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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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Delineation uncertainties of tumour volumes on MRI of head and neck cancer patients. Clin Transl Radiat Oncol 2022; 36:121-126. [PMID: 36017132 PMCID: PMC9395751 DOI: 10.1016/j.ctro.2022.08.005] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Revised: 07/31/2022] [Accepted: 08/04/2022] [Indexed: 11/28/2022] Open
Abstract
Role of target delineation uncertainties in head and neck cancer patients. Knowing contouring variations for MRI allows better adaptation of MRLinac for H&N cancers. An interobserver variation for GTV among 8 observers was below 2 mm using MRI. Variability between observers might improve using other imaging modalities.
Background During the last decade, radiotherapy using MR Linac has gone from research to clinical implementation for different cancer locations. For head and neck cancer (HNC), target delineation based only on MR images is not yet standard, and the utilisation of MRI instead of PET/CT in radiotherapy planning is not well established. We aimed to analyse the inter-observer variation (IOV) in delineating GTV (gross tumour volume) on MR images only for patients with HNC. Material/methods 32 HNC patients from two independent departments were included. Four clinical oncologists from Denmark and four radiation oncologists from Australia had independently contoured primary tumour GTVs (GTV-T) and nodal GTVs (GTV-N) on T2-weighted MR images obtained at the time of treatment planning. Observers were provided with sets of images, delineation guidelines and patient synopsis. Simultaneous truth and performance level estimation (STAPLE) reference volumes were generated for each structure using all observer contours. The IOV was assessed using the DICE Similarity Coefficient (DSC) and mean absolute surface distance (MASD). Results 32 GTV-Ts and 68 GTV-Ns were contoured per observer. The median MASD for GTV-Ts and GTV-Ns across all patients was 0.17 cm (range 0.08–0.39 cm) and 0.07 cm (range 0.04–0.33 cm), respectively. Median DSC relative to a STAPLE volume for GTV-Ts and GTV-Ns across all patients were 0.73 and 0.76, respectively. A significant correlation was seen between median DSCs and median volumes of GTV-Ts (Spearman correlation coefficient 0.76, p < 0.001) and of GTV-Ns (Spearman correlation coefficient 0.55, p < 0.001). Conclusion Contouring GTVs in patients with HNC on MRI showed that the median IOV for GTV-T and GTV-N was below 2 mm, based on observes from two separate radiation departments. However, there are still specific regions in tumours that are difficult to resolve as either malignant tissue or oedema that potentially could be improved by further training in MR-only delineation.
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3
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Duncan S, Walker A, Kumar S, Dundas K, Bell K, Wallis A, Surjan Y, Aly F, Lee M. Novel methodology to quantify dehydration in head and neck cancer radiotherapy using DIXON MRI. J Med Radiat Sci 2022; 69:448-455. [PMID: 35762562 DOI: 10.1002/jmrs.605] [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: 11/24/2021] [Accepted: 06/10/2022] [Indexed: 11/10/2022] Open
Abstract
INTRODUCTION Head and neck cancer (HNC) patients are at risk of weight change, due to inadequate nutrition intake or dehydration, when receiving radiotherapy (RT). This study aimed to develop methodology to measure water content changes on magnetic resonance imaging (MRI) scans of the head and neck region over the course of RT. METHODS Retrospective datasets of 54 patients were analysed. Eligible patients had been treated for HNC with cisplatin chemoradiation (CRT) or RT alone and underwent a minimum of 2 MRI scans from weeks 0, 3 and 6 of their treatment. Anatomical regions consisting of ≥90% water, on T2-weighted DIXON MRI sequences, were contoured. Water volume changes of all patients were evaluated, within an anatomically standardised external volume, by comparing the absolute water fraction volume (cc) (VEx90WF) and relative water fraction volume (%) (RelVEx90WF) at weeks 0 and 6 of RT. RESULTS There was a statistically significant difference between the RelVEx90WF at weeks 0 and 6 (P = 0.005). However, no statistically significant difference was identified between weeks 0 and 6 VEx90WF (P = 0.064). There were no statistically significant differences identified between patients who received CRT versus RT alone. CONCLUSION This study developed a novel method for measuring changes in water fraction volumes over time, using T2-weighted DIXON MRIs. The methodology created in this study requires further validation through phantom imaging, with known fat and water values.
