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Kandemir O, Demir F, Avcı GG. The Prognostic Significance of Tumor SUVmax Value in Pre- and Post-Chemoradiotherapy 18F-FDG PET/CT Imaging in Patients with Localized and Advanced Head and Neck Squamous Cell Carcinoma. Niger J Clin Pract 2024; 27:748-753. [PMID: 38943299 DOI: 10.4103/njcp.njcp_856_23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2023] [Accepted: 04/17/2024] [Indexed: 07/01/2024]
Abstract
BACKGROUND Some parameters of 18F-2-fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (18F-FDG PET/CT) can predict tumor chemosensitivity and survival in patients with head and neck squamous cell carcinoma (HNSCC). AIM The aim of the study was to investigate the prognostic value of pre- and post-treatment maximum standardized uptake values (SUVmax) in 18F-FDG PET/CT imaging for predicting mortality in patients with HNSCC, as well as its prognostic value in terms of disease progression, overall survival (OS), and progression-free survival (PFS). METHODS This retrospective study included 37 patients with a histopathological diagnosis of HNSCCs between 2015 and 2018. In patients with HNSCC, the first 18F-FDG PET/CT imaging was performed for pre-treatment staging, and the second imaging was performed to evaluate post-treatment response. In these imaging studies, SUVmax values of the primary tumor before and after treatment were determined. After the second imaging, patients were re-evaluated and followed up. ROC analysis was used to determine the predictive value of 18F-FDG PET/CT SUVmax parameters in terms of death and progression, and Cox regression analysis was used to investigate the prognostic value in terms of OS and PFS. RESULTS Cut-off value 15 for SUVmax1 (pre-treatment) had a significant predictive value for mortality (P = 0.02). Cut-off value 3.1 for SUVmax2 (post-treatment) had a significant predictive value for progression (P = 0.024). In univariate analysis, both SUVmax1 and SUVmax2 values were significant prognostic factors for OS (P = 0.047, P = 0.004). However, for PFS, only the SUVmax2 value was a significant prognostic factor (P = 0.001). CONCLUSION SUVmax1 value of the primary tumor at diagnosis in HNSCC patients has a predictive value for mortality and a prognostic value for OS. However, the SUVmax2 value in the primary tumor after treatment is a predictive factor for progression and a prognostic factor for both OS and PFS.
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Affiliation(s)
- O Kandemir
- Department of Nuclear Medicine, Faculty of Medicine, Sıtkı Kocman University, Mugla, Turkey
| | - F Demir
- Department, Nuclear Medicine, Kayseri City Health Application and Research Center Kayseri, Health Sciences University, Tokat, Turkey
| | - G G Avcı
- Department of Radiation Oncology, Faculty of Medicine, Gaziosmanpasa University, Tokat, Turkey
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Lee NY, Sherman EJ, Schöder H, Wray R, Boyle JO, Singh B, Grkovski M, Paudyal R, Cunningham L, Zhang Z, Hatzoglou V, Katabi N, Diplas BH, Han J, Imber BS, Pham K, Yu Y, Zakeri K, McBride SM, Kang JJ, Tsai CJ, Chen LC, Gelblum DY, Shah JP, Ganly I, Cohen MA, Cracchiolo JR, Morris LG, Dunn LA, Michel LS, Fetten JV, Kripani A, Pfister DG, Ho AL, Shukla-Dave A, Humm JL, Powell SN, Li BT, Reis-Filho JS, Diaz LA, Wong RJ, Riaz N. Hypoxia-Directed Treatment of Human Papillomavirus-Related Oropharyngeal Carcinoma. J Clin Oncol 2024; 42:940-950. [PMID: 38241600 PMCID: PMC10927322 DOI: 10.1200/jco.23.01308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2023] [Revised: 09/18/2023] [Accepted: 11/08/2023] [Indexed: 01/21/2024] Open
Abstract
PURPOSE Standard curative-intent chemoradiotherapy for human papillomavirus (HPV)-related oropharyngeal carcinoma results in significant toxicity. Since hypoxic tumors are radioresistant, we posited that the aerobic state of a tumor could identify patients eligible for de-escalation of chemoradiotherapy while maintaining treatment efficacy. METHODS We enrolled patients with HPV-related oropharyngeal carcinoma to receive de-escalated definitive chemoradiotherapy in a phase II study (ClinicalTrials.gov identifier: NCT03323463). Patients first underwent surgical removal of disease at their primary site, but not of gross disease in the neck. A baseline 18F-fluoromisonidazole positron emission tomography scan was used to measure tumor hypoxia and was repeated 1-2 weeks intratreatment. Patients with nonhypoxic tumors received 30 Gy (3 weeks) with chemotherapy, whereas those with hypoxic tumors received standard chemoradiotherapy to 70 Gy (7 weeks). The primary objective was achieving a 2-year locoregional control (LRC) of 95% with a 7% noninferiority margin. RESULTS One hundred fifty-eight patients with T0-2/N1-N2c were enrolled, of which 152 patients were eligible for analyses. Of these, 128 patients met criteria for 30 Gy and 24 patients received 70 Gy. The 2-year LRC was 94.7% (95% CI, 89.8 to 97.7), meeting our primary objective. With a median follow-up time of 38.3 (range, 22.1-58.4) months, the 2-year progression-free survival (PFS) and overall survival (OS) rates were 94% and 100%, respectively, for the 30-Gy cohort. The 70-Gy cohort had similar 2-year PFS and OS rates at 96% and 96%, respectively. Acute grade 3-4 adverse events were more common in 70 Gy versus 30 Gy (58.3% v 32%; P = .02). Late grade 3-4 adverse events only occurred in the 70-Gy cohort, in which 4.5% complained of late dysphagia. CONCLUSION Tumor hypoxia is a promising approach to direct dosing of curative-intent chemoradiotherapy for HPV-related carcinomas with preserved efficacy and substantially reduced toxicity that requires further investigation.
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Affiliation(s)
- Nancy Y. Lee
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Eric J. Sherman
- Department of Medical Oncology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - HeiKo Schöder
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Rick Wray
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Jay O. Boyle
- Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Bhuvanesh Singh
- Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Milan Grkovski
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Ramesh Paudyal
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Louise Cunningham
- Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Zhigang Zhang
- Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Vaios Hatzoglou
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Nora Katabi
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Bill H. Diplas
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - James Han
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Brandon S. Imber
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Khoi Pham
- Department of Finance, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Yao Yu
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Kaveh Zakeri
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Sean M. McBride
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Jung J. Kang
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - C. Jillian Tsai
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Linda C. Chen
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Daphna Y. Gelblum
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Jatin P. Shah
- Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Ian Ganly
- Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Marc A. Cohen
- Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY
| | | | - Luc G.T. Morris
- Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Lara A. Dunn
- Department of Medical Oncology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Loren S. Michel
- Department of Medical Oncology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - James V. Fetten
- Department of Medical Oncology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Anuja Kripani
- Department of Medical Oncology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - David G. Pfister
- Department of Medical Oncology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Alan L. Ho
- Department of Medical Oncology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Amita Shukla-Dave
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY
| | - John L. Humm
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Simon N. Powell
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Bob T. Li
- Department of Medical Oncology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Jorge S. Reis-Filho
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Luis A. Diaz
- Department of Medical Oncology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Richard J. Wong
- Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Nadeem Riaz
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY
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Fujimoto K, Shiinoki T, Kawazoe Y, Yuasa Y, Mukaidani W, Manabe Y, Kajima M, Tanaka H. Biomechanical imaging biomarker during chemoradiotherapy predicts treatment response in head and neck squamous cell carcinoma. Phys Med Biol 2024; 69:055033. [PMID: 38359451 DOI: 10.1088/1361-6560/ad29b9] [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: 06/23/2023] [Accepted: 02/15/2024] [Indexed: 02/17/2024]
Abstract
Objective. For response-adapted adaptive radiotherapy (R-ART), promising biomarkers are needed to predict post-radiotherapy (post-RT) responses using routine clinical information obtained during RT. In this study, a patient-specific biomechanical model (BM) of the head and neck squamous cell carcinoma (HNSCC) was proposed using the pre-RT maximum standardized uptake value (SUVmax) of18F-fluorodeoxyglucose (FDG) and tumor structural changes during RT as evaluated using computed tomography (CT). In addition, we evaluated the predictive performance of BM-driven imaging biomarkers for the treatment response of patients with HNSCC who underwent concurrent chemoradiotherapy (CCRT).Approach. Patients with histologically confirmed HNSCC treated with definitive CCRT were enrolled in this study. All patients underwent CT two times as follows: before the start of RT (pre-RT) and 3 weeks after the start of RT (mid-RT). Among these patients, 67 patients who underwent positron emission tomography/CT during the pre-RT period were included in the final analysis. The locoregional control (LC), progression-free survival (PFS), and overall survival (OS) prediction performances of whole tumor stress change (TS) between pre- and mid-RT computed using BM were assessed using univariate, multivariate, and Kaplan-Meier survival curve analyses, respectively. Furthermore, performance was compared with the pre and post-RT SUVmax, tumor volume reduction rate (TVRR) during RT, and other clinical prognostic factors.Main results. For both univariate, multivariate, and survival curve analyses, the significant prognostic factors were as follows (p< 0.05): TS and TVRR for LC; TS and pre-RT FDG-SUVmaxfor PFS; and TS only for OS. In addition, for 2 year LC, PFS, and OS prediction, TS showed a comparable predictive performance to post-RT FDG-SUVmax.Significance. BM-driven TS is an effective prognostic factor for tumor treatment response after CCRT. The proposed method can be a feasible functional imaging biomarker that can be acquired during RT using only routine clinical data and may provide useful information for decision-making during R-ART.
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Affiliation(s)
- Koya Fujimoto
- Department of Radiation Oncology, Graduate School of Medicine, Yamaguchi University, Ube, Japan
| | - Takehiro Shiinoki
- Department of Radiation Oncology, Graduate School of Medicine, Yamaguchi University, Ube, Japan
| | - Yusuke Kawazoe
- Department of Radiation Oncology, Graduate School of Medicine, Yamaguchi University, Ube, Japan
- Department of Radiological Technology, Yamaguchi University Hospital, Ube, Japan
| | - Yuki Yuasa
- Department of Radiological Technology, Yamaguchi University Hospital, Ube, Japan
| | - Wataru Mukaidani
- Department of Radiological Technology, Yamaguchi University Hospital, Ube, Japan
| | - Yuki Manabe
- Department of Radiation Oncology, Graduate School of Medicine, Yamaguchi University, Ube, Japan
| | - Miki Kajima
- Department of Radiation Oncology, Graduate School of Medicine, Yamaguchi University, Ube, Japan
| | - Hidekazu Tanaka
- Department of Radiation Oncology, Graduate School of Medicine, Yamaguchi University, Ube, Japan
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McDonald BA, Dal Bello R, Fuller CD, Balermpas P. The Use of MR-Guided Radiation Therapy for Head and Neck Cancer and Recommended Reporting Guidance. Semin Radiat Oncol 2024; 34:69-83. [PMID: 38105096 PMCID: PMC11372437 DOI: 10.1016/j.semradonc.2023.10.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Although magnetic resonance imaging (MRI) has become standard diagnostic workup for head and neck malignancies and is currently recommended by most radiological societies for pharyngeal and oral carcinomas, its utilization in radiotherapy has been heterogeneous during the last decades. However, few would argue that implementing MRI for annotation of target volumes and organs at risk provides several advantages, so that implementation of the modality for this purpose is widely accepted. Today, the term MR-guidance has received a much broader meaning, including MRI for adaptive treatments, MR-gating and tracking during radiotherapy application, MR-features as biomarkers and finally MR-only workflows. First studies on treatment of head and neck cancer on commercially available dedicated hybrid-platforms (MR-linacs), with distinct common features but also differences amongst them, have also been recently reported, as well as "biological adaptation" based on evaluation of early treatment response via functional MRI-sequences such as diffusion weighted ones. Yet, all of these approaches towards head and neck treatment remain at their infancy, especially when compared to other radiotherapy indications. Moreover, the lack of standardization for reporting MR-guided radiotherapy is a major obstacle both to further progress in the field and to conduct and compare clinical trials. Goals of this article is to present and explain all different aspects of MR-guidance for radiotherapy of head and neck cancer, summarize evidence, as well as possible advantages and challenges of the method and finally provide a comprehensive reporting guidance for use in clinical routine and trials.
