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Yang M, Li X, Cai C, Liu C, Ma M, Qu W, Zhong S, Zheng E, Zhu H, Jin F, Shi H. [ 18F]FDG PET-CT radiomics signature to predict pathological complete response to neoadjuvant chemoimmunotherapy in non-small cell lung cancer: a multicenter study. Eur Radiol 2024; 34:4352-4363. [PMID: 38127071 DOI: 10.1007/s00330-023-10503-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Revised: 11/07/2023] [Accepted: 11/29/2023] [Indexed: 12/23/2023]
Abstract
OBJECTIVES This study aims to develop and validate a radiomics model based on 18F-fluorodeoxyglucose positron emission tomography-computed tomography ([18F]FDG PET-CT) images to predict pathological complete response (pCR) to neoadjuvant chemoimmunotherapy in non-small cell lung cancer (NSCLC). MATERIALS AND METHODS One hundred eighty-five patients receiving neoadjuvant chemoimmunotherapy for NSCLC at 5 centers from January 2019 to December 2022 were included and divided into a training cohort and a validation cohort. Radiomics models were constructed via the least absolute shrinkage and selection operator (LASSO) method. The performances of models were evaluated by the area under the receiver operating characteristic curve (AUC). In addition, genetic analyses were conducted to reveal the underlying biological basis of the radiomics score. RESULTS After the LASSO process, 9 PET-CT radiomics features were selected for pCR prediction. In the validation cohort, the ability of PET-CT radiomics model to predict pCR was shown to have an AUC of 0.818 (95% confidence interval [CI], 0.711, 0.925), which was better than the PET radiomics model (0.728 [95% CI, 0.610, 0.846]), CT radiomics model (0.732 [95% CI, 0.607, 0.857]), and maximum standard uptake value (0.603 [95% CI, 0.473, 0.733]) (p < 0.05). Moreover, a high radiomics score was related to the upregulation of pathways suppressing tumor proliferation and the infiltration of antitumor immune cell. CONCLUSION The proposed PET-CT radiomics model was capable of predicting pCR to neoadjuvant chemoimmunotherapy in NSCLC patients. CLINICAL RELEVANCE STATEMENT This study indicated that the generated 18F-fluorodeoxyglucose positron emission tomography-computed tomography radiomics model could predict pathological complete response to neoadjuvant chemoimmunotherapy, implying the potential of our radiomics model to personalize the neoadjuvant chemoimmunotherapy in lung cancer patients. KEY POINTS • Recognizing patients potentially benefiting neoadjuvant chemoimmunotherapy is critical for individualized therapy of lung cancer. • [18F]FDG PET-CT radiomics could predict pathological complete response to neoadjuvant immunotherapy in non-small cell lung cancer. • [18F]FDG PET-CT radiomics model could personalize neoadjuvant chemoimmunotherapy in lung cancer patients.
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Affiliation(s)
- Minglei Yang
- Department of Thoracic Surgery, Ningbo No. 2 Hospital, Ningbo, China
| | - Xiaoxiao Li
- Shanghai Universal Cloud Medical Imaging Diagnostic Center, Shanghai, China
| | - Chuang Cai
- School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang, Jiangsu, China
| | - Chunli Liu
- Shanghai Universal Cloud Medical Imaging Diagnostic Center, Shanghai, China
| | - Minjie Ma
- Department of Thoracic Surgery, The First Hospital of Lanzhou University, Lanzhou, Gansu, China
| | - Wendong Qu
- Department of Thoracic Surgery, The Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, China.
| | | | - Enkuo Zheng
- Department of Thoracic Surgery, Ningbo No. 2 Hospital, Ningbo, China
| | - Huangkai Zhu
- Department of Thoracic Surgery, Ningbo No. 2 Hospital, Ningbo, China
| | - Feng Jin
- Shandong Key Laboratory of Infectious Respiratory Diseases, Shandong Public Health Clinical Center, Shandong University, Shandong, China.
| | - Huazheng Shi
- Shanghai Universal Cloud Medical Imaging Diagnostic Center, Shanghai, China.
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Barbe R, Belkouchi Y, Menu Y, Cohen R, David C, Kind M, Harguem S, Dawi L, Hadchiti J, Selhane F, Billet N, Ammari S, Bertin A, Lawrance L, Cervantes B, Hollebecque A, Balleyguier C, Cournede PH, Talbot H, Lassau N, Andre T. Imaging-guided prognostic score-based approach to assess the benefits of combotherapy versus monotherapy with immune checkpoint inhibitors in metastatic MSI-H colorectal cancer patients. Eur J Cancer 2024; 202:114020. [PMID: 38502988 DOI: 10.1016/j.ejca.2024.114020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Revised: 03/04/2024] [Accepted: 03/10/2024] [Indexed: 03/21/2024]
Abstract
BACKGROUND This retrospective study determined survival responses to immune checkpoint inhibitors (ICIs), comparing mono- (mono) and combo-immunotherapy (combo) in patients with microsatellite instability-high (MSI-H) metastatic colorectal cancer (mCRC) by analyzing quantitative imaging data and clinical factors. METHODS One hundred fifty patients were included from two centers and divided into training (n = 105) and validation (n = 45) cohorts. Radiologists manually annotated chest-abdomen-pelvis computed tomography and calculated tumor burden. Progression-free survival (PFS) was assessed, and variables were selected through Recursive Feature Elimination. Cutoff values were determined using maximally selected rank statistics to binarize features, forming a risk score with hazard ratio-derived weights. RESULTS In total, 2258 lesions were annotated with excellent reproducibility. Key variables in the training cohort included: total tumor volume (cutoff: 73 cm3), lesion count (cutoff: 20), age (cutoff: 60) and the presence of peritoneal carcinomatosis. Their respective weights were 1.13, 0.96, 0.91, and 0.38, resulting in a risk score cutoff of 1.36. Low-score patients showed similar overall survival and PFS regardless of treatment, while those with a high-score had significantly worse survivals with mono vs combo (P = 0.004 and P = 0.0001). In the validation set, low-score patients exhibited no significant difference in overall survival and PFS with mono or combo. However, patients with a high-score had worse PFS with mono (P = 0.046). CONCLUSIONS A score based on total tumor volume, lesion count, the presence of peritoneal carcinomatosis, and age can guide MSI-H mCRC treatment decisions, allowing oncologists to identify suitable candidates for mono and combo ICI therapies.
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Affiliation(s)
- Rémy Barbe
- Département d'imagerie, Gustave Roussy, Villejuif, France
| | - Younes Belkouchi
- Laboratoire BIOMAPS, CNRS, INSERM, CEA, Université Paris Saclay, Villejuif, France; Université Paris-Saclay, Centrale-Supelec, Centre de vision numérique, Gif-Sur-Yvette, France
| | - Yves Menu
- Département d'imagerie, Gustave Roussy, Villejuif, France; SIRIC CURAMUS, INSERM, Unité Mixte de Recherche Scientifique 938, Centre de Recherche Saint-Antoine, Equipe Instabilité des Microsatellites et Cancer, Equipe Labellisée par la Ligue Nationale Contre le Cancer, Paris, France; Sorbonne University, Department of Medical Oncology, Saint-Antoine Hospital, AP-HP, INSERM, Unité Mixte de Recherche Scientifique 938, Centre de Recherche Saint-Antoine, Equipe Instabilité des Microsatellites et Cancer, Equipe Labellisée par la Ligue Nationale Contre le Cancer, Paris, France
| | - Romain Cohen
- SIRIC CURAMUS, INSERM, Unité Mixte de Recherche Scientifique 938, Centre de Recherche Saint-Antoine, Equipe Instabilité des Microsatellites et Cancer, Equipe Labellisée par la Ligue Nationale Contre le Cancer, Paris, France; Sorbonne University, Department of Medical Oncology, Saint-Antoine Hospital, AP-HP, INSERM, Unité Mixte de Recherche Scientifique 938, Centre de Recherche Saint-Antoine, Equipe Instabilité des Microsatellites et Cancer, Equipe Labellisée par la Ligue Nationale Contre le Cancer, Paris, France
| | - Clemence David
- Laboratoire BIOMAPS, CNRS, INSERM, CEA, Université Paris Saclay, Villejuif, France
| | - Michele Kind
- Département d'imagerie, Institut Bergonié, Bordeaux, France
| | - Sana Harguem
- Département d'imagerie, Gustave Roussy, Villejuif, France
| | - Lama Dawi
- Département d'imagerie, Gustave Roussy, Villejuif, France
| | - Joya Hadchiti
- Département d'imagerie, Gustave Roussy, Villejuif, France
| | - Fatine Selhane
- Département d'imagerie, Gustave Roussy, Villejuif, France
| | - Nicolas Billet
- Laboratoire BIOMAPS, CNRS, INSERM, CEA, Université Paris Saclay, Villejuif, France
| | - Samy Ammari
- Département d'imagerie, Gustave Roussy, Villejuif, France; Laboratoire BIOMAPS, CNRS, INSERM, CEA, Université Paris Saclay, Villejuif, France
| | - Ambroise Bertin
- Laboratoire BIOMAPS, CNRS, INSERM, CEA, Université Paris Saclay, Villejuif, France
| | - Littisha Lawrance
- Laboratoire BIOMAPS, CNRS, INSERM, CEA, Université Paris Saclay, Villejuif, France
| | - Baptiste Cervantes
- SIRIC CURAMUS, INSERM, Unité Mixte de Recherche Scientifique 938, Centre de Recherche Saint-Antoine, Equipe Instabilité des Microsatellites et Cancer, Equipe Labellisée par la Ligue Nationale Contre le Cancer, Paris, France; Sorbonne University, Department of Medical Oncology, Saint-Antoine Hospital, AP-HP, INSERM, Unité Mixte de Recherche Scientifique 938, Centre de Recherche Saint-Antoine, Equipe Instabilité des Microsatellites et Cancer, Equipe Labellisée par la Ligue Nationale Contre le Cancer, Paris, France
| | - Antoine Hollebecque
- Département d'Innovation Thérapeutique et Essais Précoces (DITEP), Gustave Roussy, Villejuif, France
| | - Corinne Balleyguier
- Département d'imagerie, Gustave Roussy, Villejuif, France; Laboratoire BIOMAPS, CNRS, INSERM, CEA, Université Paris Saclay, Villejuif, France
| | - Paul-Henry Cournede
- Université Paris-Saclay, Centrale-Supelec, Lab of Mathematics and Informatics, Gif-Sur-Yvette, France
| | - Hugues Talbot
- Université Paris-Saclay, Centrale-Supelec, Centre de vision numérique, Gif-Sur-Yvette, France
| | - Nathalie Lassau
- Département d'imagerie, Gustave Roussy, Villejuif, France; Laboratoire BIOMAPS, CNRS, INSERM, CEA, Université Paris Saclay, Villejuif, France
| | - Thierry Andre
- SIRIC CURAMUS, INSERM, Unité Mixte de Recherche Scientifique 938, Centre de Recherche Saint-Antoine, Equipe Instabilité des Microsatellites et Cancer, Equipe Labellisée par la Ligue Nationale Contre le Cancer, Paris, France; Sorbonne University, Department of Medical Oncology, Saint-Antoine Hospital, AP-HP, INSERM, Unité Mixte de Recherche Scientifique 938, Centre de Recherche Saint-Antoine, Equipe Instabilité des Microsatellites et Cancer, Equipe Labellisée par la Ligue Nationale Contre le Cancer, Paris, France.
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Huang W, Son MH, Ha LN, Kang L, Cai W. Challenges coexist with opportunities: development of a macrocyclic peptide PET radioligand for PD-L1. Eur J Nucl Med Mol Imaging 2024; 51:1574-1577. [PMID: 38492018 PMCID: PMC11131584 DOI: 10.1007/s00259-024-06680-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/18/2024]
Affiliation(s)
- Wenpeng Huang
- Department of Nuclear Medicine, Peking University First Hospital, No.8 Xishiku Str, Xicheng District, Beijing, 100034, China
| | - Mai Hong Son
- Department of Nuclear Medicine, Hospital 108, Hanoi, Vietnam
| | - Le Ngoc Ha
- Department of Nuclear Medicine, Hospital 108, Hanoi, Vietnam
| | - Lei Kang
- Department of Nuclear Medicine, Peking University First Hospital, No.8 Xishiku Str, Xicheng District, Beijing, 100034, China.
| | - Weibo Cai
- Departments of Radiology and Medical Physics, University of Wisconsin - Madison, K6/562 Clinical Science Center, 600 Highland Ave, Madison, WI, 53705-2275, USA.
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Tricarico P, Chardin D, Martin N, Contu S, Hugonnet F, Otto J, Humbert O. Total metabolic tumor volume on 18F-FDG PET/CT is a game-changer for patients with metastatic lung cancer treated with immunotherapy. J Immunother Cancer 2024; 12:e007628. [PMID: 38649279 PMCID: PMC11043703 DOI: 10.1136/jitc-2023-007628] [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] [Accepted: 03/25/2024] [Indexed: 04/25/2024] Open
Abstract
PURPOSE Because of atypical response imaging patterns in patients with metastatic non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICPIs), new biomarkers are needed for a better monitoring of treatment efficacy. The aim of this prospective study was to evaluate the prognostic value of volume-derived positron-emission tomography (PET) parameters on baseline and follow-up 18F-fluoro-deoxy-glucose PET (18F-FDG-PET) scans and compare it with the conventional PET Response Criteria in Solid Tumors (PERCIST). METHODS Patients with metastatic NSCLC were included in two different single-center prospective trials. 18F-FDG-PET studies were performed before the start of immunotherapy (PETbaseline), after 6-8 weeks (PETinterim1) and after 12-16 weeks (PETinterim2) of treatment, using PERCIST criteria for tumor response assessment. Different metabolic parameters were evaluated: absolute values of maximum standardized uptake value (SUVmax) of the most intense lesion, total metabolic tumor volume (TMTV), total lesion glycolysis (TLG), but also their percentage changes between PET studies (ΔSUVmax, ΔTMTV and ΔTLG). The median follow-up of patients was 31 (7.3-31.8) months. Prognostic values and optimal thresholds of PET parameters were estimated by ROC (Receiver Operating Characteristic) curve analysis of 12-month overall survival (12M-OS) and 6-month progression-free survival (6M-PFS). Tumor progression needed to be confirmed by a multidisciplinary tumor board, considering atypical response patterns on imaging. RESULTS 110 patients were prospectively included. On PETbaseline, TMTV was predictive of 12M-OS [AUC (Area Under Curve) =0.64; 95% CI: 0.61 to 0.66] whereas SUVmax and TLG were not. On PETinterim1 and PETinterim2, all metabolic parameters were predictive for 12M-OS and 6M-PFS, the residual TMTV on PETinterim1 (TMTV1) being the strongest prognostic biomarker (AUC=0.83 and 0.82; 95% CI: 0.74 to 0.91, for 12M-OS and 6M-PFS, respectively). Using the optimal threshold by ROC curve to classify patients into three TMTV1 subgroups (0 cm3; 0-57 cm3; >57 cm3), TMTV1 prognostic stratification was independent of PERCIST criteria on both PFS and OS, and significantly outperformed them. Subgroup analysis demonstrated that TMTV1 remained a strong prognostic biomarker of 12M-OS for non-responding patients (p=0.0003) according to PERCIST criteria. In the specific group of patients with PERCIST progression on PETinterim1, low residual tumor volume (<57 cm3) was still associated with a very favorable patients' outcome (6M-PFS=73%; 24M-OS=55%). CONCLUSION The absolute value of residual metabolic tumor volume, assessed 6-8 weeks after the start of ICPI, is an optimal and independent prognostic measure, exceeding and complementing conventional PERCIST criteria. Oncologists should consider it in patients with first tumor progression according to PERCIST criteria, as it helps identify patients who benefit from continued treatment. TRIAL REGISTRATION NUMBER 2018-A02116-49; NCT03584334.
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Affiliation(s)
- Pierre Tricarico
- Department of Nuclear Medicine, Centre Antoine-Lacassagne, Nice, France
| | - David Chardin
- Department of Nuclear Medicine, Centre Antoine-Lacassagne, Nice, France
- IBV, Université Côte d'Azur, CNRS, Inserm, Nice, France
| | - Nicolas Martin
- Department of Medical Oncology, Centre Antoine-Lacassagne, Nice, France
| | - Sara Contu
- Department of Biostatistics, Centre Antoine-Lacassagne, Nice, France
| | - Florent Hugonnet
- Department of Nuclear Medicine, Centre Hospitalier Princesse Grâce, Monaco
| | - Josiane Otto
- Department of Medical Oncology, Centre Antoine-Lacassagne, Nice, France
| | - Olivier Humbert
- Department of Nuclear Medicine, Centre Antoine-Lacassagne, Nice, France
- IBV, Université Côte d'Azur, CNRS, Inserm, Nice, France
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Tarai S, Lundström E, Sjöholm T, Jönsson H, Korenyushkin A, Ahmad N, Pedersen MA, Molin D, Enblad G, Strand R, Ahlström H, Kullberg J. Improved automated tumor segmentation in whole-body 3D scans using multi-directional 2D projection-based priors. Heliyon 2024; 10:e26414. [PMID: 38390107 PMCID: PMC10882139 DOI: 10.1016/j.heliyon.2024.e26414] [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: 11/14/2023] [Revised: 02/09/2024] [Accepted: 02/13/2024] [Indexed: 02/24/2024] Open
Abstract
Early cancer detection, guided by whole-body imaging, is important for the overall survival and well-being of the patients. While various computer-assisted systems have been developed to expedite and enhance cancer diagnostics and longitudinal monitoring, the detection and segmentation of tumors, especially from whole-body scans, remain challenging. To address this, we propose a novel end-to-end automated framework that first generates a tumor probability distribution map (TPDM), incorporating prior information about the tumor characteristics (e.g. size, shape, location). Subsequently, the TPDM is integrated with a state-of-the-art 3D segmentation network along with the original PET/CT or PET/MR images. This aims to produce more meaningful tumor segmentation masks compared to using the baseline 3D segmentation network alone. The proposed method was evaluated on three independent cohorts (autoPET, CAR-T, cHL) of images containing different cancer forms, obtained with different imaging modalities, and acquisition parameters and lesions annotated by different experts. The evaluation demonstrated the superiority of our proposed method over the baseline model by significant margins in terms of Dice coefficient, and lesion-wise sensitivity and precision. Many of the extremely small tumor lesions (i.e. the most difficult to segment) were missed by the baseline model but detected by the proposed model without additional false positives, resulting in clinically more relevant assessments. On average, an improvement of 0.0251 (autoPET), 0.144 (CAR-T), and 0.0528 (cHL) in overall Dice was observed. In conclusion, the proposed TPDM-based approach can be integrated with any state-of-the-art 3D UNET with potentially more accurate and robust segmentation results.
