absolute values). CONCLUSION RCs is a simple method for PVE correction easily applicable in clinical routine. The use of two different models for organs and lesions has permitted to closely mimic the situation in a living subject. A marked improvement in the quantification of activity was observed when PVE correction was adopted, even if further investigations should be performed for more accurate models of PVE corrections.
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Affiliation(s)
- Domenico Finocchiaro
- Azienda Unità Sanitaria Locale - IRCCS di Reggio Emilia, Medical Physics Unit, Reggio Emilia, Italy; Department of Physics, University of Bologna, Italy
| | | | - Elisa Grassi
- Azienda Unità Sanitaria Locale - IRCCS di Reggio Emilia, Medical Physics Unit, Reggio Emilia, Italy.
| | - Valentina Bertolini
- Azienda Unità Sanitaria Locale - IRCCS di Reggio Emilia, Medical Physics Unit, Reggio Emilia, Italy
| | | | | | - Annibale Versari
- Azienda Unità Sanitaria Locale - IRCCS di Reggio Emilia, Nuclear Medicine Unit, Reggio Emilia, Italy
| | - Emiliano Spezi
- School of Engineering, Cardiff University, Cardiff, UK; Department of Medical Physics, Velindre Cancer Centre, Cardiff, UK
| | - Mauro Iori
- Azienda Unità Sanitaria Locale - IRCCS di Reggio Emilia, Medical Physics Unit, Reggio Emilia, Italy
| | - Federica Fioroni
- Azienda Unità Sanitaria Locale - IRCCS di Reggio Emilia, Medical Physics Unit, Reggio Emilia, Italy
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Pretreatment tumor volume and tumor sphericity as prognostic factors in patients with oral cavity squamous cell carcinoma. J Craniomaxillofac Surg 2019; 47:510-515. [PMID: 30642733 DOI: 10.1016/j.jcms.2018.12.019] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2018] [Accepted: 12/27/2018] [Indexed: 01/17/2023] Open
Abstract
PURPOSE This study was designed as a retrospective observational study, focusing on the correlation between the preoperative CT-scan tumor volume, tumor sphericity, and the disease-related prognosis. METHODS A total of 30 consecutive patients, affected by primary oral cancer, were retrospectively identified from our oral cancer database. The preoperative images (DICOM data) for the study population were uploaded into a modular software package designed to convert patients' medical images into 3D digital models. Multislice interpolation and threshold segmentation tools were used to segment the tumor mass. This was then converted into a 3D mesh and exported in STL format, in order to calculate the corresponding volume. We applied the concept of sphericity - a measurement of how closely the shape of an object approaches that of a mathematically perfect sphere - to the segmented tumor mass. RESULTS Mean tumor volume was larger in patients with tumor recurrence and/or who had died than in patients who were disease free/alive. Tumor sphericity was influential on clinical outcomes. It appeared to be lower in patients who had tumor recurrence and/or who had died (0.54 ± 0.09 and 0.53 ± 0.05) than in patients who were disease free/alive (0.65 ± 0.07). This difference was statistically significant (p < 0.05). Cumulative recurrence-free survival was 86.2% for patients with a tumor volume lower than the cut-off value. Otherwise, it was 0% for those with a tumor volume higher than the cut-off value (p < 0.01; log rank test). Cumulative recurrence-free survival was 86.3% for patients with a higher sphericity index, compared with 13.6% for those with a lower sphericity index. CONCLUSION The prognostic model, based on a tridimensional, CT-based characterization of the tumor size, which includes both tumor volume and tumor sphericity, uses readily available information and could be considered when formulating prognoses for patients with oral cancer.
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Fujima N, Hirata K, Shiga T, Li R, Yasuda K, Onimaru R, Tsuchiya K, Kano S, Mizumachi T, Homma A, Kudo K, Shirato H. Integrating quantitative morphological and intratumoural textural characteristics in FDG-PET for the prediction of prognosis in pharynx squamous cell carcinoma patients. Clin Radiol 2018; 73:1059.e1-1059.e8. [PMID: 30245069 DOI: 10.1016/j.crad.2018.08.011] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2018] [Accepted: 08/24/2018] [Indexed: 12/15/2022]
Abstract
AIM To assess potential prognostic factors in pharynx squamous cell carcinoma (SCC) patients by quantitative morphological and intratumoural characteristics obtained by 2-[18F]-fluoro-2-deoxy-d-glucose positron-emission tomography/computed tomography (FDG-PET/CT). MATERIALS AND METHODS The cases of 54 patients with pharynx SCC who underwent chemoradiation therapy were analysed retrospectively. Using their FDG-PET data, the quantitative morphological and intratumoural characteristics of 14 parameters were calculated. The progression-free survival (PFS) and overall survival (OS) information was obtained from patient medical records. Univariate and multivariate analyses were performed to assess the 14 quantitative parameters as well as the T-stage, N-stage, and tumour location data for their relation to PFS and OS. When an independent predictor was suggested in the multivariate analysis, the parameter was further assessed using the Kaplan-Meier method. RESULTS In the assessment of PFS, the univariate and multivariate analyses indicated the following as independent predictors: the texture parameter of homogeneity and the morphological parameter of sphericity. In the Kaplan-Meier analysis, the PFS rate was significantly improved in the patients who had both a higher value of homogeneity (p=0.01) and a higher value of sphericity (p=0.002). With the combined use of homogeneity and sphericity, the patients with different PFS rates could be divided more clearly. CONCLUSION The quantitative parameters of homogeneity and sphericity obtained by FDG-PET can be useful for the prediction of the PFS of pharynx SCC patients, especially when used in combination.