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Affiliation(s)
- Brigid A McDonald
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Riccardo Dal Bello
- Department of Radiation Oncology, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Clifton D Fuller
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Panagiotis Balermpas
- Department of Radiation Oncology, University Hospital Zurich and University of Zurich, Zurich, Switzerland.
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Trada Y, Keall P, Jameson M, Moses D, Lin P, Chlap P, Holloway L, Min M, Forstner D, Fowler A, Lee MT. Changes in serial multiparametric MRI and FDG-PET/CT functional imaging during radiation therapy can predict treatment response in patients with head and neck cancer. Eur Radiol 2023; 33:8788-8799. [PMID: 37405500 PMCID: PMC10667402 DOI: 10.1007/s00330-023-09843-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Revised: 04/03/2023] [Accepted: 04/14/2023] [Indexed: 07/06/2023]
Abstract
OBJECTIVES To test if tumour changes measured using combination of diffusion-weighted imaging (DWI) MRI and FDG-PET/CT performed serially during radiotherapy (RT) in mucosal head and neck carcinoma can predict treatment response. METHODS Fifty-five patients from two prospective imaging biomarker studies were analysed. FDG-PET/CT was performed at baseline, during RT (week 3), and post RT (3 months). DWI was performed at baseline, during RT (weeks 2, 3, 5, 6), and post RT (1 and 3 months). The ADCmean from DWI and FDG-PET parameters SUVmax, SUVmean, metabolic tumour volume (MTV), and total lesion glycolysis (TLG) were measured. Absolute and relative change (%∆) in DWI and PET parameters were correlated to 1-year local recurrence. Patients were categorised into favourable, mixed, and unfavourable imaging response using optimal cut-off (OC) values of DWI and FDG-PET parameters and correlated to local control. RESULTS The 1-year local, regional, and distant recurrence rates were 18.2% (10/55), 7.3% (4/55), and 12.7% (7/55), respectively. ∆Week 3 ADCmean (AUC 0.825, p = 0.003; OC ∆ > 24.4%) and ∆MTV (AUC 0.833, p = 0.001; OC ∆ > 50.4%) were the best predictors of local recurrence. Week 3 was the optimal time point for assessing DWI imaging response. Using a combination of ∆ADCmean and ∆MTV improved the strength of correlation to local recurrence (p ≤ 0.001). In patients who underwent both week 3 MRI and FDG-PET/CT, significant differences in local recurrence rates were seen between patients with favourable (0%), mixed (17%), and unfavourable (78%) combined imaging response. CONCLUSIONS Changes in mid-treatment DWI and FDG-PET/CT imaging can predict treatment response and could be utilised in the design of future adaptive clinical trials. CLINICAL RELEVANCE STATEMENT Our study shows the complementary information provided by two functional imaging modalities for mid-treatment response prediction in patients with head and neck cancer. KEY POINTS •FDG-PET/CT and DWI MRI changes in tumour during radiotherapy in head and neck cancer can predict treatment response. •Combination of FDG-PET/CT and DWI parameters improved correlation to clinical outcome. •Week 3 was the optimal time point for DWI MRI imaging response assessment.
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Affiliation(s)
- Yuvnik Trada
- Department of Radiation Oncology, Calvary Mater Newcastle, Edith St, Waratah, NSW, 2298, Australia.
- Faculty of Medicine and Health, Sydney Medical School, The University of Sydney, Sydney, NSW, Australia.
| | - Paul Keall
- Faculty of Medicine and Health, Sydney Medical School, The University of Sydney, Sydney, NSW, Australia
- ACRF Image X Institute, University of Sydney, Sydney, NSW, Australia
| | - Michael Jameson
- GenesisCare St Vincents Hospital, Sydney, NSW, Australia
- St Vincents Clinical School, Faculty of Medicine, University of Sydney, Sydney, NSW, Australia
| | - Daniel Moses
- Faculty of Medicine and Health, Sydney Medical School, The University of Sydney, Sydney, NSW, Australia
- Graduate School of Biomedical Engineering, Faculty of Engineering, University of New South Wales, Sydney, NSW, Australia
- Department of Medical Imaging, Prince of Wales Hospital, Randwick, NSW, Australia
| | - Peter Lin
- Department of Nuclear Medicine and PET, Liverpool Hospital, Liverpool, NSW, Australia
- School of Medicine, Western Sydney University, Sydney, NSW, Australia
| | - Phillip Chlap
- Department of Radiation Oncology, Cancer Therapy Centre, Liverpool Hospital, Liverpool, NSW, Australia
- South Western Clinical School, School of Medicine, University of New South Wales, Sydney, NSW, Australia
- Ingham Institute of Applied Medical Research, Liverpool, NSW, Australia
| | - Lois Holloway
- Department of Radiation Oncology, Cancer Therapy Centre, Liverpool Hospital, Liverpool, NSW, Australia
- South Western Clinical School, School of Medicine, University of New South Wales, Sydney, NSW, Australia
- Ingham Institute of Applied Medical Research, Liverpool, NSW, Australia
| | - Myo Min
- University of Sunshine Coast, Birtinya, QLD, Australia
- Sunshine Coast University Hospital, Sunshine Coast, QLD, Australia
- Griffith University, Sunshine Coast, QLD, Australia
| | - Dion Forstner
- GenesisCare St Vincents Hospital, Sydney, NSW, Australia
- St Vincents Clinical School, Faculty of Medicine, University of Sydney, Sydney, NSW, Australia
| | - Allan Fowler
- Department of Radiation Oncology, Cancer Therapy Centre, Liverpool Hospital, Liverpool, NSW, Australia
| | - Mark T Lee
- Department of Radiation Oncology, Cancer Therapy Centre, Liverpool Hospital, Liverpool, NSW, Australia
- South Western Clinical School, School of Medicine, University of New South Wales, Sydney, NSW, Australia
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Chao YK, Chang CB, Chang YC, Chan SC, Chiu CH, Ng SH, Hsieh JCH, Wang JH. Baseline and interim [18F]FDG-PET/MRI to assess treatment response and survival in patients with M0 esophageal squamous cell carcinoma treated by curative-intent therapy. Cancer Imaging 2023; 23:109. [PMID: 37932848 PMCID: PMC10629192 DOI: 10.1186/s40644-023-00630-2] [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: 06/23/2023] [Accepted: 11/01/2023] [Indexed: 11/08/2023] Open
Abstract
BACKGROUND To investigate the value of [18F]FDG-PET/MRI in predicting treatment response and survival in patients with primary M0 esophageal squamous cell carcinoma. METHODS Patients with esophageal squamous cell carcinoma received [18F]FDG-PET/MRI at baseline and during neoadjuvant or definitive chemoradiotherapy. The treatment response was classified according to the Response Evaluation Criteria for Solid Tumors 1.1. We used Kaplan-Meier and Cox regression analyses to assess the association between PET/MRI parameters and overall survival (OS) or progression-free survival (PFS). RESULTS We included 40 M0 patients in the final analysis. The volume transfer constant (Ktrans) from baseline PET/MRI (area under the curve (AUC) = 0.688, P = 0.034) and total lesion glycolysis (TLG) from baseline PET/MRI (AUC = 0.723, P = 0.006) or interim PET/MRI (AUC = 0.853, P < 0.001) showed acceptable AUC for predicting treatment response. The TLG from interim PET/MRI (interim TLG, P < 0.001) and extracellular volume fraction (Ve) on interim PET/MRI (interim Ve, P = 0.001) were identified as independent prognostic factors for OS. Baseline Ve (P = 0.044) and interim TLG (P = 0.004) were significant predictors of PFS. The c-indices of the prognostic models combining interim TLG with Ve for predicting OS, and baseline Ve and interim TLG for predicting PFS were 0.784 and 0.699, respectively. These values were significantly higher than the corresponding c-indices of the TNM staging system (P = 0.002 and P = 0.047, respectively). CONCLUSIONS Combining the baseline and interim [18F]FDG-PET/MRI qualitative imaging parameters aids in predicting the prognosis of patients with M0 esophageal squamous cell carcinoma. TRIAL REGISTRATION The study was registered at Clinicaltrials.gov (identifier: NCT05855291 and NCT05855278).
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Affiliation(s)
- Yin-Kai Chao
- Division of Thoracic Surgery, Chang Gung Memorial Hospital-Linko, Chang Gung University, Taoyuan, 333423, Taiwan
| | - Chun-Bi Chang
- Department of Diagnostic Radiology, Linkou Chang Gung Memorial Hospital, Chang Gung University, Taoyuan, 333423, Taiwan
| | - Yu-Chuan Chang
- Department of Nuclear Medicine and Molecular Imaging Center, Chang Gung Memorial Hospital-Linko, Chang Gung University, Taoyuan, 333423, Taiwan
| | - Sheng-Chieh Chan
- Department of Nuclear Medicine, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien, 970423, Taiwan.
- School of Medicine, Tzu Chi University, Hualien, 970423, Taiwan.
| | - Chien-Hung Chiu
- Division of Thoracic Surgery, Chang Gung Memorial Hospital-Linko, Chang Gung University, Taoyuan, 333423, Taiwan
| | - Shu-Hang Ng
- Department of Diagnostic Radiology, Linkou Chang Gung Memorial Hospital, Chang Gung University, Taoyuan, 333423, Taiwan
| | - Jason Chia-Hsun Hsieh
- Division of Hematology/Oncology, Department of Internal Medicine, Linkou Chang Gung Memorial Hospital, Chang Gung University, Taoyuan, 333423, Taiwan
| | - Jen-Hung Wang
- Department of Medical Research, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien, 970423, Taiwan
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Longitudinal diffusion and volumetric kinetics of head and neck cancer magnetic resonance on a 1.5 T MR-linear accelerator hybrid system: A prospective R-IDEAL stage 2a imaging biomarker characterization/pre-qualification study. Clin Transl Radiat Oncol 2023; 42:100666. [PMID: 37583808 PMCID: PMC10424120 DOI: 10.1016/j.ctro.2023.100666] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2023] [Revised: 07/18/2023] [Accepted: 07/22/2023] [Indexed: 08/17/2023] Open
Abstract
Objectives We aim to characterize the serial quantitative apparent diffusion coefficient (ADC) changes of the target disease volume using diffusion-weighted imaging (DWI) acquired weekly during radiation therapy (RT) on a 1.5 T MR-Linac and correlate these changes with tumor response and oncologic outcomes for head and neck squamous cell carcinoma (HNSCC) patients as part of a programmatic R-IDEAL biomarker characterization effort. Methods Thirty patients with HNSCC who received curative-intent RT at MD Anderson Cancer Center, were included. Baseline and weekly MRI were obtained, and various ADC parameters were extracted from the regions of interest (ROIs). Baseline and weekly ADC parameters were correlated with response during and after RT, and the recurrence using the Mann-Whitney U test. The Wilcoxon signed-rank test was used to compare the weekly ADC versus baseline values. Weekly volumetric changes (Δvolume) for each ROI were correlated with ΔADC using Spearman's Rho test. Recursive partitioning analysis (RPA) identified the optimal ΔADC threshold associated with different oncologic outcomes. Results There was a significant rise in all ADC parameters at different time points of RT compared to baseline for both gross primary disease (GTV-P) and gross nodal disease volumes (GTV-N). The increased ADC values for GTV-P were statistically significant only for primary tumors achieving complete remission (CR) during RT. RPA identified GTV-P ΔADC 5th percentile > 13% at the mid-RT as the most significant parameter associated with primary tumors' CR during RT (p < 0.001). There was a significant decrease in residual volume of both GTV-P & GTV-N throughout the course of RT. A significant negative correlation between mean ΔADC and Δvolume for GTV-P at the 3rd and 4th week of RT was detected (r = -0.39, p = 0.044 & r = -0.45, p = 0.019, respectively). Conclusion Assessment of ADC kinetics at regular intervals throughout RT seems to be correlated with RT response. Further studies with larger cohorts and multi-institutional data are needed for validation of ΔADC as a model for prediction of response to RT.
