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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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Li X, Huang W, Holmes JH. Dynamic Contrast-Enhanced (DCE) MRI. Magn Reson Imaging Clin N Am 2024; 32:47-61. [PMID: 38007282 DOI: 10.1016/j.mric.2023.09.001] [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] [Indexed: 11/27/2023]
Abstract
The non-invasive dynamic contrast-enhanced MRI (DCE-MRI) method provides valuable insights into tissue perfusion and vascularity. Primarily used in oncology, DCE-MRI is typically utilized to assess morphology and contrast agent (CA) kinetics in the tissue of interest. Interpretation of the temporal signatures of DCE-MRI data includes qualitative, semi-quantitative, and quantitative approaches. Recent advances in MRI technology allow simultaneous high spatial and temporal resolutions in DCE-MRI data acquisition on most vendor platforms, enabling the more desirable approach of quantitative data analysis using pharmacokinetic (PK) modeling. Many technical factors, including signal-to-noise ratio, temporal resolution, quantifications of arterial input function and native tissue T1, and PK model selection, need to be carefully considered when performing quantitative DCE-MRI. Standardization in data acquisition and analysis is especially important in multi-center studies.
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Affiliation(s)
- Xin Li
- Advanced Imaging Research Center, Oregon Health & Science University, 3181 SW Sam Jackson Park Road, Portland, OR 97239, USA
| | - Wei Huang
- Advanced Imaging Research Center, Oregon Health & Science University, 3181 SW Sam Jackson Park Road, Portland, OR 97239, USA
| | - James H Holmes
- Radiology, Biomedical Engineering, and Holden Cancer Center, University of Iowa, 169 Newton Road, Iowa City, IA 52242, USA.
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Kåstad Høiskar M, Sæther O, Delange Alsaker M, Røe Redalen K, Winter RM. Quantitative dynamic contrast-enhanced magnetic resonance imaging in head and neck cancer: A systematic comparison of different modelling approaches. Phys Imaging Radiat Oncol 2024; 29:100548. [PMID: 38380153 PMCID: PMC10876686 DOI: 10.1016/j.phro.2024.100548] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Revised: 01/24/2024] [Accepted: 02/05/2024] [Indexed: 02/22/2024] Open
Abstract
Background and purpose Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) describes tissue microvasculature and has prognostic and predictive potential in radiotherapy for head and neck cancer (HNC). However, lack in standardization of DCE-MRI hinders comparison of studies and clinical implementation. This study investigated the accuracy and robustness of the population arterial input function (AIF), correlations between pharmacokinetic parameters and their association to T stage and human papillomavirus (HPV) status for HNC. Materials and methods DCE-MRI was acquired for 44 HNC patients. Population AIFs were calculated with six different approaches. DCE-MRI was analysed in primary and lymph node tumours using Tofts model (TM) with population AIFs and individual AIFs, extended TM (ETM) with individual AIFs, Brix model (BM), and areas under the curve (AUCs). Intraclass correlation, concordance correlation, Pearson correlation and Whitney Mann U test helped examining the robustness and accuracy of population AIF, correlations between DCE-MRI parameters and their association to T stage and HPV status, respectively. Results The population AIF was robust but differed from individual AIFs. There was significant correlation between KtransTM/ETM and ve, TM/ETM, and KtransTM/ETM and Kep, TM/ETM. ABrix and AUCs correlated for lymph nodes. Kep, Brix correlated with ABrix, KtransTM/ETM and Kep, TM/ETM for primary tumours. Kep, TM significantly decreased with increasing T stage. Both the correlations and the parameters' association to T stage were stronger for HPV negative lesions. Conclusions Individual AIF was preferred for accurate pharmacokinetic modelling of DCE-MRI. DCE-MRI parameters and their correlations were affected by the lesion type, HPV status and T staging.
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Affiliation(s)
- Marte Kåstad Høiskar
- Department of Physics, Norwegian University of Science and Technology, Trondheim, Norway
| | - Oddbjørn Sæther
- Department of Radiology and Nuclear Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | | | - Kathrine Røe Redalen
- Department of Physics, Norwegian University of Science and Technology, Trondheim, Norway
| | - René M. Winter
- Department of Physics, Norwegian University of Science and Technology, Trondheim, Norway
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Boeke S, Winter RM, Leibfarth S, Krueger MA, Bowden G, Cotton J, Pichler BJ, Zips D, Thorwarth D. Machine learning identifies multi-parametric functional PET/MR imaging cluster to predict radiation resistance in preclinical head and neck cancer models. Eur J Nucl Med Mol Imaging 2023; 50:3084-3096. [PMID: 37148296 PMCID: PMC10382355 DOI: 10.1007/s00259-023-06254-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Accepted: 04/25/2023] [Indexed: 05/08/2023]
Abstract
PURPOSE Tumor hypoxia and other microenvironmental factors are key determinants of treatment resistance. Hypoxia positron emission tomography (PET) and functional magnetic resonance imaging (MRI) are established prognostic imaging modalities to identify radiation resistance in head-and-neck cancer (HNC). The aim of this preclinical study was to develop a multi-parametric imaging parameter specifically for focal radiotherapy (RT) dose escalation using HNC xenografts of different radiation sensitivities. METHODS A total of eight human HNC xenograft models were implanted into 68 immunodeficient mice. Combined PET/MRI using dynamic [18F]-fluoromisonidazole (FMISO) hypoxia PET, diffusion-weighted (DW), and dynamic contrast-enhanced MRI was carried out before and after fractionated RT (10 × 2 Gy). Imaging data were analyzed on voxel-basis using principal component (PC) analysis for dynamic data and apparent diffusion coefficients (ADCs) for DW-MRI. A data- and hypothesis-driven machine learning model was trained to identify clusters of high-risk subvolumes (HRSs) from multi-dimensional (1-5D) pre-clinical imaging data before and after RT. The stratification potential of each 1D to 5D model with respect to radiation sensitivity was evaluated using Cohen's d-score and compared to classical features such as mean/peak/maximum standardized uptake values (SUVmean/peak/max) and tumor-to-muscle-ratios (TMRpeak/max) as well as minimum/valley/maximum/mean ADC. RESULTS Complete 5D imaging data were available for 42 animals. The final preclinical model for HRS identification at baseline yielding the highest stratification potential was defined in 3D imaging space based on ADC and two FMISO PCs ([Formula: see text]). In 1D imaging space, only clusters of ADC revealed significant stratification potential ([Formula: see text]). Among all classical features, only ADCvalley showed significant correlation to radiation resistance ([Formula: see text]). After 2 weeks of RT, FMISO_c1 showed significant correlation to radiation resistance ([Formula: see text]). CONCLUSION A quantitative imaging metric was described in a preclinical study indicating that radiation-resistant subvolumes in HNC may be detected by clusters of ADC and FMISO using combined PET/MRI which are potential targets for future functional image-guided RT dose-painting approaches and require clinical validation.
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Affiliation(s)
- Simon Boeke
- Department of Radiation Oncology, University of Tübingen, Tübingen, Germany
- German Cancer Consortium (DKTK), partner site Tübingen, and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - René M Winter
- Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Hoppe-Seyler-Str. 3, 72076, Tübingen, Germany
| | - Sara Leibfarth
- Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Hoppe-Seyler-Str. 3, 72076, Tübingen, Germany
| | - Marcel A Krueger
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, University of Tübingen, Tübingen, Germany
| | - Gregory Bowden
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, University of Tübingen, Tübingen, Germany
| | - Jonathan Cotton
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, University of Tübingen, Tübingen, Germany
| | - Bernd J Pichler
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, University of Tübingen, Tübingen, Germany
- Cluster of Excellence iFIT (EXC 2180) "Image Guided and Functionally Instructed Tumor Therapies", University of Tübingen, Tübingen, Germany
| | - Daniel Zips
- Department of Radiation Oncology, University of Tübingen, Tübingen, Germany
- German Cancer Consortium (DKTK), partner site Tübingen, and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Daniela Thorwarth
- German Cancer Consortium (DKTK), partner site Tübingen, and German Cancer Research Center (DKFZ), Heidelberg, Germany.
- Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Hoppe-Seyler-Str. 3, 72076, Tübingen, Germany.
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5
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Yu J, Xu W, Wang L, Jiang N, Dou W, Li C, Sun L. The clinical value of DCE-MRI for differentiating secondary laryngeal cartilage lesions. Medicine (Baltimore) 2023; 102:e33352. [PMID: 37000106 PMCID: PMC10063300 DOI: 10.1097/md.0000000000033352] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 03/02/2023] [Accepted: 03/03/2023] [Indexed: 04/01/2023] Open
Abstract
To explore the value of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in the assessment of laryngeal cartilage lesions. In this study, 3 groups of cases were selected, including 16 cases benign lesions of the laryngopharynx as the benign group, 17 cases malignant lesions of laryngopharynx as the malignant group and 23 healthy adults as the control group. Conventional magnetic resonance imaging and DCE-MRI were performed with a 3.0 T MR scanner. cutoff, sensitivity, specificity and area under the curve values were calculated via receiver operating characteristic curve analysis based on the pathologic findings of surgically resected specimens. There were significant differences in the values of the volume transfer constant (Ktrans), the rate constant between the extravascular extracellular space and blood plasma (Kep) and The extravascular extracellular space fractional volume (Ve) between the control, benign and malignant groups (P < .005). Among the 3 groups, the malignant group had the highest Ktrans and Ve values (0.8681 ± 0.3034 and 0.6186 ± 0.2405, respectively), and the benign group had the highest Kep value (2.445 ± 0.7346). The cutoff points of the Ktrans, Kep, and Ve values of the control, benign and malignant groups were 0.39, 1.261, and 0.195; 0.471, 0.964, and 0.235; and 0.706, 2.005, and 0.659, respectively. The Ktrans, Kep, and Ve values obtained via DCE-MRI may enable differentiating laryngeal cartilage lesions. DCE-MRI can be used to evaluate laryngeal cartilage lesions accurately and quantitatively.
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Affiliation(s)
- Jinfen Yu
- Department of Medical Imaging Center, Shandong Second Provincial General Hospital, Jinan, Shandong, P. R. China
| | - Wei Xu
- Department of Medical Imaging Center, Shandong Second Provincial General Hospital, Jinan, Shandong, P. R. China
| | - Linsheng Wang
- Department of Medical Imaging Center, Shandong Second Provincial General Hospital, Jinan, Shandong, P. R. China
| | - Nan Jiang
- Department of Medical Imaging Center, Shandong Second Provincial General Hospital, Jinan, Shandong, P. R. China
| | - Weiqiang Dou
- GE Healthcare, MR Research China, Beijing, P. R. China
| | - Chuanting Li
- Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, P. R. China
| | - Lixin Sun
- Department of Medical Imaging Center, Shandong Second Provincial General Hospital, Jinan, Shandong, P. R. China
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Radiomics Applications in Head and Neck Tumor Imaging: A Narrative Review. Cancers (Basel) 2023; 15:cancers15041174. [PMID: 36831517 PMCID: PMC9954362 DOI: 10.3390/cancers15041174] [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: 12/21/2022] [Revised: 01/31/2023] [Accepted: 02/08/2023] [Indexed: 02/16/2023] Open
Abstract
Recent advances in machine learning and artificial intelligence technology have ensured automated evaluation of medical images. As a result, quantifiable diagnostic and prognostic biomarkers have been created. We discuss radiomics applications for the head and neck region in this paper. Molecular characterization, categorization, prognosis and therapy recommendation are given special consideration. In a narrative manner, we outline the fundamental technological principles, the overall idea and usual workflow of radiomic analysis and what seem to be the present and potential challenges in normal clinical practice. Clinical oncology intends for all of this to ensure informed decision support for personalized and useful cancer treatment. Head and neck cancers present a unique set of diagnostic and therapeutic challenges. These challenges are brought on by the complicated anatomy and heterogeneity of the area under investigation. Radiomics has the potential to address these barriers. Future research must be interdisciplinary and focus on the study of certain oncologic functions and outcomes, with external validation and multi-institutional cooperation in order to achieve this.