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Affiliation(s)
- Sophie Duncan
- Medical Radiation Science (MRS), School of Health Sciences, The University of Newcastle, Callaghan, New South Wales, Australia.,Liverpool and Macarthur Cancer Therapy Centres, Sydney, New South Wales, Australia.,Ingham Institute of Applied Medical Research, Sydney, New South Wales, Australia
| | - Amy Walker
- Liverpool and Macarthur Cancer Therapy Centres, Sydney, New South Wales, Australia.,Ingham Institute of Applied Medical Research, Sydney, New South Wales, Australia.,South West Sydney Clinical School, University of New South Wales, Sydney, New South Wales, Australia.,Centre for Medical Radiation Physics, University of Wollongong, Wollongong, Australia
| | - Shivani Kumar
- Liverpool and Macarthur Cancer Therapy Centres, Sydney, New South Wales, Australia.,Ingham Institute of Applied Medical Research, Sydney, New South Wales, Australia.,South West Sydney Clinical School, University of New South Wales, Sydney, New South Wales, Australia
| | - Kylie Dundas
- Liverpool and Macarthur Cancer Therapy Centres, Sydney, New South Wales, Australia.,Ingham Institute of Applied Medical Research, Sydney, New South Wales, Australia.,South West Sydney Clinical School, University of New South Wales, Sydney, New South Wales, Australia
| | - Katherine Bell
- Dietetics Department, Liverpool Hospital, Sydney, New South Wales, Australia
| | - Andrew Wallis
- Liverpool and Macarthur Cancer Therapy Centres, Sydney, New South Wales, Australia
| | - Yolanda Surjan
- Medical Radiation Science (MRS), School of Health Sciences, The University of Newcastle, Callaghan, New South Wales, Australia.,The University of Newcastle, College of Health and Wellbeing, Callaghan, New South Wales, Australia
| | - Farhannah Aly
- Liverpool and Macarthur Cancer Therapy Centres, Sydney, New South Wales, Australia.,Ingham Institute of Applied Medical Research, Sydney, New South Wales, Australia.,South West Sydney Clinical School, University of New South Wales, Sydney, New South Wales, Australia
| | - Mark Lee
- Liverpool and Macarthur Cancer Therapy Centres, Sydney, New South Wales, Australia.,South West Sydney Clinical School, University of New South Wales, Sydney, New South Wales, Australia
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de Ridder M, Raaijmakers CPJ, Pameijer FA, de Bree R, Reinders FCJ, Doornaert PAH, Terhaard CHJ, Philippens MEP. Target Definition in MR-Guided Adaptive Radiotherapy for Head and Neck Cancer. Cancers (Basel) 2022; 14:3027. [PMID: 35740691 PMCID: PMC9220977 DOI: 10.3390/cancers14123027] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 06/14/2022] [Accepted: 06/14/2022] [Indexed: 02/01/2023] Open
Abstract
In recent years, MRI-guided radiotherapy (MRgRT) has taken an increasingly important position in image-guided radiotherapy (IGRT). Magnetic resonance imaging (MRI) offers superior soft tissue contrast in anatomical imaging compared to computed tomography (CT), but also provides functional and dynamic information with selected sequences. Due to these benefits, in current clinical practice, MRI is already used for target delineation and response assessment in patients with head and neck squamous cell carcinoma (HNSCC). Because of the close proximity of target areas and radiosensitive organs at risk (OARs) during HNSCC treatment, MRgRT could provide a more accurate treatment in which OARs receive less radiation dose. With the introduction of several new radiotherapy techniques (i.e., adaptive MRgRT, proton therapy, adaptive cone beam computed tomography (CBCT) RT, (daily) adaptive radiotherapy ensures radiation dose is accurately delivered to the target areas. With the integration of a daily adaptive workflow, interfraction changes have become visible, which allows regular and fast adaptation of target areas. In proton therapy, adaptation is even more important in order to obtain high quality dosimetry, due to its susceptibility for density differences in relation to the range uncertainty of the protons. The question is which adaptations during radiotherapy treatment are oncology safe and at the same time provide better sparing of OARs. For an optimal use of all these new tools there is an urgent need for an update of the target definitions in case of adaptive treatment for HNSCC. This review will provide current state of evidence regarding adaptive target definition using MR during radiotherapy for HNSCC. Additionally, future perspectives for adaptive MR-guided radiotherapy will be discussed.