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Adjogatse D, Michaelidou A, Sanchez Nieto B, Kozarski R, Sassoon I, Evans M, Rackley T, Shah S, Eaton D, Pike L, Curry S, Gould SM, Thomas C, Kong A, Petkar I, Reis-Ferreira M, Connor S, Barrington SF, Lei M, Guerrero Urbano T. Protocol letter: Intra-treatment Image Guided Adaptive Radiotherapy Dose-escalation Study (InGReS) - A Phase 1 multicentre feasibility study. Radiother Oncol 2023; 183:109645. [PMID: 36997123 DOI: 10.1016/j.radonc.2023.109645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Accepted: 03/21/2023] [Indexed: 03/30/2023]
Affiliation(s)
- Delali Adjogatse
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; Department of Clinical Oncology, Guy's and St Thomas' NHS Foundation Trust, London, UK.
| | - Andriana Michaelidou
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; Department of Clinical Oncology, Guy's and St Thomas' NHS Foundation Trust, London, UK
| | | | - Robert Kozarski
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Isabel Sassoon
- Computer Science Department, Brunel University London, Uxbridge, UK
| | - Mererid Evans
- Department of Oncology, Velindre University NHS Trust, Cardiff, UK
| | - Thomas Rackley
- Department of Oncology, Velindre University NHS Trust, Cardiff, UK
| | - Simon Shah
- Department of Medical Physics, Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - David Eaton
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; Department of Medical Physics, Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Lucy Pike
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Sorcha Curry
- King's College and Guy's and St Thomas' Hospital PET Centre, London, UK
| | - Sarah-May Gould
- King's College and Guy's and St Thomas' Hospital PET Centre, London, UK
| | - Christopher Thomas
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; Department of Medical Physics, Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Anthony Kong
- Department of Clinical Oncology, Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Imran Petkar
- Department of Clinical Oncology, Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Miguel Reis-Ferreira
- Department of Clinical Oncology, Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Stephen Connor
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; Department of Radiology Guy's and St Thomas' NHS Foundation Trust, London, UK; Department of Neuroradiology, King's College Hospital, London UK
| | - Sally Fiona Barrington
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; King's College and Guy's and St Thomas' Hospital PET Centre, London, UK
| | - Mary Lei
- Department of Clinical Oncology, Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Teresa Guerrero Urbano
- Department of Clinical Oncology, Guy's and St Thomas' NHS Foundation Trust, London, UK; King's College London, Faculty of Dentistry, Oral and Craniofacial Sciences, London, UK
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9
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Goodburn RJ, Philippens MEP, Lefebvre TL, Khalifa A, Bruijnen T, Freedman JN, Waddington DEJ, Younus E, Aliotta E, Meliadò G, Stanescu T, Bano W, Fatemi‐Ardekani A, Wetscherek A, Oelfke U, van den Berg N, Mason RP, van Houdt PJ, Balter JM, Gurney‐Champion OJ. The future of MRI in radiation therapy: Challenges and opportunities for the MR community. Magn Reson Med 2022; 88:2592-2608. [PMID: 36128894 PMCID: PMC9529952 DOI: 10.1002/mrm.29450] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 08/17/2022] [Accepted: 08/22/2022] [Indexed: 01/11/2023]
Abstract
Radiation therapy is a major component of cancer treatment pathways worldwide. The main aim of this treatment is to achieve tumor control through the delivery of ionizing radiation while preserving healthy tissues for minimal radiation toxicity. Because radiation therapy relies on accurate localization of the target and surrounding tissues, imaging plays a crucial role throughout the treatment chain. In the treatment planning phase, radiological images are essential for defining target volumes and organs-at-risk, as well as providing elemental composition (e.g., electron density) information for radiation dose calculations. At treatment, onboard imaging informs patient setup and could be used to guide radiation dose placement for sites affected by motion. Imaging is also an important tool for treatment response assessment and treatment plan adaptation. MRI, with its excellent soft tissue contrast and capacity to probe functional tissue properties, holds great untapped potential for transforming treatment paradigms in radiation therapy. The MR in Radiation Therapy ISMRM Study Group was established to provide a forum within the MR community to discuss the unmet needs and fuel opportunities for further advancement of MRI for radiation therapy applications. During the summer of 2021, the study group organized its first virtual workshop, attended by a diverse international group of clinicians, scientists, and clinical physicists, to explore our predictions for the future of MRI in radiation therapy for the next 25 years. This article reviews the main findings from the event and considers the opportunities and challenges of reaching our vision for the future in this expanding field.
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Affiliation(s)
- Rosie J. Goodburn
- Joint Department of PhysicsInstitute of Cancer Research and Royal Marsden NHS Foundation TrustLondonUnited Kingdom
| | | | - Thierry L. Lefebvre
- Department of PhysicsUniversity of CambridgeCambridgeUnited Kingdom
- Cancer Research UK Cambridge Research InstituteUniversity of CambridgeCambridgeUnited Kingdom
| | - Aly Khalifa
- Department of Medical BiophysicsUniversity of TorontoTorontoOntarioCanada
| | - Tom Bruijnen
- Department of RadiotherapyUniversity Medical Center UtrechtUtrechtNetherlands
| | | | - David E. J. Waddington
- Faculty of Medicine and Health, Sydney School of Health Sciences, ACRF Image X InstituteThe University of SydneySydneyNew South WalesAustralia
| | - Eyesha Younus
- Department of Medical Physics, Odette Cancer CentreSunnybrook Health Sciences CentreTorontoOntarioCanada
| | - Eric Aliotta
- Department of Medical PhysicsMemorial Sloan Kettering Cancer CenterNew YorkNew YorkUSA
| | - Gabriele Meliadò
- Unità Operativa Complessa di Fisica SanitariaAzienda Ospedaliera Universitaria Integrata VeronaVeronaItaly
| | - Teo Stanescu
- Department of Radiation Oncology, University of Toronto and Medical Physics, Princess Margaret Cancer CentreUniversity Health NetworkTorontoOntarioCanada
| | - Wajiha Bano
- Joint Department of PhysicsInstitute of Cancer Research and Royal Marsden NHS Foundation TrustLondonUnited Kingdom
| | - Ali Fatemi‐Ardekani
- Department of PhysicsJackson State University (JSU)JacksonMississippiUSA
- SpinTecxJacksonMississippiUSA
- Department of Radiation OncologyCommunity Health Systems (CHS) Cancer NetworkJacksonMississippiUSA
| | - Andreas Wetscherek
- Joint Department of PhysicsInstitute of Cancer Research and Royal Marsden NHS Foundation TrustLondonUnited Kingdom
| | - Uwe Oelfke
- Joint Department of PhysicsInstitute of Cancer Research and Royal Marsden NHS Foundation TrustLondonUnited Kingdom
| | - Nico van den Berg
- Department of RadiotherapyUniversity Medical Center UtrechtUtrechtNetherlands
| | - Ralph P. Mason
- Department of RadiologyUniversity of Texas Southwestern Medical CenterDallasTexasUSA
| | - Petra J. van Houdt
- Department of Radiation OncologyNetherlands Cancer InstituteAmsterdamNetherlands
| | - James M. Balter
- Department of Radiation OncologyUniversity of MichiganAnn ArborMichiganUSA
| | - Oliver J. Gurney‐Champion
- Imaging and Biomarkers, Cancer Center Amsterdam, Amsterdam UMCUniversity of AmsterdamAmsterdamNetherlands
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10
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Zhao D, Fang X, Fan W, Meng L, Luo Y, Chen N, Li J, Zang X, Li M, Guo X, Cao B, Wu C, Tan X, Cai B, Ma L. A comparative study of functional MRI in predicting response of regional nodes to induction chemotherapy in patients with nasopharyngeal carcinoma. Front Oncol 2022; 12:960490. [PMID: 36119537 PMCID: PMC9472652 DOI: 10.3389/fonc.2022.960490] [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: 06/03/2022] [Accepted: 08/09/2022] [Indexed: 11/13/2022] Open
Abstract
PurposeTo identify and compare the value of functional MRI (fMRI) in predicting the early response of metastatic cervical lymph nodes (LNs) to induction chemotherapy (IC) in nasopharyngeal carcinoma (NPC) patients.MethodsThis prospective study collected 94 metastatic LNs from 40 consecutive NPC patients treated with IC from January 2021 to May 2021. Conventional diffusion-weighted imaging, diffusion kurtosis imaging, intravoxel incoherent motion, and dynamic contrast-enhanced magnetic resonance imaging were performed before and after IC. The parameter maps apparent diffusion coefficient (ADC), mean diffusion coefficient (MD), mean kurtosis (MK), Dslow, Dfast, perfusion fraction (PF), Ktrans, Ve, and Kep) of the metastatic nodes were calculated by the Functool postprocessing software. All LNs were classified as the responding group (RG) and non-responding group (NRG) according to Response Evaluation Criteria in Solid Tumors 1.1. The fMRI parameters were compared before and after IC and between the RG and the NRG. The significant parameters are fitted by logistic regression analysis to produce new predictive factor (PRE)–predicted probabilities. Logistic regression analysis and receiver operating characteristic (ROC) curves were performed to further identify and compare the efficacy of the parameters.ResultsAfter IC, the mean values of ADC, MD, and Dslow significantly increased, while MK, Dfast, and Ktrans values decreased dramatically, while no significant difference was detected in Ve and Kep. Compared with NRG, PF-pre and Ktrans-pre values in the RG were higher statistically. The areas under the ROC for the pretreatment PF, Ktrans, and PRE were 0.736, 0.722, and 0.810, respectively, with the optimal cutoff value of 222 × 10-4, 934 × 10-3/min, and 0.6624, respectively.ConclusionsThe pretreatment fMRI parameters PF and Ktrans showed promising potential in predicting the response of the metastatic LNs to IC in NPC patients.Clinical Trial RegistrationThis study was approved by the ethics board of the Chinese PLA General Hospital, and registered on 30 January 2021, in the Chinese Clinical Trial Registry; http://www.chictr.org.cn/showproj.aspx?proj=121198, identifier (ChiCTR2100042863).