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7
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Mierzwa ML, Aryal M, Lee C, Schipper M, VanTil M, Rivera KM, Swiecicki PL, Casper KA, Malloy KM, Spector ME, Shuman AG, Chinn SB, Prince ME, Stucken CL, Rosko AJ, Lawrence TS, Brenner JC, Rosen B, Schonewolf CA, Shah J, Eisbruch A, Worden FP, Cao Y. Randomized Phase II Study of Physiologic MRI-Directed Adaptive Radiation Boost in Poor Prognosis Head and Neck Cancer. Clin Cancer Res 2022; 28:5049-5057. [PMID: 36107219 PMCID: PMC9773159 DOI: 10.1158/1078-0432.ccr-22-1522] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Revised: 07/06/2022] [Accepted: 09/13/2022] [Indexed: 01/24/2023]
Abstract
PURPOSE We conducted a randomized phase II multicenter clinical trial to test the hypothesis that physiologic MRI-based radiotherapy (RT) dose escalation would improve the outcome of patients with poor prognosis head and neck cancer. PATIENTS AND METHODS MRI was acquired at baseline and at RT fraction 10 to create low blood volume/apparent diffusion coefficient maps for RT boost subvolume definition in gross tumor volume. Patients were randomized to receive 70 Gy (standard RT) or 80 Gy to the boost subvolume (RT boost) with concurrent weekly platinum. The primary endpoint was disease-free survival (DFS) with significance defined at a one-sided 0.1 level, and secondary endpoints included locoregional failure (LRF), overall survival (OS), comparison of adverse events and patient reported outcomes (PRO). RESULTS Among 81 randomized patients, neither the primary endpoint of DFS (HR = 0.849, P = 0.31) nor OS (HR = 1.19, P = 0.66) was significantly improved in the RT boost arm. However, the incidence of LRF was significantly improved with the addition of the RT boost (HR = 0.43, P = 0.047). Two-year estimates [90% confidence interval (CI)] of the cumulative incidence of LRF were 40% (27%-53%) in the standard RT arm and 18% (10%-31%) in the RT boost arm. Two-year estimates (90% CI) for DFS were 48% (34%-60%) in the standard RT arm and 57% (43%-69%) in the RT boost arm. There were no significant differences in toxicity or longitudinal differences seen in EORTC QLQ30/HN35 subscales between treatment arms in linear mixed-effects models. CONCLUSIONS Physiologic MRI-based RT boost decreased LRF without a significant increase in grade 3+ toxicity or longitudinal PRO differences, but did not significantly improve DFS or OS. Additional improvements in systemic therapy are likely necessary to realize improvements in DFS and OS.
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Affiliation(s)
- Michelle L Mierzwa
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Madhava Aryal
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Choonik Lee
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Matthew Schipper
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, Michigan
| | - Monica VanTil
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, Michigan
| | | | - Paul L. Swiecicki
- Department of Internal Medicine, Medical Oncology, University of Michigan, Ann Arbor, Michigan
| | - Keith A. Casper
- Department of Otolaryngology, University of Michigan, Ann Arbor, Michigan
| | - Kelly M. Malloy
- Department of Otolaryngology, University of Michigan, Ann Arbor, Michigan
| | - Matthew E. Spector
- Department of Otolaryngology, University of Michigan, Ann Arbor, Michigan
| | - Andrew G. Shuman
- Department of Otolaryngology, University of Michigan, Ann Arbor, Michigan
| | - Steven B. Chinn
- Department of Otolaryngology, University of Michigan, Ann Arbor, Michigan
| | - Mark E.P. Prince
- Department of Otolaryngology, University of Michigan, Ann Arbor, Michigan
| | - Chaz L. Stucken
- Department of Otolaryngology, University of Michigan, Ann Arbor, Michigan
| | - Andrew J. Rosko
- Department of Otolaryngology, University of Michigan, Ann Arbor, Michigan
| | | | - J Chad Brenner
- Department of Otolaryngology, University of Michigan, Ann Arbor, Michigan
| | - Benjamin Rosen
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | | | - Jennifer Shah
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Avraham Eisbruch
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Francis P. Worden
- Department of Internal Medicine, Medical Oncology, University of Michigan, Ann Arbor, Michigan
| | - Yue Cao
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
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Prognostic Value of 18F-Fluorodeoxyglucose–Positron Emission Tomography/Magnetic Resonance Imaging in Patients With Hypopharyngeal Squamous Cell Carcinoma. J Comput Assist Tomogr 2022; 46:968-977. [DOI: 10.1097/rct.0000000000001365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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9
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Chawla S, Loevner L, Mohan S, Lin A, Sehgal CM, Poptani H. Dynamic contrast-enhanced MRI and Doppler sonography in patients with squamous cell carcinoma of head and neck treated with induction chemotherapy. JOURNAL OF CLINICAL ULTRASOUND : JCU 2022; 50:1353-1359. [PMID: 36205388 DOI: 10.1002/jcu.23361] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 09/05/2022] [Accepted: 09/15/2022] [Indexed: 06/16/2023]
Abstract
In view of the inherent limitations associated with performing dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI) in clinical settings, current study was designed to provide a proof of principle that Doppler sonography and DCE-MRI derived perfusion parameters yield similar hemodynamic information from metastatic lymph nodes in squamous cell carcinomas of head and neck (HNSCCs). Strong positive correlations between volume fraction of plasma space in tissues (Vp ) and blood volume (r = 0.72, p = 0.02) and between Vp and %area perfused (r = 0.65, p = 0.04) were observed. Additionally, a moderate positive correlation trending towards significance was obtained between volume transfer constant (Ktrans ) and %area perfused (r = 0.49, p = 0.09).
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Affiliation(s)
- Sanjeev Chawla
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Laurie Loevner
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Suyash Mohan
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Alexander Lin
- Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Chandra M Sehgal
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Harish Poptani
- Department of Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool, UK
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10
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Lavigne D, Ng SP, O’Sullivan B, Nguyen-Tan PF, Filion E, Létourneau-Guillon L, Fuller CD, Bahig H. Magnetic Resonance-Guided Radiation Therapy for Head and Neck Cancers. Curr Oncol 2022; 29:8302-8315. [PMID: 36354715 PMCID: PMC9689607 DOI: 10.3390/curroncol29110655] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2022] [Revised: 10/25/2022] [Accepted: 10/28/2022] [Indexed: 11/06/2022] Open
Abstract
Despite the significant evolution of radiation therapy (RT) techniques in recent years, many patients with head and neck cancer still experience significant toxicities during and after treatments. The increased soft tissue contrast and functional sequences of magnetic resonance imaging (MRI) are particularly attractive in head and neck cancer and have led to the increasing development of magnetic resonance-guided RT (MRgRT). This approach refers to the inclusion of the additional information acquired from a diagnostic or planning MRI in radiation treatment planning, and now extends to online high-quality daily imaging generated by the recently developed MR-Linac. MRgRT holds numerous potentials, including enhanced baseline and planning evaluations, anatomical and functional treatment adaptation, potential for hypofractionation, and multiparametric assessment of response. This article offers a structured review of the current literature on these established and upcoming roles of MRI for patients with head and neck cancer undergoing RT.
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Affiliation(s)
- Danny Lavigne
- Department of Radiation Oncology, Centre Hospitalier de l’Université de Montréal, University of Montreal, Montreal, QC H2X 3E4, Canada
| | - Sweet Ping Ng
- Department of Radiation Oncology, Olivia Newton-John Cancer Centre, Austin Health, Melbourne, VI 3084, Australia
| | - Brian O’Sullivan
- Department of Radiation Oncology, Centre Hospitalier de l’Université de Montréal, University of Montreal, Montreal, QC H2X 3E4, Canada
| | - Phuc Felix Nguyen-Tan
- Department of Radiation Oncology, Centre Hospitalier de l’Université de Montréal, University of Montreal, Montreal, QC H2X 3E4, Canada
| | - Edith Filion
- Department of Radiation Oncology, Centre Hospitalier de l’Université de Montréal, University of Montreal, Montreal, QC H2X 3E4, Canada
| | - Laurent Létourneau-Guillon
- Department of Radiology, Centre Hospitalier de l’Université de Montréal, University of Montreal, Montreal, QC H2X 3E4, Canada
| | - Clifton D. Fuller
- Department of Radiation Oncology, MD Anderson Cancer Center, University of Texas, Houston, TX 77030, USA
| | - Houda Bahig
- Department of Radiation Oncology, Centre Hospitalier de l’Université de Montréal, University of Montreal, Montreal, QC H2X 3E4, Canada
- Correspondence:
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11
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Target Definition in MR-Guided Adaptive Radiotherapy for Head and Neck Cancer. Cancers (Basel) 2022; 14:cancers14123027. [PMID: 35740691 PMCID: PMC9220977 DOI: 10.3390/cancers14123027] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [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
Simple Summary Adaptive radiotherapy for head and neck cancer has become more routine due to an increase in imaging quality and improvement in radiation techniques. With the availability of faster adaptive workflows, it is possible to adapt more easily to (daily) changes. MRI offers besides great anatomical imaging, also functional information about the tumor and surrounding tissue. The aim of this review is to provide current state of evidence about target definition on MRI for adaptive strategies in the treatment of head and neck cancer. 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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12
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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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13
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Lobo R, Turk S, Bapuraj JR, Srinivasan A. Advanced CT and MR Imaging of the Posttreatment Head and Neck. Neuroimaging Clin N Am 2021; 32:133-144. [PMID: 34809834 DOI: 10.1016/j.nic.2021.08.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
Advances in MR and computed tomography (CT) techniques have resulted in greater fidelity in the assessment of treatment response and residual tumor on one hand and the assessment of recurrent head and neck malignancies on the other hand. The advances in MR techniques primarily are related to diffusion and perfusion imaging which rely on the intrinsic architecture of the tissues and organ systems. The techniques exploit the density of the cellular architecture; and the vascularity of benign and malignant lesions which in turn affect the changes in the passage of contrast through the vascular bed. Dual-energy CT and CT perfusion are the major advances in CT techniques that have found significant applications in the assessment of treatment response and tumor recurrence.
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Affiliation(s)
- Remy Lobo
- Neuroradiology Division, Radiology, Michigan Medicine, 1500 E Medical Center Drive, Ann Arbor, MI 48109, USA
| | - Sevcan Turk
- Neuroradiology Division, Radiology, Michigan Medicine, 1500 E Medical Center Drive, Ann Arbor, MI 48109, USA
| | - J Rajiv Bapuraj
- Neuroradiology Division, Radiology, Michigan Medicine, 1500 E Medical Center Drive, B2A209, Ann Arbor, MI 48109, USA
| | - Ashok Srinivasan
- Neuroradiology Division, Radiology, Michigan Medicine, 1500 E Medical Center Drive, B2A209, Ann Arbor, MI 48109, USA.
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14
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Bülbül HM, Bülbül O, Sarıoğlu S, Özdoğan Ö, Doğan E, Karabay N. Relationships Between DCE-MRI, DWI, and 18F-FDG PET/CT Parameters with Tumor Grade and Stage in Patients with Head and Neck Squamous Cell Carcinoma. Mol Imaging Radionucl Ther 2021; 30:177-186. [PMID: 34658826 PMCID: PMC8522517 DOI: 10.4274/mirt.galenos.2021.25633] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022] Open
Abstract
Objectives Properties of head and neck squamous cell carcinoma (HNSCC) such as cellularity, vascularity, and glucose metabolism interact with each other. This study aimed to investigate the associations between diffusion-weighted imaging (DWI), dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), and positron emission tomography/computed tomography (PET/CT) in patients with HNSCC. Methods Fourteen patients who were diagnosed with HNSCC were investigated using DCE-MRI, DCE, and 18fluoride-fluorodeoxyglucose PET/CT and evaluated retrospectively. Ktrans, Kep, Ve, and initial area under the curve (iAUC) parameters from DCE-MRI, ADCmax, ADCmean, and ADCmin parameters from DWI, and maximum standardized uptake value (SUVmax), SUVmean, metabolic tumor volume (MTV), and total lesion glycolysis (TLG) parameters from PET were obtained. Spearman's correlation coefficient was used to analyze associations between these parameters. In addition, these parameters were grouped according to tumor grade and T and N stages, and the difference between the groups was evaluated using the Mann-Whitney U test. Results Correlations at varying degrees were observed in the parameters investigated. ADCmean moderately correlated with Ve (p=0.035; r=0.566). Ktrans inversely correlated with SUVmax (p=0.017; r=-0.626). iAUC inversely correlated with SUVmax, SUVmean, TLG, and MTV (p<0.05, r≤-0.700). MTV (40% threshold) was significantly higher in T4 tumors than in T1-3 tumors (p=0.020). No significant difference was found in the grouping made according to tumor grade and N stage in terms of these parameters. Conclusion Tumor cellularity, vascular permeability, and glucose metabolism had significant correlations at different degrees. Furthermore, MTV may be useful in predicting T4 tumors.
