Advertisement
Review Article| Volume 34, ISSUE 1, P293-306, February 2020

Imaging for Response Assessment in Radiation Oncology

Current and Emerging Techniques
Published:October 30, 2019DOI:https://doi.org/10.1016/j.hoc.2019.09.010

      Keywords

      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'

      Subscribers receive full online access to your subscription and archive of back issues up to and including 2002.

      Content published before 2002 is available via pay-per-view purchase only.

      Subscribe:

      Subscribe to Hematology/Oncology Clinics
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect

      References

        • Vera P.
        • Thureau S.
        • Chaumet-Riffaud P.
        • et al.
        Phase II study of a radiotherapy total dose increase in hypoxic lesions identified by (18)F-Misonidazole PET/CT in patients with non-small cell lung carcinoma (RTEP5 study).
        J Nucl Med. 2017; 58: 1045-1053
        • Mohamed A.S.R.
        • Bahig H.
        • Aristophanous M.
        • et al.
        Prospective in silico study of the feasibility and dosimetric advantages of MRI-guided dose adaptation for human papillomavirus positive oropharyngeal cancer patients compared with standard IMRT.
        Clin Transl Radiat Oncol. 2018; 11: 11-18
        • Fave X.
        • Mackin D.
        • Yang J.
        • et al.
        Can radiomics features be reproducibly measured from CBCT images for patients with non-small cell lung cancer?.
        Med Phys. 2015; 42: 6784-6797
        • Eisenhauer E.A.
        • Therasse P.
        • Bogaerts J.
        • et al.
        New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1).
        Eur J Cancer. 2009; 45: 228-247
        • Thorwarth D.
        Functional imaging for radiotherapy treatment planning: current status and future directions—a review.
        Br J Radiol. 2015; 88: 20150056
        • O'Connor J.P.
        • Tofts P.S.
        • Miles K.A.
        • et al.
        Dynamic contrast-enhanced imaging techniques: CT and MRI.
        Br J Radiol. 2011; 84: S112-S120
        • Coolens C.
        • Driscoll B.
        • Chung C.
        • et al.
        Automated voxel-based analysis of volumetric dynamic contrast-enhanced CT data improves measurement of serial changes in tumor vascular biomarkers.
        Int J Radiat Oncol Biol Phys. 2015; 91: 48-57
        • Cao Y.
        • Pan C.
        • Balter J.M.
        • et al.
        Liver function after irradiation based on computed tomographic portal vein perfusion imaging.
        Int J Radiat Oncol Biol Phys. 2008; 70: 154-160
        • Even A.J.G.
        • Reymen B.
        • La Fontaine M.D.
        • et al.
        Clustering of multi-parametric functional imaging to identify high-risk subvolumes in non-small cell lung cancer.
        Radiother Oncol. 2017; 125: 379-384
        • Abramyuk A.
        • Hietschold V.
        • Appold S.
        • et al.
        Radiochemotherapy-induced changes of tumour vascularity and blood supply estimated by dynamic contrast-enhanced CT and fractal analysis in malignant head and neck tumours.