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Affiliation(s)
- Mischa de Ridder
- Department of Radiotherapy, University Medical Center Utrecht, 3584 Utrecht, The Netherlands; (C.P.J.R.); (F.C.J.R.); (P.A.H.D.); (C.H.J.T.); (M.E.P.P.)
| | - Cornelis P. J. Raaijmakers
- Department of Radiotherapy, University Medical Center Utrecht, 3584 Utrecht, The Netherlands; (C.P.J.R.); (F.C.J.R.); (P.A.H.D.); (C.H.J.T.); (M.E.P.P.)
| | - Frank A. Pameijer
- Department of Radiology, University Medical Center Utrecht, 3584 Utrecht, The Netherlands;
| | - Remco de Bree
- Department of Head and Neck Surgical Oncology, University Medical Center Utrecht, 3584 Utrecht, The Netherlands;
| | - Floris C. J. Reinders
- Department of Radiotherapy, University Medical Center Utrecht, 3584 Utrecht, The Netherlands; (C.P.J.R.); (F.C.J.R.); (P.A.H.D.); (C.H.J.T.); (M.E.P.P.)
| | - Patricia A. H. Doornaert
- Department of Radiotherapy, University Medical Center Utrecht, 3584 Utrecht, The Netherlands; (C.P.J.R.); (F.C.J.R.); (P.A.H.D.); (C.H.J.T.); (M.E.P.P.)
| | - Chris H. J. Terhaard
- Department of Radiotherapy, University Medical Center Utrecht, 3584 Utrecht, The Netherlands; (C.P.J.R.); (F.C.J.R.); (P.A.H.D.); (C.H.J.T.); (M.E.P.P.)
| | - Marielle E. P. Philippens
- Department of Radiotherapy, University Medical Center Utrecht, 3584 Utrecht, The Netherlands; (C.P.J.R.); (F.C.J.R.); (P.A.H.D.); (C.H.J.T.); (M.E.P.P.)
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Tang S, Rai R, Vinod SK, Elwadia D, Forstner D, Moretti D, Tran T, Do V, King O, Lim K, Liney G, Goozee G, Holloway L. Rates of MRI simulator utilisation in a tertiary cancer therapy centre. J Med Imaging Radiat Oncol 2022; 66:717-723. [PMID: 35687525 DOI: 10.1111/1754-9485.13422] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Accepted: 04/27/2022] [Indexed: 11/28/2022]
Abstract
Magnetic resonance imaging (MRI) is increasingly being integrated into the radiation oncology workflow, due to its improved soft tissue contrast without additional exposure to ionising radiation. A review of MRI utilisation according to evidence based departmental guidelines was performed. Guideline utilisation rates were calculated to be 50% (true utilisation rate was 46%) of all new cancer patients treated with adjuvant or curative intent, excluding simple skin and breast cancer patients. Guideline utilisation rates were highest in the lower gastrointestinal and gynaecological subsites, with the lowest being in the upper gastrointestinal and thorax subsites. Head and neck (38% vs 45%) and CNS (46% vs 67%) cancers had the largest discrepancy between true and guideline utilisation rates due to unnamed reasons and non-contemporaneous diagnostic imaging respectively. This report outlines approximate MRI utilisation rates in a tertiary radiation oncology service and may help guide planning for future departments contemplating installation of an MRI simulator.