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Affiliation(s)
- Hande Melike Bülbül
- Recep Tayyip Erdoğan Training and Research Hospital, Clinic of Radiology, Rize, Turkey
| | - Ogün Bülbül
- Recep Tayyip Erdoğan Training and Research Hospital, Clinic of Nuclear Medicine, Rize, Turkey
| | - Sülen Sarıoğlu
- Dokuz Eylül University Faculty of Medicine, Department of Medical Pathology, İzmir, Turkey
| | - Özhan Özdoğan
- Dokuz Eylül University Faculty of Medicine, Department of Nuclear Medicine, İzmir, Turkey
| | - Ersoy Doğan
- Dokuz Eylül University Faculty of Medicine, Department of Otorhinolaryngology, İzmir, Turkey
| | - Nuri Karabay
- Dokuz Eylül University Faculty of Medicine, Department of Radiology, İzmir, Turkey
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15
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Clancy K, Dadashzadeh ER, Handzel R, Rieser C, Moses JB, Rosenblum L, Wu S. Machine learning for the prediction of pathologic pneumatosis intestinalis. Surgery 2021; 170:797-805. [PMID: 33926706 PMCID: PMC8405549 DOI: 10.1016/j.surg.2021.03.049] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Revised: 03/19/2021] [Accepted: 03/22/2021] [Indexed: 11/18/2022]
Abstract
BACKGROUND The radiographic finding of pneumatosis intestinalis can indicate a spectrum of underlying processes ranging from a benign finding to a life-threatening condition. Although radiographic pneumatosis intestinalis is relatively common, there is no validated clinical tool to guide surgical management. METHODS Using a retrospective cohort of 300 pneumatosis intestinalis cases from a single institution, we developed 3 machine learning models for 2 clinical tasks: (1) the distinction of benign from pathologic pneumatosis intestinalis cases and (2) the determination of patients who would benefit from an operation. The 3 models are (1) an imaging model based on radiomic features extracted from computed tomography scans, (2) a clinical model based on clinical variables, and (3) a combination model using both the imaging and clinical variables. RESULTS The combination model achieves an area under the curve of 0.91 (confidence interval: 0.87-0.94) for task I and an area under the curve of 0.84 (confidence interval: 0.79-0.88) for task II. The combination model significantly (P < .05) outperforms the imaging model and the clinical model for both tasks. The imaging model achieves an area under the curve of 0.72 (confidence interval: 0.57-0.87) for task I and 0.68 (confidence interval: 0.61-0.74) for task II. The clinical model achieves an area under the curve of 0.87 (confidence interval: 0.83-0.91) for task I and 0.76 (confidence interval: 0.70-0.81) for task II. CONCLUSION This study suggests that combined radiographic and clinical features can identify pathologic pneumatosis intestinalis and aid in patient selection for surgery. This tool may better inform the surgical decision-making process for patients with pneumatosis intestinalis.
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Affiliation(s)
- Kadie Clancy
- Department of Computer Science, University of Pittsburgh, PA
| | | | - Robert Handzel
- Department of Surgery, University of Pittsburgh Medical Center, PA
| | - Caroline Rieser
- Department of Surgery, University of Pittsburgh Medical Center, PA
| | - J B Moses
- Department of Surgery, University of Pittsburgh Medical Center, PA
| | - Lauren Rosenblum
- Department of Surgery, University of Pittsburgh Medical Center, PA
| | - Shandong Wu
- Departments of Radiology, Biomedical Informatics, and Bioengineering, University of Pittsburgh, PA.
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16
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Lu H, Wu Y, Liu X, Huang H, Jiang H, Zhu C, Man Y, Liu P, Li X, Chen Z, Long X, Pang Q, Deng S, Gu J. The Role of Dynamic Contrast-Enhanced Magnetic Resonance Imaging in Predicting Treatment Response for Cervical Cancer Treated with Concurrent Chemoradiotherapy. Cancer Manag Res 2021; 13:6065-6078. [PMID: 34377025 PMCID: PMC8349537 DOI: 10.2147/cmar.s314289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Accepted: 07/26/2021] [Indexed: 11/23/2022] Open
Abstract
Purpose To evaluate the role of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in predicting early treatment response. Materials and Methods Patients with locally advanced cervical cancer (LACC) treated with concurrent chemoradiotherapy (CCRT) were enrolled. Pelvic DCE-MRI scans were performed before RT (pre-RT), in the middle of RT (mid-RT), and at the end of RT (post-RT), separately. Parameters (ie, Ktrans, Kep, and Ve) were measured. Pre-, mid-, and post-RT Ktrans were denoted as Ktrans-preTx, Ktrans-midTx, and Ktrans-postTx, respectively. And the same denoting rule also went for Kep and Ve. Difference for the same parameter such as Ktrans measured between two consecutive time points was calculated as second Ktrans value minus first Ktrans value. The differences in Ktrans between pre-RT and post-RT, between pre-RT and mid-RT, and between mid-RT and post-RT were denoted as ΔKtrans-post-preTx, ΔKtrans-mid-preTx, and ΔKtrans-post-midTx, respectively, and the same denoting rule was also applied to Kep and Ve. Results A total of 57 patients were enrolled. After the treatment, 31 patients had complete response (CR group). The remaining 26 patients had partial response (NCR group). Significant differences were found in Ktrans-postTx, Kep-postTx, Ve-midTx, ΔKtrans-post-preTx, ΔKtrans-post-midTx, ΔKep-post-preTx, ΔKep-mid-preTx and ΔKep-post-midTx between the two groups. Receiver operating characteristic (ROC) analysis for their performances in predicting treatment response showed an area under curve (AUC) of 0.656-0.849, sensitivity of 61.3-93.5%, specificity of 46.1-73.1%, and maximal Youden Index of 36.5-66.6. Among those parameters, Kep-postTx was the best, and its AUC, sensitivity, specificity, maximal Youden Index, and cutoff value were 0.849, 87.1%, 73.1%, 60.2, and 0.341, respectively. These combined parameters showed an AUC of 0.952, with sensitivity of 87.1%, specificity of 96.1%, and maximal Youden Index of 83.2. Conclusion DCE-MRI parameters can predict early treatment outcome. Among those parameters, Kep-postTx is the best predictor. The combination of multi-parameters can increase the predictive potency.
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Affiliation(s)
- Heming Lu
- Department of Radiation Oncology, People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, 530021, People's Republic of China
| | - Yuying Wu
- Department of Gynecology, People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, 530021, People's Republic of China
| | - Xu Liu
- Department of Radiation Oncology, People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, 530021, People's Republic of China
| | - Huixian Huang
- Department of Radiation Oncology, People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, 530021, People's Republic of China
| | - Hailan Jiang
- Department of Radiation Oncology, People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, 530021, People's Republic of China
| | - Chaohua Zhu
- Department of Radiation Oncology, People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, 530021, People's Republic of China
| | - Yuping Man
- Department of Radiology, People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, 530021, People's Republic of China
| | - Pei Liu
- Department of Oncology, Youjiang Medical University for Nationalities, Baise, 533000, People's Republic of China
| | - Xianglong Li
- Department of Radiation Oncology, People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, 530021, People's Republic of China
| | - Zhaohong Chen
- Department of Radiation Oncology, People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, 530021, People's Republic of China
| | - Xianfeng Long
- Department of Radiation Oncology, People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, 530021, People's Republic of China
| | - Qiang Pang
- Department of Radiation Oncology, People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, 530021, People's Republic of China
| | - Shan Deng
- Department of Radiation Oncology, People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, 530021, People's Republic of China
| | - Junzhao Gu
- Department of Radiation Oncology, People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, 530021, People's Republic of China
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Paudyal R, Grkovski M, Oh JH, Schöder H, Nunez DA, Hatzoglou V, Deasy JO, Humm JL, Lee NY, Shukla-Dave A. Application of Community Detection Algorithm to Investigate the Correlation between Imaging Biomarkers of Tumor Metabolism, Hypoxia, Cellularity, and Perfusion for Precision Radiotherapy in Head and Neck Squamous Cell Carcinomas. Cancers (Basel) 2021; 13:3908. [PMID: 34359810 PMCID: PMC8345739 DOI: 10.3390/cancers13153908] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2021] [Revised: 07/26/2021] [Accepted: 07/30/2021] [Indexed: 11/17/2022] Open
Abstract
The present study aimed to investigate the correlation at pre-treatment (TX) between quantitative metrics derived from multimodality imaging (MMI), including 18F-FDG-PET/CT, 18F-FMISO-PET/CT, DW- and DCE-MRI, using a community detection algorithm (CDA) in head and neck squamous cell carcinoma (HNSCC) patients. Twenty-three HNSCC patients with 27 metastatic lymph nodes underwent a total of 69 MMI exams at pre-TX. Correlations among quantitative metrics derived from FDG-PET/CT (SUL), FMSIO-PET/CT (K1, k3, TBR, and DV), DW-MRI (ADC, IVIM [D, D*, and f]), and FXR DCE-MRI [Ktrans, ve, and τi]) were investigated using the CDA based on a "spin-glass model" coupled with the Spearman's rank, ρ, analysis. Mean MRI T2 weighted tumor volumes and SULmean values were moderately positively correlated (ρ = 0.48, p = 0.01). ADC and D exhibited a moderate negative correlation with SULmean (ρ ≤ -0.42, p < 0.03 for both). K1 and Ktrans were positively correlated (ρ = 0.48, p = 0.01). In contrast, Ktrans and k3max were negatively correlated (ρ = -0.41, p = 0.03). CDA revealed four communities for 16 metrics interconnected with 33 edges in the network. DV, Ktrans, and K1 had 8, 7, and 6 edges in the network, respectively. After validation in a larger population, the CDA approach may aid in identifying useful biomarkers for developing individual patient care in HNSCC.
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Affiliation(s)
- Ramesh Paudyal
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (R.P.); (M.G.); (J.H.O.); (D.A.N.); (J.O.D.); (J.L.H.)
| | - Milan Grkovski
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (R.P.); (M.G.); (J.H.O.); (D.A.N.); (J.O.D.); (J.L.H.)
| | - Jung Hun Oh
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (R.P.); (M.G.); (J.H.O.); (D.A.N.); (J.O.D.); (J.L.H.)
| | - Heiko Schöder
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (H.S.); (V.H.)
| | - David Aramburu Nunez
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (R.P.); (M.G.); (J.H.O.); (D.A.N.); (J.O.D.); (J.L.H.)
| | - Vaios Hatzoglou
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (H.S.); (V.H.)
| | - Joseph O. Deasy
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (R.P.); (M.G.); (J.H.O.); (D.A.N.); (J.O.D.); (J.L.H.)
| | - John L. Humm
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (R.P.); (M.G.); (J.H.O.); (D.A.N.); (J.O.D.); (J.L.H.)
| | - Nancy Y. Lee
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA;
| | - Amita Shukla-Dave
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (R.P.); (M.G.); (J.H.O.); (D.A.N.); (J.O.D.); (J.L.H.)
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (H.S.); (V.H.)
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18
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LoCastro E, Paudyal R, Mazaheri Y, Hatzoglou V, Oh JH, Lu Y, Konar AS, Vom Eigen K, Ho A, Ewing JR, Lee N, Deasy JO, Shukla-Dave A. Computational Modeling of Interstitial Fluid Pressure and Velocity in Head and Neck Cancer Based on Dynamic Contrast-Enhanced Magnetic Resonance Imaging: Feasibility Analysis. ACTA ACUST UNITED AC 2021; 6:129-138. [PMID: 32548289 PMCID: PMC7289251 DOI: 10.18383/j.tom.2020.00005] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
We developed and tested the feasibility of computational fluid modeling (CFM) based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for quantitative estimation of interstitial fluid pressure (IFP) and velocity (IFV) in patients with head and neck (HN) cancer with locoregional lymph node metastases. Twenty-two patients with HN cancer, with 38 lymph nodes, underwent pretreatment standard MRI, including DCE-MRI, on a 3-Tesla scanner. CFM simulation was performed with the finite element method in COMSOL Multiphysics software. The model consisted of a partial differential equation (PDE) module to generate 3D parametric IFP and IFV maps, using the Darcy equation and Ktrans values (min−1, estimated from the extended Tofts model) to reflect fluid influx into tissue from the capillary microvasculature. The Spearman correlation (ρ) was calculated between total tumor volumes and CFM estimates of mean tumor IFP and IFV. CFM-estimated tumor IFP and IFV mean ± standard deviation for the neck nodal metastases were 1.73 ± 0.39 (kPa) and 1.82 ± 0.9 × (10−7 m/s), respectively. High IFP estimates corresponds to very low IFV throughout the tumor core, but IFV rises rapidly near the tumor boundary where the drop in IFP is precipitous. A significant correlation was found between pretreatment total tumor volume and CFM estimates of mean tumor IFP (ρ = 0.50, P = 0.004). Future studies can validate these initial findings in larger patients with HN cancer cohorts using CFM of the tumor in concert with DCE characterization, which holds promise in radiation oncology and drug-therapy clinical trials.