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Affiliation(s)
- Dawei Zhao
- Department of Radiation Oncology, First Medical Center of Chinese PLA General Hospital, Beijing, China
- Department of Radiology, Characteristic Medical Center of Chinese People’s Armed Police Force, Tianjin, China
| | - Xuemei Fang
- Department of Radiation Oncology, First Medical Center of Chinese PLA General Hospital, Beijing, China
- Department of Ultrasound, Tianjin Medical University General Hospital Airport Hospital, Tianjin, China
| | - Wenjun Fan
- Department of Radiation Oncology, First Medical Center of Chinese PLA General Hospital, Beijing, China
- Affiliated Foshan Maternity & Child Healthcare Hospital, Southern Medical University, Foshan, China
- Department of Oncology, Armed Police Forces Corps Hospital of Henan Province, Zhengzhou, China
| | - Lingling Meng
- Department of Radiation Oncology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Yanrong Luo
- Department of Radiation Oncology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Nanxiang Chen
- Department of Otolaryngology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Jinfeng Li
- Department of Radiology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Xiao Zang
- Department of Radiology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Meng Li
- Department of Radiology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Xingdong Guo
- Department of Radiation Oncology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Biyang Cao
- Department of Radiation Oncology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Chenchen Wu
- Department of Radiation Oncology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Xin Tan
- Department of Radiation Oncology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Boning Cai
- Department of Radiation Oncology, First Medical Center of Chinese PLA General Hospital, Beijing, China
- Department of Radiation Oncology, Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
- *Correspondence: Boning Cai, ; Lin Ma,
| | - Lin Ma
- Department of Radiation Oncology, First Medical Center of Chinese PLA General Hospital, Beijing, China
- Department of Radiation Oncology, Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
- *Correspondence: Boning Cai, ; Lin Ma,
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11
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Kooreman ES, van Pelt V, Nowee ME, Pos F, van der Heide UA, van Houdt PJ. Longitudinal Correlations Between Intravoxel Incoherent Motion (IVIM) and Dynamic Contrast-Enhanced (DCE) MRI During Radiotherapy in Prostate Cancer Patients. Front Oncol 2022; 12:897130. [PMID: 35747819 PMCID: PMC9210504 DOI: 10.3389/fonc.2022.897130] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 05/03/2022] [Indexed: 11/13/2022] Open
Abstract
Purpose Intravoxel incoherent motion (IVIM) is a promising technique that can acquire perfusion information without the use of contrast agent, contrary to the more established dynamic contrast-enhanced (DCE) technique. This is of interest for treatment response monitoring, where patients can be imaged on each treatment fraction. In this study, longitudinal correlations between IVIM- and DCE parameters were assessed in prostate cancer patients receiving radiation treatment. Materials and Methods 20 prostate cancer patients were treated on a 1.5 T MR-linac with 20 x 3 or 3.1 Gy. Weekly IVIM and DCE scans were acquired. Tumors, the peripheral zone (PZ), and the transition zone (TZ) were delineated on a T2-weighted scan acquired on the first fraction. IVIM and DCE scans were registered to this scan and the delineations were propagated. Median values from these delineations were used for further analysis. The IVIM parameters D, f, D* and the product fD* were calculated. The Tofts model was used to calculate the DCE parameters Ktrans, kep and ve. Pearson correlations were calculated for the IVIM and DCE parameters on values from the first fraction for each region of interest (ROI). For longitudinal analysis, the repeated measures correlation coefficient was used to determine correlations between IVIM and DCE parameters in each ROI. Results When averaging over patients, an increase during treatment in all IVIM and DCE parameters was observed in all ROIs, except for D in the PZ and TZ. No significant Pearson correlations were found between any pair of IVIM and DCE parameters measured on the first fraction. Significant but low longitudinal correlations were found for some combinations of IVIM and DCE parameters in the PZ and TZ, while no significant longitudinal correlations were found in the tumor. Notably in the TZ, for both f and fD*, significant longitudinal correlations with all DCE parameters were found. Conclusions The increase in IVIM- and DCE parameters when averaging over patients indicates a measurable response to radiation treatment with both techniques. Although low, significant longitudinal correlations were found which suggests that IVIM could potentially be used as an alternative to DCE for treatment response monitoring.
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12
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D’Urso P, Farneti A, Marucci L, Marzi S, Piludu F, Vidiri A, Sanguineti G. Predictors of Outcome after (Chemo)Radiotherapy for Node-Positive Oropharyngeal Cancer: The Role of Functional MRI. Cancers (Basel) 2022; 14:cancers14102477. [PMID: 35626084 PMCID: PMC9139324 DOI: 10.3390/cancers14102477] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Revised: 05/13/2022] [Accepted: 05/14/2022] [Indexed: 02/04/2023] Open
Abstract
The prognosis of a subset of patients with locally advanced oropharyngeal cancer (LA-OPC) is still poor despite improvements in patient selection and treatment. Identifying specific patient- and tumor-related factors can help to select those patients who need intensified treatment. We aimed to assess the role of historical risk factors and novel magnetic resonance imaging (MRI) biomarkers in predicting outcomes in these patients. Patients diagnosed with LA-OPC were studied with diffusion-weighted imaging (DWI) and dynamic-contrast enhanced MRI at baseline and at the 10th radiotherapy (RT) fraction. Clinical information was collected as well. The endpoint of the study was the development of disease progression, locally or distantly. Of the 97 patients enrolled, 68 were eligible for analysis. Disease progression was recorded in 21 patients (11 had loco-regional progression, 10 developed distant metastases). We found a correlation between N diameter and disease control (p = 0.02); features such as p16 status and extranodal extension only showed a trend towards statistical significance. Among perfusion MRI features, higher median values of Kep both in primary tumor (T, p = 0.016) and lymph node (N, p = 0.003) and lower median values of ve (p = 0.018 in T, p = 0.004 in N) correlated with better disease control. Kep P90 and N diameter were identified by MRMR algorithm as the best predictors of outcome. In conclusion, the association of non-invasive MRI biomarkers and patients and tumor characteristics may help in predicting disease behavior and patient outcomes in order to ensure a more customized treatment.
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Affiliation(s)
- Pasqualina D’Urso
- Department of Radiotherapy, IRCCS Regina Elena National Cancer Institute, 00144 Rome, Italy; (A.F.); (L.M.); (G.S.)
- Correspondence:
| | - Alessia Farneti
- Department of Radiotherapy, IRCCS Regina Elena National Cancer Institute, 00144 Rome, Italy; (A.F.); (L.M.); (G.S.)
| | - Laura Marucci
- Department of Radiotherapy, IRCCS Regina Elena National Cancer Institute, 00144 Rome, Italy; (A.F.); (L.M.); (G.S.)
| | - Simona Marzi
- Medical Physics Laboratory, IRCCS Regina Elena National Cancer Institute, 00144 Rome, Italy;
| | - Francesca Piludu
- Radiology and Diagnostic Imaging Department, IRCCS Regina Elena National Cancer Institute, 00144 Rome, Italy; (F.P.); (A.V.)
| | - Antonello Vidiri
- Radiology and Diagnostic Imaging Department, IRCCS Regina Elena National Cancer Institute, 00144 Rome, Italy; (F.P.); (A.V.)
| | - Giuseppe Sanguineti
- Department of Radiotherapy, IRCCS Regina Elena National Cancer Institute, 00144 Rome, Italy; (A.F.); (L.M.); (G.S.)
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13
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Early Response Prediction of Multiparametric Functional MRI and 18F-FDG-PET in Patients with Head and Neck Squamous Cell Carcinoma Treated with (Chemo)Radiation. Cancers (Basel) 2022; 14:cancers14010216. [PMID: 35008380 PMCID: PMC8750157 DOI: 10.3390/cancers14010216] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2021] [Revised: 12/20/2021] [Accepted: 12/23/2021] [Indexed: 12/14/2022] Open
Abstract
Simple Summary Patients with locally-advanced head and neck squamous cell carcinoma (HNSCC) have variable responses to (chemo)radiotherapy. A reliable early prediction of outcomes allows for enhancing treatment efficacy and follow-up monitoring. Early tumoral changes can be captured by functional imaging (DWI/IVIM/DCE/18F-FDG-PET-CT) parameters, which allow for the construction of accurate patient-specific prognostic models for locoregional recurrence-free survival, distant metastasis-free survival and overall survival. We also present clinical applicable risk stratification in high/medium/low risks for these patient outcomes. This can enable personalized treatment (adaptation) management early on during treatment, improve counseling and enhance patient-specific post-therapy monitoring. Abstract Background: Patients with locally-advanced head and neck squamous cell carcinoma (HNSCC) have variable responses to (chemo)radiotherapy. A reliable prediction of outcomes allows for enhancing treatment efficacy and follow-up monitoring. Methods: Fifty-seven histopathologically-proven HNSCC patients with curative (chemo)radiotherapy were prospectively included. All patients had an MRI (DW,-IVIM, DCE-MRI) and 18F-FDG-PET/CT before and 10 days after start-treatment (intratreatment). Primary tumor functional imaging parameters were extracted. Univariate and multivariate analysis were performed to construct prognostic models and risk stratification for 2 year locoregional recurrence-free survival (LRFFS), distant metastasis-free survival (DMFS) and overall survival (OS). Model performance was measured by the cross-validated area under the receiver operating characteristic curve (AUC). Results: The best LRFFS model contained the pretreatment imaging parameters ADC_kurtosis, Kep and SUV_peak, and intratreatment imaging parameters change (Δ) Δ-ADC_skewness, Δ-f, Δ-SUV_peak and Δ-total lesion glycolysis (TLG) (AUC = 0.81). Clinical parameters did not enhance LRFFS prediction. The best DMFS model contained pretreatment ADC_kurtosis and SUV_peak (AUC = 0.88). The best OS model contained gender, HPV-status, N-stage, pretreatment ADC_skewness, D, f, metabolic-active tumor volume (MATV), SUV_mean and SUV_peak (AUC = 0.82). Risk stratification in high/medium/low risk was significantly prognostic for LRFFS (p = 0.002), DMFS (p < 0.001) and OS (p = 0.003). Conclusions: Intratreatment functional imaging parameters capture early tumoral changes that only provide prognostic information regarding LRFFS. The best LRFFS model consisted of pretreatment, intratreatment and Δ functional imaging parameters; the DMFS model consisted of only pretreatment functional imaging parameters, and the OS model consisted ofHPV-status, gender and only pretreatment functional imaging parameters. Accurate clinically applicable risk stratification calculators can enable personalized treatment (adaptation) management, early on during treatment, improve counseling and enhance patient-specific post-therapy monitoring.
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14
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Zhao DW, Fan WJ, Meng LL, Luo YR, Wei J, Liu K, Liu G, Li JF, Zang X, Li M, Zhang XX, Ma L. Comparison of the pre-treatment functional MRI metrics' efficacy in predicting Locoregionally advanced nasopharyngeal carcinoma response to induction chemotherapy. Cancer Imaging 2021; 21:59. [PMID: 34758876 PMCID: PMC8579637 DOI: 10.1186/s40644-021-00428-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2021] [Accepted: 09/10/2021] [Indexed: 02/07/2023] Open
Abstract
Background Functional MRI (fMRI) parameters analysis has been proven to be a promising tool of predicting therapeutic response to induction chemotherapy (IC) in nasopharyngeal carcinoma (NPC). The study was designed to identify and compare the value of fMRI parameters in predicting early response to IC in patients with NPC. Methods This prospective study enrolled fifty-six consecutively NPC patients treated with IC from January 2021 to May 2021. Conventional diffusion weighted imaging (DWI), diffusion kurtosis imaging (DKI), intravoxel incoherent motion (IVIM) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) protocols were performed before and after IC. Parameters maps (ADC, MD, MK, Dslow, Dfast, PF, Ktrans, Ve and Kep) of the primary tumor were calculated by the Functool post-processing software. The participants were classified as responding group (RG) and non-responding group (NRG) according to Response Evaluation Criteria in Solid Tumors 1.1. The fMRI parameters were compared before and after IC and between RG with NRG. Logistic regression analysis and ROC were performed to further identify and compare the efficacy of the parameters. Results After IC, the mean values of ADC(p < 0.001), MD(p < 0.001), Dslow(p = 0.001), PF(p = 0.030) and Ve(p = 0.003) significantly increased, while MK(p < 0.001), Dfast(p = 0.009) and Kep(p = 0.003) values decreased dramatically, while no significant difference was detected in Ktrans(p = 0.130). Compared with NRG, ADC-pre(p < 0.001), MD-pre(p < 0.001) and Dslow-pre(p = 0.002) values in RG were lower, while MK-pre(p = 0.017) values were higher. The areas under the ROC curves for the ADC-pre, MD-pre, MK-pre, Dslow-pre and PRE were 0.885, 0.855, 0.809, 0.742 and 0.912, with the optimal cutoff value of 1210 × 10− 6 mm2/s, 1010 × 10− 6 mm2/s, 832 × 10− 6, 835 × 10− 6 mm2/s and 0.799 respectively. Conclusions The pretreatment conventional DWI (ADC), DKI (MD and MK), and IVIM (Dslow) values derived from fMRI showed a promising potential in predicting the response of the primary tumor to IC in NPC patients. Trial registration This study was approved by ethics board of the Chinese PLA General Hospital, and registered on January 30, 2021, in Chinese Clinical Trial Registry (ChiCTR2100042863). Supplementary Information The online version contains supplementary material available at 10.1186/s40644-021-00428-0.