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Affiliation(s)
- N Fujima
- Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, N14 W5, Kita-Ku, Sapporo 0608638, Japan.
| | - K Hirata
- Department of Nuclear Medicine, Hokkaido University Graduate School of Medicine, N15 W7, Kita-Ku, Sapporo 0608638, Japan
| | - T Shiga
- Department of Nuclear Medicine, Hokkaido University Graduate School of Medicine, N15 W7, Kita-Ku, Sapporo 0608638, Japan
| | - R Li
- Department of Radiation Oncology, Stanford University, 875 Blake Wilbur Drive, Stanford, CA 94305-5847, USA; The Global Station for Quantum Medical Science and Engineering, Global Institution for Collaborative Research and Education, N15 W8, Kita-Ku, Sapporo 0608638, Japan
| | - K Yasuda
- The Global Station for Quantum Medical Science and Engineering, Global Institution for Collaborative Research and Education, N15 W8, Kita-Ku, Sapporo 0608638, Japan; Department of Radiation Medicine, Hokkaido University Graduate School of Medicine, N15 W7, Kita-Ku, Sapporo 0608638, Japan
| | - R Onimaru
- Department of Radiation Medicine, Hokkaido University Graduate School of Medicine, N15 W7, Kita-Ku, Sapporo 0608638, Japan
| | - K Tsuchiya
- Department of Radiation Oncology, Otaru General Hospital, Wakamatsu1-1-1, Otaru 0478550, Japan
| | - S Kano
- Department of Otolaryngology-Head and Neck Surgery, Hokkaido University Graduate School of Medicine, N15 W7, Kita-Ku, Sapporo 0608638, Japan
| | - T Mizumachi
- Department of Otolaryngology-Head and Neck Surgery, Hokkaido University Graduate School of Medicine, N15 W7, Kita-Ku, Sapporo 0608638, Japan
| | - A Homma
- Department of Otolaryngology-Head and Neck Surgery, Hokkaido University Graduate School of Medicine, N15 W7, Kita-Ku, Sapporo 0608638, Japan
| | - K Kudo
- Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, N14 W5, Kita-Ku, Sapporo 0608638, Japan
| | - H Shirato
- The Global Station for Quantum Medical Science and Engineering, Global Institution for Collaborative Research and Education, N15 W8, Kita-Ku, Sapporo 0608638, Japan; Department of Radiation Medicine, Hokkaido University Graduate School of Medicine, N15 W7, Kita-Ku, Sapporo 0608638, Japan
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Fujima N, Hirata K, Shiga T, Yasuda K, Onimaru R, Tsuchiya K, Kano S, Mizumachi T, Homma A, Kudo K, Shirato H. Semi-quantitative analysis of pre-treatment morphological and intratumoral characteristics using 18F-fluorodeoxyglucose positron-emission tomography as predictors of treatment outcome in nasal and paranasal squamous cell carcinoma. Quant Imaging Med Surg 2018; 8:788-795. [PMID: 30306059 DOI: 10.21037/qims.2018.09.09] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Background To investigate the utility of quantitative morphological and intratumoral characteristics obtained by 18F-fluorodeoxyglucose positron-emission tomography/computed tomography (FDG-PET/CT) for the prediction of treatment outcome in patients with nasal or paranasal cavity squamous cell carcinoma (SCC). Methods Twenty-four patients with nasal or paranasal cavity SCC who received curative non-surgical therapy (a combination of super-selective arterial cisplatin infusion and radiotherapy) were retrospectively analyzed. From pre-treatment FDG-PET data, a total of 13 parameters of quantitative morphological characteristics (tumor volume, surface area and sphericity), intratumoral characteristics (the maximum and mean standard uptake value, three intratumoral histogram and four textural parameters) and total lesion glycolysis (TLG) were respectively calculated. Information regarding the treatment outcome was determined from the histological diagnosis or clinical follow-up. Each of the 13 quantitative parameters as well as T- and N-stage was assessed for its relation to treatment outcome of local control or failure. Results In univariate analysis, significant differences in surface area and sphericity between the local control and failure groups were observed. The receiver operating characteristic (ROC) curve analysis showed that sphericity had the highest accuracy of 0.88. In the multivariate analysis, sphericity was revealed as an independent predictor of the local control or failure. Conclusions The quantitative parameters of sphericity are useful to predict the treatment outcome in patients with nasal or paranasal SCC.