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Affiliation(s)
| | | | - Yousef Mazaheri
- Departments of Medical Physics and.,Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Vaios Hatzoglou
- Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | | | - Yonggang Lu
- Department of Radiology, Medical College of Wisconsin, Milwaukee, WI
| | | | | | - Alan Ho
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY
| | - James R Ewing
- Departments of Neurology and.,Neurosurgery, Henry Ford Hospital, Detroit, MI; and
| | - Nancy Lee
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY
| | | | - Amita Shukla-Dave
- Departments of Medical Physics and.,Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
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19
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van Dijk LV, Fuller CD. Artificial Intelligence and Radiomics in Head and Neck Cancer Care: Opportunities, Mechanics, and Challenges. Am Soc Clin Oncol Educ Book 2021; 41:1-11. [PMID: 33929877 DOI: 10.1200/edbk_320951] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
The advent of large-scale high-performance computing has allowed the development of machine-learning techniques in oncologic applications. Among these, there has been substantial growth in radiomics (machine-learning texture analysis of images) and artificial intelligence (which uses deep-learning techniques for "learning algorithms"); however, clinical implementation has yet to be realized at scale. To improve implementation, opportunities, mechanics, and challenges, models of imaging-enabled artificial intelligence approaches need to be understood by clinicians who make the treatment decisions. This article aims to convey the basic conceptual premises of radiomics and artificial intelligence using head and neck cancer as a use case. This educational overview focuses on approaches for head and neck oncology imaging, detailing current research efforts and challenges to implementation.
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Affiliation(s)
- Lisanne V van Dijk
- Department of Radiation Oncology, MD Anderson Cancer Center, Houston, TX.,Department of Radiation Oncology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Clifton D Fuller
- Department of Radiation Oncology, MD Anderson Cancer Center, Houston, TX
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20
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MRI Dynamic Contrast Imaging of Oral Cavity and Oropharyngeal Tumors. Top Magn Reson Imaging 2021; 30:97-104. [PMID: 33828061 DOI: 10.1097/rmr.0000000000000283] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
ABSTRACT In the past decade, dynamic contrast-enhanced magnetic resonance imaging has had an increasing role in assessing the microvascular characteristics of various tumors, including head and neck cancer. Dynamic contrast-enhanced magnetic resonance imaging allows noninvasive assessment of permeability and blood flow, both important parametric features of tumor hypoxia, which is in turn a marker for treatment resistance for head and neck cancer.In this article we will provide a comprehensive review technique in evaluating tumor proliferation and application of its parameters in differentiating between various tumor types of the oral cavity and how its parameters can correlate between epidermal growth factor receptor and human papillomavirus which can have an implication in patient's overall survival rates.We will also review how the parameters of this method can predict local tumor control after treatment and compare its efficacy with other imaging modalities. Lastly, we will review how its parameters can be used prospectively to identify early complications from treatment.
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21
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Smits HJG, Assili S, Kauw F, Philippens MEP, de Bree R, Dankbaar JW. Prognostic imaging variables for recurrent laryngeal and hypopharyngeal carcinoma treated with primary chemoradiotherapy: A systematic review and meta-analysis. Head Neck 2021; 43:2202-2215. [PMID: 33797818 PMCID: PMC8252607 DOI: 10.1002/hed.26698] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 02/09/2021] [Accepted: 03/16/2021] [Indexed: 01/10/2023] Open
Abstract
Background In this systematic review, we aim to identify prognostic imaging variables of recurrent laryngeal or hypopharyngeal carcinoma after chemoradiotherapy. Methods A systematic search was performed in PubMed and EMBASE (1990–2020). The crude data and effect estimates were extracted for each imaging variable. The level of evidence of each variable was assessed and pooled risk ratios (RRs) were calculated. Results Twenty‐two articles were included in this review, 17 on computed tomography (CT) and 5 on magnetic resonance imaging (MRI) variables. We found strong evidence for the prognostic value of tumor volume at various cut‐off points (pooled RRs ranging from 2.09 to 3.03). Anterior commissure involvement (pooled RR 2.19), posterior commissure involvement (pooled RR 2.44), subglottic extension (pooled RR 2.25), and arytenoid cartilage extension (pooled RR 2.10) were also strong prognostic factors. Conclusion Pretreatment tumor volume and involvement of several subsites are prognostic factors for recurrent laryngeal or hypopharyngeal carcinoma after chemoradiotherapy.
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Affiliation(s)
- Hilde J G Smits
- Department of Radiology, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands
| | - Sanam Assili
- Department of Radiology, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands
| | - Frans Kauw
- Department of Radiology, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands
| | - Marielle E P Philippens
- Department of Radiology, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands
| | - Remco de Bree
- Department of Head and Neck Surgical Oncology, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands
| | - Jan W Dankbaar
- Department of Radiology, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands
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Paudyal R, Chen L, Oh JH, Zakeri K, Hatzoglou V, Tsai CJ, Lee N, Shukla-Dave A. Nongaussian Intravoxel Incoherent Motion Diffusion Weighted and Fast Exchange Regime Dynamic Contrast-Enhanced-MRI of Nasopharyngeal Carcinoma: Preliminary Study for Predicting Locoregional Failure. Cancers (Basel) 2021; 13:1128. [PMID: 33800762 PMCID: PMC7961986 DOI: 10.3390/cancers13051128] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Revised: 03/02/2021] [Accepted: 03/02/2021] [Indexed: 12/28/2022] Open
Abstract
The aim of the present study was to identify whether the quantitative metrics from pre-treatment (TX) non-Gaussian intravoxel incoherent motion (NGIVIM) diffusion weighted (DW-) and fast exchange regime (FXR) dynamic contrast enhanced (DCE)-MRI can predict patients with locoregional failure (LRF) in nasopharyngeal carcinoma (NPC). Twenty-nine NPC patients underwent pre-TX DW- and DCE-MRI on a 3T MR scanner. DW imaging data from primary tumors were fitted to monoexponential (ADC) and NGIVIM (D, D*, f, and K) models. The metrics Ktrans, ve, and τi were estimated using the FXR model. Cumulative incidence (CI) analysis and Fine-Gray (FG) modeling were performed considering death as a competing risk. Mean ve values were significantly different between patients with and without LRF (p = 0.03). Mean f values showed a trend towards the difference between the groups (p = 0.08). Histograms exhibited inter primary tumor heterogeneity. The CI curves showed significant differences for the dichotomized cutoff value of ADC ≤ 0.68 × 10-3 (mm2/s), D ≤ 0.74 × 10-3 (mm2/s), and f ≤ 0.18 (p < 0.05). τi ≤ 0.89 (s) cutoff value showed borderline significance (p = 0.098). FG's modeling showed a significant difference for the K cutoff value of ≤0.86 (p = 0.034). Results suggest that the role of pre-TX NGIVIM DW- and FXR DCE-MRI-derived metrics for predicting LRF in NPC than alone.
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Affiliation(s)
- Ramesh Paudyal
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (R.P.); (J.H.O.)
| | - Linda Chen
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (L.C.); (K.Z.); (C.J.T.); (N.L.)
| | - Jung Hun Oh
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (R.P.); (J.H.O.)
| | - Kaveh Zakeri
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (L.C.); (K.Z.); (C.J.T.); (N.L.)
| | - Vaios Hatzoglou
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA;
| | - C. Jillian Tsai
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (L.C.); (K.Z.); (C.J.T.); (N.L.)
| | - Nancy Lee
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (L.C.); (K.Z.); (C.J.T.); (N.L.)
| | - Amita Shukla-Dave
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (R.P.); (J.H.O.)
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA;
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Johnson M, Sreela LS, Mathew P, Prasad TS. Actual applications of magnetic resonance imaging in dentomaxillofacial region. Oral Radiol 2021; 38:17-28. [PMID: 33635492 DOI: 10.1007/s11282-021-00521-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2020] [Accepted: 02/13/2021] [Indexed: 11/24/2022]
Abstract
Magnetic resonance imaging (MRI) is a versatile imaging modality utilized in various medical fields. Specifically used for evaluation of soft tissues, with non-ionizing radiation and multiplanar sections that has provided great guidance to diagnosis. Nowadays, use of MRI in dental practice is becoming more pervasive, especially for the evaluation of head-and-neck cancer, detection of salivary gland lesions, lymphadenopathy, and temporomandibular joint disorders. Understanding the basic principles, its recent advances, and multiple applications in dentomaxillofacial region helps significantly in the diagnostic decision making. In this article, the principle of MRI and its recent advances are reviewed, with further discussion on the appearance of various maxillofacial pathosis.
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Affiliation(s)
- Migi Johnson
- Department of Oral Medicine and Radiology, Government Dental College Kottayam, Gandhinagar, Kottayam, 686008, Kerala, India.
| | - L S Sreela
- Department of Oral Medicine and Radiology, Government Dental College Kottayam, Gandhinagar, Kottayam, 686008, Kerala, India
| | - Philips Mathew
- Department of Oral Medicine and Radiology, Government Dental College Kottayam, Gandhinagar, Kottayam, 686008, Kerala, India
| | - Twinkle S Prasad
- Department of Oral Medicine and Radiology, Government Dental College Kottayam, Gandhinagar, Kottayam, 686008, Kerala, India
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24
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Liu B, Hu L, Wang L, Xing D, Peng L, Chen P, Zeng F, Liu WV, Liu H, Zha Y. Evaluation of microvascular permeability of skeletal muscle and texture analysis based on DCE-MRI in alloxan-induced diabetic rabbits. Eur Radiol 2021; 31:5669-5679. [PMID: 33547478 DOI: 10.1007/s00330-021-07705-3] [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: 02/20/2020] [Revised: 11/24/2020] [Accepted: 01/21/2021] [Indexed: 02/08/2023]
Abstract
OBJECTIVES To estimate the microvascular permeability and perfusion of skeletal muscle by using quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and explore the feasibility of using texture analysis (TA) to evaluate subtle structural changes of diabetic muscles. METHODS Twenty-four rabbits were randomly divided into diabetic (n = 14) and control (n = 10) groups, and underwent axial DCE-MRI of the multifidus muscle (0, 4, 8, 12, and 16 weeks after alloxan injection). The pharmacokinetic model was used to calculate the permeability parameters; texture parameters were extracted from volume transfer constant (Ktrans) map. The two-sample t test/Mann-Whitney U test, repeated measures analysis of variance/Friedman test, and Pearson correlations were used for data analysis. RESULTS In the diabetic group, Ktrans and rate constant (Kep) increased significantly at week 8 and then showed a decreasing trend. Extravascular extracellular space volume fraction (Ve) increased and plasma volume fraction (Vp) decreased significantly from the 8th week. Skewness began to decrease at the 4th week. Median Ktrans and entropy increased significantly, while inverse difference moment decreased from the 8th week. Energy decreased while contrast increased only at week 8. Muscle fibre cross-sectional area was negatively correlated with Ve. The capillary-to-fibre ratio was positively correlated with Vp (p < 0.05, all). CONCLUSIONS Quantitative DCE-MRI can be used to evaluate microvascular permeability and perfusion in diabetic skeletal muscle at an early stage; TA based on Ktrans map can identify microarchitectural modifications in diabetic muscles. KEY POINTS • Four quantitative parameters of DCE-MRI can be used to evaluate microvascular permeability and perfusion of skeletal muscle in diabetic models at early stages. • Texture analysis based on Ktrans map can identify subtle structural changes in diabetic muscles.
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Affiliation(s)
- Baiyu Liu
- Department of Radiology, Renmin Hospital of Wuhan University, Wuhan, 430060, China
| | - Lei Hu
- Department of Radiology, Renmin Hospital of Wuhan University, Wuhan, 430060, China
| | - Li Wang
- Department of Radiology, Renmin Hospital of Wuhan University, Wuhan, 430060, China
| | - Dong Xing
- Department of Radiology, Renmin Hospital of Wuhan University, Wuhan, 430060, China
| | - Lin Peng
- Department of Radiology, Renmin Hospital of Wuhan University, Wuhan, 430060, China
| | - Pianpian Chen
- Department of Radiology, Renmin Hospital of Wuhan University, Wuhan, 430060, China
| | - Feifei Zeng
- Department of Radiology, Renmin Hospital of Wuhan University, Wuhan, 430060, China
| | | | - Huan Liu
- GE Healthcare, Shanghai, 201203, China
| | - Yunfei Zha
- Department of Radiology, Renmin Hospital of Wuhan University, Wuhan, 430060, China.