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Affiliation(s)
- Sambit Tarai
- Department of Surgical Sciences, Uppsala University, SE-75185, Uppsala, Sweden
| | - Elin Lundström
- Department of Surgical Sciences, Uppsala University, SE-75185, Uppsala, Sweden
| | - Therese Sjöholm
- Department of Surgical Sciences, Uppsala University, SE-75185, Uppsala, Sweden
| | - Hanna Jönsson
- Department of Surgical Sciences, Uppsala University, SE-75185, Uppsala, Sweden
| | | | - Nouman Ahmad
- Department of Surgical Sciences, Uppsala University, SE-75185, Uppsala, Sweden
| | - Mette A Pedersen
- Department of Nuclear Medicine & PET-Centre, Aarhus University Hospital, 8200 Aarhus N, Denmark
- Department of Biomedicine, Aarhus University, 8000 Aarhus C, Denmark
- Steno Diabetes Center Aarhus, Aarhus University Hospital, 8200 Aarhus N, Denmark
| | - Daniel Molin
- Department of Immunology, Genetics and Pathology, Uppsala University, SE-75185 Uppsala, Sweden
| | - Gunilla Enblad
- Department of Immunology, Genetics and Pathology, Uppsala University, SE-75185 Uppsala, Sweden
| | - Robin Strand
- Department of Information Technology, Uppsala University, SE-75237, Uppsala, Sweden
| | - Håkan Ahlström
- Department of Surgical Sciences, Uppsala University, SE-75185, Uppsala, Sweden
- Antaros Medical AB, SE-43153, Mölndal, Sweden
| | - Joel Kullberg
- Department of Surgical Sciences, Uppsala University, SE-75185, Uppsala, Sweden
- Antaros Medical AB, SE-43153, Mölndal, Sweden
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Kifjak D, Hochmair M, Sobotka D, Haug AR, Ambros R, Prayer F, Heidinger BH, Roehrich S, Milos RI, Wadsak W, Fuereder T, Krenbek D, Fazekas A, Meilinger M, Mayerhoefer ME, Langs G, Herold C, Prosch H, Beer L. Metabolic tumor volume and sites of organ involvement predict outcome in NSCLC immune-checkpoint inhibitor therapy. Eur J Radiol 2024; 170:111198. [PMID: 37992608 DOI: 10.1016/j.ejrad.2023.111198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2023] [Revised: 10/13/2023] [Accepted: 11/13/2023] [Indexed: 11/24/2023]
Abstract
PURPOSE The purpose of this study was to assess the ability of pretreatment PET parameters and peripheral blood biomarkers to predict progression-free survival (PFS) and overall survival (OS) in NSCLC patients treated with ICIT. METHODS We prospectively included 87 patients in this study who underwent pre-treatment [18F]-FDG PET/CT. Organ-specific and total metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were measured using a semiautomatic software. Sites of organ involvement (SOI) were assessed by PET/CT. The log-rank test and Cox-regression analysis were used to assess associations between clinical, laboratory, and imaging parameters with PFS and OS. Time dependent ROC were calculated and model performance was evaluated in terms of its clinical utility. RESULTS MTV increased with the number of SOI and was correlated with neutrophil and lymphocyte cell count (Spearman's rho = 0.27 or 0.32; p =.02 or 0.003; respectively). Even after adjustment for known risk factors, such as PD-1 expression and neutrophil cell count, the MTV and the number of SOI were independent risk factors for progression (per 100 cm3; adjusted hazard ratio [aHR]: 1.13; 95% confidence interval [95%CI]: 1.01-1.28; p =.04; single SOI vs. ≥ 4 SOI: aHR: 2.26, 95%CI: 1.04-4.94; p =.04). MTV and the number of SOI were independent risk factors for overall survival (per 100 cm3 aHR: 1.11, 95%CI: 1.01-1.23; p =.03; single SOI vs. ≥ 4 SOI: aHR: 4.54, 95%CI: 1.64-12.58; p =.04). The combination of MTV and the number of SOI improved the risk stratification for PFS and OS (log-rank test p <.001; C-index: 0.64 and 0.67). CONCLUSION The MTV and the number of SOI are simple imaging markers that provide complementary information to facilitate risk stratification in NSCLC patients scheduled for ICIT.
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Affiliation(s)
- Daria Kifjak
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria; Department of Radiology, UMass Memorial Medical Center and University of Massachusetts Chan Medical School, Worcester, MA, USA; Christian Doppler Laboratory for Machine Learning Driven Precision, Medicine, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Austria
| | - Maximilian Hochmair
- Department of Respiratory and Critical Care Medicine, Karl Landsteiner Institute of Lung Research and Pulmonary Oncology, Klinik Floridsdorf, Vienna, Austria
| | - Daniel Sobotka
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Alexander R Haug
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Raphael Ambros
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Florian Prayer
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Benedikt H Heidinger
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Sebastian Roehrich
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Ruxandra-Iulia Milos
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Wolfgang Wadsak
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria; Center for Biomarker Research in Medicine, CBmed, Graz, Austria
| | - Thorsten Fuereder
- Department of Internal Medicine I & Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria
| | - Dagmar Krenbek
- Department of Pathology and Bacteriology, Klinik Floridsdorf, Brünner Strasse 68, 1210 Vienna, Austria
| | - Andreas Fazekas
- Department of Respiratory and Critical Care Medicine, Karl Landsteiner Institute of Lung Research and Pulmonary Oncology, Klinik Floridsdorf, Vienna, Austria
| | - Michael Meilinger
- Department of Respiratory and Critical Care Medicine, Karl Landsteiner Institute of Lung Research and Pulmonary Oncology, Klinik Floridsdorf, Vienna, Austria
| | - Marius E Mayerhoefer
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Georg Langs
- Christian Doppler Laboratory for Machine Learning Driven Precision, Medicine, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Austria; Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Christian Herold
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Helmut Prosch
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria; Christian Doppler Laboratory for Machine Learning Driven Precision, Medicine, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Austria.
| | - Lucian Beer
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria; Christian Doppler Laboratory for Machine Learning Driven Precision, Medicine, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Austria
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Yin X, Li J, Chen B, Liu K, Hu S. The predictive value of 18F-FDG PET/CT combined with inflammatory index for major pathological reactions in resectable NSCLC receiving neoadjuvant immunochemotherapy. Lung Cancer 2023; 186:107389. [PMID: 37820538 DOI: 10.1016/j.lungcan.2023.107389] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 09/05/2023] [Accepted: 09/29/2023] [Indexed: 10/13/2023]
Abstract
OBJECTIVES To investigate whether the combination of inflammatory biomarkers and metabolic parameters of 18F-FDG PET/CT could predict the major pathological reactions (MPR) in resectable NSCLC patients after neoadjuvant immunochemotherapy more accurately and screen out patients who may benefit from the neoadjuvant therapy. MATERIALS AND METHODS 114 resectable NSCLC patients who underwent neoadjuvant immunochemotherapy and radical surgery were retrospectively enrolled. Detailed clinical characteristics, B-R and 18F-FDG PET/CT images were collected for analyzing their correlation with MPR. A metabolic-inflammation comprehensive prognostic index (MICPI) combined 18F-FDG PET/CT metabolic parameters and inflammatory index was proposed to predict MPR. RESULTS 66.7 % patients achieved MPR. Smoking history, gender and ILO were influencing factors for MPR acquisition in NSCLC patients. High absolute neutrophils count (PreN ≥ 3.65), metabolic parameters (PreSUVmax ≥ 11.73) before treatment and ΔSUVmean (≥54.18) were significantly associated with MPR (P<0.01, P<0.05 and P<0.001 respectively). MICPI-B based on PreN and PreSUVmax categorized NSCLC patients into three groups and among the groups of high, intermediate and low MICPI-B score, MPR accounted for 80.00 %, 51.72 % and 28.57 % respectively (P < 0.01). In high, intermediate and low MICPI-P groups which based on PreN and ΔSUVmean, MPR accounted for 92.31 %, 53.57 % and 11.11 %, respectively (P < 0.001). CONCLUSION PreN and metabolic parameter of 18F-FDG PET/CT may be an accurate alternative biomarker for predicting MPR in NSCLC patients after neoadjuvant immunochemotherapy. Moreover, MICPI can stratify patients into different groups based on their likelihood of obtaining MPR, allowing clinicians to identify patients who may most likely benefit from neoadjuvant immunochemotherapy.
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Affiliation(s)
- Xiaoqin Yin
- Department of PET Center, Xiangya Hospital, Central South University, Changsha 410008, China
| | - Jian Li
- Department of PET Center, Xiangya Hospital, Central South University, Changsha 410008, China
| | - Bei Chen
- Department of PET Center, Xiangya Hospital, Central South University, Changsha 410008, China
| | - Kehuang Liu
- Department of PET Center, Xiangya Hospital, Central South University, Changsha 410008, China
| | - Shuo Hu
- Department of PET Center, Xiangya Hospital, Central South University, Changsha 410008, China.
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8
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Zhang X, Cai X, Yan C. Opportunities and challenges in combining immunotherapy and radiotherapy in esophageal cancer. J Cancer Res Clin Oncol 2023; 149:18253-18270. [PMID: 37985502 PMCID: PMC10725359 DOI: 10.1007/s00432-023-05499-z] [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: 10/11/2023] [Accepted: 10/30/2023] [Indexed: 11/22/2023]
Abstract
BACKGROUND Immunotherapy has shown promise in the treatment of esophageal cancer, but using it alone only benefits a small number of patients. Most patients either do not have a significant response or develop secondary drug resistance. The combination of radiotherapy and immunotherapy appears to be a promising approach to treating esophageal cancer. PURPOSE We reviewed milestone clinical trials of radiotherapy combined with immunotherapy for esophageal cancer. We then discussed potential biomarkers for radiotherapy combined with immunotherapy, including programmed cell death-ligand 1 (PD-L1) status, tumor mutation burden (TMB), tumor-infiltrating lymphocytes, ct-DNA, imaging biomarkers, and clinical factors. Furthermore, we emphasize the key mechanisms of radiation therapy-induced immune stimulation and immune suppression in order to propose strategies for overcoming immune resistance in radiation therapy (RT). Lastly, we discussed the emerging role of low-dose radiotherapy (LDRT) , which has become a promising approach to overcome the limitations of high-dose radiotherapy. CONCLUSION Radiotherapy can be considered a triggering factor for systemic anti-tumor immune response and, with the assistance of immunotherapy, can serve as a systemic treatment option and potentially become the standard treatment for cancer patients.
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Affiliation(s)
- Xinyu Zhang
- Weifang Hospital of Traditional Chinese Medicine, 666 Weizhou Road, Weifang, 261000, Shandong, China
- Shandong University of Traditional Chinese Medicine, Jinan, 250000, Shandong, China
| | - Xinsheng Cai
- Weifang Hospital of Traditional Chinese Medicine, 666 Weizhou Road, Weifang, 261000, Shandong, China
| | - Chaoguang Yan
- Weifang Hospital of Traditional Chinese Medicine, 666 Weizhou Road, Weifang, 261000, Shandong, China.
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9
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Nakahama K, Izumi M, Yoshimoto N, Fukui M, Sugimoto A, Nagamine H, Ogawa K, Sawa K, Tani Y, Kaneda H, Mitsuoka S, Watanabe T, Asai K, Kawaguchi T. Clinical significance of KL-6 in immune-checkpoint inhibitor treatment for non-small cell lung cancer. Cancer Chemother Pharmacol 2023; 92:381-390. [PMID: 37606723 DOI: 10.1007/s00280-023-04573-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 07/29/2023] [Indexed: 08/23/2023]
Abstract
PURPOSE Krebs von den Lungen-6 (KL-6) functions as a tumor marker, as well as a diagnostic tool for interstitial pneumonia (IP). However, the significance of KL-6 in the immune-checkpoint inhibitor (ICI) treatment of non-small cell lung cancer (NSCLC), especially in patients without IP, is unknown. METHODS This multicenter, retrospective study, which included patients with advanced NSCLC who received ICI therapy, analyzed the association between serum KL-6 values and ICI efficacy and the association between serum KL-6 values and ICI-induced interstitial lung disease (ILD) occurrence, focusing primarily on patients without IP. RESULTS In total, 322 patients had available KL-6 values before ICI therapy. Among 202 patients without IP who received ICI monotherapy, the high-KL-6 group (≥ 500 U/mL) showed significantly shorter progression-free survival (PFS) and overall survival (OS) than the low-KL-6 group (< 500 U/mL) (median: 2.1 vs. 3.6 months, p = 0.048; median: 9.2 vs. 14.5 months, p = 0.035). There was no significant difference in response rate between the KL-6 high and low groups (19% vs. 29%, p = 0.14). In the multivariate analysis, high KL-6 was a significant predictor of poor PFS (hazard ratio [HR], 1.52; 95% confidence interval [CI] 1.10-2.11, p = 0.012) and OS (HR, 1.51; 95% CI 1.07 - 2.13, p = 0.019) for patients treated with ICI monotherapy. There was no significant difference in the occurrence rate of ILD between the high KL-6 and low KL-6 groups in patients with (20% vs. 15%, p = 1.00) or without IP (12% vs. 12%, p = 1.00). CONCLUSION In ICI monotherapy for NSCLC without IP, elevated serum KL-6 levels were associated with poorer outcomes.
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Affiliation(s)
- Kenji Nakahama
- Department of Respiratory Medicine, Graduate School of Medicine, Osaka Metropolitan University, Asahimachi 1-4-3, Abeno-ku, Osaka City, Osaka, 545-8585, Japan.
| | - Motohiro Izumi
- Department of Pulmonary Medicine, Bell Land General Hospital, Sakai, Japan
| | - Naoki Yoshimoto
- Department of Pulmonary Medicine, Ishikiriseiki Hospital, Higashiosaka, Japan
| | - Mitsuru Fukui
- Department of Laboratory of Statistics, Graduate School of Medicine, Osaka Metropolitan University, Osaka, Japan
| | - Akira Sugimoto
- Department of Respiratory Medicine, Graduate School of Medicine, Osaka Metropolitan University, Asahimachi 1-4-3, Abeno-ku, Osaka City, Osaka, 545-8585, Japan
| | - Hiroaki Nagamine
- Department of Respiratory Medicine, Graduate School of Medicine, Osaka Metropolitan University, Asahimachi 1-4-3, Abeno-ku, Osaka City, Osaka, 545-8585, Japan
| | - Koichi Ogawa
- Department of Respiratory Medicine, Graduate School of Medicine, Osaka Metropolitan University, Asahimachi 1-4-3, Abeno-ku, Osaka City, Osaka, 545-8585, Japan
| | - Kenji Sawa
- Department of Respiratory Medicine, Graduate School of Medicine, Osaka Metropolitan University, Asahimachi 1-4-3, Abeno-ku, Osaka City, Osaka, 545-8585, Japan
| | - Yoko Tani
- Department of Clinical Oncology, Graduate School of Medicine, Osaka Metropolitan University, Osaka, Japan
| | - Hiroyasu Kaneda
- Department of Clinical Oncology, Graduate School of Medicine, Osaka Metropolitan University, Osaka, Japan
| | - Shigeki Mitsuoka
- Department of Clinical Oncology, Graduate School of Medicine, Osaka Metropolitan University, Osaka, Japan
| | - Tetsuya Watanabe
- Department of Respiratory Medicine, Graduate School of Medicine, Osaka Metropolitan University, Asahimachi 1-4-3, Abeno-ku, Osaka City, Osaka, 545-8585, Japan
| | - Kazuhisa Asai
- Department of Respiratory Medicine, Graduate School of Medicine, Osaka Metropolitan University, Asahimachi 1-4-3, Abeno-ku, Osaka City, Osaka, 545-8585, Japan
| | - Tomoya Kawaguchi
- Department of Respiratory Medicine, Graduate School of Medicine, Osaka Metropolitan University, Asahimachi 1-4-3, Abeno-ku, Osaka City, Osaka, 545-8585, Japan
- Department of Clinical Oncology, Graduate School of Medicine, Osaka Metropolitan University, Osaka, Japan
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10
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Gabiache G, Zadro C, Rozenblum L, Vezzosi D, Mouly C, Thoulouzan M, Guimbaud R, Otal P, Dierickx L, Rousseau H, Trepanier C, Dercle L, Mokrane FZ. Image-Guided Precision Medicine in the Diagnosis and Treatment of Pheochromocytomas and Paragangliomas. Cancers (Basel) 2023; 15:4666. [PMID: 37760633 PMCID: PMC10526298 DOI: 10.3390/cancers15184666] [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: 06/15/2023] [Revised: 09/11/2023] [Accepted: 09/18/2023] [Indexed: 09/29/2023] Open
Abstract
In this comprehensive review, we aimed to discuss the current state-of-the-art medical imaging for pheochromocytomas and paragangliomas (PPGLs) diagnosis and treatment. Despite major medical improvements, PPGLs, as with other neuroendocrine tumors (NETs), leave clinicians facing several challenges; their inherent particularities and their diagnosis and treatment pose several challenges for clinicians due to their inherent complexity, and they require management by multidisciplinary teams. The conventional concepts of medical imaging are currently undergoing a paradigm shift, thanks to developments in radiomic and metabolic imaging. However, despite active research, clinical relevance of these new parameters remains unclear, and further multicentric studies are needed in order to validate and increase widespread use and integration in clinical routine. Use of AI in PPGLs may detect changes in tumor phenotype that precede classical medical imaging biomarkers, such as shape, texture, and size. Since PPGLs are rare, slow-growing, and heterogeneous, multicentric collaboration will be necessary to have enough data in order to develop new PPGL biomarkers. In this nonsystematic review, our aim is to present an exhaustive pedagogical tool based on real-world cases, dedicated to physicians dealing with PPGLs, augmented by perspectives of artificial intelligence and big data.
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Affiliation(s)
- Gildas Gabiache
- Department of Radiology, Rangueil University Hospital, 31400 Toulouse, France (F.-Z.M.)
| | - Charline Zadro
- Department of Radiology, Rangueil University Hospital, 31400 Toulouse, France (F.-Z.M.)
| | - Laura Rozenblum
- Department of Nuclear Medicine, Sorbonne Université, AP-HP, Hôpital La Pitié-Salpêtrière, 75013 Paris, France
| | - Delphine Vezzosi
- Department of Endocrinology, Rangueil University Hospital, 31400 Toulouse, France
| | - Céline Mouly
- Department of Endocrinology, Rangueil University Hospital, 31400 Toulouse, France
| | | | - Rosine Guimbaud
- Department of Oncology, Rangueil University Hospital, 31400 Toulouse, France
| | - Philippe Otal
- Department of Radiology, Rangueil University Hospital, 31400 Toulouse, France (F.-Z.M.)
| | - Lawrence Dierickx
- Department of Nuclear Medicine, IUCT-Oncopole, 31059 Toulouse, France;
| | - Hervé Rousseau
- Department of Radiology, Rangueil University Hospital, 31400 Toulouse, France (F.-Z.M.)
| | - Christopher Trepanier
- New York-Presbyterian Hospital/Department of Radiology, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Laurent Dercle
- New York-Presbyterian Hospital/Department of Radiology, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Fatima-Zohra Mokrane
- Department of Radiology, Rangueil University Hospital, 31400 Toulouse, France (F.-Z.M.)