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Affiliation(s)
- Noriyuki Fujima
- Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan
| | - Kenji Hirata
- Department of Nuclear Medicine, Hokkaido University Graduate School of Medicine, Sapporo, Japan
| | - Tohru Shiga
- Department of Nuclear Medicine, Hokkaido University Graduate School of Medicine, Sapporo, Japan
| | - Koichi Yasuda
- Department of Radiation Medicine, Hokkaido University Graduate School of Medicine, Sapporo, Japan.,The Global Station for Quantum Medical Science and Engineering, Global Institution for Collaborative Research and Education, Sapporo, Japan
| | - Rikiya Onimaru
- Department of Radiation Medicine, Hokkaido University Graduate School of Medicine, Sapporo, Japan
| | - Kazuhiko Tsuchiya
- Department of Radiation Oncology, Otaru General Hospital, Otaru, Japan
| | - Satoshi Kano
- Department of Otolaryngology-Head and Neck Surgery, Hokkaido University Graduate School of Medicine, Sapporo, Japan
| | - Takatsugu Mizumachi
- Department of Otolaryngology-Head and Neck Surgery, Hokkaido University Graduate School of Medicine, Sapporo, Japan
| | - Akihiro Homma
- Department of Otolaryngology-Head and Neck Surgery, Hokkaido University Graduate School of Medicine, Sapporo, Japan
| | - Kohsuke Kudo
- Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan
| | - Hiroki Shirato
- Department of Radiation Medicine, Hokkaido University Graduate School of Medicine, Sapporo, Japan.,The Global Station for Quantum Medical Science and Engineering, Global Institution for Collaborative Research and Education, Sapporo, Japan
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PET-based prognostic survival model after radiotherapy for head and neck cancer. Eur J Nucl Med Mol Imaging 2018; 46:638-649. [DOI: 10.1007/s00259-018-4134-9] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2018] [Accepted: 08/13/2018] [Indexed: 12/23/2022]
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Lange C, Suppa P, Mäurer A, Ritter K, Pietrzyk U, Steinhagen-Thiessen E, Fiebach JB, Spies L, Buchert R. Mental speed is associated with the shape irregularity of white matter MRI hyperintensity load. Brain Imaging Behav 2018; 11:1720-1730. [PMID: 27796731 DOI: 10.1007/s11682-016-9647-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
Brain MRI white matter hyperintensities (WMHs) are common in elderly subjects. Their impact on cognition, however, appears highly variable. Complementing conventional scoring of WMH load (volume and location) by quantitative characterization of the shape irregularity of WMHs might improve the understanding of the relationship between WMH load and cognitive performance. Here we propose the "confluency sum score" (COSU) as a marker of the total shape irregularity of WMHs in the brain. The study included two independent patient samples: 87 cognitively impaired geriatric inpatients from a prospective neuroimaging study (iDSS) and 198 subjects from the National Alzheimer's Coordinating Center (NACC) database (132 with, 66 w/o cognitive impairment). After automatic segmentation and clustering of the WMHs on FLAIR (LST toolbox, SPM8), the confluency of the i-th contiguous WMH cluster was computed as confluencyi = [1/(36π)∙surfacei3/volumei2]1/3-1. The COSU was obtained by summing the confluency over all WMH clusters. COSU was tested for correlation with CERAD-plus subscores. Correlation analysis was restricted to subjects with at least moderate WMH load (≥ 13.5 ml; iDSS / NACC: n = 52 / 80). In the iDSS sample, among the 12 CERAD-plus subtests the trail making test A (TMT-A) was most strongly correlated with the COSU (Spearman rho = -0.345, p = 0.027). TMT-A performance was not associated with total WMH volume (rho = 0.147, p = 0.358). This finding was confirmed in the NACC sample (rho = -0.261, p = 0.023 versus rho = -0.040, p = 0.732). Cognitive performance in specific domains including mental speed and fluid abilities seems to be more strongly associated with the shape irregularity of white matter MRI hyperintensities than with their volume.
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Affiliation(s)
- Catharina Lange
- Department of Nuclear Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany.,School of Mathematics and Natural Science, University of Wuppertal, Wuppertal, Germany
| | - Per Suppa
- Department of Nuclear Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany.,jung diagnostics GmbH, Hamburg, Germany
| | - Anja Mäurer
- Evangelisches Geriatriezentrum Berlin, Berlin, Germany
| | - Kerstin Ritter
- Berlin Center for Advanced Neuroimaging, Bernstein Center for Computational Neuroscience, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Uwe Pietrzyk
- School of Mathematics and Natural Science, University of Wuppertal, Wuppertal, Germany.,Institute of Neuroscience and Medicine, Forschungszentrum Jülich, Jülich, Germany
| | | | - Jochen B Fiebach
- Center for Stroke Research Berlin, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | | | - Ralph Buchert
- Department of Nuclear Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany.
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Rogasch JMM, Hundsdoerfer P, Hofheinz F, Wedel F, Schatka I, Amthauer H, Furth C. Pretherapeutic FDG-PET total metabolic tumor volume predicts response to induction therapy in pediatric Hodgkin's lymphoma. BMC Cancer 2018; 18:521. [PMID: 29724189 PMCID: PMC5934894 DOI: 10.1186/s12885-018-4432-4] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2018] [Accepted: 04/25/2018] [Indexed: 11/17/2022] Open
Abstract
Background Standardized treatment in pediatric patients with Hodgkin’s lymphoma (HL) follows risk stratification by tumor stage, erythrocyte sedimentation rate and tumor bulk. We aimed to identify quantitative parameters from pretherapeutic FDG-PET to assist prediction of response to induction chemotherapy. Methods Retrospective analysis in 50 children with HL (f:18; m:32; median age, 14.8 [4–18] a) consecutively treated according to EuroNet-PHL-C1 (n = 42) or -C2 treatment protocol (n = 8). Total metabolic tumor volume (MTV) in pretherapeutic FDG-PET was defined using a semi-automated, background-adapted threshold. Metabolic (SUVmax, SUVmean, SUVpeak, total lesion glycolysis [MTV*SUVmean]) and heterogeneity parameters (asphericity [ASP], entropy, contrast, local homogeneity, energy, and cumulative SUV-volume histograms) were derived. Early response assessment (ERA) was performed after 2 cycles of induction chemotherapy according to treatment protocol and verified by reference rating. Prediction of inadequate response (IR) in ERA was based on ROC analysis separated by stage I/II (1 and 26 patients) and stage III/IV disease (7 and 16 patients) or treatment group/level (TG/TL) 1 to 3. Results IR was seen in 28/50 patients (TG/TL 1, 6/12 patients; TG/TL 2, 10/17; TG/TL 3, 12/21). Among all PET parameters, MTV best predicted IR; ASP was the best heterogeneity parameter. AUC of MTV was 0.84 (95%-confidence interval, 0.69–0.99) in stage I/II and 0.86 (0.7–1.0) in stage III/IV. In patients of TG/TL 1, AUC of MTV was 0.92 (0.74–1.0); in TG/TL 2 0.71 (0.44–0.99), and in TG/TL 3 0.85 (0.69–1.0). Patients with high vs. low MTV had IR in 86 vs. 0% in TG/TL 1, 80 vs. 29% in TG/TL 2, and 90 vs. 27% in TG/TL 3 (cut-off, > 80 ml, > 160 ml, > 410 ml). Conclusions In this explorative study, high total MTV best predicted inadequate response to induction therapy in pediatric HL of all pretherapeutic FDG-PET parameters – in both low and high stages as well as the 3 different TG/TL. Trial registration Ethics committee number: EA2/151/16 (retrospectively registered). Electronic supplementary material The online version of this article (10.1186/s12885-018-4432-4) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Julian M M Rogasch
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Nuclear Medicine, Augustenburger Platz 1, D-13353, Berlin, Germany.