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Subramaniam N, Poptani H, Schache A, Bhat V, Iyer S, Sunil HV, Chandrasekhar N, Pillai V, Chaturvedi P, Krishna S, Krishnamurthy A, Kekatpure V, Kuriakose M, Iyer NG, Thakkar A, Kantharia R, Sonkar A, Shetty V, Rangappa V, Kolur T, Vidhyadharan S, Murthy S, Kudpaje A, Srinivasalu V, Mahajan A. Imaging advances in oral cavity cancer and perspectives from a population in need: Consensus from the UK-India oral cancer imaging group. JOURNAL OF HEAD & NECK PHYSICIANS AND SURGEONS 2021. [DOI: 10.4103/jhnps.jhnps_10_21] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
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Chen J, Hagiwara M, Givi B, Schmidt B, Liu C, Chen Q, Logan J, Mikheev A, Rusinek H, Kim SG. Assessment of metastatic lymph nodes in head and neck squamous cell carcinomas using simultaneous 18F-FDG-PET and MRI. Sci Rep 2020; 10:20764. [PMID: 33247166 PMCID: PMC7695736 DOI: 10.1038/s41598-020-77740-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Accepted: 11/02/2020] [Indexed: 11/09/2022] Open
Abstract
In this study, we investigate the feasibility of using dynamic contrast enhanced magnetic resonance imaging (DCE-MRI), diffusion weighted imaging (DWI), and dynamic positron emission tomography (PET) for detection of metastatic lymph nodes in head and neck squamous cell carcinoma (HNSCC) cases. Twenty HNSCC patients scheduled for lymph node dissection underwent DCE-MRI, dynamic PET, and DWI using a PET-MR scanner within one week prior to their planned surgery. During surgery, resected nodes were labeled to identify their nodal levels and sent for routine clinical pathology evaluation. Quantitative parameters of metastatic and normal nodes were calculated from DCE-MRI (ve, vp, PS, Fp, Ktrans), DWI (ADC) and PET (Ki, K1, k2, k3) to assess if an individual or a combination of parameters can classify normal and metastatic lymph nodes accurately. There were 38 normal and 11 metastatic nodes covered by all three imaging methods and confirmed by pathology. 34% of all normal nodes had volumes greater than or equal to the smallest metastatic node while 4 normal nodes had SUV > 4.5. Among the MRI parameters, the median vp, Fp, PS, and Ktrans values of the metastatic lymph nodes were significantly lower (p = <0.05) than those of normal nodes. ve and ADC did not show any statistical significance. For the dynamic PET parameters, the metastatic nodes had significantly higher k3 (p value = 8.8 × 10-8) and Ki (p value = 5.3 × 10-8) than normal nodes. K1 and k2 did not show any statistically significant difference. Ki had the best separation with accuracy = 0.96 (sensitivity = 1, specificity = 0.95) using a cutoff of Ki = 5.3 × 10-3 mL/cm3/min, while k3 and volume had accuracy of 0.94 (sensitivity = 0.82, specificity = 0.97) and 0.90 (sensitivity = 0.64, specificity = 0.97) respectively. 100% accuracy can be achieved using a multivariate logistic regression model of MRI parameters after thresholding the data with Ki < 5.3 × 10-3 mL/cm3/min. The results of this preliminary study suggest that quantitative MRI may provide additional value in distinguishing metastatic nodes, particularly among small nodes, when used together with FDG-PET.
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Affiliation(s)
- Jenny Chen
- grid.137628.90000 0004 1936 8753Department of Radiology, Center for Biomedical Imaging (CBI), Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, 660 First Avenue, New York, NY 10016 USA
| | - Mari Hagiwara
- grid.137628.90000 0004 1936 8753Department of Radiology, Center for Biomedical Imaging (CBI), Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, 660 First Avenue, New York, NY 10016 USA
| | - Babak Givi
- grid.137628.90000 0004 1936 8753Department of Otolaryngology-Head and Neck Surgery, New York University School of Medicine, New York, NY USA
| | - Brian Schmidt
- grid.137628.90000 0004 1936 8753Department of Oral and Maxillofacial Surgery, Bluestone Center for Clinical Research, New York University College of Dentistry, New York, NY USA
| | - Cheng Liu
- grid.137628.90000 0004 1936 8753Department of Pathology, New York University School of Medicine, New York, NY USA
| | - Qi Chen
- grid.137628.90000 0004 1936 8753Department of Radiology, Center for Biomedical Imaging (CBI), Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, 660 First Avenue, New York, NY 10016 USA
| | - Jean Logan
- grid.137628.90000 0004 1936 8753Department of Radiology, Center for Biomedical Imaging (CBI), Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, 660 First Avenue, New York, NY 10016 USA
| | - Artem Mikheev
- grid.137628.90000 0004 1936 8753Department of Radiology, Center for Biomedical Imaging (CBI), Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, 660 First Avenue, New York, NY 10016 USA
| | - Henry Rusinek
- grid.137628.90000 0004 1936 8753Department of Radiology, Center for Biomedical Imaging (CBI), Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, 660 First Avenue, New York, NY 10016 USA
| | - Sungheon Gene Kim
- Department of Radiology, Center for Biomedical Imaging (CBI), Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, 660 First Avenue, New York, NY, 10016, USA. .,Department of Radiology, Weill Cornell Medical College, New York, NY, USA.
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27
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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: 1.5] [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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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: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2020] [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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Xu L, Ge X, Sun N, Liu X. Dynamic contrast-enhanced MRI histogram parameters predict progression-free survival in patients with advanced esophageal squamous carcinoma receiving concurrent chemoradiotherapy. Acta Radiol 2020; 61:1316-1325. [PMID: 32053003 DOI: 10.1177/0284185120903139] [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] [Indexed: 01/21/2023]
Abstract
BACKGROUND There is increased interest in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for predicting the outcomes of patients with advanced esophageal cancer. PURPOSE To explore whether DCE-MRI histogram parameters can predict 12-month progression-free survival (PFS) in patients with advanced esophageal squamous carcinoma receiving concurrent chemoradiation therapy (CRT). MATERIAL AND METHODS This retrospective study enrolled 134 patients with advanced esophageal squamous carcinoma who were receiving CRT. The pre-CRT DCE-MRI histogram parameters (median, mean, SD, skewness, kurtosis, and 10th and 90th percentiles) of Ktrans, Kep, and Ve were collected. PFS analyses were performed using the Kaplan-Meier method and log-rank tests to compute the survival curves. The significant prognostic predictors among the data characteristics and DCE-MRI parameters were determined using multivariate Cox proportional hazards regression analyses. RESULTS There were 65 good responders (PFS ≥ 12 months) and 69 poor responders (PFS < 12 months). The median and mean values of Ktrans were higher, and the kurtosis value of Ktrans was lower in good responders. The median, mean, and 10th and 90th percentile values of Ktrans were higher, and the kurtosis values of Ktrans and Ve were lower in good responders. The PFS of patients aged ≥60 years, a CR effect, or a 10th percentile value of Ktrans ≥0.13 was increased (P < 0.001, <0.001, and 0.014, respectively). CONCLUSION DCE-MRI histogram parameters can be used to evaluate the response to CRT in patients with advanced esophageal squamous carcinoma. The 10th percentile value of Ktrans has significant prognostic value for 12-month PFS.
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Affiliation(s)
- Lulu Xu
- Department of Radiology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, PR China
| | - Xiaolin Ge
- Department of Radiotherapy, the First Affiliated Hospital of Nanjing Medical University, Nanjing, PR China
| | - Nana Sun
- Department of Radiology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, PR China
| | - Xisheng Liu
- Department of Radiology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, PR China
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30
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Li HM, Tang W, Feng F, Zhao SH, Gu WY, Zhang GF, Qiang JW. Whole solid tumor volume histogram parameters for predicting the recurrence in patients with epithelial ovarian carcinoma: a feasibility study on quantitative DCE-MRI. Acta Radiol 2020; 61:1266-1276. [PMID: 31955611 DOI: 10.1177/0284185119898654] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
BACKGROUND Preoperative prediction of the recurrence of epithelial ovarian carcinoma (EOC) can guide the clinical treatment and improve the prognosis. However, there are still no reliable predictive biomarkers. PURPOSE To evaluate whether whole solid tumor volume histogram parameters measured from quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can predict the recurrence in patients with EOC. MATERIAL AND METHODS We followed up 56 patients with surgical and histopathologically diagnosed EOC who underwent quantitative DCE-MRI scans. The differences of the histogram parameters between patients with and without recurrence were compared. Mann-Whitney U test, Pearson's Chi-squared test, or Fisher's exact test, and receiver operating characteristic (ROC) curves were used for statistical analysis. RESULTS All histogram parameters of Ktrans, kep, and ve were not significantly different between EOC patients with and without recurrence (P>0.05). For 30 patients with high-grade serous ovarian carcinoma (HGSOC), the histogram parameters of Ktrans (mean and 5th, 10th, 25th, 50th, 75th percentiles) and kep (mean and 50th percentile) in 12 patients with recurrence were significantly lower than those in 18 patients without recurrence (all P<0.05). ROC curves showed that the 5th percentile of Ktrans had the largest area under the curve (AUC) of 0.792 for predicting the recurrence in patients with HGSOC. When the threshold value was ≤0.0263/min, the sensitivity, specificity, and accuracy were 100%, 66.7%, and 80%, respectively. CONCLUSION Instead of predicting the recurrence of EOC, whole solid tumor volume quantitative DCE-MRI histogram parameters could predict the recurrence of HGSOC and may be potential biomarkers for the prediction of HGSOC recurrence.
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Affiliation(s)
- Hai Ming Li
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, PR China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, PR China
- Department of Radiology, Jinshan Hospital, Fudan University, Shanghai, PR China
| | - Wei Tang
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, PR China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, PR China
| | - Feng Feng
- Department of Radiology, Nantong Cancer Hospital, Nantong University, Nantong, Jiangsu, PR China
| | - Shu Hui Zhao
- Department of Radiology, Xinhua Hospital, Shanghai Jiao Tong University, Shanghai, PR China
| | - Wei Yong Gu
- Department of Pathology, Obstetrics & Gynecology Hospital, Fudan University, Shanghai, PR China
| | - Guo Fu Zhang
- Department of Radiology, Obstetrics & Gynecology Hospital, Fudan University, Shanghai, PR China
| | - Jin Wei Qiang
- Department of Radiology, Jinshan Hospital, Fudan University, Shanghai, PR China
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Chawla S, Kim SG, Loevner LA, Wang S, Mohan S, Lin A, Poptani H. Prediction of distant metastases in patients with squamous cell carcinoma of head and neck using DWI and DCE-MRI. Head Neck 2020; 42:3295-3306. [PMID: 32737951 DOI: 10.1002/hed.26386] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2019] [Revised: 05/30/2020] [Accepted: 06/26/2020] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND The primary purpose was to evaluate the prognostic potential of diffusion imaging (DWI) and dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) in predicting distant metastases in squamous cell carcinoma of head and neck (HNSCC) patients. The secondary aim was to examine differences in DWI and DCE-MRI-derived parameters on the basis of human papilloma virus (HPV) status, differentiation grade, and nodal stage of HNSCC. METHODS Fifty-six patients underwent pretreatment DWI and DCE-MRI. Patients were divided into groups who subsequently did (n = 12) or did not develop distant metastases (n = 44). Median values of apparent diffusion coefficient (ADC), volume transfer constant (Ktrans ), and mean intracellular water-lifetime (τi ) and volume were computed from metastatic lymph nodes and were compared between two groups. Prognostic utility of HPV status, differentiation grading, and nodal staging was also evaluated both in isolation or in combination with MRI parameters in distinguishing patients with and without distant metastases. Additionally, MRI parameters were compared between two groups based on dichotomous HPV status, differentiation grade, and nodal stage. RESULTS Lower but not significantly different Ktrans (0.51 ± 0.15 minute-1 vs 0.60 ± 0.05 minute-1 ) and not significantly different τi (0.13 ± 0.03 second vs 0.19 ± 0.02 second) were observed in patients who developed distant metastases than those who did not. Additionally, no significant differences in ADC or volume were found. τi, was the best parameter in discriminating two groups with moderate sensitivity (67%) and specificity (61.4%). Multivariate logistic regression analyses did not improve the overall prognostic performance for combination of all variables. A trend toward higher τi was observed in HPV-positive patients than those with HPV-negative patients. Also, a trend toward higher Ktrans was observed in poorly differentiated HNSCCs than those with moderately differentiated HNSCCs. CONCLUSION Pretreatment DCE-MRI may be useful in predicting distant metastases in HNSCC.