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11
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Liang S, Wang H, Tian H, Xu Z, Wu M, Hua D, Li C. The prognostic biological markers of immunotherapy for non-small cell lung cancer: current landscape and future perspective. Front Immunol 2023; 14:1249980. [PMID: 37753089 PMCID: PMC10518408 DOI: 10.3389/fimmu.2023.1249980] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 08/24/2023] [Indexed: 09/28/2023] Open
Abstract
The emergence of immunotherapy, particularly programmed cell death 1 (PD-1) and programmed cell death ligand-1 (PD-L1) produced profound transformations for treating non-small cell lung cancer (NSCLC). Nevertheless, not all NSCLC patients can benefit from immunotherapy in clinical practice. In addition to limited response rates, exorbitant treatment costs, and the substantial threats involved with immune-related adverse events, the intricate interplay between long-term survival outcomes and early disease progression, including early immune hyperprogression, remains unclear. Consequently, there is an urgent imperative to identify robust predictive and prognostic biological markers, which not only possess the potential to accurately forecast the therapeutic efficacy of immunotherapy in NSCLC but also facilitate the identification of patient subgroups amenable to personalized treatment approaches. Furthermore, this advancement in patient stratification based on certain biological markers can also provide invaluable support for the management of immunotherapy in NSCLC patients. Hence, in this review, we comprehensively examine the current landscape of individual biological markers, including PD-L1 expression, tumor mutational burden, hematological biological markers, and gene mutations, while also exploring the potential of combined biological markers encompassing radiological and radiomic markers, as well as prediction models that have the potential to better predict responders to immunotherapy in NSCLC with an emphasis on some directions that warrant further investigation which can also deepen the understanding of clinicians and provide a reference for clinical practice.
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Affiliation(s)
- Shuai Liang
- Department of Oncology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi, China
| | - Hanyu Wang
- Wuxi School of Medicine, Jiangnan University, Wuxi, China
| | - Haixia Tian
- Department of Oncology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi, China
| | - Zhicheng Xu
- Department of Oncology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi, China
| | - Min Wu
- Suzhou Cancer Center Core Laboratory, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, China
| | - Dong Hua
- Department of Oncology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi, China
- Wuxi School of Medicine, Jiangnan University, Wuxi, China
| | - Chengming Li
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
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12
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Chen X, Bai G, Zang R, Song P, Bie F, Huai Q, Li Y, Liu Y, Zhou B, Bie Y, Yang Z, Gao S. Utility of 18F-FDG uptake in predicting major pathological response to neoadjuvant immunotherapy in patients with resectable non‑small cell lung cancer. Transl Oncol 2023; 35:101725. [PMID: 37421908 DOI: 10.1016/j.tranon.2023.101725] [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: 02/20/2023] [Revised: 06/10/2023] [Accepted: 06/17/2023] [Indexed: 07/10/2023] Open
Abstract
PURPOSE The aim of present study was to investigate the efficiency of 18F-FDG uptake in predicting major pathological response (MPR) in resectable non-small cell lung cancer (NSCLC) patients with neoadjuvant immunotherapy. METHODS A total of 104 patients with stage I-IIIB NSCLC were retrospectively derived from National Cancer Center of China, of which 36 cases received immune checkpoint inhibitors (ICIs) monotherapy (I-M) and 68 cases with ICI combination therapy (I-C). 18F-FDG PET-CT scans were performed at baseline and after neoadjuvant therapy (NAT). Receiver-operating characteristic (ROC) curve analyses were conducted and area under ROC curve (AUC) was calculated for biomarkers including maximum standardized uptake value (SUVmax), inflammatory biomarkers, tumor mutation burden (TMB), PD-L1 tumor proportion score (TPS) and iRECIST. RESULTS Fifty-four resected NSCLC tumors achieved MPR (51.9%, 54/104). In both neoadjuvant I-M and I-C cohorts, post-NAT SUVmax and the percentage changes of SUVmax (ΔSUVmax%) were significantly lower in the patients with MPR versus non-MPR (p < 0.01), and were also negatively correlated with the degree of pathological regression (p < 0.01). The AUC of ΔSUVmax% for predicting MPR was respectively 1.00 (95% CI: 1.00-1.00) in neoadjuvant I-M cohort and 0.94 (95% CI: 0.86-1.00) in I-C cohort. Baseline SUVmax had a statistical prediction value for MPR only in I-M cohort, with an AUC up to 0.76 at the threshold of 17.0. ΔSUVmax% showed an obvious advantage in MPR prediction over inflammatory biomarkers, TMB, PD-L1 TPS and iRECIST. CONCLUSION 18F-FDG uptake can predict MPR in NSCLC patients with neoadjuvant immunotherapy.
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Affiliation(s)
- Xiaowei Chen
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Guangyu Bai
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Ruochuan Zang
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Peng Song
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Fenglong Bie
- Institute of Oncology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
| | - Qilin Huai
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yuan Li
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yang Liu
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Bolun Zhou
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yifan Bie
- Department of Radiology, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Zhenlin Yang
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
| | - Shugeng Gao
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
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13
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Holzgreve A, Taugner J, Käsmann L, Müller P, Tufman A, Reinmuth N, Li M, Winkelmann M, Unterrainer LM, Nieto AE, Bartenstein P, Kunz WG, Ricke J, Belka C, Eze C, Unterrainer M, Manapov F. Metabolic patterns on [ 18F]FDG PET/CT in patients with unresectable stage III NSCLC undergoing chemoradiotherapy ± durvalumab maintenance treatment. Eur J Nucl Med Mol Imaging 2023; 50:2466-2476. [PMID: 36951991 PMCID: PMC10250493 DOI: 10.1007/s00259-023-06192-6] [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: 01/03/2023] [Accepted: 03/05/2023] [Indexed: 03/24/2023]
Abstract
PURPOSE In patients with unresectable stage III non-small-cell lung cancer (NSCLC), durvalumab maintenance treatment after chemoradiotherapy (CRT) significantly improves survival. So far, however, metabolic changes of tumoral lesions and secondary lymphoid organs under durvalumab are unknown. Hence, we assessed changes on [18F]FDG PET/CT in comparison to patients undergoing CRT alone. METHODS Forty-three patients with [18F]FDG PET/CT both before and after standard CRT for unresectable stage III NSCLC were included, in 16/43 patients durvalumab maintenance treatment was initiated (CRT-IO) prior to the second PET/CT. Uptake of tumor sites and secondary lymphoid organs was compared between CRT and CRT-IO. Also, readers were blinded for durvalumab administration and reviewed scans for findings suspicious for immunotherapy-related adverse events (irAE). RESULTS Initial uptake characteristics were comparable. However, under durvalumab, diverging metabolic patterns were noted: There was a significantly higher reduction of tumoral uptake intensity in CRT-IO compared to CRT, e.g. median decrease of SUVmax -70.0% vs. -24.8%, p = 0.009. In contrast, the spleen uptake increased in CRT-IO while it dropped in CRT (median + 12.5% vs. -4.4%, p = 0.029). Overall survival was significantly longer in CRT-IO compared to CRT with few events (progression/death) noted in CRT-IO. Findings suggestive of irAE were present on PET/CT more often in CRT-IO (12/16) compared to CRT (8/27 patients), p = 0.005. CONCLUSION Durvalumab maintenance treatment after CRT leads to diverging tumoral metabolic changes, but also increases splenic metabolism and leads to a higher proportion of findings suggestive of irAE compared to patients without durvalumab. Due to significantly prolonged survival with durvalumab, survival analysis will be substantiated in correlation to metabolic changes as soon as more clinical events are present.
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Affiliation(s)
- Adrien Holzgreve
- Department of Nuclear Medicine, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.
| | - Julian Taugner
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - Lukas Käsmann
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
- Member of the German Center for Lung Research (DZL), Comprehensive Pneumology Center Munich (CPC-M), Munich, Germany
- German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
| | - Philipp Müller
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Amanda Tufman
- Member of the German Center for Lung Research (DZL), Comprehensive Pneumology Center Munich (CPC-M), Munich, Germany
- Department of Internal Medicine V, University Hospital, LMU Munich, Munich, Germany
| | | | - Minglun Li
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - Michael Winkelmann
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Lena M Unterrainer
- Department of Nuclear Medicine, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany
| | - Alexander E Nieto
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - Peter Bartenstein
- Department of Nuclear Medicine, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany
- German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
| | - Wolfgang G Kunz
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Jens Ricke
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Claus Belka
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
- Member of the German Center for Lung Research (DZL), Comprehensive Pneumology Center Munich (CPC-M), Munich, Germany
- German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
| | - Chukwuka Eze
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - Marcus Unterrainer
- Department of Nuclear Medicine, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany
- German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Farkhad Manapov
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
- Member of the German Center for Lung Research (DZL), Comprehensive Pneumology Center Munich (CPC-M), Munich, Germany
- German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
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14
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Kudura K, Ritz N, Templeton AJ, Kutzker T, Foerster R, Antwi K, Kreissl MC, Hoffmann MHK. Predictive Value of Total Metabolic Tumor Burden Prior to Treatment in NSCLC Patients Treated with Immune Checkpoint Inhibition. J Clin Med 2023; 12:jcm12113725. [PMID: 37297920 DOI: 10.3390/jcm12113725] [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: 03/29/2023] [Revised: 04/29/2023] [Accepted: 05/26/2023] [Indexed: 06/12/2023] Open
Abstract
OBJECTIVES We aimed to assess the predictive value of the total metabolic tumor burden prior to treatment in patients with advanced non-small-cell lung cancer (NSCLC) receiving immune checkpoint inhibitors (ICIs). METHODS Pre-treatment 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography/computed tomography (PET/CT) scans performed in two consecutive years for staging in adult patients with confirmed NSCLC were considered. Volume, maximum/mean standardized uptake value (SUVmax/SUVmean), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were assessed per delineated malignant lesion (including primary tumor, regional lymph nodes and distant metastases) in addition to the morphology of the primary tumor and clinical data. Total metabolic tumor burden was captured by totalMTV and totalTLG. Overall survival (OS), progression-free survival (PFS) and clinical benefit (CB) were used as endpoints for response to treatment. RESULTS A total of 125 NSCLC patients were included. Osseous metastases were the most frequent distant metastases (n = 17), followed by thoracal distant metastases (pulmonal = 14 and pleural = 13). Total metabolic tumor burden prior to treatment was significantly higher in patients treated with ICIs (mean totalMTV ± standard deviation (SD) 72.2 ± 78.7; mean totalTLG ± SD 462.2 ± 538.9) compared to those without ICI treatment (mean totalMTV ± SD 58.1 ± 233.8; mean totalTLG ± SD 290.0 ± 784.2). Among the patients who received ICIs, a solid morphology of the primary tumor on imaging prior to treatment was the strongest outcome predictor for OS (Hazard ratio HR 28.04, p < 0.01), PFS (HR 30.89, p < 0.01) and CB (parameter estimation PE 3.46, p < 0.01), followed by the metabolic features of the primary tumor. Interestingly, total metabolic tumor burden prior to immunotherapy showed a negligible impact on OS (p = 0.04) and PFS (p = 0.01) after treatment given the hazard ratios of 1.00, but also on CB (p = 0.01) given the PE < 0.01. Overall, biomarkers on pre-treatment PET/CT scans showed greater predictive power in patients receiving ICIs, compared to patients without ICI treatment. CONCLUSIONS Morphological and metabolic properties of the primary tumors prior to treatment in advanced NSCLC patients treated with ICI showed great outcome prediction performances, as opposed to the pre-treatment total metabolic tumor burdens, captured by totalMTV and totalTLG, both with negligible impact on OS, PFS and CB. However, the outcome prediction performance of the total metabolic tumor burden might be influenced by the value itself (e.g., poorer prediction performance at very high or very low values of total metabolic tumor burden). Further studies including subgroup analysis with regards to different values of total metabolic tumor burden and their respective outcome prediction performances might be needed.
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Affiliation(s)
- Ken Kudura
- Department of Nuclear Medicine, Sankt Clara Hospital, 4058 Basel, Switzerland
- Department of Radiology, Sankt Clara Hospital, 4058 Basel, Switzerland
- Sankt Clara Research, 4002 Basel, Switzerland
- Division of Nuclear Medicine, Department of Radiology and Nuclear Medicine, University Hospital Magdeburg, 39120 Magdeburg, Germany
| | - Nando Ritz
- Faculty of Medicine, University of Basel, 4001 Basel, Switzerland
| | - Arnoud J Templeton
- Sankt Clara Research, 4002 Basel, Switzerland
- Faculty of Medicine, University of Basel, 4001 Basel, Switzerland
| | - Tim Kutzker
- Faculty of Applied Statistics, Humboldt University, 10117 Berlin, Germany
| | - Robert Foerster
- Department of Radiooncology, Cantonal Hospital Winterthur, 8400 Winterthur, Switzerland
| | - Kwadwo Antwi
- Department of Nuclear Medicine, Sankt Clara Hospital, 4058 Basel, Switzerland
- Department of Radiology, Sankt Clara Hospital, 4058 Basel, Switzerland
| | - Michael C Kreissl
- Division of Nuclear Medicine, Department of Radiology and Nuclear Medicine, University Hospital Magdeburg, 39120 Magdeburg, Germany
| | - Martin H K Hoffmann
- Department of Nuclear Medicine, Sankt Clara Hospital, 4058 Basel, Switzerland
- Department of Radiology, Sankt Clara Hospital, 4058 Basel, Switzerland
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15
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Malet J, Ancel J, Moubtakir A, Papathanassiou D, Deslée G, Dewolf M. Assessment of the Association between Entropy in PET/CT and Response to Anti-PD-1/PD-L1 Monotherapy in Stage III or IV NSCLC. Life (Basel) 2023; 13:life13041051. [PMID: 37109580 PMCID: PMC10142835 DOI: 10.3390/life13041051] [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: 03/09/2023] [Revised: 04/12/2023] [Accepted: 04/17/2023] [Indexed: 04/29/2023] Open
Abstract
Anti-PD-1/PD-L1 therapy indications are broadened in non-small cell lung cancer (NSCLC) although immune checkpoint inhibitors (ICI) do not provide benefits for the entire population. Texture features based on positron emission tomography/computed tomography (PET/CT), especially entropy (based on a gray-level co-occurrence matrix (GLCM)), could be interesting as predictors in NSCLC. The aim of our retrospective study was to evaluate the association between GLCM-entropy and response to anti-PD-1/PD-L1 monotherapy at the first evaluation in stage III or IV NSCLC, comparing patients with progressive disease (PD) and non-progressive disease (non-PD). In total, 47 patients were included. Response Evaluation Criteria in Solid Tumors (RECIST 1.1) were used to evaluate the response to ICI treatment (nivolumab, pembrolizumab, or atezolizumab). At the first evaluation, 25 patients were PD and 22 were non-PD. GLCM-entropy was not predictive of response at the first evaluation. Furthermore, GLCM-entropy was not associated with progression-free survival (PFS) (p = 0.393) or overall survival (OS) (p = 0.220). Finally, GLCM-entropy measured in PET/CT performed before ICI initiation in stage III or IV NSCLC was not predictive of response at the first evaluation. However, this study demonstrates the feasibility of using texture parameters in routine clinical practice. The interest of measuring PET/CT texture parameters in NSCLC remains to be evaluated in larger prospective studies.
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Affiliation(s)
- Julie Malet
- Department of Respiratory Diseases, Reims University Hospital, 45, Rue Cognacq-Jay, 51100 Reims, France
| | - Julien Ancel
- Department of Respiratory Diseases, Reims University Hospital, 45, Rue Cognacq-Jay, 51100 Reims, France
- INSERM UMRS 1250, University of Reims Champagne-Ardenne, 51100 Reims, France
| | - Abdenasser Moubtakir
- Department of Nuclear Medicine, Institut Godinot, 1, Rue du Général Koenig, 51100 Reims, France
| | - Dimitri Papathanassiou
- Department of Nuclear Medicine, Institut Godinot, 1, Rue du Général Koenig, 51100 Reims, France
- UFR de Médecine, Reims-Champagne Ardenne University, 1, Rue Cognacq-Jay, CEDEX 51095 Reims, France
- CReSTIC (Centre de Recherche en Sciences et Technologies de l'Information et de la Communication), EA 3804, University of Reims Champagne-Ardenne, Moulin de la Housse, BP 1039, CEDEX 51687 Reims, France
| | - Gaëtan Deslée
- Department of Respiratory Diseases, Reims University Hospital, 45, Rue Cognacq-Jay, 51100 Reims, France
- INSERM UMRS 1250, University of Reims Champagne-Ardenne, 51100 Reims, France
| | - Maxime Dewolf
- Department of Respiratory Diseases, Reims University Hospital, 45, Rue Cognacq-Jay, 51100 Reims, France
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Ventura D, Schindler P, Masthoff M, Görlich D, Dittmann M, Heindel W, Schäfers M, Lenz G, Wardelmann E, Mohr M, Kies P, Bleckmann A, Roll W, Evers G. Radiomics of Tumor Heterogeneity in 18F-FDG-PET-CT for Predicting Response to Immune Checkpoint Inhibition in Therapy-Naïve Patients with Advanced Non-Small-Cell Lung Cancer. Cancers (Basel) 2023; 15:cancers15082297. [PMID: 37190228 DOI: 10.3390/cancers15082297] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 03/31/2023] [Accepted: 04/11/2023] [Indexed: 05/17/2023] Open
Abstract
We aimed to evaluate the predictive and prognostic value of baseline 18F-FDG-PET-CT (PET-CT) radiomic features (RFs) for immune checkpoint-inhibitor (CKI)-based first-line therapy in advanced non-small-cell lung cancer (NSCLC) patients. In this retrospective study 44 patients were included. Patients were treated with either CKI-monotherapy or combined CKI-based immunotherapy-chemotherapy as first-line treatment. Treatment response was assessed by the Response Evaluation Criteria in Solid Tumors (RECIST). After a median follow-up of 6.4 months patients were stratified into "responder" (n = 33) and "non-responder" (n = 11). RFs were extracted from baseline PET and CT data after segmenting PET-positive tumor volume of all lesions. A Radiomics-based model was developed based on a Radiomics signature consisting of reliable RFs that allow classification of response and overall progression using multivariate logistic regression. These RF were additionally tested for their prognostic value in all patients by applying a model-derived threshold. Two independent PET-based RFs differentiated well between responders and non-responders. For predicting response, the area under the curve (AUC) was 0.69 for "PET-Skewness" and 0.75 predicting overall progression for "PET-Median". In terms of progression-free survival analysis, patients with a lower value of PET-Skewness (threshold < 0.2014; hazard ratio (HR) 0.17, 95% CI 0.06-0.46; p < 0.001) and higher value of PET-Median (threshold > 0.5233; HR 0.23, 95% CI 0.11-0.49; p < 0.001) had a significantly lower probability of disease progression or death. Our Radiomics-based model might be able to predict response in advanced NSCLC patients treated with CKI-based first-line therapy.