| | - Patrick Hundsdoerfer
- Berlin Institute of Health, Department of Pediatric Oncology/Hematology, Berlin, Germany.,Berlin Institute of Health (BIH), Anna-Louisa-Karsch-Str. 2, Berlin, Germany
| | - Frank Hofheinz
- PET Center, Helmholtz Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany
| | - Florian Wedel
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Nuclear Medicine, Augustenburger Platz 1, D-13353, Berlin, Germany
| | - Imke Schatka
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Nuclear Medicine, Augustenburger Platz 1, D-13353, Berlin, Germany
| | - Holger Amthauer
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Nuclear Medicine, Augustenburger Platz 1, D-13353, Berlin, Germany
| | - Christian Furth
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Nuclear Medicine, Augustenburger Platz 1, D-13353, Berlin, Germany
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40
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Carles M, Bach T, Torres-Espallardo I, Baltas D, Nestle U, Martí-Bonmatí L. Significance of the impact of motion compensation on the variability of PET image features. Phys Med Biol 2018; 63:065013. [PMID: 29469054 DOI: 10.1088/1361-6560/aab180] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
In lung cancer, quantification by positron emission tomography/computed tomography (PET/CT) imaging presents challenges due to respiratory movement. Our primary aim was to study the impact of motion compensation implied by retrospectively gated (4D)-PET/CT on the variability of PET quantitative parameters. Its significance was evaluated by comparison with the variability due to (i) the voxel size in image reconstruction and (ii) the voxel size in image post-resampling. The method employed for feature extraction was chosen based on the analysis of (i) the effect of discretization of the standardized uptake value (SUV) on complementarity between texture features (TF) and conventional indices, (ii) the impact of the segmentation method on the variability of image features, and (iii) the variability of image features across the time-frame of 4D-PET. Thirty-one PET-features were involved. Three SUV discretization methods were applied: a constant width (SUV resolution) of the resampling bin (method RW), a constant number of bins (method RN) and RN on the image obtained after histogram equalization (method EqRN). The segmentation approaches evaluated were 40[Formula: see text] of SUVmax and the contrast oriented algorithm (COA). Parameters derived from 4D-PET images were compared with values derived from the PET image obtained for (i) the static protocol used in our clinical routine (3D) and (ii) the 3D image post-resampled to the voxel size of the 4D image and PET image derived after modifying the reconstruction of the 3D image to comprise the voxel size of the 4D image. Results showed that TF complementarity with conventional indices was sensitive to the SUV discretization method. In the comparison of COA and 40[Formula: see text] contours, despite the values not being interchangeable, all image features showed strong linear correlations (r > 0.91, [Formula: see text]). Across the time-frames of 4D-PET, all image features followed a normal distribution in most patients. For our patient cohort, the compensation of tumor motion did not have a significant impact on the quantitative PET parameters. The variability of PET parameters due to voxel size in image reconstruction was more significant than variability due to voxel size in image post-resampling. In conclusion, most of the parameters (apart from the contrast of neighborhood matrix) were robust to the motion compensation implied by 4D-PET/CT. The impact on parameter variability due to the voxel size in image reconstruction and in image post-resampling could not be assumed to be equivalent.