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Affiliation(s)
- Sanjeev Chawla
- Department of Radiology, Perelman School of Medicine, the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Sungheon G Kim
- Department of Radiology, Perelman School of Medicine, the University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Radiology, New York University Langone Medical Center, New York, New York, USA
| | - Laurie A Loevner
- Department of Radiology, Perelman School of Medicine, the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Sumei Wang
- Department of Radiology, Perelman School of Medicine, the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Suyash Mohan
- Department of Radiology, Perelman School of Medicine, the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Alexander Lin
- Department of Radiation Oncology, Perelman School of Medicine, the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Harish Poptani
- Department of Radiology, Perelman School of Medicine, the University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Cellular and Molecular Physiology, University of Liverpool, Liverpool, UK
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Simplified perfusion fraction from diffusion-weighted imaging in preoperative prediction of IDH1 mutation in WHO grade II-III gliomas: comparison with dynamic contrast-enhanced and intravoxel incoherent motion MRI. Radiol Oncol 2020; 54:301-310. [PMID: 32559177 PMCID: PMC7409598 DOI: 10.2478/raon-2020-0037] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2020] [Accepted: 05/13/2020] [Indexed: 11/20/2022] Open
Abstract
Background Effect of isocitr ate dehydrogenase 1 (IDH1) mutation in neovascularization might be linked with tissue perfusion in gliomas. At present, the need of injection of contrast agent and the increasing scanning time limit the application of perfusion techniques. We used a simplified intravoxel incoherent motion (IVIM)-derived perfusion fraction (SPF) calculated from diffusion-weighted imaging (DWI) using only three b-values to quantitatively assess IDH1-linked tissue perfusion changes in WHO grade II-III gliomas (LGGs). Additionally, by comparing accuracy with dynamic contrast-enhanced (DCE) and full IVIM MRI, we tried to find the optimal imaging markers to predict IDH1 mutation status. Patients and methods Thirty patients were prospectively examined using DCE and multi-b-value DWI. All parameters were compared between the IDH1 mutant and wild-type LGGs using the Mann-Whitney U test, including the DCE MRI-derived Ktrans, ve and vp, the conventional apparen t diffusion coefficient (ADC0,1000), IVIM-de rived perfusion fraction (f), diffusion coefficient (D) and pseudo-diffusion coefficient (D*), SPF. We evaluated the diagnostic performance by receive r operating characteristic (ROC) analysis. Results Significant differences were detected between WHO grade II-III gliomas for all perfusion and diffusion parameters (P < 0.05). When compared to IDH1 mutant LGGs, IDH1 wild-type LGGs exhibited significantly higher perfusion metrics (P < 0.05) and lower diffusion metrics (P < 0.05). Among all parameters, SPF showed a higher diagnostic performance (area under the curve 0.861), with 94.4% sensitivity and 75% specificity. Conclusions DWI, DCE and IVIM MRI may noninvasively help discriminate IDH1 mutation statuses in LGGs. Specifically, simplified DWI-derived SPF showed a superior diagnostic performance.
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Patella F, Sansone M, Franceschelli G, Tofanelli L, Petrillo M, Fusco M, Nicolino GM, Buccimazza G, Fusco R, Gopalakrishnan V, Pesapane F, Biglioli F, Cariati M. Quantification of heterogeneity to classify benign parotid tumors: a feasibility study on most frequent histotypes. Future Oncol 2020; 16:763-778. [PMID: 32250169 DOI: 10.2217/fon-2019-0736] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Aim: To differentiate Warthin tumors (WTs) and pleomorphic adenomas (PAs) measuring heterogeneity of intravoxel incoherent motion (IVIM) and dynamic-contrast enhanced-magnetic resonance imaging biomarkers. Methods: Volumes of interest were traced on 18 WT and 18 PA in 25 patients. For each IVIM and dynamic-contrast enhanced biomarker, histogram parameters were calculated and then compared using the Wilcoxon-signed-rank test. Receiver operating characteristic curves and multivariate analysis were employed to identify the parameters and their pairs with the best accuracy. Results: Most of the biomarkers exhibited significant difference (p < 0.05) between PA and WT for histogram parameters. Time to peak median and skewness, and D* median and entropy showed the highest area under the curve. No meaningful improvement of accuracy was obtained using two features. Conclusion: IVIM and dynamic-contrast enhanced histogram descriptors may help in the classification of WT and PA.
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Affiliation(s)
- Francesca Patella
- Università degli Studi di Milano, Postgraduate School in Radiodiagnostics Milano, Lombardia, Italy.,Diagnostic & Interventional Radiology Service, San Paolo Hospital, Milan, Italy
| | - Mario Sansone
- Department of Electrical Engineering & Information Technologies, University 'Federico II' of Naples, Via Claudio, Naples, Italy
| | | | - Laura Tofanelli
- Università degli Studi di Milano, Postgraduate School in Radiodiagnostics Milano, Lombardia, Italy
| | - Mario Petrillo
- Diagnostic & Interventional Radiology Service, San Paolo Hospital, Milan, Italy
| | - Massimo Fusco
- Università degli Studi di Milano, Postgraduate School in Radiodiagnostics Milano, Lombardia, Italy
| | - Gabriele Maria Nicolino
- Università degli Studi di Milano, Postgraduate School in Radiodiagnostics Milano, Lombardia, Italy
| | - Giorgio Buccimazza
- Università degli Studi di Milano, Postgraduate School in Radiodiagnostics Milano, Lombardia, Italy
| | - Roberta Fusco
- Radiology Unit, 'Dipartimento di supporto ai percorsi oncologici Area Diagnostica, Istituto Nazionale Tumori - IRCCS - Fondazione G. Pascale', Via Mariano Semmola, Naples, Italy
| | | | - Filippo Pesapane
- Università degli Studi di Milano, Postgraduate School in Radiodiagnostics Milano, Lombardia, Italy
| | - Federico Biglioli
- Maxillofacial Surgery Unit, ASST Santi Paolo e Carlo, Università degli Studi di Milano, Milan, Italy
| | - Maurizio Cariati
- Diagnostic & Interventional Radiology Service, San Paolo Hospital, Milan, Italy
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Touska P, Connor SEJ. Recent advances in MRI of the head and neck, skull base and cranial nerves: new and evolving sequences, analyses and clinical applications. Br J Radiol 2019; 92:20190513. [PMID: 31529977 PMCID: PMC6913354 DOI: 10.1259/bjr.20190513] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2019] [Revised: 09/09/2019] [Accepted: 09/12/2019] [Indexed: 12/14/2022] Open
Abstract
MRI is an invaluable diagnostic tool in the investigation and management of patients with pathology of the head and neck. However, numerous technical challenges exist, owing to a combination of fine anatomical detail, complex geometry (that is subject to frequent motion) and susceptibility effects from both endogenous structures and exogenous implants. Over recent years, there have been rapid developments in several aspects of head and neck imaging including higher resolution, isotropic 3D sequences, diffusion-weighted and diffusion-tensor imaging as well as permeability and perfusion imaging. These have led to improvements in anatomic, dynamic and functional imaging. Further developments using contrast-enhanced 3D FLAIR for the delineation of endolymphatic structures and black bone imaging for osseous structures are opening new diagnostic avenues. Furthermore, technical advances in compressed sensing and metal artefact reduction have the capacity to improve imaging speed and quality, respectively. This review explores novel and evolving MRI sequences that can be employed to evaluate diseases of the head and neck, including the skull base.
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Affiliation(s)
- Philip Touska
- Department of Radiology, Guy’s and St. Thomas’ NHS Foundation Trust, Guy’s Hospital, Great Maze Pond, London, SE1 9RT, United Kingdom
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Meyer HJ, Hamerla G, Leifels L, Höhn AK, Surov A. Histogram analysis parameters derived from DCE-MRI in head and neck squamous cell cancer – Associations with microvessel density. Eur J Radiol 2019; 120:108669. [DOI: 10.1016/j.ejrad.2019.108669] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2018] [Revised: 09/04/2019] [Accepted: 09/10/2019] [Indexed: 01/21/2023]
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Qin Y, Yu X, Hou J, Hu Y, Li F, Wen L, Lu Q, Liu S. Prognostic Value of the Pretreatment Primary Lesion Quantitative Dynamic Contrast-Enhanced Magnetic Resonance Imaging for Nasopharyngeal Carcinoma. Acad Radiol 2019; 26:1473-1482. [PMID: 30772137 DOI: 10.1016/j.acra.2019.01.021] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2018] [Revised: 01/22/2019] [Accepted: 01/22/2019] [Indexed: 12/19/2022]
Abstract
RATIONALE AND OBJECTIVES Early identifying the long-term outcome of chemoradiotherapy is helpful for personalized treatment in nasopharyngeal carcinoma (NPC). This study aimed to investigate the prognostic significance of pretreatment quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for NPC. MATERIALS AND METHODS The relationships between the prognosis and pretreatment quantitative DCE-MRI (Ktrans, Kep, Ve, and fpv) values of the primary tumors were analyzed in 134 NPC patients who received chemoradiotherapy. Kaplan-Meier analysis was performed to calculate the local-regional relapse-free survival (LRRFS), local relapse-free survival (LRFS), regional relapse-free survival, distant metastasis-free survival (DMFS), progression-free survival, and overall survival rates. Cox proportional hazards model was used to explore the independent predictors for prognosis. RESULTS The local-failure group had significantly higher Ve (p = 0.033) and fpv values (p = 0.005) than the non-local-failure group. The Ve-high group showed significantly lower LRRFS (p = 0.015) , LRFS (p = 0.013) , DMFS (p = 0.027) and progression-free survival (p = 0.035) rates than the Ve-low group. The fpv-high group exhibited significantly lower LRRFS (p = 0.004) and LRFS (p = 0.005) rates than the fpv-low group. Ve was the independent predictor for LRRFS (p = 0.008), LRFS (p = 0.007), DMFS (p = 0.041), and overall survival (p = 0.022). fpv was the independent indicator for LRRFS (p = 0.003) and LRFS (p = 0.001). CONCLUSION Baseline quantitative DCE-MRI may be valuable in predicting the prognosis for NPC.
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Affiliation(s)
- Yuhui Qin
- Department of Diagnostic Radiology, the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University and Hunan Cancer Hospital, 283 Tongzipo Road, Changsha 410013, Hunan, PR China
| | - Xiaoping Yu
- Department of Diagnostic Radiology, the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University and Hunan Cancer Hospital, 283 Tongzipo Road, Changsha 410013, Hunan, PR China.
| | - Jing Hou
- Department of Diagnostic Radiology, the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University and Hunan Cancer Hospital, 283 Tongzipo Road, Changsha 410013, Hunan, PR China
| | - Ying Hu
- Department of Radiotherapy, the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, Hunan, PR China
| | - Feiping Li
- Department of Diagnostic Radiology, the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University and Hunan Cancer Hospital, 283 Tongzipo Road, Changsha 410013, Hunan, PR China
| | - Lu Wen
- Department of Diagnostic Radiology, the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University and Hunan Cancer Hospital, 283 Tongzipo Road, Changsha 410013, Hunan, PR China
| | - Qiang Lu
- Department of Diagnostic Radiology, the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University and Hunan Cancer Hospital, 283 Tongzipo Road, Changsha 410013, Hunan, PR China
| | - Siye Liu
- Department of Diagnostic Radiology, the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University and Hunan Cancer Hospital, 283 Tongzipo Road, Changsha 410013, Hunan, PR China
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PET and MRI based RT treatment planning: Handling uncertainties. Cancer Radiother 2019; 23:753-760. [PMID: 31427076 DOI: 10.1016/j.canrad.2019.08.002] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Accepted: 08/03/2019] [Indexed: 12/11/2022]
Abstract
Imaging provides the basis for radiotherapy. Multi-modality images are used for target delineation (primary tumor and nodes, boost volume) and organs at risk, treatment guidance, outcome prediction, and treatment assessment. Next to anatomical information, more and more functional imaging is being used. The current paper provides a brief overview of the different applications of imaging techniques used in the radiotherapy process, focusing on uncertainties and QA. The paper mainly focuses on PET and MRI, but also provides a short discussion on DCE-CT. A close collaboration between radiology, nuclear medicine and radiotherapy departments provides the key to improve the quality of radiotherapy. Jointly developed imaging protocols (RT position setup, immobilization tools, lasers, flat table…), and QA programs are mandatory. For PET, suitable windowing in consultation with a Nuclear Medicine Physician is crucial (differentiation benign/malignant lesions, artifacts…). A basic knowledge of MRI sequences is required, in such a way that geometrical distortions are easily recognized by all members the RT and RT physics team. If this is not the case, then the radiologist should be introduced systematically in the delineation process and multidisciplinary meetings need to be organized regularly. For each image modality and each image registration process, the associated uncertainties need to be determined and integrated in the PTV margin. When using functional information for dose painting, response assessment or outcome prediction, collaboration between the different departments is even more important. Limitations of imaging based biomarkers (specificity, sensitivity) should be known.