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Affiliation(s)
- David Ventura
- Department of Nuclear Medicine, University Hospital Muenster, 48149 Muenster, Germany
- West German Cancer Center (WTZ), 48149 Muenster, Germany
| | - Philipp Schindler
- West German Cancer Center (WTZ), 48149 Muenster, Germany
- Clinic for Radiology, University and University Hospital Muenster, 48149 Muenster, Germany
| | - Max Masthoff
- West German Cancer Center (WTZ), 48149 Muenster, Germany
- Clinic for Radiology, University and University Hospital Muenster, 48149 Muenster, Germany
| | - Dennis Görlich
- Institute of Biostatistics and Clinical Research, University of Muenster, 48149 Muenster, Germany
| | - Matthias Dittmann
- Department of Nuclear Medicine, University Hospital Muenster, 48149 Muenster, Germany
- West German Cancer Center (WTZ), 48149 Muenster, Germany
| | - Walter Heindel
- West German Cancer Center (WTZ), 48149 Muenster, Germany
- Clinic for Radiology, University and University Hospital Muenster, 48149 Muenster, Germany
| | - Michael Schäfers
- Department of Nuclear Medicine, University Hospital Muenster, 48149 Muenster, Germany
- West German Cancer Center (WTZ), 48149 Muenster, Germany
| | - Georg Lenz
- West German Cancer Center (WTZ), 48149 Muenster, Germany
- Department of Medicine A-Hematology, Oncology, Hemostaseology and Pneumology, University Hospital Muenster, 48149 Muenster, Germany
| | - Eva Wardelmann
- West German Cancer Center (WTZ), 48149 Muenster, Germany
- Gerhard-Domagk-Institute of Pathology, University Hospital Muenster, 48149 Muenster, Germany
| | - Michael Mohr
- West German Cancer Center (WTZ), 48149 Muenster, Germany
- Department of Medicine A-Hematology, Oncology, Hemostaseology and Pneumology, University Hospital Muenster, 48149 Muenster, Germany
| | - Peter Kies
- Department of Nuclear Medicine, University Hospital Muenster, 48149 Muenster, Germany
- West German Cancer Center (WTZ), 48149 Muenster, Germany
| | - Annalen Bleckmann
- West German Cancer Center (WTZ), 48149 Muenster, Germany
- Department of Medicine A-Hematology, Oncology, Hemostaseology and Pneumology, University Hospital Muenster, 48149 Muenster, Germany
| | - Wolfgang Roll
- Department of Nuclear Medicine, University Hospital Muenster, 48149 Muenster, Germany
- West German Cancer Center (WTZ), 48149 Muenster, Germany
| | - Georg Evers
- West German Cancer Center (WTZ), 48149 Muenster, Germany
- Department of Medicine A-Hematology, Oncology, Hemostaseology and Pneumology, University Hospital Muenster, 48149 Muenster, Germany
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Grambow-Velilla J, Seban RD, Chouahnia K, Assié JB, Champion L, Girard N, Bonardel G, Matton L, Soussan M, Chouaïd C, Duchemann B. Total Metabolic Tumor Volume on 18F-FDG PET/CT Is a Useful Prognostic Biomarker for Patients with Extensive Small-Cell Lung Cancer Undergoing First-Line Chemo-Immunotherapy. Cancers (Basel) 2023; 15:cancers15082223. [PMID: 37190152 DOI: 10.3390/cancers15082223] [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: 03/02/2023] [Revised: 03/25/2023] [Accepted: 04/06/2023] [Indexed: 05/17/2023] Open
Abstract
Background: We aimed to evaluate the prognostic value of imaging biomarkers on 18F-FDG PET/CT in extensive-stage small-cell lung cancer (ES-SCLC) patients undergoing first-line chemo-immunotherapy. Methods: In this multicenter and retrospective study, we considered two cohorts, depending on the type of first-line therapy: chemo-immunotherapy (CIT) versus chemotherapy alone (CT). All patients underwent baseline 18-FDG PET/CT before therapy between June 2016 and September 2021. We evaluated clinical, biological, and PET parameters, and used cutoffs from previously published studies or predictiveness curves to assess the association with progression-free survival (PFS) or overall survival (OS) with Cox prediction models. Results: Sixty-eight patients were included (CIT: CT) (36: 32 patients). The median PFS was 5.9:6.5 months, while the median OS was 12.1:9.8 months. dNLR (the derived neutrophils/(leucocytes-neutrophils) ratio) was an independent predictor of short PFS and OS in the two cohorts (p < 0.05). High total metabolic tumor volume (TMTVhigh if > 241 cm3) correlated with outcomes, but only in the CIT cohort (PFS for TMTVhigh in multivariable analysis: HR 2.5; 95%CI 1.1-5.9). Conclusion: Baseline 18F-FDG PET/CT using TMTV could help to predict worse outcomes for ES-SCLC patients undergoing first-line CIT. This suggests that baseline TMTV may be used to identify patients that are unlikely to benefit from CIT.
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Affiliation(s)
- Julia Grambow-Velilla
- Department of Nuclear Medicine, AP-HP, Avicenne University Hospital, 93000 Bobigny, France
- Department of Nuclear Medicine, AP-HP, European Hospital Georges-Pompidou, University of Paris, 75015 Paris, France
| | - Romain-David Seban
- Department of Nuclear Medicine, Institut Curie, 92210 Saint-Cloud, France
- Laboratoire d'Imagerie Translationnelle en Oncologie, Inserm, Institut Curie, 91401 Orsay, France
| | - Kader Chouahnia
- Department of Medical Thoracic and Medical Oncology, AP-HP, Avicenne University Hospital, 93000 Bobigny, France
| | | | - Laurence Champion
- Department of Nuclear Medicine, Institut Curie, 92210 Saint-Cloud, France
- Laboratoire d'Imagerie Translationnelle en Oncologie, Inserm, Institut Curie, 91401 Orsay, France
| | - Nicolas Girard
- Institut du Thorax Curie Montsouris, Institut Curie, 75005 Paris, France
- Paris Saclay, UVSQ, UFR Simone Veil, 78180 Versailles, France
| | - Gerald Bonardel
- Nuclear Medicine, Centre Cardiologique du Nord, 93200 Saint-Denis, France
| | - Lise Matton
- Department of Medical Thoracic and Medical Oncology, AP-HP, Avicenne University Hospital, 93000 Bobigny, France
| | - Michael Soussan
- Department of Nuclear Medicine, AP-HP, Avicenne University Hospital, 93000 Bobigny, France
| | - Christos Chouaïd
- Department of Pneumology, Centre Hospitalier Inter-Communal de Créteil, Paris-Est University, 94010 Créteil, France
| | - Boris Duchemann
- Department of Medical Thoracic and Medical Oncology, AP-HP, Avicenne University Hospital, 93000 Bobigny, France
- Inserm UMR 1272 "Hypoxie et Poumon", UFR SMBH Léonard de Vinci, Université Sorbonne Paris Nord, 93000 Bobigny, France
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18
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Zhang L, Xu C, Zhang X, Wang J, Jiang H, Chen J, Zhang H. A novel analytical approach for outcome prediction in newly diagnosed NSCLC based on [ 18F]FDG PET/CT metabolic parameters, inflammatory markers, and clinical variables. Eur Radiol 2023; 33:1757-1768. [PMID: 36222865 DOI: 10.1007/s00330-022-09150-2] [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: 05/07/2022] [Revised: 08/24/2022] [Accepted: 09/06/2022] [Indexed: 11/04/2022]
Abstract
OBJECTIVES To develop a novel analytical approach based on 18F-fluorodeoxyglucose ([18F]FDG) positron emission tomography (PET) metabolic parameters, serum inflammatory markers, and clinical variables to improve the outcome prediction in NSCLC. METHODS A total of 190 newly diagnosed NSCLC patients who underwent pretreatment [18F]FDG PET/CT were retrospectively enrolled and divided into a training cohort (n = 127) and a test cohort (n = 63). Cox regression analysis was used to investigate the predictive values of PET metabolic parameters, inflammation markers, and clinical variables for progression-free survival (PFS) and overall survival (OS). Based on the results of multivariate analysis, PET-based, clinical, and combined models were constructed. The predictive performance of different models was evaluated using time-dependent ROC curve analysis, Harrell concordance index (C-index), calibration curve, and decision curve analysis. RESULTS The combined models incorporating SULmax, MTV, NLR, and ECOG PS demonstrated significant prognostic superiority over PET-based models, clinical models, and TNM stage in terms of both PFS (C-index: 0.813 vs. 0.786 vs. 0.776 vs. 0.678, respectively) and OS (C-index: 0.856 vs. 0.792 vs. 0.781 vs. 0.674, respectively) in the training cohort. Similar results were observed in the test cohort for PFS (C-index: 0.808 vs. 0.764 vs. 0.748 vs. 0.679, respectively) and OS (C-index: 0.836 vs. 0.785 vs. 0.726 vs. 0.660, respectively) prediction. The combined model calibrated well in two cohorts. Decision curve analysis supported the clinical utility of the combined model. CONCLUSIONS We reported a novel analytical approach combining PET metabolic information with inflammatory biomarker and clinical characteristics, which could significantly improve outcome prediction in newly diagnosed NSCLC. KEY POINTS • The nomogram incorporating SULmax, MTV, NLR, and ECOG PS outperformed the TNM stage for outcome prediction in patients with newly diagnosed NSCLC. • The established nomogram could provide refined prognostic stratification.
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Affiliation(s)
- Lixia Zhang
- Department of Nuclear Medicine, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, 310006, Zhejiang, China
| | - Caiyun Xu
- Department of Nuclear Medicine, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, 310006, Zhejiang, China
| | - Xiaohui Zhang
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, Zhejiang, China. .,Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, 310009, Zhejiang, China. .,Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, 310009, Zhejiang, China.
| | - Jing Wang
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, Zhejiang, China. .,Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, 310009, Zhejiang, China. .,Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, 310009, Zhejiang, China.
| | - Han Jiang
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, Zhejiang, China.,Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, 310009, Zhejiang, China.,Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, 310009, Zhejiang, China
| | - Jinyan Chen
- Department of Nuclear Medicine, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, 310006, Zhejiang, China
| | - Hong Zhang
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, Zhejiang, China. .,Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, 310009, Zhejiang, China. .,Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, 310009, Zhejiang, China.
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19
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FDG-PET metrics in advanced non-small cell lung cancer (NSCLC): a review and meta-analysis. Clin Transl Imaging 2023. [DOI: 10.1007/s40336-023-00542-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/12/2023]
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20
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Wang X, Yang X, Wang J, Dong C, Ding J, Wu M, Wang Y, Ding H, Zhang H, Sang X, Zhao H, Huo L. Metabolic Tumor Volume Measured by 18F-FDG PET/CT is Associated with the Survival of Unresectable Hepatocellular Carcinoma Treated with PD-1/PD-L1 Inhibitors Plus Molecular Targeted Agents. J Hepatocell Carcinoma 2023; 10:587-598. [PMID: 37063093 PMCID: PMC10094465 DOI: 10.2147/jhc.s401647] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Accepted: 03/21/2023] [Indexed: 04/18/2023] Open
Abstract
Purpose The combination of PD-1/PD-L1 inhibitors and molecular targeted agents showed promising efficacy for unresectable hepatocellular carcinoma (uHCC). This study aimed to investigate the prognostic value of metabolic parameters from 18F-fluorodeoxyglucose positron emission tomography-computed tomography (18F-FDG PET/CT) in patients with uHCC underwent the combined therapies. Patients and Methods Patients with uHCC treated with a combination of immunotherapy and targeted therapy who underwent baseline 18F-FDG PET/CT between July 2018 and December 2021 were recruited retrospectively. The metabolic tumor volume (MTV), total lesion glycolysis (TLG), maximum standardized uptake values (SUVmax), and clinical and biological parameters were recorded. A multivariate prediction model was developed for overall survival (OS) using these parameters together with clinical prognostic factors. Results Seventy-seven patients were finally included. The median OS was 16.8 months. We found that a high MTV (≥39.65 cm3 as the median value) was significantly associated with OS (P<0.05). In multivariate analyses for OS, a high MTV, high Eastern Cooperative Oncology Group performance status (ECOG-PS, ≥1), Child-Pugh (B-C) grade, and the presence of bone metastasis were significantly associated with poor OS (HR 1.371, HR 3.73, HR 15.384, and HR 2.994, all P<0.05, respectively). A multivariate prognostic model including MTV and prognostic factors, such as ECOG-PS, Child-Pugh grade, and bone metastasis, further improved the identification of different OS subgroups. Conclusion High MTV is an adverse prognostic factor in patients with uHCC treated with a combination of immunotherapy and molecular targeted agents. Integrating PET/CT parameters with clinical prognostic factors could help to personalize immunotherapy.
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Affiliation(s)
- Xuezhu Wang
- Department of Nuclear Medicine, Beijing Key Laboratory of Molecular Targeted Diagnosis and Therapy in Nuclear Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Center for Rare Diseases Research, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
| | - Xu Yang
- Department of Liver Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
| | - Jingnan Wang
- Department of Nuclear Medicine, Beijing Key Laboratory of Molecular Targeted Diagnosis and Therapy in Nuclear Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Center for Rare Diseases Research, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
| | - Chengyan Dong
- GE Healthcare China, Beijing, People’s Republic of China
| | - Jie Ding
- Department of Nuclear Medicine, Beijing Key Laboratory of Molecular Targeted Diagnosis and Therapy in Nuclear Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Center for Rare Diseases Research, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
| | - Meiqi Wu
- Department of Nuclear Medicine, Beijing Key Laboratory of Molecular Targeted Diagnosis and Therapy in Nuclear Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Center for Rare Diseases Research, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
| | - Yanyu Wang
- Department of Liver Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
| | - Haiyan Ding
- Department of Biomedical Engineering, Tsinghua University, Beijing, People’s Republic of China
| | - Hui Zhang
- Department of Biomedical Engineering, Tsinghua University, Beijing, People’s Republic of China
| | - Xinting Sang
- Department of Liver Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
| | - Haitao Zhao
- Department of Liver Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
- Correspondence: Li Huo; Haitao Zhao, #1 Shuaifuyuan, Dongcheng District, Beijing, People’s Republic of China, Tel +86 13910801986; +86 13901246374, Email ;
| | - Li Huo
- Department of Nuclear Medicine, Beijing Key Laboratory of Molecular Targeted Diagnosis and Therapy in Nuclear Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Center for Rare Diseases Research, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
- Correspondence: Li Huo; Haitao Zhao, #1 Shuaifuyuan, Dongcheng District, Beijing, People’s Republic of China, Tel +86 13910801986; +86 13901246374, Email ;
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21
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Kudura K, Ritz N, Kutzker T, Hoffmann MHK, Templeton AJ, Foerster R, Kreissl MC, Antwi K. Predictive Value of Baseline FDG-PET/CT for the Durable Response to Immune Checkpoint Inhibition in NSCLC Patients Using the Morphological and Metabolic Features of Primary Tumors. Cancers (Basel) 2022; 14:cancers14246095. [PMID: 36551581 PMCID: PMC9776660 DOI: 10.3390/cancers14246095] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 12/01/2022] [Accepted: 12/09/2022] [Indexed: 12/14/2022] Open
Abstract
Objectives: We aimed to investigate the predictive value of baseline 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography/computed tomography (FDG-PET/CT) for durable responses to immune checkpoint inhibitors (ICIs) by linking the morphological and metabolic features of primary tumors (PTs) in nonsmall cell lung cancer (NSCLC) patients. Methods: For the purpose of this single-center study, the imaging data of the patients with a first diagnosis of NSCLC and an available baseline FDG-PET/CT between 2020 and 2021 were retrospectively assessed. The baseline characteristics were collected based on clinical reports and interdisciplinary tumor board documentation. The metabolic (such as standardized uptake value SUV maximum and mean (SUVmax, SUV mean), metabolic tumor volume (MTV), total lesion glycolysis (TLG)) and morphological (such as volume, morphology, margin, and presence of lymphangiosis through imaging) features of all the PTs were retrospectively assessed using FDG-PET/CT. Overall survival (OS), progression-free survival (PFS), clinical benefit (CB) and mortality rate were used as endpoints to define the long-term response to therapy. A backward, stepwise logistic regression analysis was performed in order to define the best model for predicting lasting responses to treatment. Statistical significance was assumed at p < 0.05. Results: A total of 125 patients (median age ± standard deviation (SD) 72.0 ± 9.5 years) were enrolled: 64 men (51.2%) and 61 women (48.8%). Adenocarcinoma was by far the most common histological subtype of NSCLC (47.2%). At the initial diagnosis, the vast majority of all the included patients showed either locally advanced disease (34.4%) or metastatic disease (36.8%). Fifty patients were treated with ICIs either as a first-line (20%) or second-line (20%) therapy, while 75 patients did not receive ICIs. The median values ± SD of PT SUVmax, mean, MTV, and TLG were respectively 10.1 ± 6.0, 6.1 ± 3.5, 13.5 ± 30.7, and 71.4 ± 247.7. The median volume of PT ± SD was 13.7 ± 30.7 cm3. The PTs were most frequently solid (86.4%) with irregular margins (76.8%). Furthermore, in one out of five cases, the morphological evidence of lymphangiosis was seen through imaging (n = 25). The median follow-up ± SD was 18.93 ± 6.98 months. The median values ± SD of OS and PFS were, respectively, 14.80 ± 8.68 months and 14.03 ± 9.02 months. Age, PT volume, SUVmax, TLG, the presence of lymphangiosis features through imaging, and clinical stage IV were very strong long-term outcome predictors of patients treated with ICIs, while no significant outcome predictors could be found for the cohort with no ICI treatment. The optimal cut-off values were determined for PT volume (26.94 cm3) and SUVmax (15.05). Finally, 58% of NSCLC patients treated with ICIs had a CB vs. 78.7% of patients in the cohort with no ICI treatment. However, almost all patients treated with ICIs and with disease progression over time died (mortality in the case of disease progression 95% vs. 62.5% in the cohort without ICIs). Conclusion: Baseline FDG-PET/CT could be used to predict a durable response to ICIs in NSCLC patients. Age, clinical stage IV, lymphangiosis features through imaging, PT volume (thus PT MTV due to a previously demonstrated linear correlation), PT SUVmax, and TLG were very strong long-term outcome predictors. Our results highlight the importance of linking clinical data, as much as morphological features, to the metabolic parameters of primary tumors in a multivariate outcome-predicting model using baseline FDG-PET/CT.