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Affiliation(s)
- M Carles
- Division of Medical Physics, Department of Radiation Oncology, Medical Center, Faculty of Medicine, University of Freiburg, German Cancer Consortium (DKTK) Partner Site Freiburg, German Cancer Research Center (DKFZ), Heidelberg, Germany. Clinical Area of Medical Imaging, Hospital Universitario y Politécnico La Fe, Valencia, Spain. Author to whom any correspondence should be addressed
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Vogelius IR, Bentzen SM. Dose Response and Fractionation Sensitivity of Prostate Cancer After External Beam Radiation Therapy: A Meta-analysis of Randomized Trials. Int J Radiat Oncol Biol Phys 2018; 100:858-865. [DOI: 10.1016/j.ijrobp.2017.12.011] [Citation(s) in RCA: 47] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2017] [Revised: 11/28/2017] [Accepted: 12/06/2017] [Indexed: 10/18/2022]
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Predictive Value of Asphericity in Pretherapeutic [ 111In]DTPA-Octreotide SPECT/CT for Response to Peptide Receptor Radionuclide Therapy with [ 177Lu]DOTATATE. Mol Imaging Biol 2018; 19:437-445. [PMID: 27743210 DOI: 10.1007/s11307-016-1018-x] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
PURPOSE The purpose of this study was to assess the value of the spatial heterogeneity of somatostatin receptor (SSR) volume, quantified as asphericity (ASP), and to predict response to peptide receptor radionuclide therapy (PRRT) in patients with metastatic gastroenteropancreatic neuroendocrine neoplasms (GEP-NEN). PROCEDURES From June 2011 to May 2013, patients suffering from GEP-NEN who underwent pretherapeutic [111In-DTPA0]octreotide scintigraphy (Octreoscan®) prior to [177Lu-DOTA0-Tyr3]octreotate ([177Lu]DOTATATE)-PRRT were enrolled in this retrospective evaluation. SSR expression in 20 NEN patients was qualitatively and quantitatively assessed using the Krenning score, the metastasis to liver uptake ratio (M/L ratio), and ASP at baseline. Response to PRRT was evaluated based on lesions, which were classified as responding lesions (RL) and non-responding lesions (NRL) after 4- and 12-month follow-ups. The values of the Krenning score, M/L ratio, and ASP for response prediction were compared by using the Mann-Whitney U test, Kruskal-Wallis test, and receiver operating characteristic (ROC) curves. RESULTS Seventy-seven metastases (liver, n = 40; lymph node, n = 24; bone, n = 11; pancreas, n = 2) showed SSR expression. A higher ASP level was significantly associated with poorer response at both time points. ROC analyses revealed the highest area under the curve (AUC) for discrimination between RL and NRL for ASP after 4 months (AUC 0.97; p = 0.019) and after 12 months (AUC 0.96; p < 0.001), followed by the Krenning score (AUC 0.74; p = 0.082 and AUC 0.85; p < 0.001, respectively) and M/L ratio (AUC 0.77; p = 0.107 and AUC 0.82; p < 0.001). The optimal cutoff value for ASP was 5.12 % (sensitivity, 90 %; specificity, 93 %). CONCLUSION Asphericity of SSR-expressing lesions in pretherapeutic single-photon emission computed tomography with integrated computed tomography (SPECT/CT) is a promising parameter for predicting response to PRRT in gastroenteropancreatic neuroendocrine neoplasms.
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Cheng NM, Fang YHD, Tsan DL, Lee LY, Chang JTC, Wang HM, Ng SH, Liao CT, Yang LY, Yen TC. Heterogeneity and irregularity of pretreatment 18F-fluorodeoxyglucose positron emission tomography improved prognostic stratification of p16-negative high-risk squamous cell carcinoma of the oropharynx. Oral Oncol 2018; 78:156-162. [PMID: 29496044 DOI: 10.1016/j.oraloncology.2018.01.030] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2017] [Revised: 12/27/2017] [Accepted: 01/30/2018] [Indexed: 12/18/2022]
Abstract
OBJECTIVES Human papillomavirus-negative oropharyngeal squamous cell carcinoma (OPSCC) has unfavorable survival outcomes. Two outcomes have been identified based on smoking history and tumor stage. We investigate the prognostic role of pre-treatment positron emission tomography (PET) in high-risk OPSCC. MATERIALS AND METHODS We enrolled 147 M0 OPSCC patients with p16-negative staining and a history of heavy smoking (>10 pack-years) or T4 disease. All patients completed primary chemoradiotherapy, and 42% maximum standard uptake values (SUVmax) were used as the threshold for primary tumor. Patients were classified into training and validation cohorts with a ratio of 1:1.5 according to the PET date. Heterogeneity and irregularity indices were obtained. PET parameters with significant impact on progression-free survival (PFS) in receiver operating characteristic curves and univariate Cox models were identified and included in recursive partitioning analysis (RPA) for constructing a prognostic model. The RPA-based prognostic model was further tested in the validation cohort using multivariate Cox models. RESULTS Fifty-eight and 89 patients were in the training and validation groups, respectively. Heterogeneity parameter, SUV-entropy (derived from histogram analysis), and irregularity index, and asphericity were significantly associated with PFS. The RPA model revealed that patients with both high SUV-entropy and high asphericity experienced the worst PFS. Results were confirmed in the validation group. The overall concordance index for PFS of the model was 0.75, which was higher than the clinical stages, performance status, SUVmax, and metabolic tumor volume of PET. CONCLUSIONS PET prognostic model provided useful prediction of PFS for patients with high-risk OPSCC.
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Affiliation(s)
- Nai-Ming Cheng
- Nuclear Medicine and Molecular Imaging Centre, Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Taoyuan City, Taiwan; Nuclear Medicine, Chang Gung Memorial Hospital, Keelung, Taiwan
| | - Yu-Hua Dean Fang
- Biomedical Engineering, National Cheng Kung University, Tainan City, Taiwan
| | - Din-Li Tsan
- Radiation Oncology, Chang Gung Memorial Hospital, Keelung, Taiwan
| | - Li-Yu Lee
- Pathology, Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Taoyuan City, Taiwan
| | - Joseph Tung-Chieh Chang
- Radiation Oncology, Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Taoyuan City, Taiwan
| | - Hung-Ming Wang
- Hematology/Oncology, Internal Medicine, Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Taoyuan City, Taiwan
| | - Shu-Hang Ng
- Diagnostic Radiology, Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Taoyuan City, Taiwan
| | - Chun-Ta Liao
- Otolaryngology, Head & Neck Surgery, Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Taoyuan City, Taiwan
| | - Lan-Yan Yang
- Biostatistics Unit, Clinical Trial Centre, Chang Gung Memorial Hospital, Taoyuan City, Taiwan
| | - Tzu-Chen Yen
- Nuclear Medicine and Molecular Imaging Centre, Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Taoyuan City, Taiwan.