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Affiliation(s)
- Simon Tang
- Central West Cancer, Gosford, New South Wales, Australia.,Ingham Institute of Applied Medical Research, Liverpool, New South Wales, Australia
| | - Robba Rai
- Ingham Institute of Applied Medical Research, Liverpool, New South Wales, Australia.,Liverpool and Macarthur Cancer Therapy Centres, Liverpool, New South Wales, Australia.,South Western Sydney Clinical School, University of New South Wales, Sydney, New South Wales, Australia
| | - Shalini K Vinod
- Ingham Institute of Applied Medical Research, Liverpool, New South Wales, Australia.,Liverpool and Macarthur Cancer Therapy Centres, Liverpool, New South Wales, Australia.,South Western Sydney Clinical School, University of New South Wales, Sydney, New South Wales, Australia
| | - Doaa Elwadia
- Liverpool and Macarthur Cancer Therapy Centres, Liverpool, New South Wales, Australia
| | - Dion Forstner
- Genesis Care, St Vincent's Clinic, Darlinghust, New South Wales, Australia
| | - Daniel Moretti
- Liverpool and Macarthur Cancer Therapy Centres, Liverpool, New South Wales, Australia
| | - Thomas Tran
- Liverpool and Macarthur Cancer Therapy Centres, Liverpool, New South Wales, Australia
| | - Viet Do
- Ingham Institute of Applied Medical Research, Liverpool, New South Wales, Australia.,Liverpool and Macarthur Cancer Therapy Centres, Liverpool, New South Wales, Australia.,South Western Sydney Clinical School, University of New South Wales, Sydney, New South Wales, Australia
| | - Odette King
- Liverpool and Macarthur Cancer Therapy Centres, Liverpool, New South Wales, Australia
| | - Karen Lim
- Ingham Institute of Applied Medical Research, Liverpool, New South Wales, Australia.,Liverpool and Macarthur Cancer Therapy Centres, Liverpool, New South Wales, Australia.,South Western Sydney Clinical School, University of New South Wales, Sydney, New South Wales, Australia
| | - Gary Liney
- Ingham Institute of Applied Medical Research, Liverpool, New South Wales, Australia.,Liverpool and Macarthur Cancer Therapy Centres, Liverpool, New South Wales, Australia.,South Western Sydney Clinical School, University of New South Wales, Sydney, New South Wales, Australia
| | - Gary Goozee
- Liverpool and Macarthur Cancer Therapy Centres, Liverpool, New South Wales, Australia
| | - Lois Holloway
- Ingham Institute of Applied Medical Research, Liverpool, New South Wales, Australia.,Liverpool and Macarthur Cancer Therapy Centres, Liverpool, New South Wales, Australia.,South Western Sydney Clinical School, University of New South Wales, Sydney, New South Wales, Australia.,University of Sydney, Sydney, New South Wales, Australia.,University of Wollongong, Wollongong, New South Wales, Australia
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Paterson C, Hargreaves S, Rumley CN. Functional Imaging to Predict Treatment Response in Head and Neck Cancer: How Close are We to Biologically Adaptive Radiotherapy? Clin Oncol (R Coll Radiol) 2020; 32:861-873. [PMID: 33127234 DOI: 10.1016/j.clon.2020.10.004] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Revised: 09/28/2020] [Accepted: 10/05/2020] [Indexed: 02/07/2023]
Abstract
It is increasingly recognised that head and neck cancer represents a spectrum of disease with a differential response to standard treatments. Although prognostic factors are well established, they do not reliably predict response. The ability to predict response early during radiotherapy would allow adaptation of treatment: intensifying treatment for those not responding adequately or de-intensifying remaining therapy for those likely to achieve a complete response. Functional imaging offers such an opportunity. Changes in parameters obtained with functional magnetic resonance imaging or positron emission tomography-computed tomography during treatment have been found to be predictive of disease control in head and neck cancer. Although many questions remain unanswered regarding the optimal implementation of these techniques, current, maturing and future studies may provide the much-needed homogeneous cohorts with larger sample sizes and external validation of parameters. With a stepwise and collaborative approach, we may be able to develop imaging biomarkers that allow us to deliver personalised, biologically adaptive radiotherapy for head and neck cancer.