        Br J Radiol. 2015; 88: 20140412
        • Hwang S.H.
        • Yoo M.R.
        • Park C.H.
        • et al.
        Dynamic contrast-enhanced CT to assess metabolic response in patients with advanced non-small cell lung cancer and stable disease after chemotherapy or chemoradiotherapy.
        Eur Radiol. 2013; 23: 1573-1581
        • Shukla-Dave A.
        • Obuchowski N.A.
        • Chenevert T.L.
        • et al.
        Quantitative imaging biomarkers alliance (QIBA) recommendations for improved precision of DWI and DCE-MRI derived biomarkers in multicenter oncology trials.
        J Magn Reson Imaging. 2019; 49: e101-e121
        • van Elmpt W.
        • Landry G.
        • Das M.
        • et al.
        Dual energy CT in radiotherapy: current applications and future outlook.
        Radiother Oncol. 2016; 119: 137-144
        • Grajo J.R.
        • Patino M.
        • Prochowski A.
        • et al.
        Dual energy CT in practice: basic principles and applications.
        Appl Radiol. 2016; 45: 6-12
        • Agrawal M.D.
        • Pinho D.F.
        • Kulkarni N.M.
        • et al.
        Oncologic applications of dual-energy CT in the abdomen.
        Radiographics. 2014; 34: 589-612
        • Bahig H.
        • Lapointe A.
        • Bedwani S.
        • et al.
        Dual-energy computed tomography for prediction of loco-regional recurrence after radiotherapy in larynx and hypopharynx squamous cell carcinoma.
        Eur J Radiol. 2019; 110: 1-6
        • Tawfik A.M.
        • Razek A.A.
        • Kerl J.M.
        • et al.
        Comparison of dual-energy CT-derived iodine content and iodine overlay of normal, inflammatory and metastatic squamous cell carcinoma cervical lymph nodes.
        Eur Radiol. 2014; 24: 574-580
        • Lapointe A.
        • Bahig H.
        • Blais D.
        • et al.
        Assessing lung function using contrast-enhanced dual-energy computed tomography for potential applications in radiation therapy.
        Med Phys. 2017; 44: 5260-5269
        • Lambin P.
        • Rios-Velazquez E.
        • Leijenaar R.
        • et al.
        Radiomics: extracting more information from medical images using advanced feature analysis.
        Eur J Cancer. 2012; 48: 441-446
        • Liu Z.
        • Wang S.
        • Dong D.
        • et al.
        The applications of radiomics in precision diagnosis and treatment of oncology: opportunities and challenges.
        Theranostics. 2019; 9: 1303-1322
        • Ramella S.
        • Fiore M.
        • Greco C.
        • et al.
        A radiomic approach for adaptive radiotherapy in non-small cell lung cancer patients.
        PLoS One. 2018; 13: e0207455
      1. Sicilia R, Cordelli E, Ramella S, et al. Exploratory radiomics for predicting adaptive radiotherapy in non-small cell lung cancer. Paper presented at: 2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS). Karlstad University, June 18–21, 2018.