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Affiliation(s)
- Ken Kudura
- Department of Nuclear Medicine, Sankt Clara Hospital, 4058 Basel, Switzerland
- Correspondence:
| | - Nando Ritz
- Faculty of Medicine, University of Basel, 4058 Basel, Switzerland
| | - Tim Kutzker
- Faculty of Applied Statistics, Humboldt University, 10 117 Berlin, Germany
| | | | - Arnoud J. Templeton
- Faculty of Medicine, University of Basel, 4058 Basel, Switzerland
- Sankt Clara Research, 4002 Basel, Switzerland
| | - Robert Foerster
- Department of Radiooncology, Cantonal Hospital Winterthur, 8400 Winterthur, Switzerland
| | - Michael C. Kreissl
- Division of Nuclear Medicine, Department of Radiology and Nuclear Medicine, University Hospital Magdeburg, 39120 Magdeburg, Germany
| | - Kwadwo Antwi
- Department of Nuclear Medicine, Sankt Clara Hospital, 4058 Basel, Switzerland
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22
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Silva SB, Wanderley CWS, Gomes Marin JF, de Macedo MP, do Nascimento ECT, Antonacio FF, Figueiredo CS, Trinconi Cunha M, Cunha FQ, de Castro Junior G. Tumor glycolytic profiling through 18F-FDG PET/CT predicts immune checkpoint inhibitor efficacy in advanced NSCLC. Ther Adv Med Oncol 2022; 14:17588359221138386. [PMID: 36506107 PMCID: PMC9730014 DOI: 10.1177/17588359221138386] [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: 06/29/2022] [Accepted: 10/24/2022] [Indexed: 12/12/2022] Open
Abstract
Background A significant proportion of patients with non-small-cell lung cancer (NSCLC) do not respond to immune checkpoint inhibitors (ICIs). Since metabolic reprogramming with increased glycolysis is a hallmark of cancer and is involved in immune evasion, we used 18F-fluorodeoxyglucose positron emission tomography-computed tomography (18F-FDG PET/CT) to evaluate the baseline glycolytic parameters of patients with advanced NSCLC submitted to ICIs, and assessed their predictive value. Methods 18F-FDG PET/CT results in the 3 months before ICIs treatment were included. Maximum standardized uptake values, whole metabolic tumor volume (wMTV), and whole-body total lesion glycolysis (wTLG) were evaluated. Cutoff values for high or low glycolytic categories were determined using receiver-operating characteristic curves. Progression-free survival (PFS) and overall survival (OS) were evaluated. Patients with a complete response and a matching group with resistance to ICIs underwent immunohistochemistry analysis. An unsupervised k-means clustering model integrating programmed cell death ligand 1 (PD-L1) expression, glycolytic parameters, and ICIs therapy was performed. Results In all, 98 patients were included. Lower baseline 18F-FDG PET/CT parameters were associated with responses to ICIs. Patients with low wMTV or wTLG had improved PFS and OS. High wTLG, strong tumor expression of glucose transporter-1, and lack of responses were significantly associated. Patients with low glycolytic parameters benefited from ICIs, regardless of chemotherapy. Conversely, those with high parameters benefited from the addition of chemotherapy. Patients with higher wTLG and lower PD-L1 were associated with progression and worse survival to ICIs monotherapy. Conclusions Glycolytic metabolic profiles established through baseline 18F-FDG PET/CT are useful biomarkers for evaluating ICI therapy in advanced NSCLC.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Fernando Q. Cunha
- Center for Research in Inflammatory Diseases (CRID) and Department of Pharmacology, Ribeirao Preto Medical School, University of Sao Paulo, Sao Paulo, Brazil
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Tankyevych O, Trousset F, Latappy C, Berraho M, Dutilh J, Tasu JP, Lamour C, Cheze Le Rest C. Development of Radiomic-Based Model to Predict Clinical Outcomes in Non-Small Cell Lung Cancer Patients Treated with Immunotherapy. Cancers (Basel) 2022; 14:cancers14235931. [PMID: 36497415 PMCID: PMC9739232 DOI: 10.3390/cancers14235931] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Revised: 11/07/2022] [Accepted: 11/23/2022] [Indexed: 12/02/2022] Open
Abstract
Purpose: We aimed to assess the ability of radiomics features extracted from baseline (PET/CT0) and follow-up PET/CT scans, as well as their evolution (delta-radiomics), to predict clinical outcome (durable clinical benefit (DCB), progression, response to therapy, OS and PFS) in non-small cell lung cancer (NSCLC) patients treated with immunotherapy. Methods: 83 NSCLC patients treated with immunotherapy who underwent a baseline PET/CT were retrospectively included. Response was assessed at 6−8 weeks (PET/CT1) using PERCIST criteria and at 3 months with iPERCIST (PET/CT2) or RECIST 1.1 criteria using CT. The predictive performance of clinical parameters (CP), standard PET metrics (SUV, Metabolic Tumor volume, Total Lesion Glycolysis), delta-radiomics and PET and CT radiomics features extracted at baseline and during follow-up were studied. Seven multivariate models with different combinations of CP and radiomics were trained on a subset of patients (75%) using least absolute shrinkage, selection operator (LASSO) and random forest classification with 10-fold cross-validation to predict outcome. Model validation was performed on the remaining patients (25%). Overall and progression-free survival was also performed by Kaplan−Meier survival analysis. Results: Numerous radiomics and delta-radiomics parameters had a high individual predictive value of patient outcome with areas under receiver operating characteristics curves (AUCs) >0.80. Their performance was superior to that of CP and standard PET metrics. Several multivariate models were also promising, especially for the prediction of progression (AUCs of 1 and 0.96 for the training and testing subsets with the PET-CT model (PET/CT0)) or DCB (AUCs of 0.85 and 0.83 with the PET-CT-CP model (PET/CT0)). Conclusions: Delta-radiomics and radiomics features extracted from baseline and follow-up PET/CT images could predict outcome in NSCLC patients treated with immunotherapy and identify patients who would benefit from this new standard. These data reinforce the rationale for the use of advanced image analysis of PET/CT scans to further improve personalized treatment management in advanced NSCLC.
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Affiliation(s)
- Olena Tankyevych
- Nuclear Medicine Department, Poitiers University Hospital, 86000 Poitiers, France
- LaTIM, INSERM, UMR 1101, 29200 Brest, France
| | - Flora Trousset
- Nuclear Medicine Department, Poitiers University Hospital, 86000 Poitiers, France
| | - Claire Latappy
- Nuclear Medicine Department, Poitiers University Hospital, 86000 Poitiers, France
| | - Moran Berraho
- Nuclear Medicine Department, Poitiers University Hospital, 86000 Poitiers, France
| | - Julien Dutilh
- Oncology Department, Poitiers University Hospital, 86000 Poitiers, France
| | - Jean Pierre Tasu
- LaTIM, INSERM, UMR 1101, 29200 Brest, France
- Medical School, University of Poitiers, 86000 Poitiers, France
- Radiology Department, Poitiers University Hospital, 86000 Poitiers, France
| | - Corinne Lamour
- Oncology Department, Poitiers University Hospital, 86000 Poitiers, France
| | - Catherine Cheze Le Rest
- Nuclear Medicine Department, Poitiers University Hospital, 86000 Poitiers, France
- LaTIM, INSERM, UMR 1101, 29200 Brest, France
- Medical School, University of Poitiers, 86000 Poitiers, France
- Correspondence:
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Ling T, Zhang L, Peng R, Yue C, Huang L. Prognostic value of 18F-FDG PET/CT in patients with advanced or metastatic non-small-cell lung cancer treated with immune checkpoint inhibitors: A systematic review and meta-analysis. Front Immunol 2022; 13:1014063. [PMID: 36466905 PMCID: PMC9713836 DOI: 10.3389/fimmu.2022.1014063] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 10/20/2022] [Indexed: 08/30/2023] Open
Abstract
PURPOSE This study aimed to investigate the value of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) in predicting early immunotherapy response of immune checkpoint inhibitors (ICIs) in patients with advanced or metastatic non-small-cell lung cancer (NSCLC). METHODS A comprehensive search of PubMed, Web of science, Embase and the Cochrane library was performed to examine the prognostic value of 18F-FDG PET/CT in predicting early immunotherapy response of ICIs in patients with NSCLC. The main outcomes for evaluation were overall survival (OS) and progression-free survival (PFS). Detailed data from each study were extracted and analyzed using STATA 14.0 software. RESULTS 13 eligible articles were included in this systematic review. Compared to baseline 18F-FDG PET/CT imaging, the pooled hazard ratios (HR) of maximum and mean standardized uptake values SUVmax, SUVmean, MTV and TLG for OS were 0.88 (95% CI: 0.69-1.12), 0.79 (95% CI: 0.50-1.27), 2.10 (95% CI: 1.57-2.82) and 1.58 (95% CI: 1.03-2.44), respectively. The pooled HR of SUVmax, SUVmean, MTV and TLG for PFS were 1.06 (95% CI: 0.68-1.65), 0.66 (95% CI: 0.48-0.90), 1.50 (95% CI: 1.26-1.79), 1.27 (95% CI: 0.92-1.77), respectively. Subgroup analysis showed that high MTV group had shorter OS than low MTV group in both first line group (HR: 1.97, 95% CI: 1.39-2.79) and undefined line group (HR: 2.11, 95% CI: 1.61-2.77). High MTV group also showed a shorter PFS in first line group (HR: 1.85, 95% CI: 1.28-2.68), and low TLG group had a longer OS in undefined group (HR: 1.37, 95% CI: 1.00-1.86). No significant differences were in other subgroup analysis. CONCLUSION Baseline MTV and TLG may have predictive value and should be prospectively studied in clinical trials. Baseline SUVmax and SUVmean may not be appropriate prognostic markers in advanced or metastatic NSCLC patients treated with ICIs. SYSTEMATIC REVIEW REGISTRATION https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=323906, identifier CRD42022323906.
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Affiliation(s)
- Tao Ling
- Department of Pharmacy, Suqian First Hospital, Suqian, China
| | - Lianghui Zhang
- Department of Oncology, Changzhou Traditional Chinese Medicine Hospital, Changzhou, China
| | - Rui Peng
- Department of General Surgery, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Chao Yue
- Department of General Surgery, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Lingli Huang
- Department of Pharmacy, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
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Kaida H, Yasuda T, Shiraishi O, Kato H, Kimura Y, Hanaoka K, Yamada M, Matsukubo Y, Tsurusaki M, Kitajima K, Hattori S, Ishii K. The usefulness of the total metabolic tumor volume for predicting the postoperative recurrence of thoracic esophageal squamous cell carcinoma. BMC Cancer 2022; 22:1176. [PMCID: PMC9664655 DOI: 10.1186/s12885-022-10281-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2022] [Accepted: 11/03/2022] [Indexed: 11/16/2022] Open
Abstract
Abstract
Background
Induction or adjuvant therapies are not always beneficial for thoracic esophageal squamous cell carcinoma (ESCC) patients, and it is thus important to identify patients at high risk for postoperative ESCC recurrence. We investigated the usefulness of the total metabolic tumor volume (TMTV) for predicting the postoperative recurrence of thoracic ESCC.
Methods
We retrospectively analyzed the cases of 163 thoracic ESCC patients (135 men, 28 women; median age of 66 [range 34–82] years) treated at our hospital in 2007–2012. The TMTV was calculated from the fluorine-18 fluorodeoxyglucose (18F-FDG) uptake in the primary lesion and lymph node metastases. The optimal cut-off values for relapse and non-relapse were obtained by the time-dependent receiver operating curve analyses. Relapse-free survival (RFS) was evaluated by the Kaplan-Meier method, and between-subgroup differences in survival were analyzed by log-rank test. The prognostic significance of metabolic parameters and clinicopathological variables was assessed by a Cox proportional hazard regression analysis. The difference in the failure patterns after surgical resection was evaluated using the χ2-test.
Results
The optimal cut-off value of TMTV for discriminating relapse from non-relapse was 3.82. The patients with a TMTV ≥3.82 showed significantly worse prognoses than those with low values (p < 0.001). The TMTV was significantly related to RFS (model 1 for preoperative risk factors: TMTV: hazard ratio [HR] =2.574, p = 0.004; model 2 for preoperative and postoperative risk factors: HR = 1.989, p = 0.044). The combination of the TMTV and cN0–1 or pN0–1 stage significantly stratified the patients into low-and high-risk recurrence groups (TMTV cN0–1, p < 0.001; TMTV pN0–1, p = 0.004). The rates of hematogenous and regional lymph node metastasis were significantly higher in the patients with TMTV ≥3.82 than those with low values (hematogenous metastasis, p < 0.001, regional lymph node metastasis, p = 0.011).
Conclusions
The TMTV was a more significantly independent prognostic factor for RFS than any other PET parameter in patients with resectable thoracic ESCC. The TMTV may be useful for the identifying thoracic ESCC patients at high risk for postoperative recurrence and for deciding the patient management.
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Berz AM, Dromain C, Vietti-Violi N, Boughdad S, Duran R. Tumor response assessment on imaging following immunotherapy. Front Oncol 2022; 12:982983. [PMID: 36387133 PMCID: PMC9641095 DOI: 10.3389/fonc.2022.982983] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 10/04/2022] [Indexed: 11/13/2022] Open
Abstract
In recent years, various systemic immunotherapies have been developed for cancer treatment, such as monoclonal antibodies (mABs) directed against immune checkpoints (immune checkpoint inhibitors, ICIs), oncolytic viruses, cytokines, cancer vaccines, and adoptive cell transfer. While being estimated to be eligible in 38.5% of patients with metastatic solid or hematological tumors, ICIs, in particular, demonstrate durable disease control across many oncologic diseases (e.g., in melanoma, lung, bladder, renal, head, and neck cancers) and overall survival benefits. Due to their unique mechanisms of action based on T-cell activation, response to immunotherapies is characterized by different patterns, such as progression prior to treatment response (pseudoprogression), hyperprogression, and dissociated responses following treatment. Because these features are not encountered in the Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST 1.1), which is the standard for response assessment in oncology, new criteria were defined for immunotherapies. The most important changes in these new morphologic criteria are, firstly, the requirement for confirmatory imaging examinations in case of progression, and secondly, the appearance of new lesions is not necessarily considered a progressive disease. Until today, five morphologic (immune-related response criteria (irRC), immune-related RECIST (irRECIST), immune RECIST (iRECIST), immune-modified RECIST (imRECIST), and intra-tumoral RECIST (itRECIST)) criteria have been developed to accurately assess changes in target lesion sizes, taking into account the specific response patterns after immunotherapy. In addition to morphologic response criteria, 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography/computed tomography (18F-FDG-PET/CT) is a promising option for metabolic response assessment and four metabolic criteria are used (PET/CT Criteria for Early Prediction of Response to Immune Checkpoint Inhibitor Therapy (PECRIT), PET Response Evaluation Criteria for Immunotherapy (PERCIMT), immunotherapy-modified PET Response Criteria in Solid Tumors (imPERCIST5), and immune PERCIST (iPERCIST)). Besides, there is evidence that parameters on 18F-FDG-PET/CT, such as the standardized uptake value (SUV)max and several radiotracers, e.g., directed against PD-L1, may be potential imaging biomarkers of response. Moreover, the emerge of human intratumoral immunotherapy (HIT-IT), characterized by the direct injection of immunostimulatory agents into a tumor lesion, has given new importance to imaging assessment. This article reviews the specific imaging patterns of tumor response and progression and available imaging response criteria following immunotherapy.
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Affiliation(s)
- Antonia M. Berz
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital, Lausanne, Switzerland
- Department of Radiology, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Clarisse Dromain
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital, Lausanne, Switzerland
| | - Naïk Vietti-Violi
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital, Lausanne, Switzerland
| | - Sarah Boughdad
- Department of Nuclear Medicine and Molecular Imaging, Lausanne University Hospital, Lausanne, Switzerland
| | - Rafael Duran
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital, Lausanne, Switzerland
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Jin P, Bai M, Liu J, Yu J, Meng X. Tumor metabolic and secondary lymphoid organ metabolic markers on 18F-fludeoxyglucose positron emission tomography predict prognosis of immune checkpoint inhibitors in advanced lung cancer. Front Immunol 2022; 13:1004351. [DOI: 10.3389/fimmu.2022.1004351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Accepted: 10/06/2022] [Indexed: 11/13/2022] Open
Abstract
BackgroundThe purpose of this study was to investigate the predictive value of tumor metabolic parameters in combination with secondary lymphoid metabolic parameters on positron emission tomography (PET)/computed tomography (CT) for immune checkpoint inhibitor (ICI) prognosis in advanced lung cancer.MethodsThis study retrospectively included 125 patients who underwent 18F-fludeoxyglucose (FDG) PET/CT before ICI therapy, including 41 patients who underwent a second PET/CT scan during ICI treatment. The measured PET/CT parameters included tumor metabolism parameters [maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), total lesion glycolysis (TLG), and total metabolic tumor volume (TMTV)] and secondary lymphoid organ metabolism parameters [spleen-to-liver SUVmax ratio (SLR) and bone marrow-to-liver SUVmax ratio (BLR)]. The correlation of PET/CT metabolic parameters with early ICI treatment response, progression-free survival (PFS), and overall survival (OS) was analyzed.ResultsWithin a median follow-up of 28.7 months, there were 44 responders and 81 non-responders. The median PFS was 8.6 months (95% confidence interval (CI): 5.872–11.328), and the median OS was 20.4 months (95% CI: 15.526–25.274). Pretreatment tumor metabolic parameters were not associated with early treatment responses. The high bone marrow metabolism (BLR >1.03) was significantly associated with a shorter PFS (p = 0.008). Patients with a high TMTV (>168 mL) and high spleen metabolism (SLR >1.08) had poor OS (p = 0.019 and p = 0.018, respectively). Among the 41 patients who underwent a second PET/CT scan, the ΔSUVmax was significantly lower (p = 0.01) and the SLR was significantly higher (p = 0.0086) in the responders. Populations with low-risk characteristics (low TMTV, low SLR, and ΔSLR > 0) had the longest survival times.ConclusionHigh pretreatment TMTV and SLR are associated with poor OS, and increased spleen metabolism after ICI therapy predicts treatment benefit. This indicates that the combination of tumor and spleen metabolic parameters is a valuable prognostic strategy.
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Gao Y, Wu C, Chen X, Ma L, Zhang X, Chen J, Liao X, Liu M. PET/CT molecular imaging in the era of immune-checkpoint inhibitors therapy. Front Immunol 2022; 13:1049043. [PMID: 36341331 PMCID: PMC9630646 DOI: 10.3389/fimmu.2022.1049043] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Accepted: 10/10/2022] [Indexed: 04/24/2024] Open
Abstract
Cancer immunotherapy, especially immune-checkpoint inhibitors (ICIs), has paved a new way for the treatment of many types of malignancies, particularly advanced-stage cancers. Accumulating evidence suggests that as a molecular imaging modality, positron emission tomography/computed tomography (PET/CT) can play a vital role in the management of ICIs therapy by using different molecular probes and metabolic parameters. In this review, we will provide a comprehensive overview of the clinical data to support the importance of 18F-fluorodeoxyglucose PET/CT (18F-FDG PET/CT) imaging in the treatment of ICIs, including the evaluation of the tumor microenvironment, discovery of immune-related adverse events, evaluation of therapeutic efficacy, and prediction of therapeutic prognosis. We also discuss perspectives on the development direction of 18F-FDG PET/CT imaging, with a particular emphasis on possible challenges in the future. In addition, we summarize the researches on novel PET molecular probes that are expected to potentially promote the precise application of ICIs.