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Affiliation(s)
- C Paterson
- Beatson West of Scotland Cancer Centre, Glasgow, UK.
| | | | - C N Rumley
- Department of Radiation Oncology, Townsville University Hospital, Douglas, Australia; South Western Clinical School, University of New South Wales, Sydney, Australia; Ingham Institute for Applied Medical Research, Sydney, Australia
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Multiparametric functional MRI and 18F-FDG-PET for survival prediction in patients with head and neck squamous cell carcinoma treated with (chemo)radiation. Eur Radiol 2020; 31:616-628. [PMID: 32851444 PMCID: PMC7813703 DOI: 10.1007/s00330-020-07163-3] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Revised: 06/17/2020] [Accepted: 08/06/2020] [Indexed: 12/02/2022]
Abstract
Objectives To assess (I) correlations between diffusion-weighted (DWI), intravoxel incoherent motion (IVIM), dynamic contrast-enhanced (DCE) MRI, and 18F-FDG-PET/CT imaging parameters capturing tumor characteristics and (II) their predictive value of locoregional recurrence-free survival (LRFS) and overall survival (OS) in patients with head and neck squamous cell carcinoma (HNSCC) treated with (chemo)radiotherapy. Methods Between 2014 and 2018, patients with histopathologically proven HNSCC, planned for curative (chemo) radiotherapy, were prospectively included. Pretreatment clinical, anatomical, and functional imaging parameters (obtained by DWI/IVIM, DCE-MRI, and 18F-FDG-PET/CT) were extracted for primary tumors (PT) and lymph node metastases. Correlations and differences between parameters were assessed. The predictive value of LRFS and OS was assessed, performing univariable, multivariable Cox and CoxBoost regression analyses. Results In total, 70 patients were included. Significant correlations between 18F-FDG-PET parameters and DWI-/DCE volume parameters were found (r > 0.442, p < 0.002). The combination of HPV (HR = 0.903), intoxications (HR = 1.065), PT ADCGTV (HR = 1.252), Ktrans (HR = 1.223), and Ve (HR = 1.215) was predictive for LRFS (C-index = 0.546; p = 0.023). N-stage (HR = 1.058), HPV positivity (HR = 0.886), hypopharyngeal tumor location (HR = 1.111), ADCGTV (HR = 1.102), ADCmean (HR = 1.137), D* (HR = 0.862), Ktrans (HR = 1.106), Ve (HR = 1.195), SUVmax (HR = 1.094), and TLG (HR = 1.433) were predictive for OS (C-index = 0.664; p = 0.046). Conclusions Functional imaging parameters, performing DWI/IVIM, DCE-MRI, and 18F-FDG-PET/CT, yielded complementary value in capturing tumor characteristics. More specific, intoxications, HPV-negative status, large tumor volume-related parameters, high permeability (Ktrans), and high extravascular extracellular space (Ve) parameters were predictive for adverse locoregional recurrence-free survival and adverse overall survival. Low cellularity (high ADC) and high metabolism (high SUV) were additionally predictive for decreased overall survival. These different predictive factors added to estimated locoregional and overall survival. Key Points • Parameters of DWI/IVIM, DCE-MRI, and 18F-FDG-PET/CT were able to capture complementary tumor characteristics. • Multivariable analysis revealed that intoxications, HPV negativity, large tumor volume and high vascular permeability (Ktrans), and extravascular extracellular space (Ve) were complementary predictive for locoregional recurrence. • In addition to predictive parameters for locoregional recurrence, also high cellularity (low ADC) and high metabolism (high SUV) were complementary predictive for overall survival. Electronic supplementary material The online version of this article (10.1007/s00330-020-07163-3) contains supplementary material, which is available to authorized users.