        • Paul J.
        • Yang C.
        • Wu H.
        • et al.
        Early assessment of treatment responses during radiation therapy for lung cancer using quantitative analysis of daily computed tomography.
        Int J Radiat Oncol Biol Phys. 2017; 98: 463-472
        • Elhalawani H.E.
        • Mohamed A.S.R.
        • Volpe S.
        • et al.
        PO-0991: serial tumor radiomic features predict response of head and neck cancer treated with radiotherapy.
        Radiother Oncol. 2018; 127: S551
        • Macdonald D.R.
        • Cascino T.L.
        • Schold Jr., S.C.
        • et al.
        Response criteria for phase II studies of supratentorial malignant glioma.
        J Clin Oncol. 1990; 8: 1277-1280
        • Wen P.Y.
        • Macdonald D.R.
        • Reardon D.A.
        • et al.
        Updated response assessment criteria for high-grade gliomas: response assessment in neuro-oncology working group.
        J Clin Oncol. 2010; 28: 1963-1972
        • van Dijken B.R.J.
        • van Laar P.J.
        • Holtman G.A.
        • et al.
        Diagnostic accuracy of magnetic resonance imaging techniques for treatment response evaluation in patients with high-grade glioma, a systematic review and meta-analysis.
        Eur Radiol. 2017; 27: 4129-4144
        • Okada H.
        • Weller M.
        • Huang R.
        • et al.
        Immunotherapy response assessment in neuro-oncology: a report of the RANO working group.
        Lancet Oncol. 2015; 16: e534-e542
        • Hu L.S.
        • Baxter L.C.
        • Smith K.A.
        • et al.
        Relative cerebral blood volume values to differentiate high-grade glioma recurrence from posttreatment radiation effect: direct correlation between image-guided tissue histopathology and localized dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging measurements.
        AJNR Am J Neuroradiol. 2009; 30: 552-558
        • Hu X.
        • Wong K.K.
        • Young G.S.
        • et al.
        Support vector machine multiparametric MRI identification of pseudoprogression from tumor recurrence in patients with resected glioblastoma.
        J Magn Reson Imaging. 2011; 33: 296-305
        • Cha J.
        • Kim S.T.
        • Kim H.J.
        • et al.
        Differentiation of tumor progression from pseudoprogression in patients with posttreatment glioblastoma using multiparametric histogram analysis.
        AJNR Am J Neuroradiol. 2014; 35: 1309-1317
        • Kamada K.
        • Houkin K.
        • Abe H.
        • et al.
        Differentiation of cerebral radiation necrosis from tumor recurrence by proton magnetic resonance spectroscopy.
        Neurol Med Chir (Tokyo). 1997; 37: 250-256
        • Kazda T.
        • Bulik M.
        • Pospisil P.
        • et al.
        Advanced MRI increases the diagnostic accuracy of recurrent glioblastoma: single institution thresholds and validation of MR spectroscopy and diffusion weighted MR imaging.
        Neuroimage Clin. 2016; 11: 316-321
        • Kimura T.
        • Sako K.
        • Tohyama Y.
        • et al.
        Diagnosis and treatment of progressive space-occupying radiation necrosis following stereotactic radiosurgery for brain metastasis: value of proton magnetic resonance spectroscopy.
        Acta Neurochir (Wien). 2003; 145 ([discussion: 564]): 557-564
        • Kim S.
        • Loevner L.
        • Quon H.
        • et al.
        Diffusion-weighted magnetic resonance imaging for predicting and detecting early response to chemoradiation therapy of squamous cell carcinomas of the head and neck.
        Clin Cancer Res. 2009; 15: 986-994
        • Lombardi M.
        • Cascone T.
        • Guenzi E.
        • et al.
        Predictive value of pre-treatment apparent diffusion coefficient (ADC) in radio-chemotherapy treated head and neck squamous cell carcinoma.
        Radiol Med. 2017; 122: 345-352
        • Ng S.H.
        • Lin C.Y.
        • Chan S.C.
        • et al.
        Clinical utility of multimodality imaging with dynamic contrast-enhanced MRI, diffusion-weighted MRI, and 18F-FDG PET/CT for the prediction of neck control in oropharyngeal or hypopharyngeal squamous cell carcinoma treated with chemoradiation.