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Affiliation(s)
- Da-Wei Zhao
- Medical School of Chinese PLA, No.28 Fuxing Road, Beijing, 100853, China.,Department of Radiology, Pingjin Hospital, Characteristic Medical center of Chinese People's Armed Police Force, Tianjin, China.,Department of Radiation Oncology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Wen-Jun Fan
- Department of Radiation Oncology, First Medical Center of Chinese PLA General Hospital, Beijing, China.,Affiliated Foshan Maternity & Child Healthcare Hospital, Southern Medical University, Foshan, China.,Armed Police Forces Corps Hospital of Henan Province, No.1 Kangfu Road, Zhengzhou, 450052, China
| | - Ling-Ling Meng
- Department of Radiation Oncology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Yan-Rong Luo
- Department of Radiation Oncology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Jian Wei
- Department of Otolaryngology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Kun Liu
- Department of Otolaryngology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Gang Liu
- Department of Radiology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Jin-Feng Li
- Department of Radiology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Xiao Zang
- Department of Radiology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Meng Li
- Department of Radiology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Xin-Xin Zhang
- Department of Otolaryngology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Lin Ma
- Department of Radiation Oncology, First Medical Center of Chinese PLA General Hospital, Beijing, China.
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15
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Bos P, van der Hulst HJ, van den Brekel MWM, Schats W, Jasperse B, Beets-Tan RGH, Castelijns JA. Prognostic functional MR imaging parameters in head and neck squamous cell carcinoma: A systematic review. Eur J Radiol 2021; 144:109952. [PMID: 34562743 DOI: 10.1016/j.ejrad.2021.109952] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Revised: 08/10/2021] [Accepted: 08/31/2021] [Indexed: 01/17/2023]
Abstract
OBJECTIVE Functional MR imaging has demonstrated potential for predicting treatment response. This systematic review gives an extensive overview of the current level of evidence for pre-treatment MR-based perfusion and diffusion imaging parameters that are prognostic for treatment outcome in head and neck squamous cell carcinoma (HNSCC) (PROSPERO registrationCRD42020210689). MATERIALS AND METHODS According to the PRISMA statements, Medline, Embase and Scopus were queried for articles with a maximum date of October 19th, 2020. Studies investigating the predictive performance of pre-treatment MR-based perfusion and/or diffusion imaging parameters in HNSCC treatment response were included. All prognosticators were extracted from the primary tumor. Risk of bias was assessed using the QUIPS tool. Results were summarized in tables and forest plots. RESULTS 31 unique studies met the inclusion criteria; among them, 11 articles described perfusion (n = 529 patients) and 28 described diffusion (n = 1626 patients) MR-imaging, eight studies were included in both categories. Higher Ktrans and Kep were associated with better treatment response for OS and DFS, respectively. Study findings for Vp and Ve were inconsistent or not significant. High-level controversy was observed between studies examining the MR diffusion parameters mean and median ADC. CONCLUSION For HNSCC patients, the accurate and consistent results of pre-treatment MR-based perfusion parameters Ktrans and Kep are potential for clinical applicability predictive of OS and DFS and treatment decision guidance. Significant heterogeneity in study designs might affect high discrepancy in study results for parameters extracted from diffusion imaging. Furthermore, recommendations for future research were summarized.
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Affiliation(s)
- Paula Bos
- Department of Radiology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Department of Head and Neck Oncology and Surgery, The Netherlands Cancer Institute, Amsterdam, the Netherlands; GROW School for Oncology and Developmental Biology - University of Maastricht, Maastricht, the Netherlands.
| | - Hedda J van der Hulst
- Department of Radiology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Department of Head and Neck Oncology and Surgery, The Netherlands Cancer Institute, Amsterdam, the Netherlands; GROW School for Oncology and Developmental Biology - University of Maastricht, Maastricht, the Netherlands
| | - Michiel W M van den Brekel
- Department of Head and Neck Oncology and Surgery, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Department of Oral and Maxillofacial Surgery, Amsterdam University Medical Center (AUMC), Amsterdam, the Netherlands
| | - Winnie Schats
- Scientific Information Service, The Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Bas Jasperse
- Department of Radiology, Amsterdam University Medical Center, Amsterdam, the Netherlands
| | - Regina G H Beets-Tan
- Department of Radiology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; GROW School for Oncology and Developmental Biology - University of Maastricht, Maastricht, the Netherlands; Department of Regional Health Research, University of Southern Denmark, Denmark
| | - Jonas A Castelijns
- Department of Radiology, The Netherlands Cancer Institute, Amsterdam, the Netherlands
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16
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van Houdt PJ, Yang Y, van der Heide UA. Quantitative Magnetic Resonance Imaging for Biological Image-Guided Adaptive Radiotherapy. Front Oncol 2021; 10:615643. [PMID: 33585242 PMCID: PMC7878523 DOI: 10.3389/fonc.2020.615643] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Accepted: 12/08/2020] [Indexed: 12/20/2022] Open
Abstract
MRI-guided radiotherapy systems have the potential to bring two important concepts in modern radiotherapy together: adaptive radiotherapy and biological targeting. Based on frequent anatomical and functional imaging, monitoring the changes that occur in volume, shape as well as biological characteristics, a treatment plan can be updated regularly to accommodate the observed treatment response. For this purpose, quantitative imaging biomarkers need to be identified that show changes early during treatment and predict treatment outcome. This review provides an overview of the current evidence on quantitative MRI measurements during radiotherapy and their potential as an imaging biomarker on MRI-guided radiotherapy systems.
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Affiliation(s)
- Petra J van Houdt
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Yingli Yang
- Department of Radiation Oncology, University of California, Los Angeles, CA, United States
| | - Uulke A van der Heide
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, Netherlands
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Koopman T, Martens R, Gurney‐Champion OJ, Yaqub M, Lavini C, de Graaf P, Castelijns J, Boellaard R, Marcus JT. Repeatability of IVIM biomarkers from diffusion-weighted MRI in head and neck: Bayesian probability versus neural network. Magn Reson Med 2021; 85:3394-3402. [PMID: 33501657 PMCID: PMC7986193 DOI: 10.1002/mrm.28671] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Revised: 12/14/2020] [Accepted: 12/17/2020] [Indexed: 12/16/2022]
Abstract
Purpose The intravoxel incoherent motion (IVIM) model for DWI might provide useful biomarkers for disease management in head and neck cancer. This study compared the repeatability of three IVIM fitting methods to the conventional nonlinear least‐squares regression: Bayesian probability estimation, a recently introduced neural network approach, IVIM‐NET, and a version of the neural network modified to increase consistency, IVIM‐NETmod. Methods Ten healthy volunteers underwent two imaging sessions of the neck, two weeks apart, with two DWI acquisitions per session. Model parameters (ADC, diffusion coefficient Dt, perfusion fraction fp, and pseudo‐diffusion coefficient Dp) from each fit method were determined in the tonsils and in the pterygoid muscles. Within‐subject coefficients of variation (wCV) were calculated to assess repeatability. Training of the neural network was repeated 100 times with random initialization to investigate consistency, quantified by the coefficient of variance. Results The Bayesian and neural network approaches outperformed nonlinear regression in terms of wCV. Intersession wCV of Dt in the tonsils was 23.4% for nonlinear regression, 9.7% for Bayesian estimation, 9.4% for IVIM‐NET, and 11.2% for IVIM‐NETmod. However, results from repeated training of the neural network on the same data set showed differences in parameter estimates: The coefficient of variances over the 100 repetitions for IVIM‐NET were 15% for both Dt and fp, and 94% for Dp; for IVIM‐NETmod, these values improved to 5%, 9%, and 62%, respectively. Conclusion Repeatabilities from the Bayesian and neural network approaches are superior to that of nonlinear regression for estimating IVIM parameters in the head and neck.
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Affiliation(s)
- Thomas Koopman
- Department of Radiology and Nuclear MedicineAmsterdam UMC, Vrije Universiteit AmsterdamAmsterdamthe Netherlands
| | - Roland Martens
- Department of Radiology and Nuclear MedicineAmsterdam UMC, Vrije Universiteit AmsterdamAmsterdamthe Netherlands
| | | | - Maqsood Yaqub
- Department of Radiology and Nuclear MedicineAmsterdam UMC, Vrije Universiteit AmsterdamAmsterdamthe Netherlands
| | - Cristina Lavini
- Department of RadiologyAmsterdam UMC, University of AmsterdamAmsterdamthe Netherlands
| | - Pim de Graaf
- Department of Radiology and Nuclear MedicineAmsterdam UMC, Vrije Universiteit AmsterdamAmsterdamthe Netherlands
| | - Jonas Castelijns
- Department of Radiology and Nuclear MedicineAmsterdam UMC, Vrije Universiteit AmsterdamAmsterdamthe Netherlands
- Department of Radiologythe Netherlands Cancer Institute–Antoni van LeeuwenhoekAmsterdamthe Netherlands
| | - Ronald Boellaard
- Department of Radiology and Nuclear MedicineAmsterdam UMC, Vrije Universiteit AmsterdamAmsterdamthe Netherlands
- Department of Nuclear Medicine and Molecular ImagingUniversity Medical Center GroningenGroningenthe Netherlands
| | - J. Tim Marcus
- Department of Radiology and Nuclear MedicineAmsterdam UMC, Vrije Universiteit AmsterdamAmsterdamthe Netherlands
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Gouw ZA, La Fontaine MD, Vogel WV, van de Kamer JB, Sonke JJ, Al-Mamgani A. Single-Center Prospective Trial Investigating the Feasibility of Serial FDG-PET Guided Adaptive Radiation Therapy for Head and Neck Cancer. Int J Radiat Oncol Biol Phys 2020; 108:960-968. [DOI: 10.1016/j.ijrobp.2020.04.030] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2020] [Revised: 04/16/2020] [Accepted: 04/20/2020] [Indexed: 12/17/2022]
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Liu B, Sun Z, Ma WL, Ren J, Zhang GW, Wei MQ, Hou WH, Hou BX, Wei LC, Huan Y, Zheng MW. DCE-MRI Quantitative Parameters as Predictors of Treatment Response in Patients With Locally Advanced Cervical Squamous Cell Carcinoma Underwent CCRT. Front Oncol 2020; 10:585738. [PMID: 33194734 PMCID: PMC7658627 DOI: 10.3389/fonc.2020.585738] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Accepted: 09/22/2020] [Indexed: 12/21/2022] Open
Abstract
Purpose To evaluate the predictive value of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) quantitative parameters in treatment response to concurrent chemoradiotherapy (CCRT) for locally advanced cervical squamous cell carcinoma (LACSC). Methods and materials LACSC patients underwent CCRT had DCE-MRI before (e0) and after 3 days of treatment (e3). Extended Tofts Linear model with a user arterial input function was adopted to generate quantitative measurements. Endothelial transfer constant (Ktrans), reflux rate (Kep), fractional extravascular extracellular space volume (Ve), and fractional plasma volume (Vp) were calculated, and percentage changes ΔKtrans, ΔKep, ΔVe, and ΔVp were computed. The correlations of these measurements with the tumor regression rate were analyzed. The predictive value of these parameters on treatment outcome was generated by the receiver operating characteristic (ROC) curve. Univariate and multivariate logistic regression analyses were conducted to find the independent variables. Results Ktrans-e0, Kep -e0, ΔKtrans, and ΔVe were positively correlated with the tumor regression rate. Mean values of Ktrans-e0, Ktrans-e3, ΔKtrans, and ΔVe were higher in the non-residual tumor group than residual tumor group and were independent prognostic factors for predicting residual tumor occurrence. Ktrans-e3 showed the highest area under the curve (AUC) for treatment response prediction. Conclusions Quantitative parameters at e0 and e3 from DCE-MRI could be used as potential indicators for predicting treatment response of LACSC.