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8
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Hsieh JCH, Wang HM, Wu MH, Chang KP, Chang PH, Liao CT, Liau CT. Review of emerging biomarkers in head and neck squamous cell carcinoma in the era of immunotherapy and targeted therapy. Head Neck 2020; 41 Suppl 1:19-45. [PMID: 31573749 DOI: 10.1002/hed.25932] [Citation(s) in RCA: 55] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2019] [Revised: 08/12/2019] [Accepted: 08/13/2019] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Biomarkers in head and neck squamous cell carcinoma (HNSCC) emerge rapidly in recent years, especially for new targeted therapies and immunotherapies. METHODS Recent, relevant peer-reviewed evidence were critically reviewed and summarized. RESULTS This review article briefly introduces essential biomarker concepts, including purposes and classifications (predictive, prognostic, and diagnostic markers), and the phases of biomarker development. We summarize current biomarkers in order of clinical utility; p16 and human papillomavirus status remain the most important and validated biomarkers in HNSCC. The rationale for biomarker study design continues to evolve with technological advances, especially whole-exome or whole-genomic sequencing. Noninvasive body fluid and liquid biopsy biomarkers appear to hold strong potential for development as tools for early cancer detection, cancer diagnosis, monitoring of disease recurrence, and outcome prediction. In light of discrepancies among different technologies, standardized approaches are needed. CONCLUSION Biomarkers from cancer tissue or blood in HNSCC could direct new anticancer therapies.
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Affiliation(s)
- Jason Chia-Hsun Hsieh
- Division of Hematology-Oncology, Department of Internal Medicine, Chang Gung Memorial Hospital, Linkou and Chang Gung University, Taoyuan, Taiwan
| | - Hung-Ming Wang
- Division of Hematology-Oncology, Department of Internal Medicine, Chang Gung Memorial Hospital, Linkou and Chang Gung University, Taoyuan, Taiwan
| | - Min-Hsien Wu
- Division of Hematology-Oncology, Department of Internal Medicine, Chang Gung Memorial Hospital, Linkou and Chang Gung University, Taoyuan, Taiwan.,Graduate Institute of Biomedical Engineering, Chang Gung University, Taoyuan, Taiwan.,Department of Chemical Engineering, Ming Chi University of Technology, New Taipei City, Taiwan
| | - Kai-Ping Chang
- Department of Otorhinolaryngology, Head and Neck Surgery, Chang Gung Memorial Hospital and Chang Gung University, Taoyuan, Taiwan
| | - Pei-Hung Chang
- Division of Hematology-Oncology, Department of Internal Medicine, Chang Gung Memorial Hospital, Keelung, Taiwan and Chang Gung University, Taoyuan, Taiwan.,Cancer Center, Chang Gung Memorial Hospital, Keelung, and Chang Gung University, Taoyuan, Taiwan
| | - Chun-Ta Liao
- Department of Otorhinolaryngology, Head and Neck Surgery, Chang Gung Memorial Hospital and Chang Gung University, Taoyuan, Taiwan
| | - Chi-Ting Liau
- Division of Hematology-Oncology, Department of Internal Medicine, Chang Gung Memorial Hospital, Linkou and Chang Gung University, Taoyuan, Taiwan
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Emerging Functional Imaging Biomarkers of Tumour Responses to Radiotherapy. Cancers (Basel) 2019; 11:cancers11020131. [PMID: 30678055 PMCID: PMC6407112 DOI: 10.3390/cancers11020131] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2018] [Revised: 01/11/2019] [Accepted: 01/13/2019] [Indexed: 12/11/2022] Open
Abstract
Tumour responses to radiotherapy are currently primarily assessed by changes in size. Imaging permits non-invasive, whole-body assessment of tumour burden and guides treatment options for most tumours. However, in most tumours, changes in size are slow to manifest and can sometimes be difficult to interpret or misleading, potentially leading to prolonged durations of ineffective treatment and delays in changing therapy. Functional imaging techniques that monitor biological processes have the potential to detect tumour responses to treatment earlier and refine treatment options based on tumour biology rather than solely on size and staging. By considering the biological effects of radiotherapy, this review focusses on emerging functional imaging techniques with the potential to augment morphological imaging and serve as biomarkers of early response to radiotherapy.
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10
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Emerging Magnetic Resonance Imaging Technologies for Radiation Therapy Planning and Response Assessment. Int J Radiat Oncol Biol Phys 2018; 101:1046-1056. [DOI: 10.1016/j.ijrobp.2018.03.028] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2017] [Revised: 03/12/2018] [Accepted: 03/22/2018] [Indexed: 12/27/2022]
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