        PLoS One. 2014; 9: e115933
        • Ng S.H.
        • Lin C.Y.
        • Chan S.C.
        • et al.
        Dynamic contrast-enhanced MR imaging predicts local control in oropharyngeal or hypopharyngeal squamous cell carcinoma treated with chemoradiotherapy.
        PLoS One. 2013; 8: e72230
        • Kim S.
        • Loevner L.A.
        • Quon H.
        • et al.
        Prediction of response to chemoradiation therapy in squamous cell carcinomas of the head and neck using dynamic contrast-enhanced MR imaging.
        AJNR Am J Neuroradiol. 2010; 31: 262-268
        • Wallyn J.
        • Anton N.
        • Akram S.
        • et al.
        Biomedical imaging: principles, technologies, clinical aspects, contrast agents, limitations and future trends in nanomedicines.
        Pharm Res. 2019; 36: 78
        • Buxton R.B.
        The physics of functional magnetic resonance imaging (fMRI).
        Rep Prog Phys. 2013; 76: 096601
        • Avanzo M.
        • Stancanello J.
        • El Naqa I.
        Beyond imaging: the promise of radiomics.
        Phys Med. 2017; 38: 122-139
        • Liu Z.
        • Li Z.
        • Qu J.
        • et al.
        Radiomics of multiparametric MRI for pretreatment prediction of pathologic complete response to neoadjuvant chemotherapy in breast cancer: a multicenter study.
        Clin Cancer Res. 2019; 25: 3538-3547
        • Xiong Q.
        • Zhou X.
        • Liu Z.
        • et al.
        Multiparametric MRI-based radiomics analysis for prediction of breast cancers insensitive to neoadjuvant chemotherapy.
        Clin Transl Oncol. 2019; ([Epub ahead of print])
        • Zhang L.L.
        • Huang M.Y.
        • Li Y.
        • et al.
        Pretreatment MRI radiomics analysis allows for reliable prediction of local recurrence in non-metastatic T4 nasopharyngeal carcinoma.
        EBioMedicine. 2019; 42: 270-280
        • Zhuo E.H.
        • Zhang W.J.
        • Li H.J.
        • et al.
        Radiomics on multi-modalities MR sequences can subtype patients with non-metastatic nasopharyngeal carcinoma (NPC) into distinct survival subgroups.
        Eur Radiol. 2019; 29: 5590-5599
        • Duron L.
        • Balvay D.
        • Vande Perre S.
        • et al.
        Gray-level discretization impacts reproducible MRI radiomics texture features.
        PLoS One. 2019; 14: e0213459
        • Zhao B.
        • Tan Y.
        • Tsai W.Y.
        • et al.
        Reproducibility of radiomics for deciphering tumor phenotype with imaging.
        Sci Rep. 2016; 6: 23428
        • Ben-Haim S.
        • Ell P.
        18F-FDG PET and PET/CT in the evaluation of cancer treatment response.
        J Nucl Med. 2009; 50: 88-99
        • Yao M.
        • Graham M.M.
        • Smith R.B.
        • et al.
        Value of FDG PET in assessment of treatment response and surveillance in head-and-neck cancer patients after intensity modulated radiation treatment: a preliminary report.
        Int J Radiat Oncol Biol Phys. 2004; 60: 1410-1418
        • Bussink J.
        • van Herpen C.M.
        • Kaanders J.H.
        • et al.
        PET-CT for response assessment and treatment adaptation in head and neck cancer.
        Lancet Oncol. 2010; 11: 661-669
        • Young H.
        • Baum R.
        • Cremerius U.
        • et al.
        Measurement of clinical and subclinical tumour response using [18F]-fluorodeoxyglucose and positron emission tomography: review and 1999 EORTC recommendations. European Organization for Research and Treatment of Cancer (EORTC) PET Study Group.
        Eur J Cancer. 1999; 35: 1773-1782
        • Wahl R.L.
        • Jacene H.
        • Kasamon Y.
        • et al.
        From RECIST to PERCIST: evolving considerations for PET response criteria in solid tumors.
        J Nucl Med. 2009; 50: 122S-150S
        • Kim J.H.
        Comparison of the EORTC criteria and PERCIST in solid tumors: a pooled analysis and review.
        Oncotarget. 2016; 7: 58105-58110