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Affiliation(s)
- Bing Liu
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Zhen Sun
- Department of Orthopedic, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Wan-Ling Ma
- Department of Radiology, Longgang District People's Hospital, Shenzhen, China
| | - Jing Ren
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Guang-Wen Zhang
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Meng-Qi Wei
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Wei-Huan Hou
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Bing-Xin Hou
- Department of Radiation Oncology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Li-Chun Wei
- Department of Radiation Oncology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Yi Huan
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Min-Wen Zheng
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
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Guo N, Zeng W, Deng H, Hu H, Cheng Z, Yang Z, Jiang S, Duan X, Shen J. Quantitative dynamic contrast-enhanced MR imaging can be used to predict the pathologic stages of oral tongue squamous cell carcinoma. BMC Med Imaging 2020; 20:117. [PMID: 33066760 PMCID: PMC7566024 DOI: 10.1186/s12880-020-00516-w] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Accepted: 10/05/2020] [Indexed: 02/06/2023] Open
Abstract
Background To investigate whether quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) pharmacokinetic parameters can be used to predict the pathologic stages of oral tongue squamous cell carcinoma (OTSCC). Methods For this prospective study, DCE-MRI was performed in participants with OTSCC from May 2016 to June 2017. The pharmacokinetic parameters, including Ktrans, Kep, Ve, and Vp, were derived from DCE-MRI by utilizing a two-compartment extended Tofts model and a three-dimensional volume of interest. The postoperative pathologic stage was determined in each patient based on the 8th AJCC cancer staging manual. The quantitative DCE-MRI parameters were compared between stage I–II and stage III–IV lesions. Logistic regression analysis was used to determine independent predictors of tumor stages, followed by receiver operating characteristic (ROC) analysis to evaluate the predictive performance. Results The mean Ktrans, Kep and Vp values were significantly lower in stage III–IV lesions compared with stage I–II lesions (p = 0.013, 0.005 and 0.011, respectively). Kep was an independent predictor for the advanced stages as determined by univariate and multivariate logistic analysis. ROC analysis showed that Kep had the highest predictive capability, with a sensitivity of 64.3%, a specificity of 82.6%, a positive predictive value of 81.8%, a negative predictive value of 65.5%, and an accuracy of 72.5%. Conclusion The quantitative DCE-MRI parameter Kep can be used as a biomarker for predicting pathologic stages of OTSCC.
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Affiliation(s)
- Na Guo
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, Guangdong, China.,Department of Nuclear Medicine, Peking University Third Hospital, No. 49 Huayuan Road North, Beijing, 100191, China
| | - Weike Zeng
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, Guangdong, China
| | - Hong Deng
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, Guangdong, China
| | - Huijun Hu
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, Guangdong, China
| | - Ziliang Cheng
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, Guangdong, China.,Guangdong Provincial Key Laboratory of Malignant Tumour Epigenetics and Gene Regulation, Medical Research Centre, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, China
| | - Zehong Yang
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, Guangdong, China.,Guangdong Provincial Key Laboratory of Malignant Tumour Epigenetics and Gene Regulation, Medical Research Centre, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, China
| | - Shuqi Jiang
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, Guangdong, China
| | - Xiaohui Duan
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, Guangdong, China. .,Guangdong Provincial Key Laboratory of Malignant Tumour Epigenetics and Gene Regulation, Medical Research Centre, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, China.
| | - Jun Shen
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, Guangdong, China. .,Guangdong Provincial Key Laboratory of Malignant Tumour Epigenetics and Gene Regulation, Medical Research Centre, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, China.
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Kedves A, Tóth Z, Emri M, Fábián K, Sipos D, Freihat O, Tollár J, Cselik Z, Lakosi F, Bajzik G, Repa I, Kovács Á. Predictive Value of Diffusion, Glucose Metabolism Parameters of PET/MR in Patients With Head and Neck Squamous Cell Carcinoma Treated With Chemoradiotherapy. Front Oncol 2020; 10:1484. [PMID: 32983984 PMCID: PMC7492555 DOI: 10.3389/fonc.2020.01484] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Accepted: 07/13/2020] [Indexed: 12/15/2022] Open
Abstract
Purpose: This study aims to evaluate the predictive value of the pretreatment, metabolic, and diffusion parameters of a primary tumor assessed with PET/MR on patient clinical outcomes. Methods: Retrospective evaluation was performed using PET/MR image data sets acquired using the single tracer injection dual imaging of 68 histologically proven head and neck cancer patients 4 weeks before receiving definitive chemoradiotherapy (CRT). PET/MR was performed before the CRT and 12 weeks after the CRT for response evaluation. Image data (PET and MRI diffusion-weighted imaging [DWI]) was used to specify the maximum standard uptake value, the peak lean body mass corrected, SUVmax, the metabolic tumor volume, the total lesion glycolysis (SUVmax, SULpeak, MTV, and TLG), and the mean apparent diffusion coefficient (ADCmean) of the primary tumor. Based on the results of the therapeutic response evaluation, two patient subgroups were created: one with a viable tumor and another without. Metabolic and diffusion data, from the pretreatment PET/MR and the therapeutic response, were correlated using Spearman's correlation coefficient and Wilcoxon's test. Results: After completing the CRT, a viable residual tumor was detected in 36/68 (53%) cases, and 32/68 (47%) patients showed complete remission. However, no significant correlation was found between the pretreatment parameter, ADCmean (p = 0.88), and the therapeutic success. The PET parameters, SUVmax and SULpeak, MTV, and TLG (p = 0.032, p = 0.01, p < 0.0001, p = 0.0004) were statistically significantly different between the two patient subgroups. Conclusion: This study found that MRI-based (ADCmean) data from FDG PET/MR pretreatment could not be used to predict therapeutic response although the PET parameters SUVmax, SULpeak, MTV, and TLG proved to be more useful; thus, their inclusion in risk stratification may also be of additional value.
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Affiliation(s)
- András Kedves
- Doctoral School of Health Sciences, University of Pécs, Pécs, Hungary.,Department of Medical Imaging, Faculty of Health Sciences, University of Pécs, Pécs, Hungary.,Dr. József Baka Diagnostic, Radiation Oncology, Research and Teaching Center, "Moritz Kaposi" Teaching Hospital, Kaposvár, Hungary
| | - Zoltán Tóth
- Doctoral School of Health Sciences, University of Pécs, Pécs, Hungary.,MEDICOPUS Healthcare Provider and Public Nonprofit Ltd., Somogy County Moritz Kaposi Teaching Hospital, Kaposvár, Hungary
| | - Miklós Emri
- Dr. József Baka Diagnostic, Radiation Oncology, Research and Teaching Center, "Moritz Kaposi" Teaching Hospital, Kaposvár, Hungary.,Department of Medical Imaging, Faculty of Health Sciences, University of Debrecen, Debrecen, Hungary
| | - Krisztián Fábián
- Department of Medical Imaging, Faculty of Health Sciences, University of Pécs, Pécs, Hungary
| | - Dávid Sipos
- Doctoral School of Health Sciences, University of Pécs, Pécs, Hungary.,Department of Medical Imaging, Faculty of Health Sciences, University of Pécs, Pécs, Hungary.,Dr. József Baka Diagnostic, Radiation Oncology, Research and Teaching Center, "Moritz Kaposi" Teaching Hospital, Kaposvár, Hungary
| | - Omar Freihat
- Doctoral School of Health Sciences, University of Pécs, Pécs, Hungary
| | - József Tollár
- Department of Medical Imaging, Faculty of Health Sciences, University of Pécs, Pécs, Hungary.,Dr. József Baka Diagnostic, Radiation Oncology, Research and Teaching Center, "Moritz Kaposi" Teaching Hospital, Kaposvár, Hungary
| | - Zsolt Cselik
- Oncoradiology, Csolnoky Ferenc County Hospital, Veszprém, Hungary
| | - Ferenc Lakosi
- Dr. József Baka Diagnostic, Radiation Oncology, Research and Teaching Center, "Moritz Kaposi" Teaching Hospital, Kaposvár, Hungary
| | - Gábor Bajzik
- Dr. József Baka Diagnostic, Radiation Oncology, Research and Teaching Center, "Moritz Kaposi" Teaching Hospital, Kaposvár, Hungary
| | - Imre Repa
- Dr. József Baka Diagnostic, Radiation Oncology, Research and Teaching Center, "Moritz Kaposi" Teaching Hospital, Kaposvár, Hungary
| | - Árpád Kovács
- Doctoral School of Health Sciences, University of Pécs, Pécs, Hungary.,Department of Medical Imaging, Faculty of Health Sciences, University of Pécs, Pécs, Hungary.,Department of Oncoradiology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary
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22
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Thureau S, Briens A, Decazes P, Castelli J, Barateau A, Garcia R, Thariat J, de Crevoisier R. PET and MRI guided adaptive radiotherapy: Rational, feasibility and benefit. Cancer Radiother 2020; 24:635-644. [PMID: 32859466 DOI: 10.1016/j.canrad.2020.06.017] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Accepted: 06/22/2020] [Indexed: 02/07/2023]
Abstract
Adaptive radiotherapy (ART) corresponds to various replanning strategies aiming to correct for anatomical variations occurring during the course of radiotherapy. The goal of the article was to report the rational, feasibility and benefit of using PET and/or MRI to guide this ART strategy in various tumor localizations. The anatomical modifications defined by scanner taking into account tumour mobility and volume variation are not always sufficient to optimise treatment. The contribution of functional imaging by PET or the precision of soft tissue by MRI makes it possible to consider optimized ART. Today, the most important data for both PET and MRI are for lung, head and neck, cervical and prostate cancers. PET and MRI guided ART appears feasible and safe, however in a very limited clinical experience. Phase I/II studies should be therefore performed, before proposing cost-effectiveness comparisons in randomized trials and before using the approach in routine practice.