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Majdoub M, Hoeben BAW, Troost EGC, Oyen WJG, Kaanders JHAM, Cheze Le Rest C, Visser EP, Visvikis D, Hatt M. Prognostic Value of Head and Neck Tumor Proliferative Sphericity From 3’-Deoxy-3’-[18F] Fluorothymidine Positron Emission Tomography. IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES 2018. [DOI: 10.1109/trpms.2017.2777890] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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Tumour functional sphericity from PET images: prognostic value in NSCLC and impact of delineation method. Eur J Nucl Med Mol Imaging 2017; 45:630-641. [PMID: 29177871 DOI: 10.1007/s00259-017-3865-3] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2017] [Accepted: 10/19/2017] [Indexed: 12/13/2022]
Abstract
PURPOSE Sphericity has been proposed as a parameter for characterizing PET tumour volumes, with complementary prognostic value with respect to SUV and volume in both head and neck cancer and lung cancer. The objective of the present study was to investigate its dependency on tumour delineation and the resulting impact on its prognostic value. METHODS Five segmentation methods were considered: two thresholds (40% and 50% of SUVmax), ant colony optimization, fuzzy locally adaptive Bayesian (FLAB), and gradient-aided region-based active contour. The accuracy of each method in extracting sphericity was evaluated using a dataset of 176 simulated, phantom and clinical PET images of tumours with associated ground truth. The prognostic value of sphericity and its complementary value with respect to volume for each segmentation method was evaluated in a cohort of 87 patients with stage II/III lung cancer. RESULTS Volume and associated sphericity values were dependent on the segmentation method. The correlation between segmentation accuracy and sphericity error was moderate (|ρ| from 0.24 to 0.57). The accuracy in measuring sphericity was not dependent on volume (|ρ| < 0.4). In the patients with lung cancer, sphericity had prognostic value, although lower than that of volume, except for that derived using FLAB for which when combined with volume showed a small improvement over volume alone (hazard ratio 2.67, compared with 2.5). Substantial differences in patient prognosis stratification were observed depending on the segmentation method used. CONCLUSION Tumour functional sphericity was found to be dependent on the segmentation method, although the accuracy in retrieving the true sphericity was not dependent on tumour volume. In addition, even accurate segmentation can lead to an inaccurate sphericity value, and vice versa. Sphericity had similar or lower prognostic value than volume alone in the patients with lung cancer, except when determined using the FLAB method for which there was a small improvement in stratification when the parameters were combined.
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Jung JH, Son SH, Kim DH, Lee J, Jeong SY, Lee SW, Park HY, Lee J, Ahn BC. CONSORT-Independent prognostic value of asphericity of pretherapeutic F-18 FDG uptake by primary tumors in patients with breast cancer. Medicine (Baltimore) 2017; 96:e8438. [PMID: 29145250 PMCID: PMC5704795 DOI: 10.1097/md.0000000000008438] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND The aim of this study was to evaluate the prognostic implication of asphericity (ASP); spatial irregularity; of pretherapeutic F 2-deoxy-2-fluoro-D-glucose (F FDG) tumor uptake in patients with invasive ductal carcinoma (IDC) of the breast. METHODS One hundred thirty-one female IDC patients (mean age = 48.1 ± 10.4 years), with pathological tumor size greater than 2 cm were retrospectively evaluated using F FDG positron emission tomography/computed tomography (PET/CT). ASP of F FDG distribution was calculated on the basis of the deviation of the tumor shape from spherical symmetry. Progression-free survival (PFS) was predicted on the basis of the univariate and multivariate analyses of the measured clinicopathologic factors and metabolic PET parameters [maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG)]. RESULTS The PFS rate among the 131 patients was 90.1%. The mean follow-up time was 50 months for the entire study cohort and 26 months for the patients with recurrent disease. It is evident from the univariate analysis that N stage, hormonal receptor (Estrogen, ER/Progesterone, PR) status, MTV (≤4.2 mL), and ASP (≤15.1%) affected the PFS. Hazard ratios (HRs) estimated from the multivariate Cox regression analysis show that N stage (HR = 17.6), ASP (HR = 11.9), and hormonal receptor status (HR = 6.9) were independent prognostic factors in predicting PFS. In the subgroup of patients with lymph node metastasis, ASP (HR = 10.9) and hormonal receptor status (HR = 9.1) were independent prognostic factors for PFS. CONCLUSION ASP of F FDG uptake is an independent predictor of outcome in IDC patients, and can be used for prognostic stratification.
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Affiliation(s)
| | | | | | - Jeeyeon Lee
- Department of Surgery, Kyungpook National University School of Medicine and Hospital, Daegu, Republic of Korea
| | | | | | - Ho Yong Park
- Department of Surgery, Kyungpook National University School of Medicine and Hospital, Daegu, Republic of Korea
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Meißner S, Janssen JC, Prasad V, Brenner W, Diederichs G, Hamm B, Hofheinz F, Makowski MR. Potential of asphericity as a novel diagnostic parameter in the evaluation of patients with 68Ga-PSMA-HBED-CC PET-positive prostate cancer lesions. EJNMMI Res 2017; 7:85. [PMID: 29058157 PMCID: PMC5651532 DOI: 10.1186/s13550-017-0333-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2017] [Accepted: 10/06/2017] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND The aim of this study was to evaluate the diagnostic value of the asphericity (ASP) as a novel quantitative parameter, reflecting the spatial heterogeneity of tracer uptake, in the staging process of patients with 68Ga-PSMA-HBED-CC positron emission tomography (PET)-positive prostate cancer (PC). In this study, 37 patients (median age 72 years, range 52-82 years) with newly diagnosed PC, who received a 68Ga-PSMA-HBED-CC PET fused with computed tomography (68Ga-PSMA-PET/CT), a magnetic resonance imaging (MRI) of the prostate, and a core needle biopsy (within 74.2 ± 80.2 days) with an available Gleason score (GSc) were extracted from the local database. The ASP and the viable tumor volume (VTV) was calculated using the rover software (ABX GmbH, Radeberg, Germany), a segmentation tool for automated tumor volume delineation. Additionally, parameters including total lesion binding rate (TLB), maximum, mean and peak standardized uptake value (SUVmax/mean/peak), prostate-specific antigen (PSA), D'Amico classification, and prostate imaging reporting and data system (PI-RADS) were analyzed. RESULTS The ASP mean differed significantly (p ≤ 0.05) between the different GSc groups: GSc 6-7: 11.9 ± 4.8%, GSc 8: 25.5 ± 4.8%, GSc 9-10: 33.3 ± 6.8%. A significant correlation between ASP and GSc (rho = 0.88; CI 0.78-0.94; p < 0.05) was measured. The ASP enabled an independent (p > 0.05) prediction of the GSc. A moderate correlation was measured between ASP and the D'Amico classification (rho = 0.6; CI 0.32-0.78; p < 0.05). The VTV showed a moderate correlation with the SUVmax (rho = 0.58; CI 0.32-0.76; p < 0.05) and the GSc (rho = 0.51; CI 0.23-0.72; p < 0.05). CONCLUSION The asphericity in 68Ga-PSMA-PET could represent a promising novel quantitative parameter for an improved non-invasive tumor staging of patients with PC.