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Radiomic and Volumetric Measurements as Clinical Trial Endpoints—A Comprehensive Review. Cancers (Basel) 2022; 14:cancers14205076. [PMID: 36291865 PMCID: PMC9599928 DOI: 10.3390/cancers14205076] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Revised: 10/12/2022] [Accepted: 10/14/2022] [Indexed: 11/23/2022] Open
Abstract
Simple Summary The extraction of quantitative data from standard-of-care imaging modalities offers opportunities to improve the relevance and salience of imaging biomarkers used in drug development. This review aims to identify the challenges and opportunities for discovering new imaging-based biomarkers based on radiomic and volumetric assessment in the single-site solid tumor sites: breast cancer, rectal cancer, lung cancer and glioblastoma. Developing approaches to harmonize three essential areas: segmentation, validation and data sharing may expedite regulatory approval and adoption of novel cancer imaging biomarkers. Abstract Clinical trials for oncology drug development have long relied on surrogate outcome biomarkers that assess changes in tumor burden to accelerate drug registration (i.e., Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST v1.1) criteria). Drug-induced reduction in tumor size represents an imperfect surrogate marker for drug activity and yet a radiologically determined objective response rate is a widely used endpoint for Phase 2 trials. With the addition of therapies targeting complex biological systems such as immune system and DNA damage repair pathways, incorporation of integrative response and outcome biomarkers may add more predictive value. We performed a review of the relevant literature in four representative tumor types (breast cancer, rectal cancer, lung cancer and glioblastoma) to assess the preparedness of volumetric and radiomics metrics as clinical trial endpoints. We identified three key areas—segmentation, validation and data sharing strategies—where concerted efforts are required to enable progress of volumetric- and radiomics-based clinical trial endpoints for wider clinical implementation.
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Hannequin P, Decroisette C, Kermanach P, Berardi G, Bourbonne V. FDG PET and CT radiomics in diagnosis and prognosis of non-small-cell lung cancer. Transl Lung Cancer Res 2022; 11:2051-2063. [PMID: 36386457 PMCID: PMC9641045 DOI: 10.21037/tlcr-22-158] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 08/22/2022] [Indexed: 09/13/2023]
Abstract
BACKGROUND 18F-FDG PET and CT radiomics has been the object of a wide research for over 20 years but its contribution to clinical practice remains not yet well established. We have investigated its impact versus that of only histo-clinical data, for the routine management of non-small-cell lung cancer (NSCLC). METHODS Our patients were retrospectively considered. They all had a FDG PET-CT and immuno-histo-chemistry (IHC) to assess PD-L1 expression at the beginning of the disease. A prognosis univariate and multivariate Cox survival analyses was performed for overall survival (OS) and progression free survival (PFS) prediction, including a training/testing procedure. Two sets of 47 PET and 47 CT radiomics features (RFs) were extracted. Difference between RFs according to PD-L1 expression, the histology status and the stage level were tested using suited non parametric statistical tests and the receiver operating characteristics (ROC) curve and the area under curve (AUC). RESULTS From 2017 to 2019, 212 NSCLC patients treated in our institution were included. The main conventional prognostic variables were stage and gender with a low added prognostic value in the models including PET and CT RFs. Neither PET nor CT RFs were significant to separate the different levels of PD-L1 expression. Several RFs differ between adenocarcinoma (ADC) and squamous cell carcinoma (SCC) tumours and a large number of PET and CT RFs are significantly linked to patient stage. CONCLUSIONS In our population, PET and CT RFs show their intrinsic power to predict survival but do not significantly improve OS and PFS prediction in the different multivariate models, in comparison to conventional data. It would seem necessary to carry out one's own survival analysis before determining a radiomics signature.
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Affiliation(s)
- Pascal Hannequin
- Annecy Nuclear Medicine Center, Le Pericles, B Allée de la Mandallaz, Metz-Tessy, France
| | - Chantal Decroisette
- Pneumology Department, CHANGE Annecy, 1 Avenue de l’hôpital, Metz-Tessy, France
| | - Pascale Kermanach
- Mont Blanc Histo-Pathology Laboratory, 40 Route de l’Aiglière, Argonay, France
| | - Giulia Berardi
- Pneumology Department, University Hospital la Tronche, Boulevard de la Chantourne, La Tronche, France
| | - Vincent Bourbonne
- Radiation Oncology Department, University Hospital, 2 Avenue Foch, Brest, France
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Kwon HR, Cho J, Park S, Lee SH, Ahn MJ, Choi JY, Lee KH, Jung HA, Moon SH. Metabolic parameters on baseline 18F-FDG PET/CT are potential predictive biomarkers for immunotherapy in patients with head and neck squamous cell carcinoma. Front Med (Lausanne) 2022; 9:896494. [PMID: 36226146 PMCID: PMC9548588 DOI: 10.3389/fmed.2022.896494] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 08/26/2022] [Indexed: 11/13/2022] Open
Abstract
PurposeWe evaluated baseline 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) metabolic parameters for predicting prognosis in patients with head and neck squamous cell carcinoma (HNSCC) who were receiving immune checkpoint inhibitors (ICIs). In addition, we also investigated the relationships between immunohistochemical (IHC) biomarkers and metabolic parameters.Materials and methodsA total of 39 patients with HNSCC who underwent 18F-FDG PET/CT prior to ICI therapy between November 2015 and December 2020 were enrolled. PET parameters of tumor lesions included standardized uptake values, metabolic tumor volume (MTV), total lesion glycolysis (TLG), and spleen-to-liver ratio (SLR). Clinical variables, IHC markers, and derived neutrophil-to-lymphocyte ratio (dNLR) were also obtained. Analysis was performed using Cox proportional hazard model, Kaplan-Meier method with log-rank test, and Spearman's correlation.ResultsTotal MTV (TMTV), total TLG (TTLG), and a combined parameter consisting of TMTV and dNLR were significant predictors for progression-free survival (PFS) in univariable analysis (TMTV, p = 0.018; TTLG, p = 0.027; combined parameter, p = 0.021). Above all, the combined parameter was an independent prognostic factor for PFS in multivariable analysis. The group with low TMTV and low dNLR had longer PFS than the group with high TMTV and high dNLR (p = 0.036). SLR was the only significant predictor for overall survival (p = 0.019). Additionally, there was a negative correlation between programmed cell death-ligand 1 expression (one of the IHC markers) and MTV in subgroup analysis.ConclusionPET parameters on baseline 18F-FDG PET/CT were predictive biomarkers for prognosis in patients with HNSCC undergoing ICI therapy. With dNLR, more accurate prognostic prediction could be possible.
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Affiliation(s)
- Hye Ryeong Kwon
- Department of Nuclear Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
- Department of Nuclear Medicine, Ilsan Paik Hospital, Inje University College of Medicine, Goyang-si, South Korea
| | - Junhun Cho
- Department of Pathology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Sehhoon Park
- Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Se-Hoon Lee
- Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Myung-Ju Ahn
- Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Joon Young Choi
- Department of Nuclear Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Kyung-Han Lee
- Department of Nuclear Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Hyun Ae Jung
- Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
- *Correspondence: Hyun Ae Jung
| | - Seung Hwan Moon
- Department of Nuclear Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
- Seung Hwan Moon
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Li Z, Zhou Q, Wang Q, Wang H, Yue W. EPHA5 mutation was associated with adverse outcome of atezolizumab treatment in late-stage non-small cell lung cancers. BMC Pulm Med 2022; 22:356. [PMID: 36123678 PMCID: PMC9487080 DOI: 10.1186/s12890-022-02161-1] [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: 04/24/2022] [Accepted: 09/13/2022] [Indexed: 11/10/2022] Open
Abstract
Background The aim of the study was to investigate predictive value of gene mutation for atezolizumab treatment response from OAK and POPLAR cohorts.
Methods Several public databases were used for analyzing gene mutation type of EPHA5 and association with alterations of other genes. Survival analysis was performed for patients receiving atezolizumab from OAK and POPLAR cohorts.
Results EPHA5 mutation have high frequency to harbor TP53 and KEAP1 mutations. The bTMB value has significant difference between EPHA5 mutant and wild-type cases. Patients with EPHA5 mutation got worse survival compared to those without gene mutations receiving atezolizumab (P = 0.0186). Conclusions EPHA5 mutant NSCLC may represent a subpopulation which showed worse response after treatment of atezolizumab compared to wild-type ones. Supplementary Information The online version contains supplementary material available at 10.1186/s12890-022-02161-1.
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Affiliation(s)
- Zhenxiang Li
- Medical Integration and Practice Center, Shandong University, Jinan, China
| | - Qing Zhou
- Hospital of Traditional Chinese Medicine of Liaocheng City, Liaocheng, China
| | - Qi Wang
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Haiyong Wang
- Medical Integration and Practice Center, Shandong University, Jinan, China. .,Department of Medical Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, 250117, China.
| | - Weiming Yue
- Department of Thoracic Surgery, Qilu Hospital of Shandong University, Jinan, 250012, Shandong, China.
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Ter Maat LS, van Duin IAJ, Elias SG, van Diest PJ, Pluim JPW, Verhoeff JJC, de Jong PA, Leiner T, Veta M, Suijkerbuijk KPM. Imaging to predict checkpoint inhibitor outcomes in cancer. A systematic review. Eur J Cancer 2022; 175:60-76. [PMID: 36096039 DOI: 10.1016/j.ejca.2022.07.034] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 07/17/2022] [Accepted: 07/21/2022] [Indexed: 11/03/2022]
Abstract
BACKGROUND Checkpoint inhibition has radically improved the perspective for patients with metastatic cancer, but predicting who will not respond with high certainty remains difficult. Imaging-derived biomarkers may be able to provide additional insights into the heterogeneity in tumour response between patients. In this systematic review, we aimed to summarise and qualitatively assess the current evidence on imaging biomarkers that predict response and survival in patients treated with checkpoint inhibitors in all cancer types. METHODS PubMed and Embase were searched from database inception to 29th November 2021. Articles eligible for inclusion described baseline imaging predictive factors, radiomics and/or imaging machine learning models for predicting response and survival in patients with any kind of malignancy treated with checkpoint inhibitors. Risk of bias was assessed using the QUIPS and PROBAST tools and data was extracted. RESULTS In total, 119 studies including 15,580 patients were selected. Of these studies, 73 investigated simple imaging factors. 45 studies investigated radiomic features or deep learning models. Predictors of worse survival were (i) higher tumour burden, (ii) presence of liver metastases, (iii) less subcutaneous adipose tissue, (iv) less dense muscle and (v) presence of symptomatic brain metastases. Hazard rate ratios did not exceed 2.00 for any predictor in the larger and higher quality studies. The added value of baseline fluorodeoxyglucose positron emission tomography parameters in predicting response to treatment was limited. Pilot studies of radioactive drug tracer imaging showed promising results. Reports on radiomics were almost unanimously positive, but numerous methodological concerns exist. CONCLUSIONS There is well-supported evidence for several imaging biomarkers that can be used in clinical decision making. Further research, however, is needed into biomarkers that can more accurately identify which patients who will not benefit from checkpoint inhibition. Radiomics and radioactive drug labelling appear to be promising approaches for this purpose.
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Affiliation(s)
- Laurens S Ter Maat
- Image Science Institute, University Medical Center Utrecht, Utrecht, the Netherlands; Utrecht University, Utrecht, the Netherlands
| | - Isabella A J van Duin
- Department of Medical Oncology, University Medical Center Utrecht, Utrecht, the Netherlands; Utrecht University, Utrecht, the Netherlands
| | - Sjoerd G Elias
- Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands; Utrecht University, Utrecht, the Netherlands
| | - Paul J van Diest
- Department of Pathology, University Medical Center Utrecht, Utrecht, the Netherlands; Utrecht University, Utrecht, the Netherlands
| | - Josien P W Pluim
- Image Science Institute, University Medical Center Utrecht, Utrecht, the Netherlands; Medical Image Analysis, Department Biomedical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands; Utrecht University, Utrecht, the Netherlands
| | - Joost J C Verhoeff
- Department of Radiotherapy, University Medical Center Utrecht, Utrecht, the Netherlands; Utrecht University, Utrecht, the Netherlands
| | - Pim A de Jong
- Department of Radiology, University Medical Center Utrecht, Utrecht, the Netherlands; Utrecht University, Utrecht, the Netherlands
| | - Tim Leiner
- Utrecht University, Utrecht, the Netherlands; Department of Radiology, Mayo Clinical, Rochester, MN, USA
| | - Mitko Veta
- Medical Image Analysis, Department Biomedical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands; Utrecht University, Utrecht, the Netherlands
| | - Karijn P M Suijkerbuijk
- Department of Medical Oncology, University Medical Center Utrecht, Utrecht, the Netherlands; Utrecht University, Utrecht, the Netherlands.
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Zhu K, Su D, Wang J, Cheng Z, Chin Y, Chen L, Chan C, Zhang R, Gao T, Ben X, Jing C. Predictive value of baseline metabolic tumor volume for non-small-cell lung cancer patients treated with immune checkpoint inhibitors: A meta-analysis. Front Oncol 2022; 12:951557. [PMID: 36147904 PMCID: PMC9487526 DOI: 10.3389/fonc.2022.951557] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 08/08/2022] [Indexed: 11/13/2022] Open
Abstract
Background Immune checkpoint inhibitors (ICIs) have emerged as a promising treatment option for advanced non-small-cell lung cancer (NSCLC) patients, highlighting the need for biomarkers to identify responders and predict the outcome of ICIs. The purpose of this study was to evaluate the predictive value of baseline standardized uptake value (SUV), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) derived from 18F-FDG-PET/CT in advanced NSCLC patients receiving ICIs. Methods PubMed and Web of Science databases were searched from January 1st, 2011 to July 18th, 2022, utilizing the search terms “non-small-cell lung cancer”, “PET/CT”, “standardized uptake value”, “metabolic tumor volume”, “ total lesion glycolysis”, and “immune checkpoint inhibitors”. Studies that analyzed the association between PET/CT parameters and objective response, immune-related adverse events (irAEs) and prognosis of NSCLC patients treated with ICIs were included. We extracted the hazard ratio (HR) with a 95% confidence interval (CI) for progression-free survival (PFS) and overall survival (OS). We performed a meta-analysis of HR using Review Manager v.5.4.1. Results Sixteen studies were included for review and thirteen for meta-analysis covering 770 patients. As for objective response and irAEs after ICIs, more studies with consistent assessment methods are needed to determine their relationship with MTV. In the meta-analysis, low SUVmax corresponded to poor PFS with a pooled HR of 0.74 (95% CI, 0.57-0.96, P=0.02). And a high level of baseline MTV level was related to shorter PFS (HR=1.45, 95% CI, 1.11-1.89, P<0.01) and OS (HR, 2.72; 95% CI, 1.97-3.73, P<0.01) especially when the cut-off value was set between 50-100 cm3. SUVmean and TLG were not associated with the prognosis of NSCLC patients receiving ICIs. Conclusions High level of baseline MTV corresponded to shorter PFS and OS, especially when the cut-off value was set between 50-100 cm3. MTV is a potential predictive value for the outcome of ICIs in NSCLC patients.
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Affiliation(s)
- Ke Zhu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
- International School, Jinan University, Guangzhou, China
| | - Danqian Su
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
- International School, Jinan University, Guangzhou, China
| | - Jianing Wang
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
- International School, Jinan University, Guangzhou, China
| | - Zhouen Cheng
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
- International School, Jinan University, Guangzhou, China
| | - Yiqiao Chin
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
- International School, Jinan University, Guangzhou, China
| | - Luyin Chen
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
- International School, Jinan University, Guangzhou, China
| | - Chingtin Chan
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
- International School, Jinan University, Guangzhou, China
| | - Rongcai Zhang
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
- International School, Jinan University, Guangzhou, China
| | - Tianyu Gao
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
| | - Xiaosong Ben
- Department of Thoracic Surgery, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- *Correspondence: Xiaosong Ben, ; Chunxia Jing,
| | - Chunxia Jing
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
- Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou, China
- *Correspondence: Xiaosong Ben, ; Chunxia Jing,
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Monitoring of Current Cancer Therapy by Positron Emission Tomography and Possible Role of Radiomics Assessment. Int J Mol Sci 2022; 23:ijms23169394. [PMID: 36012657 PMCID: PMC9409366 DOI: 10.3390/ijms23169394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 07/31/2022] [Accepted: 08/16/2022] [Indexed: 11/17/2022] Open
Abstract
Evaluation of cancer therapy with imaging is crucial as a surrogate marker of effectiveness and survival. The unique response patterns to therapy with immune-checkpoint inhibitors have facilitated the revision of response evaluation criteria using FDG-PET, because the immune response recalls reactive cells such as activated T-cells and macrophages, which show increased glucose metabolism and apparent progression on morphological imaging. Cellular metabolism and function are critical determinants of the viability of active cells in the tumor microenvironment, which would be novel targets of therapies, such as tumor immunity, metabolism, and genetic mutation. Considering tumor heterogeneity and variation in therapy response specific to the mechanisms of therapy, appropriate response evaluation is required. Radiomics approaches, which combine objective image features with a machine learning algorithm as well as pathologic and genetic data, have remarkably progressed over the past decade, and PET radiomics has increased quality and reliability based on the prosperous publications and standardization initiatives. PET and multimodal imaging will play a definitive role in personalized therapeutic strategies by the precise monitoring in future cancer therapy.
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36
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Prognostic Potential of Metabolic Activity on 18F-FDG Accumulation in Advanced NSCLC Receiving Combining Chemotherapy Plus PD-1 Blockade. J Immunother 2022; 45:349-357. [PMID: 35980360 DOI: 10.1097/cji.0000000000000434] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 07/06/2022] [Indexed: 11/25/2022]
Abstract
Combined chemotherapy plus programmed death-1 (PD-1) blockade is an established treatment against patients with advanced non-small cell lung cancer (NSCLC). However, a promising predictor besides programmed death ligand-1 expression remains uncertain. We examined the prognostic significance of baseline 18F-FDG-positron emission tomography for predicting first-line combined chemotherapy plus PD-1 blockade in NSCLC patients. Forty-five patients with advanced NSCLC who received 18F-FDG-positron emission tomography immediately before combined platinum-based chemotherapy with PD-1 blockade as first-line setting were eligible for this study, and assessment of maximum of standard uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) on 18F-FDG uptake was performed. The objective response rate, median progression-free survival, and overall survival were 51.2%, 206 days, and 681 days, respectively. High SUVmax, TLG, and MTV significantly correlated with age and performance status (PS), C-reactive protein (CRP), and PS, CRP, albumin, and baseline tumor size, respectively. Univariate analysis identified albumin, TLG and MTV as significant predictors of progression-free survival, and CRP, albumin, TLG and MTV as significant factors for predicting overall survival. High TLG was confirmed as an independent factor associated with poor prognosis in multivariate analysis. In particular, TLG is identified as the most powerful predictor in patients with good PS, adenocarcinoma, programmed death ligand-1≥1%, and low baseline tumor size. The tumor metabolic volume by MTV and TLG at pretreatment was clarified as a significant predictor for combined chemotherapy with PD-1 blockade, but not maximal glycolytic level by SUVmax.