        • Cheson B.D.
        • Fisher R.I.
        • Barrington S.F.
        • et al.
        Recommendations for initial evaluation, staging, and response assessment of Hodgkin and non-Hodgkin lymphoma: the Lugano classification.
        J Clin Oncol. 2014; 32: 3059-3068
        • Laing R.E.
        • Nair-Gill E.
        • Witte O.N.
        • et al.
        Visualizing cancer and immune cell function with metabolic positron emission tomography.
        Curr Opin Genet Dev. 2010; 20: 100-105
        • Prestwich R.J.
        • Subesinghe M.
        • Gilbert A.
        • et al.
        Delayed response assessment with FDG-PET-CT following (chemo) radiotherapy for locally advanced head and neck squamous cell carcinoma.
        Clin Radiol. 2012; 67: 966-975
        • Weber W.A.
        Monitoring tumor response to therapy with 18F-FLT PET.
        J Nucl Med. 2010; 51: 841-844
        • Liberti M.V.
        • Locasale J.W.
        The Warburg effect: how does it benefit cancer cells?.
        Trends Biochem Sci. 2016; 41: 211-218
        • Wilson W.R.
        • Hay M.P.
        Targeting hypoxia in cancer therapy.
        Nat Rev Cancer. 2011; 11: 393-410
        • Sun X.
        • Niu G.
        • Chan N.
        • et al.
        Tumor hypoxia imaging.
        Mol Imaging Biol. 2011; 13: 399-410
        • Lopci E.
        • Grassi I.
        • Chiti A.
        • et al.
        PET radiopharmaceuticals for imaging of tumor hypoxia: a review of the evidence.
        Am J Nucl Med Mol Imaging. 2014; 4: 365-384
        • Stieb S.
        • Eleftheriou A.
        • Warnock G.
        • et al.
        Longitudinal PET imaging of tumor hypoxia during the course of radiotherapy.
        Eur J Nucl Med Mol Imaging. 2018; 45: 2201-2217
        • Langendijk J.A.
        • Lambin P.
        • De Ruysscher D.
        • et al.
        Selection of patients for radiotherapy with protons aiming at reduction of side effects: the model-based approach.
        Radiother Oncol. 2013; 107: 267-273
        • Lomax A.
        Intensity modulation methods for proton radiotherapy.
        Phys Med Biol. 1999; 44: 185-205
        • Pollard J.M.
        • Wen Z.
        • Sadagopan R.
        • et al.
        The future of image-guided radiotherapy will be MR guided.
        Br J Radiol. 2017; 90: 20160667
        • van Dijk L.V.
        • Brouwer C.L.
        • van der Laan H.P.
        • et al.
        Geometric image biomarker changes of the parotid gland are associated with late xerostomia.
        Int J Radiat Oncol Biol Phys. 2017; 99: 1101-1110
        • Broggi S.
        • Fiorino C.
        • Dell'Oca I.
        • et al.
        A two-variable linear model of parotid shrinkage during IMRT for head and neck cancer.
        Radiother Oncol. 2010; 94: 206-212
        • Wu H.
        • Chen X.
        • Yang X.
        • et al.
        Early prediction of acute xerostomia during radiation therapy for head and neck cancer based on texture analysis of daily CT.
        Int J Radiat Oncol Biol Phys. 2018; 102: 1308-1318
        • Cunliffe A.
        • Armato 3rd, S.G.
        • Castillo R.
        • et al.
        Lung texture in serial thoracic computed tomography scans: correlation of radiomics-based features with radiation therapy dose and radiation pneumonitis development.
        Int J Radiat Oncol Biol Phys. 2015; 91: 1048-1056
        • Gillies R.J.
        • Kinahan P.E.
        • Hricak H.
        Radiomics: images are more than pictures, they are data.
        Radiology. 2016; 278: 563-577
        • Aerts H.J.
        • Velazquez E.R.
        • Leijenaar R.T.
        • et al.
        Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach.
        Nat Commun. 2014; 5: 4006
        • van Dijk L.V.
        • Brouwer C.L.
        • van der Schaaf A.
        • et al.
        CT image biomarkers to improve patient-specific prediction of radiation-induced xerostomia and sticky saliva.
        Radiother Oncol. 2017; 122: 185-191
        • Rosen B.S.
        • Hawkins P.G.
        • Polan D.F.
        • et al.