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Affiliation(s)
- S Thureau
- Département de radiothérapie et de physique médicale, centre Henri-Becquerel, QuantIF EA 4108, université de Rouen, 76000 Rouen, France.
| | - A Briens
- Département de radiothérapie, centre Eugène-Marquis, rue de la Bataille-Flandres-Dunkerque, CS 44229, 35042 Rennes cedex, France
| | - P Decazes
- Département de médecine nucléaire, center Henri-Becquerel, QuantIF EA 4108, université de Rouen, Rouen, France
| | - J Castelli
- Département de radiothérapie, centre Eugène Marquis, rue de la Bataille-Flandres-Dunkerque, CS 44229, 35042 Rennes cedex, France; CLCC Eugène Marquis, Inserm, LTSI-UMR 1099, université de Rennes, 35000 Rennes, France
| | - A Barateau
- Département de radiothérapie, centre Eugène Marquis, rue de la Bataille-Flandres-Dunkerque, CS 44229, 35042 Rennes cedex, France; CLCC Eugène Marquis, Inserm, LTSI-UMR 1099, université de Rennes, 35000 Rennes, France
| | - R Garcia
- Service de physique médicale, institut Sainte-Catherine, 84918 Avignon, France
| | - J Thariat
- Department of radiation oncology, centre François-Baclesse, 14000 Caen, France; Laboratoire de physique corpusculaire IN2P3/ENSICAEN-UMR6534-Unicaen-Normandie université, 14000 Caen, France; ARCHADE Research Community, 14000 Caen, France
| | - R de Crevoisier
- Département de radiothérapie, centre Eugène-Marquis, rue de la Bataille-Flandres-Dunkerque, CS 44229, 35042 Rennes cedex, France; CLCC Eugène Marquis, Inserm, LTSI-UMR 1099, université de Rennes, 35000 Rennes, France
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23
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Gurney-Champion OJ, Kieselmann JP, Wong KH, Ng-Cheng-Hin B, Harrington K, Oelfke U. A convolutional neural network for contouring metastatic lymph nodes on diffusion-weighted magnetic resonance images for assessment of radiotherapy response. Phys Imaging Radiat Oncol 2020; 15:1-7. [PMID: 33043156 PMCID: PMC7536306 DOI: 10.1016/j.phro.2020.06.002] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2020] [Revised: 06/09/2020] [Accepted: 06/09/2020] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND AND PURPOSE Retrieving quantitative parameters from magnetic resonance imaging (MRI), e.g. for early assessment of radiotherapy treatment response, necessitates contouring regions of interest, which is time-consuming and prone to errors. This becomes more pressing for daily imaging on MRI-guided radiotherapy systems. Therefore, we trained a deep convolutional neural network to automatically contour involved lymph nodes on diffusion-weighted (DW) MRI of head and neck cancer (HNC) patients receiving radiotherapy. MATERIALS AND METHODS DW-images from 48 HNC patients (18 induction-chemotherapy + chemoradiotherapy; 30 definitive chemoradiotherapy) with 68 involved lymph nodes were obtained on a diagnostic 1.5 T MR-scanner prior to and 2-3 timepoints throughout treatment. A radiation oncologist delineated the lymph nodes on the b = 50 s/mm2 images. A 3D U-net was trained to contour involved lymph nodes. Its performance was evaluated in all 48 patients using 8-fold cross-validation and calculating the Dice similarity coefficient (DSC) and the absolute difference in median apparent diffusion coefficient (ΔADC) between the manual and generated contours. Additionally, the performance was evaluated in an independent dataset of three patients obtained on a 1.5 T MR-Linac. RESULTS In the definitive chemoradiotherapy patients (n = 96 patients/lymphnodes/timepoints) the DSC was 0.87 (0.81-0.91) [median (1st-3rd quantiles)] and ΔADC was 1.9% (0.8-3.4%) and both remained stable throughout treatment. The network performed worse in the patients receiving induction-chemotherapy (n = 65), with DSC = 0.80 (0.71-0.87) and ΔADC = 3.3% (1.6-8.0%). The network performed well on the MR-Linac data (n = 8) with DSC = 0.80 (0.75-0.82) and ΔADC = 4.0% (0.6-9.1%). CONCLUSIONS We established accurate automatic contouring of involved lymph nodes for HNC patients on diagnostic and MR-Linac DW-images.
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Affiliation(s)
- Oliver J. Gurney-Champion
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Jennifer P. Kieselmann
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Kee H. Wong
- The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Brian Ng-Cheng-Hin
- Targeted Therapy Team, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Kevin Harrington
- Targeted Therapy Team, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Uwe Oelfke
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom
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Wiedenmann N, Grosu AL, Büchert M, Rischke HC, Ruf J, Bielak L, Majerus L, Rühle A, Bamberg F, Baltas D, Hennig J, Mix M, Bock M, Nicolay NH. The utility of multiparametric MRI to characterize hypoxic tumor subvolumes in comparison to FMISO PET/CT. Consequences for diagnosis and chemoradiation treatment planning in head and neck cancer. Radiother Oncol 2020; 150:128-135. [PMID: 32544609 DOI: 10.1016/j.radonc.2020.06.013] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Revised: 06/02/2020] [Accepted: 06/10/2020] [Indexed: 12/15/2022]
Abstract
BACKGROUND AND PURPOSE Hypoxia is an essential metabolic marker that determines chemo- and radiation resistance in head-and-neck squamous cell carcinoma (HNSCC) patients. Our exploratory analysis aimed to identify multiparametric MRI (mpMRI) parameters linked to hypoxia that might be used as surrogate for [18F]FMISO-PET in diagnosis and chemoradiation treatment (CRT) of HNSCC. MATERIALS AND METHODS 21 patients undergoing definitive CRT for HNSCC were prospectively imaged with serial [18F]FMISO-PET and 3 Tesla mpMRI for T1- and T2-weighted and dynamic contrast-enhanced perfusion and diffusion-weighted measurements (ktrans, ve, kep, ADC) in weeks 0, 2 and 5 and FDG-PET in week 0. [18F]FMISO-PET-derived hypoxic subvolumes (HSV) and complementary non-hypoxic subvolumes (nonHSV) were created for tumor and lymph nodes and projected on the mpMRI scans after PET/MRI co-registration. MpMRI and [18F]FMISO-PET parameters within HSVs and nonHSVs were statistically compared. RESULTS FMISO-PET-based HSVs of the primary tumors on MRI were characterized by lower ADC at all time points (p = 0.012 at baseline; p = 0.015 in week 2) and reduced interstitial space volume fraction ve and perfusion ktrans at baseline (p = 0.006, p = 0.047) compared to nonHSVs. Hypoxic lymph nodes were characterized by significantly lower ADC values at baseline (p = 0.039), but not at later time points and a reduction in ktrans-based perfusion at week 2 (p = 0.018). CONCLUSION MpMRI parameters differ significantly between hypoxic and non-hypoxic tumor regions, defined on FMISO-PET/CT as gold standard and might represent surrogate markers for tumor hypoxia. These findings suggest that mpMRI may be useful in the future as a surrogate modality for hypoxia imaging in order to personalize CRT.
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Affiliation(s)
- Nicole Wiedenmann
- Department of Radiation Oncology, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; German Cancer Consortium (DKTK), Partner site Freiburg, Germany; German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Anca-Ligia Grosu
- Department of Radiation Oncology, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; German Cancer Consortium (DKTK), Partner site Freiburg, Germany; German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Martin Büchert
- Department of Radiology, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Hans C Rischke
- Department of Radiation Oncology, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; Department of Nuclear Medicine, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; German Cancer Consortium (DKTK), Partner site Freiburg, Germany; German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Juri Ruf
- Department of Nuclear Medicine, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; German Cancer Consortium (DKTK), Partner site Freiburg, Germany; German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Lars Bielak
- Department of Radiology, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Liette Majerus
- Department of Radiation Oncology, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; German Cancer Consortium (DKTK), Partner site Freiburg, Germany; German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Alexander Rühle
- Department of Radiation Oncology, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; German Cancer Consortium (DKTK), Partner site Freiburg, Germany; German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Fabian Bamberg
- Department of Radiology, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; German Cancer Consortium (DKTK), Partner site Freiburg, Germany; German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Dimos Baltas
- Department of Radiation Oncology, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; German Cancer Consortium (DKTK), Partner site Freiburg, Germany; German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Jürgen Hennig
- Department of Radiology, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; German Cancer Consortium (DKTK), Partner site Freiburg, Germany; German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Michael Mix
- Department of Nuclear Medicine, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; German Cancer Consortium (DKTK), Partner site Freiburg, Germany; German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Michael Bock
- Department of Radiology, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; German Cancer Consortium (DKTK), Partner site Freiburg, Germany; German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Nils H Nicolay
- Department of Radiation Oncology, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; German Cancer Consortium (DKTK), Partner site Freiburg, Germany; German Cancer Research Center (DKFZ), Heidelberg, Germany.
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Gurney-Champion OJ, Mahmood F, van Schie M, Julian R, George B, Philippens MEP, van der Heide UA, Thorwarth D, Redalen KR. Quantitative imaging for radiotherapy purposes. Radiother Oncol 2020; 146:66-75. [PMID: 32114268 PMCID: PMC7294225 DOI: 10.1016/j.radonc.2020.01.026] [Citation(s) in RCA: 61] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2019] [Revised: 01/22/2020] [Accepted: 01/29/2020] [Indexed: 02/07/2023]
Abstract
Quantitative imaging biomarkers show great potential for use in radiotherapy. Quantitative images based on microscopic tissue properties and tissue function can be used to improve contouring of the radiotherapy targets. Furthermore, quantitative imaging biomarkers might be used to predict treatment response for several treatment regimens and hence be used as a tool for treatment stratification, either to determine which treatment modality is most promising or to determine patient-specific radiation dose. Finally, patient-specific radiation doses can be further tailored to a tissue/voxel specific radiation dose when quantitative imaging is used for dose painting. In this review, published standards, guidelines and recommendations on quantitative imaging assessment using CT, PET and MRI are discussed. Furthermore, critical issues regarding the use of quantitative imaging for radiation oncology purposes and resultant pending research topics are identified.
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Affiliation(s)
- Oliver J Gurney-Champion
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom.
| | - Faisal Mahmood
- Department of Oncology, Odense University Hospital, Denmark; Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Marcel van Schie
- Department of Radiation Oncology, the Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Robert Julian
- Department of Radiotherapy Physics, Royal Surrey NHS Foundation Trust, Guildford, United Kingdom
| | - Ben George
- Radiation Therapy Medical Physics Group, CRUK/MRC Oxford Institute for Radiation Oncology, University of Oxford, United Kingdom
| | | | - Uulke A van der Heide
- Department of Radiation Oncology, the Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Daniela Thorwarth
- Section for Biomedical Physics, Department of Radiation Oncology, Eberhard Karls University of Tübingen, Germany
| | - Kathrine R Redalen
- Department of Physics, Norwegian University of Science and Technology, Trondheim, Norway
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Chan SC, Ng SH, Yeh CH, Chang KP. Multiparametric positron emission tomography/magnetic resonance imaging in nasopharyngeal carcinoma: Correlations between magnetic resonance imaging functional parameters and 18F-fluorodeoxyglucose positron emission tomography imaging biomarkers and their predictive value for treatment failure. Tzu Chi Med J 2020; 33:61-69. [PMID: 33505880 PMCID: PMC7821831 DOI: 10.4103/tcmj.tcmj_4_20] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Revised: 02/10/2020] [Accepted: 02/27/2020] [Indexed: 12/20/2022] Open
Abstract
Objectives: The clinical significance of positron emission tomography/magnetic resonance imaging (PET/MRI) functional parameters in nasopharyngealcarcinoma (NPC) remains unclear. The purpose of this prospective study was two-fold: (1) to investigate the associations between simultaneously acquired PET/MRI perfusion, diffusion, and glucose metabolism parameters in patients with NPC and (2) to analyze their predictive value with respect to treatment failure. Materials and Methods: We enrolled 85 patients with primary NPC who simultaneously underwent18F-fluorodeoxyglucose PET/CT and PET/MRI before definitive treatment. The following variables were determined: (1) functional parameters from the MRI component, including perfusion values (Ktrans,kep,ve, and initial area under the enhancement curve) and apparent diffusion coefficient (ADC) values, and (2) PET parameters, including metabolic tumor volume (MTV). The reciprocal interrelationships between these parameters and their correlations with treatment failure were examined. Results: We observed significant negative associations between Ktrans and ADC (r = −0.215, P = 0.049) as well as between ve and ADC (r = −0.22, P = 0.04). Correlations between PET and MRI functional parameters were not statistically significant. Treatment failures were observed in 21.2% of patients without distant metastases. Multivariate analysis identified ve as a significant independent predictor for treatment failure (P = 0.022), whereas MTV showed a borderline significance (P = 0.095). Patients in whom both ve and MTV values were increased had a significantly higher rate of treatment failure (62.5%) than those with either one (21.9%) or no (7.7%) increased parameter (P = 0.004). Conclusion: Correlation analyses revealed complex interrelationships among PET and MRI indices measured in patients with NPC. These parameters may have a complementary role in predicting treatment failure in this clinical setting.