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van de Donk PP, Oosting SF, Knapen DG, van der Wekken AJ, Brouwers AH, Lub-de Hooge MN, de Groot DJA, de Vries EG. Molecular imaging to support cancer immunotherapy. J Immunother Cancer 2022; 10:jitc-2022-004949. [PMID: 35922089 PMCID: PMC9352987 DOI: 10.1136/jitc-2022-004949] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/08/2022] [Indexed: 11/04/2022] Open
Abstract
The advent of immune checkpoint inhibitors has reinvigorated the field of immuno-oncology. These monoclonal antibody-based therapies allow the immune system to recognize and eliminate malignant cells. This has resulted in improved survival of patients across several tumor types. However, not all patients respond to immunotherapy therefore predictive biomarkers are important. There are only a few Food and Drug Administration-approved biomarkers to select patients for immunotherapy. These biomarkers do not consider the heterogeneity of tumor characteristics across lesions within a patient. New molecular imaging tracers allow for whole-body visualization with positron emission tomography (PET) of tumor and immune cell characteristics, and drug distribution, which might guide treatment decision making. Here, we summarize recent developments in molecular imaging of immune checkpoint molecules, such as PD-L1, PD-1, CTLA-4, and LAG-3. We discuss several molecular imaging approaches of immune cell subsets and briefly summarize the role of FDG-PET for evaluating cancer immunotherapy. The main focus is on developments in clinical molecular imaging studies, next to preclinical studies of interest given their potential translation to the clinic.
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Affiliation(s)
- Pim P van de Donk
- Department of Medical Oncology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Sjoukje F Oosting
- Department of Medical Oncology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Daan G Knapen
- Department of Medical Oncology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Anthonie J van der Wekken
- Department of Pulmonary Medicine, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Adrienne H Brouwers
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Marjolijn N Lub-de Hooge
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.,Department of Clinical Pharmacy and Pharmacology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Derk-Jan A de Groot
- Department of Medical Oncology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Elisabeth Ge de Vries
- Department of Medical Oncology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
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Liu WL, Zhang YQ, Li LT, Zhu YY, Ming ZH, Chen WL, Yang RQ, Li RH, Chen M, Zhang GJ. Application of molecular imaging in immune checkpoints therapy: From response assessment to prognosis prediction. Crit Rev Oncol Hematol 2022; 176:103746. [PMID: 35752425 DOI: 10.1016/j.critrevonc.2022.103746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 05/30/2022] [Accepted: 06/13/2022] [Indexed: 11/17/2022] Open
Abstract
Recently, immune checkpoint therapy (ICT) represented by programmed cell death1 (PD-1) and its major ligands, programmed death ligand 1 (PD-L1), has achieved significant success. Detection of PD-L1 by immunohistochemistry (IHC) is a classic method to guide the treatment of ICT patients. However, PD-L1 expression in the tumor microenvironment is highly complex. Thus, PD-L1 IHC is inadequate to fully understand the relevance of PD-L1 levels in the whole body and their dynamics to improve therapeutic outcomes. Intriguingly, numerous studies have revealed that molecular imaging technologies could potentially meet this need. Therefore, the purpose of this narrative review is to summarize the preclinical and clinical application of ICT guided by molecular imaging technology, and to explore the future opportunities and practical difficulties of these innovations.
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Affiliation(s)
- Wan-Ling Liu
- Department of Breast-Thyroid-Surgery and Cancer Center, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, 2000 East Xiang'an Road, Xiamen, China; Fujian Key Laboratory of Precision Diagnosis and Treatment in Breast Cancer (Xiang'an Hospital of Xiamen University), 2000 East Xiang'an Road, Xiamen, China; Xiamen Key Laboratory for Endocrine Related Cancer Precision Medicine, Xiang'an Hospital of Xiamen University, 2000 East Xiang'an Road, Xiamen, China; Xiamen Research Center of Clinical Medicine in Breast & Thyroid Cancers, 2000 East Xiang'an Road, Xiamen, China
| | - Yong-Qu Zhang
- Department of Breast-Thyroid-Surgery and Cancer Center, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, 2000 East Xiang'an Road, Xiamen, China; Fujian Key Laboratory of Precision Diagnosis and Treatment in Breast Cancer (Xiang'an Hospital of Xiamen University), 2000 East Xiang'an Road, Xiamen, China; Xiamen Key Laboratory for Endocrine Related Cancer Precision Medicine, Xiang'an Hospital of Xiamen University, 2000 East Xiang'an Road, Xiamen, China; Xiamen Research Center of Clinical Medicine in Breast & Thyroid Cancers, 2000 East Xiang'an Road, Xiamen, China
| | - Liang-Tao Li
- Department of Breast-Thyroid-Surgery and Cancer Center, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, 2000 East Xiang'an Road, Xiamen, China; Fujian Key Laboratory of Precision Diagnosis and Treatment in Breast Cancer (Xiang'an Hospital of Xiamen University), 2000 East Xiang'an Road, Xiamen, China; Xiamen Key Laboratory for Endocrine Related Cancer Precision Medicine, Xiang'an Hospital of Xiamen University, 2000 East Xiang'an Road, Xiamen, China; Xiamen Research Center of Clinical Medicine in Breast & Thyroid Cancers, 2000 East Xiang'an Road, Xiamen, China
| | - Yuan-Yuan Zhu
- Department of Breast-Thyroid-Surgery and Cancer Center, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, 2000 East Xiang'an Road, Xiamen, China; Fujian Key Laboratory of Precision Diagnosis and Treatment in Breast Cancer (Xiang'an Hospital of Xiamen University), 2000 East Xiang'an Road, Xiamen, China; Xiamen Key Laboratory for Endocrine Related Cancer Precision Medicine, Xiang'an Hospital of Xiamen University, 2000 East Xiang'an Road, Xiamen, China; Xiamen Research Center of Clinical Medicine in Breast & Thyroid Cancers, 2000 East Xiang'an Road, Xiamen, China
| | - Zi-He Ming
- Department of Breast-Thyroid-Surgery and Cancer Center, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, 2000 East Xiang'an Road, Xiamen, China; Fujian Key Laboratory of Precision Diagnosis and Treatment in Breast Cancer (Xiang'an Hospital of Xiamen University), 2000 East Xiang'an Road, Xiamen, China; Xiamen Key Laboratory for Endocrine Related Cancer Precision Medicine, Xiang'an Hospital of Xiamen University, 2000 East Xiang'an Road, Xiamen, China; Xiamen Research Center of Clinical Medicine in Breast & Thyroid Cancers, 2000 East Xiang'an Road, Xiamen, China
| | - Wei-Ling Chen
- Department of Breast-Thyroid-Surgery and Cancer Center, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, 2000 East Xiang'an Road, Xiamen, China; Fujian Key Laboratory of Precision Diagnosis and Treatment in Breast Cancer (Xiang'an Hospital of Xiamen University), 2000 East Xiang'an Road, Xiamen, China; Xiamen Key Laboratory for Endocrine Related Cancer Precision Medicine, Xiang'an Hospital of Xiamen University, 2000 East Xiang'an Road, Xiamen, China; Xiamen Research Center of Clinical Medicine in Breast & Thyroid Cancers, 2000 East Xiang'an Road, Xiamen, China
| | - Rui-Qin Yang
- Department of Breast-Thyroid-Surgery and Cancer Center, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, 2000 East Xiang'an Road, Xiamen, China; Fujian Key Laboratory of Precision Diagnosis and Treatment in Breast Cancer (Xiang'an Hospital of Xiamen University), 2000 East Xiang'an Road, Xiamen, China; Xiamen Key Laboratory for Endocrine Related Cancer Precision Medicine, Xiang'an Hospital of Xiamen University, 2000 East Xiang'an Road, Xiamen, China; Xiamen Research Center of Clinical Medicine in Breast & Thyroid Cancers, 2000 East Xiang'an Road, Xiamen, China
| | - Rong-Hui Li
- Fujian Key Laboratory of Precision Diagnosis and Treatment in Breast Cancer (Xiang'an Hospital of Xiamen University), 2000 East Xiang'an Road, Xiamen, China; Department of Medical Oncology, Xiang'an Hospital of Xiamen University, 2000 East Xiang'an Road, Xiamen, China
| | - Min Chen
- Fujian Key Laboratory of Precision Diagnosis and Treatment in Breast Cancer (Xiang'an Hospital of Xiamen University), 2000 East Xiang'an Road, Xiamen, China; Xiamen Key Laboratory for Endocrine Related Cancer Precision Medicine, Xiang'an Hospital of Xiamen University, 2000 East Xiang'an Road, Xiamen, China.
| | - Guo-Jun Zhang
- Department of Breast-Thyroid-Surgery and Cancer Center, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, 2000 East Xiang'an Road, Xiamen, China; Fujian Key Laboratory of Precision Diagnosis and Treatment in Breast Cancer (Xiang'an Hospital of Xiamen University), 2000 East Xiang'an Road, Xiamen, China; Xiamen Key Laboratory for Endocrine Related Cancer Precision Medicine, Xiang'an Hospital of Xiamen University, 2000 East Xiang'an Road, Xiamen, China; Xiamen Research Center of Clinical Medicine in Breast & Thyroid Cancers, 2000 East Xiang'an Road, Xiamen, China; Cancer Research Center, School of Medicine, Xiamen University, 4221 South Xiang'an Road, Xiamen, China.
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Lopci E, Hicks RJ, Dimitrakopoulou-Strauss A, Dercle L, Iravani A, Seban RD, Sachpekidis C, Humbert O, Gheysens O, Glaudemans AWJM, Weber W, Wahl RL, Scott AM, Pandit-Taskar N, Aide N. Joint EANM/SNMMI/ANZSNM practice guidelines/procedure standards on recommended use of [ 18F]FDG PET/CT imaging during immunomodulatory treatments in patients with solid tumors version 1.0. Eur J Nucl Med Mol Imaging 2022; 49:2323-2341. [PMID: 35376991 PMCID: PMC9165250 DOI: 10.1007/s00259-022-05780-2] [Citation(s) in RCA: 39] [Impact Index Per Article: 19.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Accepted: 03/22/2022] [Indexed: 12/13/2022]
Abstract
PURPOSE The goal of this guideline/procedure standard is to assist nuclear medicine physicians, other nuclear medicine professionals, oncologists or other medical specialists for recommended use of [18F]FDG PET/CT in oncological patients undergoing immunotherapy, with special focus on response assessment in solid tumors. METHODS In a cooperative effort between the EANM, the SNMMI and the ANZSNM, clinical indications, recommended imaging procedures and reporting standards have been agreed upon and summarized in this joint guideline/procedure standard. CONCLUSIONS The field of immuno-oncology is rapidly evolving, and this guideline/procedure standard should not be seen as definitive, but rather as a guidance document standardizing the use and interpretation of [18F]FDG PET/CT during immunotherapy. Local variations to this guideline should be taken into consideration. PREAMBLE The European Association of Nuclear Medicine (EANM) is a professional non-profit medical association founded in 1985 to facilitate worldwide communication among individuals pursuing clinical and academic excellence in nuclear medicine. The Society of Nuclear Medicine and Molecular Imaging (SNMMI) is an international scientific and professional organization founded in 1954 to promote science, technology and practical application of nuclear medicine. The Australian and New Zealand Society of Nuclear Medicine (ANZSNM), founded in 1969, represents the major professional society fostering the technical and professional development of nuclear medicine practice across Australia and New Zealand. It promotes excellence in the nuclear medicine profession through education, research and a commitment to the highest professional standards. EANM, SNMMI and ANZSNM members are physicians, technologists, physicists and scientists specialized in the research and clinical practice of nuclear medicine. All three societies will periodically put forth new standards/guidelines for nuclear medicine practice to help advance the science of nuclear medicine and improve service to patients. Existing standards/guidelines will be reviewed for revision or renewal, as appropriate, on their fifth anniversary or sooner, if indicated. Each standard/guideline, representing a policy statement by the EANM/SNMMI/ANZSNM, has undergone a thorough consensus process, entailing extensive review. These societies recognize that the safe and effective use of diagnostic nuclear medicine imaging requires particular training and skills, as described in each document. These standards/guidelines are educational tools designed to assist practitioners in providing appropriate and effective nuclear medicine care for patients. These guidelines are consensus documents based on current knowledge. They are not intended to be inflexible rules or requirements of practice, nor should they be used to establish a legal standard of care. For these reasons and those set forth below, the EANM, SNMMI and ANZSNM caution against the use of these standards/guidelines in litigation in which the clinical decisions of a practitioner are called into question. The ultimate judgment regarding the propriety of any specific procedure or course of action must be made by medical professionals considering the unique circumstances of each case. Thus, there is no implication that an action differing from what is laid out in the guidelines/procedure standards, standing alone, is below standard of care. To the contrary, a conscientious practitioner may responsibly adopt a course of action different from that set forth in the standards/guidelines when, in the reasonable judgment of the practitioner, such course of action is indicated by the condition of the patient, limitations of available resources or advances in knowledge or technology subsequent to publication of the guidelines/procedure standards. The practice of medicine involves not only the science, but also the art of dealing with the prevention, diagnosis, alleviation and treatment of disease. The variety and complexity of human conditions make it impossible for general guidelines to consistently allow for an accurate diagnosis to be reached or a particular treatment response to be predicted. Therefore, it should be recognized that adherence to these standards/ guidelines will not ensure a successful outcome. All that should be expected is that practitioners follow a reasonable course of action, based on their level of training, current knowledge, clinical practice guidelines, available resources and the needs/context of the patient being treated. The sole purpose of these guidelines is to assist practitioners in achieving this objective. The present guideline/procedure standard was developed collaboratively by the EANM, the SNMMI and the ANZSNM, with the support of international experts in the field. They summarize also the views of the Oncology and Theranostics and the Inflammation and Infection Committees of the EANM, as well as the procedure standards committee of the SNMMI, and reflect recommendations for which the EANM and SNMMI cannot be held responsible. The recommendations should be taken into the context of good practice of nuclear medicine and do not substitute for national and international legal or regulatory provisions.
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Affiliation(s)
- E Lopci
- Nuclear Medicine Unit, IRCCS - Humanitas Research Hospital, Via Manzoni 56, 20089, Rozzano, Milano, Italy.
| | - R J Hicks
- The Department of Medicine, St Vincent's Medical School, the University of Melbourne, Melbourne, Australia
| | - A Dimitrakopoulou-Strauss
- Clinical Cooperation Unit Nuclear Medicine, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69210, Heidelberg, Germany
| | - L Dercle
- Department of Radiology, New York Presbyterian, Columbia University Irving Medical Center, New York, NY, USA
| | - A Iravani
- Department of Molecular Imaging and Therapeutic Nuclear Medicine, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- The Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, Victoria, Australia
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - R D Seban
- Department of Nuclear Medicine and Endocrine Oncology, Institut Curie, 92210, Saint-Cloud, France
- Laboratoire d'Imagerie Translationnelle en Oncologie, Inserm, Institut Curie, 91401, Orsay, France
| | - C Sachpekidis
- Clinical Cooperation Unit Nuclear Medicine, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69210, Heidelberg, Germany
| | - O Humbert
- Department of Nuclear Medicine, Centre Antoine-Lacassagne, Université Côte d'Azur, Nice, France
- TIRO-UMR E 4320, Université Côte d'Azur, Nice, France
| | - O Gheysens
- Department of Nuclear Medicine, Cliniques Universitaires Saint-Luc, Université Catholique de Louvain (UCLouvain), Brussels, Belgium
| | - A W J M Glaudemans
- Nuclear Medical Imaging Center, Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - W Weber
- Department of Nuclear Medicine, Klinikum Rechts Der Isar, Technical University Munich, Ismaninger Str. 22, 81675, Munich, Germany
| | - R L Wahl
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - A M Scott
- Department of Molecular Imaging and Therapy, Austin Health, Studley Rd, Heidelberg, Victoria, 3084, Australia
- Olivia Newton-John Cancer Research Institute, Heidelberg, Australia
- Faculty of Medicine, University of Melbourne, Melbourne, Australia
- School of Cancer Medicine, La Trobe University, Melbourne, Australia
| | - N Pandit-Taskar
- Nuclear Medicine Service, Department of Radiology, Memorial Sloan-Kettering Cancer Center, 1275 York Ave., New York, NY, 10021, USA
| | - N Aide
- Nuclear Medicine Department, University Hospital, Caen, France
- INSERM ANTICIPE, Normandie University, Caen, France
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Hicks RJ. The value of the Standardized Uptake Value (SUV) and Metabolic Tumor Volume (MTV) in lung cancer. Semin Nucl Med 2022; 52:734-744. [PMID: 35624032 DOI: 10.1053/j.semnuclmed.2022.04.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Accepted: 04/21/2022] [Indexed: 11/11/2022]
Abstract
The diagnosis, staging and therapeutic monitoring of lung cancer were amongst the first applications for which the utility of FDG PET was documented and FDG PET/CT is now a routine diagnostic tool for clinical decision-making. As well as having high sensitivity for detection of disease sites, which provides critical information about stage, the intensity of uptake provides deeper biological characterization, while the burden of disease also has potential clinical significance. These disease characteristics can easily be quantified on delayed whole-body imaging as the maximum standardized uptake value (SUVmax) and metabolic tumor volume (MTV), respectively. There have been significant efforts to harmonize the measurement of these features, particularly within the context of clinical trials. Nevertheless, however calculated, in general, a high SUVmax and large MTV have been shown to have an adverse prognostic significance. Nevertheless, the use of these parameters in the interpretation and reporting of clinical scans remains inconsistent and somewhat controversial. This review details the current status of semi-quantitative FDG PET/CT in the evaluation of lung cancer.
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Affiliation(s)
- Rodney J Hicks
- Department of Medicine, St Vincent's Medical School, University of Melbourne, Melbourne Academic Centre for Health, University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Central Clinical School, Alfred Hospital, Monash University, Melbourne VIC, Australia.