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Affiliation(s)
- Sebastian Meißner
- Department of Radiology, Charité Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany.
| | - Jan-Carlo Janssen
- Department of Radiology, Charité Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany
| | - Vikas Prasad
- Department of Nuclear Medicine, Charité, Charitéplatz 1, 10117, Berlin, Germany
| | - Winfried Brenner
- Department of Nuclear Medicine, Charité, Charitéplatz 1, 10117, Berlin, Germany
| | - Gerd Diederichs
- Department of Radiology, Charité Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany
| | - Bernd Hamm
- Department of Radiology, Charité Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany
| | - Frank Hofheinz
- Helmholtz Zentrum Dresden-Rossendorf, Bautzner Landstraße 400, 01328, Dresden, Germany
| | - Marcus R Makowski
- Department of Radiology, Charité Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany
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Rogasch JMM, Hundsdoerfer P, Furth C, Wedel F, Hofheinz F, Krüger PC, Lode H, Brenner W, Eggert A, Amthauer H, Schatka I. Individualized risk assessment in neuroblastoma: does the tumoral metabolic activity on 123I-MIBG SPECT predict the outcome? Eur J Nucl Med Mol Imaging 2017; 44:2203-2212. [PMID: 28808732 DOI: 10.1007/s00259-017-3786-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2017] [Accepted: 07/19/2017] [Indexed: 01/26/2023]
Abstract
PURPOSE Risk-adapted treatment in children with neuroblastoma (NB) is based on clinical and genetic factors. This study evaluated the metabolic tumour volume (MTV) and its asphericity (ASP) in pretherapeutic 123I-MIBG SPECT for individualized image-based prediction of outcome. METHODS This retrospective study included 23 children (11 girls, 12 boys; median age 1.8 years, range 0.3-6.8 years) with newly diagnosed NB consecutively examined with pretherapeutic 123I-MIBG SPECT. Primary tumour MTV and ASP were defined using semiautomatic thresholds. Cox regression analysis, receiver operating characteristic analysis (cut-off determination) and Kaplan-Meier analysis with the log-rank test for event-free survival (EFS) were performed for ASP, MTV, laboratory parameters (including urinary homovanillic acid-to-creatinine ratio, HVA/C), and clinical (age, stage) and genetic factors. Predictive accuracy of the optimal multifactorial model was determined in terms of Harrell's C and likelihood ratio χ 2. RESULTS Median follow-up was 36 months (range 7-107 months; eight patients showed disease progression/relapse, four patients died). The only significant predictors of EFS in the univariate Cox regression analysis were ASP (p = 0.029; hazard ratio, HR, 1.032 for a one unit increase), MTV (p = 0.038; HR 1.012) and MYCN amplification status (p = 0.047; HR 4.67). The mean EFS in patients with high ASP (>32.0%) and low ASP were 21 and 88 months, respectively (p = 0.013), and in those with high MTV (>46.7 ml) and low MTV were 22 and 87 months, respectively (p = 0.023). A combined risk model of either high ASP and high HVA/C or high MTV and high HVA/C best predicted EFS. CONCLUSIONS In this exploratory study, pretherapeutic image-derived and laboratory markers of tumoral metabolic activity in NB (ASP, MTV, urinary HVA/C) allowed the identification of children with a high and low risk of progression/relapse under current therapy.
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Affiliation(s)
- Julian M M Rogasch
- Department of Nuclear Medicine, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany.