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Affiliation(s)
- Sheng-Chieh Chan
- Department of Nuclear Medicine, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien, Taiwan
| | - Shu-Hang Ng
- Department of Diagnostic Radiology, Linkou Chang Gung Memorial Hospital and Chang Gung University, Taoyuan, Taiwan
| | - Chih-Hua Yeh
- Department of Diagnostic Radiology, Linkou Chang Gung Memorial Hospital and Chang Gung University, Taoyuan, Taiwan
| | - Kai-Ping Chang
- Department of Otorhinolaryngology, Linkou Chang Gung Memorial Hospital and Chang Gung University, Taoyuan, Taiwan
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Diagnosis of spinal lesions using perfusion parameters measured by DCE-MRI and metabolism parameters measured by PET/CT. EUROPEAN SPINE JOURNAL : OFFICIAL PUBLICATION OF THE EUROPEAN SPINE SOCIETY, THE EUROPEAN SPINAL DEFORMITY SOCIETY, AND THE EUROPEAN SECTION OF THE CERVICAL SPINE RESEARCH SOCIETY 2019; 29:1061-1070. [PMID: 31754820 DOI: 10.1007/s00586-019-06213-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/08/2019] [Revised: 05/08/2019] [Accepted: 11/07/2019] [Indexed: 12/13/2022]
Abstract
PURPOSE To investigate the correlation of parameters measured by dynamic-contrast-enhanced MRI (DCE-MRI) and 18F-FDG PET/CT in spinal tumors, and their role in differential diagnosis. METHODS A total of 49 patients with pathologically confirmed spinal tumors, including 38 malignant, six benign and five borderline tumors, were analyzed. The MRI and PET/CT were done within 3 days, before biopsy. On MRI, the ROI was manually placed on area showing the strongest enhancement to measure pharmacokinetic parameters Ktrans and kep. On PET, the maximum standardized uptake value SUVmax was measured. The parameters in different histological groups were compared. ROC was performed to differentiate between the two largest subtypes, metastases and plasmacytomas. Spearman rank correlation was performed to compare DCE-MRI and PET/CT parameters. RESULTS The Ktrans, kep and SUVmax were not statistically different among malignant, benign and borderline groups (P = 0.95, 0.50, 0.11). There was no significant correlation between Ktrans and SUVmax (r = - 0.20, P = 0.18), or between kep and SUVmax (r = - 0.16, P = 0.28). The kep was significantly higher in plasmacytoma than in metastasis (0.78 ± 0.17 vs. 0.61 ± 0.18, P = 0.02); in contrast, the SUVmax was significantly lower in plasmacytoma than in metastasis (5.58 ± 2.16 vs. 9.37 ± 4.26, P = 0.03). In differential diagnosis, the AUC of kep and SUVmax was 0.79 and 0.78, respectively. CONCLUSIONS The vascular parameters measured by DCE-MRI and glucose metabolism measured by PET/CT from the most aggressive tumor area did not show a significant correlation. The results suggest they provide complementary information reflecting different aspects of the tumor, which may aid in diagnosis of spinal lesions. These slides can be retrieved under Electronic Supplementary Material.
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Associations between Histogram Analysis Parameters Derived from DCE-MRI and Histopathological Features including Expression of EGFR, p16, VEGF, Hif1-alpha, and p53 in HNSCC. CONTRAST MEDIA & MOLECULAR IMAGING 2019; 2019:5081909. [PMID: 30718984 PMCID: PMC6334376 DOI: 10.1155/2019/5081909] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/05/2018] [Accepted: 12/05/2018] [Indexed: 12/14/2022]
Abstract
Background Our purpose was to elucidate possible correlations between histogram parameters derived from dynamic contrast-enhanced MRI (DCE-MRI) with several histopathological features in head and neck squamous cell carcinomas (HNSCC). Methods Thirty patients with primary HNSCC were prospectively acquired. Histogram analysis was derived from the DCE-MRI parameters: Ktrans, Kep, and Ve. Additionally, in all cases, expression of human papilloma virus (p16) hypoxia-inducible factor-1-alpha (Hif1-alpha), vascular endothelial growth factor (VEGF), epidermal growth factor receptor (EGFR), and tumor suppressor protein p53 were estimated. Results Kep kurtosis was significantly higher in p16 tumors, and Ve min was significantly lower in p16 tumors compared to the p16 negative tumors. In the overall sample, Kep entropy correlated well with EGFR expression (p=0.38, P=0.04). In p16 positive carcinomas, Ktrans max correlated with VEGF expression (p=0.46, P=0.04), Ktrans kurtosis correlated with Hif1-alpha expression (p=0.46, P=0.04), and Ktrans entropy correlated with EGFR expression (p=0.50, P=0.03). Regarding Kep parameters, mode correlated with VEGF expression (p=0.51, P=0.02), and entropy correlated with Hif1-alpha expression (p=0.47, P=0.04). In p16 negative carcinomas, Kep mode correlated with Her2 expression (p=−0.72, P=0.03), Ve max correlated with p53 expression (p=−0.80, P=0.009), and Ve p10 correlated with EGFR expression (p=0.68, P=0.04). Conclusion DCE-MRI can reflect several histopathological features in HNSCC. Associations between DCE-MRI and histopathology in HNSCC depend on p16 status. Kep kurtosis and Ve min can differentiate p16 positive and p16 negative carcinomas.
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Hunt A, Hansen VN, Oelfke U, Nill S, Hafeez S. Adaptive Radiotherapy Enabled by MRI Guidance. Clin Oncol (R Coll Radiol) 2018; 30:711-719. [PMID: 30201276 DOI: 10.1016/j.clon.2018.08.001] [Citation(s) in RCA: 79] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2018] [Revised: 08/10/2018] [Accepted: 08/20/2018] [Indexed: 12/11/2022]
Abstract
Adaptive radiotherapy (ART) strategies systematically monitor variations in target and neighbouring structures to inform treatment-plan modification during radiotherapy. This is necessary because a single plan designed before treatment is insufficient to capture the actual dose delivered to the target and adjacent critical structures during the course of radiotherapy. Magnetic resonance imaging (MRI) provides superior soft-tissue image contrast over current standard X-ray-based technologies without additional radiation exposure. With integrated MRI and radiotherapy platforms permitting motion monitoring during treatment delivery, it is possible that adaption can be informed by real-time anatomical imaging. This allows greater treatment accuracy in terms of dose delivered to target with smaller, individualised treatment margins. The use of functional MRI sequences would permit ART to be informed by imaging biomarkers, so allowing both personalised geometric and biological adaption. In this review, we discuss ART solutions enabled by MRI guidance and its potential gains for our patients across tumour types.
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Affiliation(s)
- A Hunt
- The Institute of Cancer Research, London, UK; The Royal Marsden NHS Foundation Trust, London, UK
| | - V N Hansen
- The Institute of Cancer Research, London, UK; Joint Department of Physics, The Royal Marsden NHS Foundation Trust, London, UK
| | - U Oelfke
- The Institute of Cancer Research, London, UK; Joint Department of Physics, The Royal Marsden NHS Foundation Trust, London, UK
| | - S Nill
- The Institute of Cancer Research, London, UK; Joint Department of Physics, The Royal Marsden NHS Foundation Trust, London, UK
| | - S Hafeez
- The Institute of Cancer Research, London, UK; The Royal Marsden NHS Foundation Trust, London, UK.
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30
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Wiedenmann N, Bunea H, Rischke HC, Bunea A, Majerus L, Bielak L, Protopopov A, Ludwig U, Büchert M, Stoykow C, Nicolay NH, Weber WA, Mix M, Meyer PT, Hennig J, Bock M, Grosu AL. Effect of radiochemotherapy on T2* MRI in HNSCC and its relation to FMISO PET derived hypoxia and FDG PET. Radiat Oncol 2018; 13:159. [PMID: 30157883 PMCID: PMC6114038 DOI: 10.1186/s13014-018-1103-1] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2018] [Accepted: 08/17/2018] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND To assess the effect of radiochemotherapy (RCT) on proposed tumour hypoxia marker transverse relaxation time (T2*) and to analyse the relation between T2* and 18F-misonidazole PET/CT (FMISO-PET) and 18F-fluorodeoxyglucose PET/CT (FDG-PET). METHODS Ten patients undergoing definitive RCT for squamous cell head-and-neck cancer (HNSCC) received repeat FMISO- and 3 Tesla T2*-weighted MRI at weeks 0, 2 and 5 during treatment and FDG-PET at baseline. Gross tumour volumes (GTV) of tumour (T), lymph nodes (LN) and hypoxic subvolumes (HSV, based on FMISO-PET) and complementary non-hypoxic subvolumes (nonHSV) were generated. Mean values for T2* and SUVmean FDG were determined. RESULTS During RCT, marked reduction of tumour hypoxia on FMISO-PET was observed (T, LN), while mean T2* did not change significantly. At baseline, mean T2* values within HSV-T (15 ± 5 ms) were smaller compared to nonHSV-T (18 ± 3 ms; p = 0.051), whereas FDG SUVmean (12 ± 6) was significantly higher for HSV-T (12 ± 6) than for nonHSV-T (6 ± 3; p = 0.026) and higher for HSV-LN (10 ± 4) than for nonHSV-LN (5 ± 2; p ≤ 0.011). Correlation between FMISO PET and FDG PET was higher than between FMSIO PET and T2* (R2 for GTV-T (FMISO/FDG) = 0.81, R2 for GTV-T (FMISO/T2*) = 0.32). CONCLUSIONS Marked reduction of tumour hypoxia between week 0, 2 and 5 found on FMISO PET was not accompanied by a significant T2*change within GTVs over time. These results suggest a relation between tumour oxygenation status and T2* at baseline, but no simple correlation over time. Therefore, caution is warranted when using T2* as a substitute for FMISO-PET to monitor tumour hypoxia during RCT in HNSCC patients. TRIAL REGISTRATION DRKS, DRKS00003830 . Registered 23.04.2012.
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Affiliation(s)
- Nicole Wiedenmann
- Department of Radiation Oncology, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany. .,German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany. .,German Cancer Research Center (DKFZ), Heidelberg, Germany.
| | - Hatice Bunea
- Department of Radiation Oncology, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.,German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany.,German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Hans C Rischke
- Department of Radiation Oncology, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.,Department of Nuclear Medicine, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.,German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany.,German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Andrei Bunea
- Department of Radiation Oncology, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.,German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany.,German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Liette Majerus
- Department of Radiation Oncology, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.,German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany.,German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Lars Bielak
- Department of Radiology, Medical Physics, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Alexey Protopopov
- Department of Radiology, Medical Physics, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Ute Ludwig
- Department of Radiology, Medical Physics, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Martin Büchert
- Department of Radiology, Medical Physics, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Christian Stoykow
- Department of Nuclear Medicine, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.,German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany.,German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Nils H Nicolay
- Department of Radiation Oncology, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.,German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany.,German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Wolfgang A Weber
- Clinic for Nuclear Medicine, Technische Universität München, Munich, Germany
| | - Michael Mix
- Department of Nuclear Medicine, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.,German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany.,German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Philipp T Meyer
- Department of Nuclear Medicine, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.,German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany.,German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Jürgen Hennig
- Department of Radiology, Medical Physics, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.,German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany.,German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Michael Bock
- Department of Radiology, Medical Physics, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.,German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany.,German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Anca L Grosu
- Department of Radiation Oncology, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.,German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany.,German Cancer Research Center (DKFZ), Heidelberg, Germany
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