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Xu B, Peng Z, An Y, Yan G, Yao X, Guan L, Sun M. Identification of Energy Metabolism-Related Gene Signatures From scRNA-Seq Data to Predict the Prognosis of Liver Cancer Patients. Front Cell Dev Biol 2022; 10:858336. [PMID: 35602603 PMCID: PMC9114438 DOI: 10.3389/fcell.2022.858336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Accepted: 04/18/2022] [Indexed: 11/13/2022] Open
Abstract
The increasingly common usage of single-cell sequencing in cancer research enables analysis of tumor development mechanisms from a wider range of perspectives. Metabolic disorders are closely associated with liver cancer development. In recent years, liver cancer has been evaluated from different perspectives and classified into different subtypes to improve targeted treatment strategies. Here, we performed an analysis of liver cancer from the perspective of energy metabolism based on single-cell sequencing data. Single-cell and bulk sequencing data of liver cancer patients were obtained from GEO and TCGA/ICGC databases, respectively. Using the Seurat R package and protocols such as consensus clustering analysis, genes associated with energy metabolism in liver cancer were identified and validated. An energy metabolism-related score (EM score) was established based on five identified genes. Finally, the sensitivity of patients in different scoring groups to different chemotherapeutic agents and immune checkpoint inhibitors was analyzed. Tumor cells from liver cancer patients were found to divide into nine clusters, with cluster 4 having the highest energy metabolism score. Based on the marker genes of this cluster and TCGA database data, the five most stable key genes (ADH4, AKR1B10, CEBPZOS, ENO1, and FOXN2) were identified as energy metabolism-related genes in liver cancer. In addition, drug sensitivity analysis showed that patients in the low EM score group were more sensitive to immune checkpoint inhibitors and chemotherapeutic agents AICAR, metformin, and methotrexate.
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Affiliation(s)
- Boyang Xu
- Department of Gastroenterology, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Ziqi Peng
- Department of Breast Surgery, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Yue An
- Department of Endoscopy, The First Hospital of China Medical University, Shenyang, China
| | - Guanyu Yan
- Department of Gastroenterology, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Xue Yao
- Department of Surgical Oncology, The First Hospital of China Medical University, Shenyang, China
| | - Lin Guan
- Department of Gastroenterology, The First Affiliated Hospital of China Medical University, Shenyang, China
- *Correspondence: Lin Guan, ; Mingjun Sun,
| | - Mingjun Sun
- Department of Gastroenterology, The First Affiliated Hospital of China Medical University, Shenyang, China
- *Correspondence: Lin Guan, ; Mingjun Sun,
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Léger MA, Routy B, Juneau D. FDG PET/CT for Evaluation of Immunotherapy Response in Lung Cancer Patients. Semin Nucl Med 2022; 52:707-719. [DOI: 10.1053/j.semnuclmed.2022.04.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Revised: 04/25/2022] [Accepted: 04/26/2022] [Indexed: 11/11/2022]
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Jiang M, Zhang X, Chen Y, Chen P, Guo X, Ma L, Gao Q, Mei W, Zhang J, Zheng J. A Review of the Correlation Between Epidermal Growth Factor Receptor Mutation Status and 18F-FDG Metabolic Activity in Non-Small Cell Lung Cancer. Front Oncol 2022; 12:780186. [PMID: 35515138 PMCID: PMC9065410 DOI: 10.3389/fonc.2022.780186] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Accepted: 03/25/2022] [Indexed: 11/15/2022] Open
Abstract
PET/CT with 18F-2-fluoro-2-deoxyglucose (18F-FDG) has been proposed as a promising modality for diagnosing and monitoring treatment response and evaluating prognosis for patients with non-small cell lung cancer (NSCLC). The status of epidermal growth factor receptor (EGFR) mutation is a critical signal for the treatment strategies of patients with NSCLC. Higher response rates and prolonged progression-free survival could be obtained in patients with NSCLC harboring EGFR mutations treated with tyrosine kinase inhibitors (TKIs) when compared with traditional cytotoxic chemotherapy. However, patients with EGFR mutation treated with TKIs inevitably develop drug resistance, so predicting the duration of resistance is of great importance for selecting individual treatment strategies. Several semiquantitative metabolic parameters, e.g., maximum standard uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG), measured by PET/CT to reflect 18F-FDG metabolic activity, have been demonstrated to be powerful in predicting the status of EGFR mutation, monitoring treatment response of TKIs, and assessing the outcome of patients with NSCLC. In this review, we summarize the biological and clinical correlations between EGFR mutation status and 18F-FDG metabolic activity in NSCLC. The metabolic activity of 18F-FDG, as an extrinsic manifestation of NSCLC, could reflect the mutation status of intrinsic factor EGFR. Both of them play a critical role in guiding the implementation of treatment modalities and evaluating therapy efficacy and outcome for patients with NSCLC.
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Affiliation(s)
- Maoqing Jiang
- Department of PET/CT Center, Hwa Mei Hospital, University of Chinese Academy of Sciences, Ningbo, China
- Ningbo Institute of Life and Health Industry, University of Chinese Academy of Sciences, Ningbo, China
- Department of Nuclear Medicine, Hwa Mei Hospital, University of Chinese Academy of Sciences, Ningbo, China
| | - Xiaohui Zhang
- Department of PET/CT Center, Hwa Mei Hospital, University of Chinese Academy of Sciences, Ningbo, China
- Ningbo Institute of Life and Health Industry, University of Chinese Academy of Sciences, Ningbo, China
| | - Yan Chen
- Department of Physical Examination Center, Ningbo First Hospital, Ningbo, China
| | - Ping Chen
- Department of Nephrology, Hwa Mei Hospital, University of Chinese Academy of Sciences, Ningbo, China
| | - Xiuyu Guo
- Department of PET/CT Center, Hwa Mei Hospital, University of Chinese Academy of Sciences, Ningbo, China
- Ningbo Institute of Life and Health Industry, University of Chinese Academy of Sciences, Ningbo, China
| | - Lijuan Ma
- Department of PET/CT Center, Hwa Mei Hospital, University of Chinese Academy of Sciences, Ningbo, China
- Ningbo Institute of Life and Health Industry, University of Chinese Academy of Sciences, Ningbo, China
| | - Qiaoling Gao
- Department of PET/CT Center, Hwa Mei Hospital, University of Chinese Academy of Sciences, Ningbo, China
- Ningbo Institute of Life and Health Industry, University of Chinese Academy of Sciences, Ningbo, China
| | - Weiqi Mei
- Department of Nuclear Medicine, Hwa Mei Hospital, University of Chinese Academy of Sciences, Ningbo, China
| | - Jingfeng Zhang
- Department of Education, Hwa Mei Hospital, University of Chinese Academy of Sciences, Ningbo, China
| | - Jianjun Zheng
- Department of PET/CT Center, Hwa Mei Hospital, University of Chinese Academy of Sciences, Ningbo, China
- Ningbo Institute of Life and Health Industry, University of Chinese Academy of Sciences, Ningbo, China
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The Role of Radiomics in the Era of Immune Checkpoint Inhibitors: A New Protagonist in the Jungle of Response Criteria. J Clin Med 2022; 11:jcm11061740. [PMID: 35330068 PMCID: PMC8948743 DOI: 10.3390/jcm11061740] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 03/08/2022] [Accepted: 03/18/2022] [Indexed: 12/15/2022] Open
Abstract
Simple Summary The introduction of immune checkpoint inhibitors has represented a milestone in cancer treatment. Despite PD-L1 expression being the standard biomarker used before the start of therapy, there is still a strict need to identify complementary non-invasive biomarkers in order to better select patients. In this context, radiomics is an emerging approach for examining medical images and clinical data by capturing multiple features hidden from human eye and is potentially able to predict response assessment and survival in the course of immunotherapy. We reviewed the available studies investigating the role of radiomics in cancer patients, focusing on non-small cell lung cancer treated with immune checkpoint inhibitors. Although preliminary research shows encouraging results, different issues need to be solved before radiomics can enter into clinical practice. Abstract Immune checkpoint inhibitors (ICI) have demonstrated encouraging results in terms of durable clinical benefit and survival in several malignancies. Nevertheless, the search to identify an “ideal” biomarker for predicting response to ICI is still far from over. Radiomics is a new translational field of study aiming to extract, by dedicated software, several features from a given medical image, ranging from intensity distribution and spatial heterogeneity to higher-order statistical parameters. Based on these premises, our review aims to summarize the current status of radiomics as a potential predictor of clinical response following immunotherapy treatment. A comprehensive search of PubMed results was conducted. All studies published in English up to and including December 2021 were selected, comprising those that explored computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET) for radiomic analyses in the setting of ICI. Several studies have demonstrated the potential applicability of radiomic features in the monitoring of the therapeutic response beyond the traditional morphologic and metabolic criteria, as well as in the prediction of survival or non-invasive assessment of the tumor microenvironment. Nevertheless, important limitations emerge from our review in terms of standardization in feature selection, data sharing, and methods, as well as in external validation. Additionally, there is still need for prospective clinical trials to confirm the potential significant role of radiomics during immunotherapy.
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Liao X, Liu M, Wang R, Zhang J. Potentials of Non-Invasive 18F-FDG PET/CT in Immunotherapy Prediction for Non–Small Cell Lung Cancer. Front Genet 2022; 12:810011. [PMID: 35186013 PMCID: PMC8855498 DOI: 10.3389/fgene.2021.810011] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Accepted: 12/31/2021] [Indexed: 12/26/2022] Open
Abstract
The immune checkpoint inhibitors (ICIs), by targeting cytotoxic-T-lymphocyte-associated protein 4, programmed cell death 1 (PD-1), or PD-ligand 1, have dramatically changed the natural history of several cancers, including non–small cell lung cancer (NSCLC). There are unusual response manifestations (such as pseudo-progression, hyper-progression, and immune-related adverse events) observed in patients with ICIs because of the unique mechanisms of these agents. These specific situations challenge response and prognostic assessment to ICIs challenging. This review demonstrates how 18F-FDG PET/CT can help identify these unusual response patterns in a non-invasive and effective way. Then, a series of semi-quantitative parameters derived from 18F-FDG PET/CT are introduced. These indexes have been recognized as the non-invasive biomarkers to predicting the efficacy of ICIs and survival of NSCLC patients according to the latest clinical studies. Moreover, the current situation regarding the functional criteria based on 18F-FDG PET/CT for immunotherapeutic response assessment is presented and analyzed. Although the criteria based on 18F-FDG PET/CT proposed some resolutions to overcome limitations of morphologic criteria in the assessment of tumor response to ICIs, further researches should be performed to validate and improve these assessing systems. Then, the last part in this review displays the present status and a perspective of novel specific PET probes targeting key molecules relevant to immunotherapy in prediction and response assessment.
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Freely available convolutional neural network-based quantification of PET/CT lesions is associated with survival in patients with lung cancer. EJNMMI Phys 2022; 9:6. [PMID: 35113252 PMCID: PMC8814082 DOI: 10.1186/s40658-022-00437-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2021] [Accepted: 01/24/2022] [Indexed: 12/11/2022] Open
Abstract
Background Metabolic positron emission tomography/computed tomography (PET/CT) parameters describing tumour activity contain valuable prognostic information, but to perform the measurements manually leads to both intra- and inter-reader variability and is too time-consuming in clinical practice. The use of modern artificial intelligence-based methods offers new possibilities for automated and objective image analysis of PET/CT data.
Purpose We aimed to train a convolutional neural network (CNN) to segment and quantify tumour burden in [18F]-fluorodeoxyglucose (FDG) PET/CT images and to evaluate the association between CNN-based measurements and overall survival (OS) in patients with lung cancer. A secondary aim was to make the method available to other researchers. Methods A total of 320 consecutive patients referred for FDG PET/CT due to suspected lung cancer were retrospectively selected for this study. Two nuclear medicine specialists manually segmented abnormal FDG uptake in all of the PET/CT studies. One-third of the patients were assigned to a test group. Survival data were collected for this group. The CNN was trained to segment lung tumours and thoracic lymph nodes. Total lesion glycolysis (TLG) was calculated from the CNN-based and manual segmentations. Associations between TLG and OS were investigated using a univariate Cox proportional hazards regression model. Results The test group comprised 106 patients (median age, 76 years (IQR 61–79); n = 59 female). Both CNN-based TLG (hazard ratio 1.64, 95% confidence interval 1.21–2.21; p = 0.001) and manual TLG (hazard ratio 1.54, 95% confidence interval 1.14–2.07; p = 0.004) estimations were significantly associated with OS. Conclusion Fully automated CNN-based TLG measurements of PET/CT data showed were significantly associated with OS in patients with lung cancer. This type of measurement may be of value for the management of future patients with lung cancer. The CNN is publicly available for research purposes.
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Prognostic value of total tumour volume, adding necrosis to metabolic tumour volume, in advanced or metastatic non-small cell lung cancer treated with first-line pembrolizumab. Ann Nucl Med 2022; 36:224-234. [DOI: 10.1007/s12149-021-01694-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Accepted: 11/08/2021] [Indexed: 12/19/2022]
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Kim CG, Hwang SH, Kim KH, Yoon HI, Shim HS, Lee JH, Han Y, Ahn BC, Hong MH, Kim HR, Cho BC, Cho A, Lim SM. Predicting treatment outcomes using 18F-FDG PET biomarkers in patients with non-small-cell lung cancer receiving chemoimmunotherapy. Ther Adv Med Oncol 2022; 14:17588359211068732. [PMID: 35035536 PMCID: PMC8753071 DOI: 10.1177/17588359211068732] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Accepted: 12/02/2021] [Indexed: 12/18/2022] Open
Abstract
Background Predictive markers for treatment response and survival outcome have not been identified in patients with advanced non-small-cell lung cancer (NSCLC) receiving chemoimmunotherapy. We aimed to evaluate whether imaging biomarkers of 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) and routinely assessed clinico-laboratory values were associated with clinical outcomes in patients with advanced NSCLC receiving pembrolizumab plus platinum-doublet chemotherapy as a first-line treatment. Methods We retrospectively enrolled 52 patients with advanced NSCLC who underwent baseline 18F-FDG PET/CT before treatment initiation. PET/CT parameters and clinico-laboratory variables, constituting the prognostic immunotherapy scoring system, were collected. Optimal cut-off values for PET/CT parameters were determined using the maximized log-rank test for progression-free survival (PFS). A multivariate prediction model was developed based on Cox models for PFS, and a scoring system was established based on hazard ratios of the predictive factors. Results During the median follow-up period of 16.7 months (95% confidence interval: 15.7-17.7 months), 43 (82.7%) and 31 (59.6%) patients experienced disease progression and death, respectively. Objective response was observed in 23 (44.2%) patients. In the multivariate analysis, maximum standardized uptake value, metabolic tumour volume2.5, total lesion glycolysis2.5, and bone marrow-to-liver uptake ratio from the PET/CT variables and neutrophil-to-lymphocyte ratio (NLR) from the clinico-laboratory variables were independently associated with PFS. The scoring system based on these independent predictive variables significantly predicted the treatment response, PFS, and overall survival. Conclusion PET/CT variables and NLR were useful biomarkers for predicting outcomes of patients with NSCLC receiving pembrolizumab and chemotherapy as a first-line treatment, suggesting their potential as effective markers for combined PD-1 blockade and chemotherapy.
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Affiliation(s)
- Chang Gon Kim
- Division of Medical Oncology, Department of Internal Medicine, Yonsei Cancer Centre, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Sang Hyun Hwang
- Department of Nuclear Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Kyung Hwan Kim
- Department of Radiation Oncology, Yonsei Cancer Centre, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Hong In Yoon
- Department of Radiation Oncology, Yonsei Cancer Centre, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Hyo Sup Shim
- Department of Pathology, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Ji Hyun Lee
- Division of Medical Oncology, Department of Internal Medicine, Yonsei Cancer Centre, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Yejeong Han
- Division of Medical Oncology, Department of Internal Medicine, Yonsei Cancer Centre, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Beung-Chul Ahn
- Division of Medical Oncology, Department of Internal Medicine, Yonsei Cancer Centre, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Min Hee Hong
- Division of Medical Oncology, Department of Internal Medicine, Yonsei Cancer Centre, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Hye Ryun Kim
- Division of Medical Oncology, Department of Internal Medicine, Yonsei Cancer Centre, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Byoung Chul Cho
- Division of Medical Oncology, Department of Internal Medicine, Yonsei Cancer Centre, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Arthur Cho
- Department of Nuclear Medicine, Severance Hospital, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea
| | - Sun Min Lim
- Division of Medical Oncology, Department of Internal Medicine, Yonsei Cancer Centre, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea
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Remon J, Facchinetti F, Besse B. The efficacy of immune checkpoint inhibitors in thoracic malignancies. Eur Respir Rev 2021; 30:200387. [PMID: 34615702 PMCID: PMC9489136 DOI: 10.1183/16000617.0387-2020] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Accepted: 02/18/2021] [Indexed: 01/22/2023] Open
Abstract
The advent of immune checkpoint inhibitors (ICIs) has rapidly transformed the treatment paradigm for multiple cancer types, including thoracic malignancies. In advanced non-small cell lung cancer (NSCLC), ICIs have shifted treatment paradigm and improved overall survival reaching almost one-third of patients alive at 5 years. ICIs therapies have also modified the therapeutic strategy in first-line setting in metastatic small-cell lung cancer (SCLC) patients as well as in malignant pleural mesothelioma (MPM) improving the overall survival compared with standard treatment. This phenomenon is of huge relevance as both SCLC and MPM were considered orphan diseases without any significant improvement in the therapeutic strategy in the first-line setting during the last 15 years. In this review, we aim to review the efficacy of ICI in thoracic malignancies either in monotherapy or in combination, according to predictive biomarkers, and to the US Food and Drug Administration and the European Medicines Agency approvals of treatment strategies. We address the efficacy of these agents, especially in NSCLC according to PD-L1 expression and histologic subtype.
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Affiliation(s)
- Jordi Remon
- Dept of Medical Oncology, Centro Integral Oncológico Clara Campal (HM-CIOCC), Hospital HM Delfos, HM Hospitales, Barcelona, Spain
| | - Francesco Facchinetti
- Université Paris-Saclay, Institut Gustave Roussy, Inserm, Biomarqueurs Prédictifs et Nouvelles Stratégies Thérapeutiques en Oncologie, Villejuif, France
| | - Benjamin Besse
- Dept of Cancer Medicine, Gustave Roussy Cancer Campus, Villejuif, France
- Université Paris-Saclay, Paris, France
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Lopci E, Morbelli S. Advances in Lung Cancer Imaging and Therapy. Cancers (Basel) 2021; 14:cancers14010058. [PMID: 35008219 PMCID: PMC8750401 DOI: 10.3390/cancers14010058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Accepted: 12/21/2021] [Indexed: 11/16/2022] Open
Abstract
This series of eight papers (five original articles, two reviews and one meta-analysis) is presented by international leaders covering various aspects of lung cancer management, starting with diagnostic imaging and analyzing the novel perspectives of therapy [...]
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Affiliation(s)
- Egesta Lopci
- Nuclear Medicine, IRCCS Humanitas Research Center, Via Manzoni 56, 20089 Rozzano, Italy
- Correspondence:
| | - Silvia Morbelli
- IRCCS Ospedale Policlinico San Martino, Nuclear Medicine, Largo Rosanna Benzi 10, 16132 Genoa, Italy;
- Department of Health Sciences (DISSAL), University of Genoa, Via Antonio Pastore 1, 16132 Genoa, Italy
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