| | - Patrick Hundsdoerfer
- Department of Pediatric Oncology/Hematology, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Berlin Institute of Health (BIH), 10178, Berlin, Germany
| | - Christian Furth
- Department of Nuclear Medicine, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Florian Wedel
- Department of Nuclear Medicine, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Frank Hofheinz
- PET Center, Helmholtz Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany
| | - Paul-Christian Krüger
- Institute for Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - Holger Lode
- Department of Pediatric Oncology and Hematology, University Medicine Greifswald, Greifswald, Germany
| | - Winfried Brenner
- Department of Nuclear Medicine, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Angelika Eggert
- Department of Pediatric Oncology/Hematology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Holger Amthauer
- Department of Nuclear Medicine, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Imke Schatka
- Department of Nuclear Medicine, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
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Folkert MR, Setton J, Apte AP, Grkovski M, Young RJ, Schöder H, Thorstad WL, Lee NY, Deasy JO, Hun Oh J. Predictive modeling of outcomes following definitive chemoradiotherapy for oropharyngeal cancer based on FDG-PET image characteristics. Phys Med Biol 2017; 62:5327-5343. [PMID: 28604368 PMCID: PMC5729737 DOI: 10.1088/1361-6560/aa73cc] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
In this study, we investigate the use of imaging feature-based outcomes research ('radiomics') combined with machine learning techniques to develop robust predictive models for the risk of all-cause mortality (ACM), local failure (LF), and distant metastasis (DM) following definitive chemoradiation therapy (CRT). One hundred seventy four patients with stage III-IV oropharyngeal cancer (OC) treated at our institution with CRT with retrievable pre- and post-treatment 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) scans were identified. From pre-treatment PET scans, 24 representative imaging features of FDG-avid disease regions were extracted. Using machine learning-based feature selection methods, multiparameter logistic regression models were built incorporating clinical factors and imaging features. All model building methods were tested by cross validation to avoid overfitting, and final outcome models were validated on an independent dataset from a collaborating institution. Multiparameter models were statistically significant on 5 fold cross validation with the area under the receiver operating characteristic curve (AUC) = 0.65 (p = 0.004), 0.73 (p = 0.026), and 0.66 (p = 0.015) for ACM, LF, and DM, respectively. The model for LF retained significance on the independent validation cohort with AUC = 0.68 (p = 0.029) whereas the models for ACM and DM did not reach statistical significance, but resulted in comparable predictive power to the 5 fold cross validation with AUC = 0.60 (p = 0.092) and 0.65 (p = 0.062), respectively. In the largest study of its kind to date, predictive features including increasing metabolic tumor volume, increasing image heterogeneity, and increasing tumor surface irregularity significantly correlated to mortality, LF, and DM on 5 fold cross validation in a relatively uniform single-institution cohort. The LF model also retained significance in an independent population.
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Affiliation(s)
- Michael R. Folkert
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Jeremy Setton
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Aditya P. Apte
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Milan Grkovski
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Robert J. Young
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Heiko Schöder
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Wade L. Thorstad
- Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Nancy Y. Lee
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Joseph O. Deasy
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Jung Hun Oh
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
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Castelli J, Depeursinge A, Ndoh V, Prior JO, Ozsahin M, Devillers A, Bouchaab H, Chajon E, de Crevoisier R, Scher N, Jegoux F, Laguerre B, De Bari B, Bourhis J. A PET-based nomogram for oropharyngeal cancers. Eur J Cancer 2017; 75:222-230. [PMID: 28237868 DOI: 10.1016/j.ejca.2017.01.018] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2016] [Revised: 11/28/2016] [Accepted: 01/14/2017] [Indexed: 12/23/2022]
Abstract
PURPOSE In the context of locally advanced oropharyngeal cancer (LAOC) treated with definitive radiotherapy (RT) (combined with chemotherapy or cetuximab), the aims of this study were: (1) to identify PET-FDG parameters correlated with overall survival (OS) from a first cohort of patients; then (2) to compute a prognostic score; and (3) finally to validate this scoring system in a second independent cohort of patients. MATERIALS AND METHODS A total of 76 consecutive patients (training cohort from Rennes) treated with chemoradiotherapy or RT with cetuximab for LAOC were used to build a predictive model of locoregional control (LRC) and OS based on PET-FDG parameters. After internal calibration and validation of this model, a nomogram and a scoring system were developed and tested in a validation cohort of 46 consecutive patients treated with definitive RT for LAOC in Lausanne. RESULTS In multivariate analysis, the metabolic tumour volume (MTV) of the primary tumour and the lymph nodes were independent predictive factors for LRC and OS. Internal calibration showed a very good adjustment between the predicted OS and the observed OS at 24 months. Using the predictive score, two risk groups were identified (median OS 42 versus 14 months, p < 0.001) and confirmed in the validation cohort from Lausanne (median OS not reached versus 26 months, p=0.008). CONCLUSIONS This is the first report of a PET-based nomogram in oropharyngeal cancer. Interestingly, it appeared stronger than the classical prognostic factors and was validated in independent cohorts markedly diverging in many aspects, which suggest that the observed signal was robust.
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Affiliation(s)
- J Castelli
- Radiotherapy Department, Lausanne University Hospital, Switzerland; INSERM, U1099, Rennes, F-35000, France; Université de Rennes 1, LTSI, Rennes, F-35000, France
| | - A Depeursinge
- Ecole Polytechnique Fédérale de Lausanne, CH-1015, Lausanne, VD, Switzerland; University of Applied Sciences Western Switzerland, 3960, Sierre, Switzerland
| | - V Ndoh
- Radiotherapy Department, Centre Eugene Marquis, Rennes, F-35000, France
| | - J O Prior
- Nuclear Medicine and Molecular Imaging Department, Lausanne University Hospital, Switzerland
| | - M Ozsahin
- Radiotherapy Department, Lausanne University Hospital, Switzerland
| | - A Devillers
- Nuclear Medicine Department, Centre Eugene Marquis, Rennes, F-35000, France
| | - H Bouchaab
- Radiotherapy Department, Lausanne University Hospital, Switzerland
| | - E Chajon
- Radiotherapy Department, Centre Eugene Marquis, Rennes, F-35000, France
| | - R de Crevoisier
- Radiotherapy Department, Centre Eugene Marquis, Rennes, F-35000, France
| | - N Scher
- Radiotherapy Department, Lausanne University Hospital, Switzerland
| | - F Jegoux
- Head and Neck Department, CHU Rennes, Rennes, F-35000, France
| | - B Laguerre
- Oncology Department, Centre Eugene Marquis, Rennes, F-35000, France
| | - B De Bari
- Radiotherapy Department, Lausanne University Hospital, Switzerland
| | - J Bourhis
- Radiotherapy Department, Lausanne University Hospital, Switzerland.
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