        Early changes in serial CBCT-measured parotid gland biomarkers predict chronic xerostomia after head and neck radiation therapy.
        Int J Radiat Oncol Biol Phys. 2018; 102: 1319-1329
        • Colen R.R.
        • Fujii T.
        • Bilen M.A.
        • et al.
        Radiomics to predict immunotherapy-induced pneumonitis: proof of concept.
        Invest New Drugs. 2018; 36: 601-607
        • Stieb S.
        • Elgohari B.
        • Fuller C.D.
        Repetitive MRI of organs at risk in head and neck cancer patients undergoing radiotherapy.
        Clin Transl Radiat Oncol. 2019; 18: 131-139
        • Popovtzer A.
        • Cao Y.
        • Feng F.Y.
        • et al.
        Anatomical changes in the pharyngeal constrictors after chemo-irradiation of head and neck cancer and their dose-effect relationships: MRI-based study.
        Radiother Oncol. 2009; 93: 510-515
        • Zhang Y.
        • Ou D.
        • Gu Y.
        • et al.
        Evaluation of salivary gland function using diffusion-weighted magnetic resonance imaging for follow-up of radiation-induced xerostomia.
        Korean J Radiol. 2018; 19: 758-766
        • Zhou N.
        • Chu C.
        • Dou X.
        • et al.
        Early evaluation of radiation-induced parotid damage in patients with nasopharyngeal carcinoma by T2 mapping and mDIXON Quant imaging: initial findings.
        Radiat Oncol. 2018; 13: 22
        • Brouwer C.L.
        • Steenbakkers R.J.
        • Gort E.
        • et al.
        Differences in delineation guidelines for head and neck cancer result in inconsistent reported dose and corresponding NTCP.
        Radiother Oncol. 2014; 111: 148-152
        • Zeilinger M.G.
        • Lell M.
        • Baltzer P.A.
        • et al.
        Impact of post-processing methods on apparent diffusion coefficient values.
        Eur Radiol. 2017; 27: 946-955
        • van Dijk L.V.
        • Thor M.
        • Steenbakkers R.
        • et al.
        Parotid gland fat related Magnetic Resonance image biomarkers improve prediction of late radiation-induced xerostomia.
        Radiother Oncol. 2018; 128: 459-466
        • Abdollahi H.
        • Mahdavi S.R.
        • Shiri I.
        • et al.
        Magnetic resonance imaging radiomic feature analysis of radiation-induced femoral head changes in prostate cancer radiotherapy.
        J Cancer Res Ther. 2019; 15: S11-S19
        • Mawlawi O.
        • WR
        • Wong W.H.
        Principles of PET/CT.
        in: Kim E.E. Lee M.C. Inoue R. Clinical PET. Springer, 2004 (ISBN 9781441923554. p. 41-61)
        • Farr K.P.
        • Khalil A.A.
        • Moller D.S.
        • et al.
        Time and dose-related changes in lung perfusion after definitive radiotherapy for NSCLC.
        Radiother Oncol. 2018; 126: 307-311
        • Cannon B.
        • Schwartz D.L.
        • Dong L.
        Metabolic imaging biomarkers of postradiotherapy xerostomia.
        Int J Radiat Oncol Biol Phys. 2012; 83: 1609-1616
        • Klein Nulent T.J.W.
        • Valstar M.H.
        • de Keizer B.
        • et al.
        Physiologic distribution of PSMA-ligand in salivary glands and seromucous glands of the head and neck on PET/CT.
        Oral Surg Oral Med Oral Pathol Oral Radiol. 2018; 125: 478-486
        • Petit S.F.
        • van Elmpt W.J.
        • Oberije C.J.
        • et al.
        [(1)(8)F]fluorodeoxyglucose uptake patterns in lung before radiotherapy identify areas more susceptible to radiation-induced lung toxicity in non-small-cell lung cancer patients.
        Int J Radiat Oncol Biol Phys. 2011; 81: 698-705
        • Zyromska A.
        • Malkowski B.
        • Wisniewski T.
        • et al.
        (15)O-H2O PET/CT as a tool for the quantitative assessment of early post-radiotherapy changes of heart perfusion in breast carcinoma patients.
        Br J Radiol. 2018; 91: 20170653
        • Unal K.
        • Unlu M.
        • Akdemir O.
        • et al.
        18F-FDG PET/CT findings of radiotherapy-related myocardial changes in patients with thoracic malignancies.
        Nucl Med Commun. 2013; 34: 855-859