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Elkin R, Nadeem S, LoCastro E, Paudyal R, Hatzoglou V, Lee NY, Shukla-Dave A, Deasy JO, Tannenbaum A. Optimal mass transport kinetic modeling for head and neck DCE-MRI: Initial analysis. Magn Reson Med 2019; 82:2314-2325. [PMID: 31273818 DOI: 10.1002/mrm.27897] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2019] [Revised: 06/13/2019] [Accepted: 06/14/2019] [Indexed: 12/21/2022]
Abstract
PURPOSE Current state-of-the-art models for estimating the pharmacokinetic parameters do not account for intervoxel movement of the contrast agent (CA). We introduce an optimal mass transport (OMT) formulation that naturally handles intervoxel CA movement and distinguishes between advective and diffusive flows. METHOD Ten patients with head and neck squamous cell carcinoma (HNSCC) were enrolled in the study between June 2014 and October 2015 and underwent DCE MRI imaging prior to beginning treatment. The CA tissue concentration information was taken as the input in the data-driven OMT model. The OMT approach was tested on HNSCC DCE data that provides quantitative information for forward flux ( Φ F ) and backward flux ( Φ B ). OMT-derived Φ F was compared with the volume transfer constant for CA, K trans , derived from the Extended Tofts Model (ETM). RESULTS The OMT-derived flows showed a consistent jump in the CA diffusive behavior across the images in accordance with the known CA dynamics. The mean forward flux was 0.0082 ± 0.0091 ( min - 1 ) whereas the mean advective component was 0.0052 ± 0.0086 ( min - 1 ) in the HNSCC patients. The diffusive percentages in forward and backward flux ranged from 8.67% to 18.76% and 12.76% to 30.36%, respectively. The OMT model accounts for intervoxel CA movement and results show that the forward flux ( Φ F ) is comparable with the ETM-derived K trans . CONCLUSIONS This is a novel data-driven study based on optimal mass transport principles applied to patient DCE imaging to analyze CA flow in HNSCC.
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Affiliation(s)
- Rena Elkin
- Applied Mathematics & Statistics, Stony Brook University, Stony Brook, New York
| | - Saad Nadeem
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Eve LoCastro
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Ramesh Paudyal
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Vaios Hatzoglou
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Nancy Y Lee
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Amita Shukla-Dave
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York.,Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Joseph O Deasy
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Allen Tannenbaum
- Computer Science and Applied Mathematics & Statistics, Stony Brook University, Stony Brook, New York
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Korn RL, Rahmanuddin S, Borazanci E. Use of Precision Imaging in the Evaluation of Pancreas Cancer. Cancer Treat Res 2019; 178:209-236. [PMID: 31209847 DOI: 10.1007/978-3-030-16391-4_8] [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] [Indexed: 12/15/2022]
Abstract
Pancreas cancer is an aggressive and fatal disease that will become one of the leading causes of cancer mortality by 2030. An all-out effort is underway to better understand the basic biologic mechanisms of this disease ranging from early development to metastatic disease. In order to change the course of this disease, diagnostic radiology imaging may play a vital role in providing a precise, noninvasive method for early diagnosis and assessment of treatment response. Recent progress in combining medical imaging, advanced image analysis and artificial intelligence, termed radiomics, can offer an innovate approach in detecting the earliest changes of tumor development as well as a rapid method for the detection of response. In this chapter, we introduce the principles of radiomics and demonstrate how it can provide additional information into tumor biology, early detection, and response assessments advancing the goals of precision imaging to deliver the right treatment to the right person at the right time.
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Affiliation(s)
- Ronald L Korn
- Virginia G Piper Cancer Center at HonorHealth, Scottsdale, AZ, USA. .,Translational Genomics Research Institute, An Affiliate of City of Hope, Phoenix, AZ, USA. .,Imaging Endpoints Core Lab, Scottsdale, AZ, USA.
| | | | - Erkut Borazanci
- Virginia G Piper Cancer Center at HonorHealth, Scottsdale, AZ, USA.,Translational Genomics Research Institute, An Affiliate of City of Hope, Phoenix, AZ, USA
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Técnicas avanzadas de resonancia magnética en patología tumoral de cabeza y cuello. RADIOLOGIA 2019; 61:191-203. [DOI: 10.1016/j.rx.2018.12.004] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2018] [Revised: 12/11/2018] [Accepted: 12/20/2018] [Indexed: 11/19/2022]
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Xiong H, Yin P, Li X, Yang C, Zhang D, Huang X, Tang Z. The features of cerebral permeability and perfusion detected by dynamic contrast-enhanced magnetic resonance imaging with Patlak model in relapsing-remitting multiple sclerosis. Ther Clin Risk Manag 2019; 15:233-240. [PMID: 30787618 PMCID: PMC6366346 DOI: 10.2147/tcrm.s189598] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
Objective To investigate the features of cerebral permeability and perfusion detected by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) with Patlak model in relapsing–remitting multiple sclerosis (RRMS) and their correlations with Expanded Disability Status Scale (EDSS) scores and disease duration. Patients and methods Twenty-seven RRMS patients underwent conventional MRI and DCE-MRI with 3.0 T magnetic resonance scanner were enrolled in the study. A Patlak model was used to quantitatively measure MRI biomarkers, including volume transfer constant (Ktrans), fractional plasma volume (Vp), cerebral blood flow (CBF), and cerebral blood volume (CBV). The correlations of MRI biomarkers with EDSS scores and disease duration were analyzed. Results The MRI biomarkers Ktrans, Vp, CBF, and CBV of contrast-enhancing (CE) lesions were significantly higher (P<0.05) than those of non-enhancing (NE) lesions and normal-appearing white matter (NAWM) regions. The skewness and kurtosis of Ktrans values in CE lesions were significantly higher (P<0.05) than that of NE lesions. No significant correlation was found among the biomarkers with EDSS scores and disease duration (P>0.05). Conclusion Our study demonstrated the abnormalities of permeability and perfusion characteristics in multiple sclerosis (MS) lesions and NAWM regions by DCE-MRI with Patlak model. The Ktrans, Vp, CBF, and CBV of CE lesions were significantly higher than that of NE lesions, but these MRI biomarkers did not associate with the severity and duration of the disease. The skewness and kurtosis of Ktrans value in CE lesions were significantly higher than that in NE lesions, indicating that these parameters of Ktrans histogram can be used to distinguish the pathology of MS lesions.
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Affiliation(s)
- Hua Xiong
- Department of Radiology, Chongqing General Hospital, University of Chinese Academy of Sciences, Chongqing 400014, China, .,Molecular and Functional Imaging Laboratory, Chongqing General Hospital, University of Chinese Academy of Sciences, Chongqing 400014, China,
| | - Ping Yin
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Xiaojiao Li
- Department of Radiology, Chongqing General Hospital, University of Chinese Academy of Sciences, Chongqing 400014, China, .,Molecular and Functional Imaging Laboratory, Chongqing General Hospital, University of Chinese Academy of Sciences, Chongqing 400014, China,
| | - Chao Yang
- Department of Radiology, Chongqing General Hospital, University of Chinese Academy of Sciences, Chongqing 400014, China, .,Molecular and Functional Imaging Laboratory, Chongqing General Hospital, University of Chinese Academy of Sciences, Chongqing 400014, China,
| | - Dan Zhang
- Department of Radiology, Chongqing General Hospital, University of Chinese Academy of Sciences, Chongqing 400014, China, .,Molecular and Functional Imaging Laboratory, Chongqing General Hospital, University of Chinese Academy of Sciences, Chongqing 400014, China,
| | - Xianlong Huang
- Department of Radiology, Chongqing General Hospital, University of Chinese Academy of Sciences, Chongqing 400014, China, .,Molecular and Functional Imaging Laboratory, Chongqing General Hospital, University of Chinese Academy of Sciences, Chongqing 400014, China,
| | - Zhuoyue Tang
- Department of Radiology, Chongqing General Hospital, University of Chinese Academy of Sciences, Chongqing 400014, China, .,Molecular and Functional Imaging Laboratory, Chongqing General Hospital, University of Chinese Academy of Sciences, Chongqing 400014, China,
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Taunk NK, Oh JH, Shukla-Dave A, Beal K, Vachha B, Holodny A, Hatzoglou V. Early posttreatment assessment of MRI perfusion biomarkers can predict long-term response of lung cancer brain metastases to stereotactic radiosurgery. Neuro Oncol 2019; 20:567-575. [PMID: 29016814 DOI: 10.1093/neuonc/nox159] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Background Imaging criteria to evaluate the response of brain metastases to stereotactic radiosurgery (SRS) in the early posttreatment period remains a crucial unmet need. The aim of this study is to correlate early (within 12 wk) posttreatment perfusion MRI changes with long-term outcomes after treatment of lung cancer brain metastases with SRS. Methods Pre- and posttreatment perfusion MRI scans were obtained in patients treated with SRS for intact non-small cell lung cancer brain metastases. Time-dependent leakage (Ktrans), blood plasma volume (Vp), and extracellular extravascular volume (Ve) were calculated for each lesion. Patients were followed longitudinally with serial MRI until death, progression, or intervention (whole brain radiation or surgery). Results We included 53 lesions treated with SRS from 41 total patients. Median follow-up after treatment was 11 months. Actuarial local control at one year was 85%. Univariate analysis demonstrated a significant difference (P = 0.032) in posttreatment Ktrans SD between patients with progressive disease (mean = 0.0317) and without progressive disease (mean = 0.0219). A posttreatment Ktrans SD cutoff value of 0.017 was highly sensitive (89%) for predicting progressive disease and no progressive disease. Early posttreatment volume change was not associated with outcome (P = 0.941). Conclusion Posttreatment Ktrans SD may be used as an early posttreatment imaging biomarker to help predict long-term response of lung cancer brain metastases to SRS. This can help identify patients who will ultimately fail SRS and allow for timelier adjustment in treatment approach. These data should be prospectively validated in larger patient cohorts and other histologies.
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Affiliation(s)
- Neil K Taunk
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Jung Hun Oh
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Amita Shukla-Dave
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Kathryn Beal
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Behroze Vachha
- Neuroradiology Service, Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Andrei Holodny
- Neuroradiology Service, Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Vaios Hatzoglou
- Neuroradiology Service, Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York
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Skewness of apparent diffusion coefficient (ADC) histogram helps predict the invasive potential of intraductal papillary neoplasms of the bile ducts (IPNBs). Abdom Radiol (NY) 2019; 44:95-103. [PMID: 30151712 DOI: 10.1007/s00261-018-1716-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
OBJECTIVE This retrospective study was to explore the value of whole lesion apparent diffusion coefficient (ADC) histogram in distinguishing invasive and noninvasive intraductal papillary neoplasms of the bile ducts (IPNBs). METHOD AND MATERIALS Fifty-two patients of IPNB underwent MRI at 1.5T with diffusion-weighted imaging (DWI, b = 500 s/mm2) before surgical resections. ADC histogram metrics were generated by using the software MR OncoTreat. The mean, standard deviation, median, skewness, kurtosis as well as the 10th, 25th, 75th, and 90th percentiles were compared between pathologically defined invasive (n = 35) and noninvasive (n = 17) IPNBs. Such conventional imaging characters as lesion location, bile duct wall dilation, and mural nodularity were also assessed. Multivariate regression analysis as well as receiver operating characteristics (ROC) analysis were then conducted to determine the predictive factors and to evaluate potential diagnostic performances. RESULTS The inter-operator reliability was good to excellent (ICC: 0.693-979). Mean median, kurtosis, and the 10th, 25th, 75th, 90th percentiles were all greater in noninvasive group than invasive ones (P: 0.00-002). Skewness was lower in noninvasive group than invasive ones (- 1.0 ± 0.6 vs. - 0.3 ± 0.6, P = 0.00). After multivariate regression, skewness (AUC = 0.822, 95%CI 0.70-0.91) and mural nodularity (accuracy = 0.808) were the only two independent factors in predicting invasive IPNBs. The diagnostic performance improved (AUC = 0.867, 95%CI 0.742-0.946) when combining skewness and mural nodularity, however, the difference did not reach statistical significance (P = 0.16). CONCLUSION The ADC histogram has capability of distinguishing invasive and noninvasive IPNBs, in which skewness was an independent predictive factor.
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Ghany HSA, Samra MFA, El-Saieed M, Gerges AS, Hasan EI, Rahman AA, Toni ND. Role of DW-MRI and ADC value in monitoring therapy of head and neck squamous cell carcinoma. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2018. [DOI: 10.1016/j.ejrnm.2018.07.016] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
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Press RH, Shu HKG, Shim H, Mountz JM, Kurland BF, Wahl RL, Jones EF, Hylton NM, Gerstner ER, Nordstrom RJ, Henderson L, Kurdziel KA, Vikram B, Jacobs MA, Holdhoff M, Taylor E, Jaffray DA, Schwartz LH, Mankoff DA, Kinahan PE, Linden HM, Lambin P, Dilling TJ, Rubin DL, Hadjiiski L, Buatti JM. The Use of Quantitative Imaging in Radiation Oncology: A Quantitative Imaging Network (QIN) Perspective. Int J Radiat Oncol Biol Phys 2018; 102:1219-1235. [PMID: 29966725 PMCID: PMC6348006 DOI: 10.1016/j.ijrobp.2018.06.023] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2018] [Revised: 05/25/2018] [Accepted: 06/14/2018] [Indexed: 02/07/2023]
Abstract
Modern radiation therapy is delivered with great precision, in part by relying on high-resolution multidimensional anatomic imaging to define targets in space and time. The development of quantitative imaging (QI) modalities capable of monitoring biologic parameters could provide deeper insight into tumor biology and facilitate more personalized clinical decision-making. The Quantitative Imaging Network (QIN) was established by the National Cancer Institute to advance and validate these QI modalities in the context of oncology clinical trials. In particular, the QIN has significant interest in the application of QI to widen the therapeutic window of radiation therapy. QI modalities have great promise in radiation oncology and will help address significant clinical needs, including finer prognostication, more specific target delineation, reduction of normal tissue toxicity, identification of radioresistant disease, and clearer interpretation of treatment response. Patient-specific QI is being incorporated into radiation treatment design in ways such as dose escalation and adaptive replanning, with the intent of improving outcomes while lessening treatment morbidities. This review discusses the current vision of the QIN, current areas of investigation, and how the QIN hopes to enhance the integration of QI into the practice of radiation oncology.
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Affiliation(s)
- Robert H. Press
- Dept. of Radiation Oncology, Winship Cancer Institute of Emory University, Atlanta, GA
| | - Hui-Kuo G. Shu
- Dept. of Radiation Oncology, Winship Cancer Institute of Emory University, Atlanta, GA
| | - Hyunsuk Shim
- Dept. of Radiation Oncology, Winship Cancer Institute of Emory University, Atlanta, GA
| | - James M. Mountz
- Dept. of Radiology, University of Pittsburgh, Pittsburgh, PA
| | | | | | - Ella F. Jones
- Dept. of Radiology, University of California, San Francisco, San Francisco, CA
| | - Nola M. Hylton
- Dept. of Radiology, University of California, San Francisco, San Francisco, CA
| | - Elizabeth R. Gerstner
- Dept. of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA
| | | | - Lori Henderson
- Cancer Imaging Program, National Cancer Institute, Bethesda, MD
| | | | - Bhadrasain Vikram
- Radiation Research Program/Division of Cancer Treatment & Diagnosis, National Cancer Institute, Bethesda, MD
| | - Michael A. Jacobs
- Dept. of Radiology and Radiological Science, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore MD
| | - Matthias Holdhoff
- Brain Cancer Program, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore MD
| | - Edward Taylor
- Princess Margaret Cancer Centre, University Health Network, Toronto, Canada
| | - David A. Jaffray
- Princess Margaret Cancer Centre, University Health Network, Toronto, Canada
| | | | - David A. Mankoff
- Dept. of Radiology, University of Pennsylvania, Philadelphia, PA
| | | | | | - Philippe Lambin
- Dept. of Radiation Oncology (MAASTRO), GROW-School for Oncology and Developmental Biology, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Thomas J. Dilling
- Dept. of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | | | | | - John M. Buatti
- Dept. of Radiation Oncology, University of Iowa, Iowa City, IA
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Dual-energy computed tomography for prediction of loco-regional recurrence after radiotherapy in larynx and hypopharynx squamous cell carcinoma. Eur J Radiol 2018; 110:1-6. [PMID: 30599844 DOI: 10.1016/j.ejrad.2018.11.005] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2018] [Revised: 10/28/2018] [Accepted: 11/04/2018] [Indexed: 11/24/2022]
Abstract
PURPOSE To investigate the role of quantitative pre-treatment dual-energy computed tomography (DECT) for prediction of loco-regional recurrence (LRR) in patients with larynx/hypopharynx squamous cell cancer (L/H SCC). METHODS Patients with L/H SCC treated with curative intent loco-regional radiotherapy and that underwent treatment planning with contrast-enhanced DECT of the neck were included. Primary and nodal gross tumor volumes (GTVp and GTVn) were contoured and transferred into a Matlab® workspace. Using a two-material decomposition, GTV iodine concentration (IC) maps were obtained. Quantitative histogram statistics (maximum, mean, standard deviation, kurtosis and skewness) were retrieved from the IC maps. Cox regression analysis was conducted to determine potential predictive factors of LRR. RESULTS Twenty-five patients, including 20 supraglottic and 5 pyriform sinus tumors were analysed. Stage I, II, III, IVa and IVb constituted 4% (1 patient), 24%, 36%, 28% and 8% of patients, respectively; 44% had concurrent chemo-radiotherapy and 28% had neodjuvant chemotherapy. Median follow-up was 21 months. Locoregional control at 1 and 2 years were 75% and 69%, respectively. For the entire cohort, GTVn volume (HR 1.177 [1.001-1.392], p = 0.05), voxel-based maximum IC of GTVp (HR 1.099 [95% CI: 1.001-1.209], p = 0.05) and IC standard deviation of GTVn (HR 9.300 [95% CI: 1.113-77.725] p = 0.04) were predictive of LRR. On subgroup analysis of patients treated with upfront radiotherapy +/- chemotherapy, both voxel-based maximum IC of GTVp (HR 1.127 [95% CI: 1.010-1.258], p = 0.05) and IC kurtosis of GTVp (HR 1.088 [95% CI: 1.014-1.166], p = 0.02) were predictive of LRR. CONCLUSION This exploratory study suggests that pre-radiotherapy DECT-derived IC quantitative analysis of tumoral volume may help predict LRR in L/H SCC.
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Winter RM, Leibfarth S, Schmidt H, Zwirner K, Mönnich D, Welz S, Schwenzer NF, la Fougère C, Nikolaou K, Gatidis S, Zips D, Thorwarth D. Assessment of image quality of a radiotherapy-specific hardware solution for PET/MRI in head and neck cancer patients. Radiother Oncol 2018; 128:485-491. [PMID: 29747873 PMCID: PMC6141811 DOI: 10.1016/j.radonc.2018.04.018] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2017] [Revised: 03/29/2018] [Accepted: 04/18/2018] [Indexed: 12/21/2022]
Abstract
BACKGROUND AND PURPOSE Functional PET/MRI has great potential to improve radiotherapy planning (RTP). However, data integration requires imaging with radiotherapy-specific patient positioning. Here, we investigated the feasibility and image quality of radiotherapy-customized PET/MRI in head-and-neck cancer (HNC) patients using a dedicated hardware setup. MATERIAL AND METHODS Ten HNC patients were examined with simultaneous PET/MRI before treatment, with radiotherapy and diagnostic scan setup, respectively. We tested feasibility of radiotherapy-specific patient positioning and compared the image quality between both setups by pairwise image analysis of 18F-FDG-PET, T1/T2-weighted and diffusion-weighted MRI. For image quality assessment, similarity measures including average symmetric surface distance (ASSD) of PET and MR-based tumor contours, MR signal-to-noise ratio (SNR) and mean apparent diffusion coefficient (ADC) value were used. RESULTS PET/MRI in radiotherapy position was feasible - all patients were successfully examined. ASSD (median/range) of PET and MR contours was 0.6 (0.4-1.2) and 0.9 (0.5-1.3) mm, respectively. For T2-weighted MRI, a reduced SNR of -26.2% (-39.0--11.7) was observed with radiotherapy setup. No significant difference in mean ADC was found. CONCLUSIONS Simultaneous PET/MRI in HNC patients using radiotherapy positioning aids is clinically feasible. Though SNR was reduced, the image quality obtained with a radiotherapy setup meets RTP requirements and the data can thus be used for personalized RTP.
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Affiliation(s)
- René M Winter
- Department of Radiation Oncology, Section for Biomedical Physics, University Hospital and Medical Faculty, Eberhard Karls University Tübingen, Germany.
| | - Sara Leibfarth
- Department of Radiation Oncology, Section for Biomedical Physics, University Hospital and Medical Faculty, Eberhard Karls University Tübingen, Germany
| | - Holger Schmidt
- Department of Diagnostic and Interventional Radiology, University Hospital and Medical Faculty, Eberhard Karls University Tübingen, Germany
| | - Kerstin Zwirner
- Department of Radiation Oncology, University Hospital and Medical Faculty, Eberhard Karls University Tübingen, Germany
| | - David Mönnich
- Department of Radiation Oncology, Section for Biomedical Physics, University Hospital and Medical Faculty, Eberhard Karls University Tübingen, Germany; German Cancer Consortium (DKTK), partner site Tübingen; and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Stefan Welz
- Department of Radiation Oncology, University Hospital and Medical Faculty, Eberhard Karls University Tübingen, Germany
| | - Nina F Schwenzer
- Department of Diagnostic and Interventional Radiology, University Hospital and Medical Faculty, Eberhard Karls University Tübingen, Germany
| | - Christian la Fougère
- Department of Nuclear Medicine, University Hospital and Medical Faculty, Eberhard Karls University Tübingen, Germany; German Cancer Consortium (DKTK), partner site Tübingen; and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Konstantin Nikolaou
- Department of Diagnostic and Interventional Radiology, University Hospital and Medical Faculty, Eberhard Karls University Tübingen, Germany; German Cancer Consortium (DKTK), partner site Tübingen; and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Sergios Gatidis
- Department of Diagnostic and Interventional Radiology, University Hospital and Medical Faculty, Eberhard Karls University Tübingen, Germany
| | - Daniel Zips
- Department of Radiation Oncology, University Hospital and Medical Faculty, Eberhard Karls University Tübingen, Germany; German Cancer Consortium (DKTK), partner site Tübingen; and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Daniela Thorwarth
- Department of Radiation Oncology, Section for Biomedical Physics, University Hospital and Medical Faculty, Eberhard Karls University Tübingen, Germany; German Cancer Consortium (DKTK), partner site Tübingen; and German Cancer Research Center (DKFZ), Heidelberg, Germany
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Marcu LG, Reid P, Bezak E. The Promise of Novel Biomarkers for Head and Neck Cancer from an Imaging Perspective. Int J Mol Sci 2018; 19:E2511. [PMID: 30149561 PMCID: PMC6165113 DOI: 10.3390/ijms19092511] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2018] [Revised: 08/18/2018] [Accepted: 08/23/2018] [Indexed: 01/25/2023] Open
Abstract
It is an agreed fact that overall survival among head and neck cancer patients has increased over the last decade. Several factors however, are still held responsible for treatment failure requiring more in-depth evaluation. Among these, hypoxia and proliferation-specific parameters are the main culprits, along with the more recently researched cancer stem cells. This paper aims to present the latest developments in the field of biomarkers for hypoxia, stemness and tumour proliferation, from an imaging perspective that includes both Positron Emission Tomography (PET) and Single Photon Emission Computed Tomography (SPECT) as well as functional magnetic resonance imaging (MRI). Quantitative imaging of biomarkers is a prerequisite for accurate treatment response assessment, bringing us closer to the highly needed personalised therapy.
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Affiliation(s)
- Loredana G Marcu
- Faculty of Science, University of Oradea, 410087 Oradea, Romania.
- Cancer Research Institute and School of Health Sciences, University of South Australia, Adelaide, SA 5001, Australia.
| | - Paul Reid
- Cancer Research Institute and School of Health Sciences, University of South Australia, Adelaide, SA 5001, Australia.
| | - Eva Bezak
- Cancer Research Institute and School of Health Sciences, University of South Australia, Adelaide, SA 5001, Australia.
- Department of Physics, University of Adelaide, Adelaide, SA 5005, Australia.
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Li Y, Tan J, Wee J, Chua M. Adaptive radiotherapy for head and neck cancers: Fact or fallacy to improve therapeutic ratio? Cancer Radiother 2018; 22:287-295. [DOI: 10.1016/j.canrad.2018.01.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2017] [Accepted: 01/18/2018] [Indexed: 12/18/2022]
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