1
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Cuenin M, Levy A, Peiffert D, Sunyach MP, Ducassou A, Cordoba A, Gillon P, Thibouw D, Lapeyre M, Lerouge D, Helfre S, Leroux A, Salleron J, Sirveaux F, Marchal F, P.Teixeira, Debordes PA, G.Vogin. Local relapse patterns after preoperative radiotherapy of limb and trunk wall soft tissue sarcomas: Prognostic role of imaging and pathologic response factors. Clin Transl Radiat Oncol 2024; 48:100825. [PMID: 39192877 PMCID: PMC11347830 DOI: 10.1016/j.ctro.2024.100825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2024] [Accepted: 07/24/2024] [Indexed: 08/29/2024] Open
Abstract
Purpose To retrospectively identify clinical, pathologic, or imaging factors predictive of local relapse (LR) after preoperative radiotherapy (RT) for soft tissue sarcomas (STS). Methods and Materials This is a retrospective multicenter study of patients who underwent preoperative RT and surgery for limb or trunk wall STS between 2007 and 2018 in French Sarcoma Group centers and were enrolled in the "Conticabase". Patterns of LR were investigated taking into account the multimodal response after preoperative RT. Diagnostic and surgical samples were compared after systematic review by expert pathologists and patients were stratified by tumor grade. Log-rank tests and Cox models were used to identify prognostic factors for radiation response and LR. Results 257 patients were included; 17 % had low-grade (LG), 72.5 % had high-grade (HG) sarcomas. In HG group, tumors were larger, mostly undifferentiated, and displayed more necrosis and perilesional edema after RT. Median follow-up was 32 months. Five-year cumulative incidence of LR was 20.3 % in the HG group versus 9.7 % in the LG group (p = 0.026). In multivariate analysis, trunk wall location (HR 6.79, p = 0.012) and proportion of viable tumor cellularity ≥ 20 % (HR 3.15, p = 0.018) were associated with LR. After adjusting for tumor location, combination of histotype and cellularity rate significantly correlated with LR. We described three prognostic subgroups for HG sarcomas, listed from the highest to lowest risk: undifferentiated sarcoma (US) with cellularity rates ≥ 20 %; non-US (NUS) with cellularity rates ≥ 20 % or US with cellularity rates < 20 %; and NUS with cellularity rates < 20 %, which shared similar prognostic risks with LG sarcomas. Conclusions HG and LG tumors have different morphological and biological behaviors in response to RT. Combination of cellularity rate with histotype could be a major prognostic for LR. Patients with undifferentiated HG sarcomas with cellularity rates ≥ 20 % after preoperative RT had the highest risk of LR and disease-specific death.
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Affiliation(s)
- M. Cuenin
- Department of Radiation Oncology, Institut de Cancérologie de Lorraine, Vandœuvre-lès-Nancy, France
| | - A. Levy
- Department of Radiation Oncology, Gustave Roussy, Thoracic Oncology Institute (IOT), Villejuif, France
| | - D. Peiffert
- Department of Radiation Oncology, Institut de Cancérologie de Lorraine, Vandœuvre-lès-Nancy, France
| | - MP. Sunyach
- Department of Radiation Oncology, Centre Léon-Bérard, Lyon, France
| | - A. Ducassou
- Department of Radiation Oncology, IUCT-oncopole, Institut Claudius-Regaud, Toulouse, France
| | - A. Cordoba
- Department of Radiation Oncology, Centre Oscar-Lambret, Lille, France
| | - P. Gillon
- Department of Radiation Oncology, Institut Bergonié, Bordeaux, France
| | - D. Thibouw
- Department of Radiation Oncology, Centre Régional De Lutte Contre Le Cancer Georges-François Leclerc C.G.F., Dijon, France
| | - M. Lapeyre
- Department of Radiation Oncology, Centre Jean-Perrin, Clermont-Ferrand, France
| | - D. Lerouge
- Department of Radiation Oncology, Centre François-Baclesse, Caen, France
| | - S. Helfre
- Department of Radiation Oncology, Institut Curie, PSL Research University, Paris, France
| | - A. Leroux
- Department of Pathology, Institut de Cancérologie de Lorraine, Vandoeuvre-les Nancy, France
| | - J. Salleron
- Department of Statistics, Institut de Cancérologie de Lorraine, Vandoeuvre-les Nancy, France
| | - F. Sirveaux
- Department of Orthopedic Surgery, Centre Chirurgical Emile Gallé, University Hospital of Nancy, Nancy, France
| | - F. Marchal
- Department of Surgical Oncology, Institut de Cancérologie de Lorraine, Vandœuvre-lès-Nancy, France
| | - P.Teixeira
- Guilloz Department of Imaging, Central Hospital, Nancy, France
| | - PA. Debordes
- Department of Orthopedic Surgery, Hopitaux universitaires de Strasbourg, Strasbourg, France
| | - G.Vogin
- CNRS, Université de Lorraine, France
- National Center of Radiotherapy, Grand-Duché du Luxembourg, Centre François Baclesse, Esch sur Alzette, Luxembourg
- Department of Oncology, Luxembourg Institute of Health, Luxembourg
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2
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Schmitz F, Sedaghat S. Inferring malignancy grade of soft tissue sarcomas from magnetic resonance imaging features: A systematic review. Eur J Radiol 2024; 177:111548. [PMID: 38852328 DOI: 10.1016/j.ejrad.2024.111548] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Revised: 04/22/2024] [Accepted: 06/02/2024] [Indexed: 06/11/2024]
Abstract
PURPOSE Systematic reviews on the grading of STS using MRI are lacking. This review analyses the role of different MRI features in inferring the histological grade of STS. MATERIALS AND METHODS A systematic review was conducted and is reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) checklist. The electronic databases of PubMed/MEDLINE were systematically searched for literature addressing the correlation of MRI findings in soft tissue sarcoma with tumor grade. As keywords "MRI", "magnetic resonance imaging", "sarcoma", "grade", "grading", and "FNCLCC" have been selected. RESULTS 14 studies have been included in this systematic review. Tumor size (p = 0.015 (51 patients) to p = 0.81 (36 patients)), tumor margin (p < 0.001 (95 patients) to 0.93 (36 patients)), necrosis (p = 0.004 (50 patients) to p = 0.65 (95 patients)), peritumoral edema (p = 0.002 (130 patients) to p = 0.337 (40 patients)), contrast enhancement (p < 0.01 (50 patients) to 0.019 (51 patients)) and polycyclic/multilobulated tumor configuration (p = 0.008 (71 patients)) were significantly associated with STS malignancy grade in most of the included studies. Heterogeneity in T2w images (p = 0.003 (130 patients) to 0.202 (40 patients)), signal intensity in T1w images/ hemorrhage (p = 0.02 (130 patients) to 0.5 (31 patients)), peritumoral contrast enhancement (p < 0.001 (95 patients) to 0.253 (51 patients)) and tumoral diffusion restriction (p = 0.01 (51 patients) to 0.53 (52 patients)) were regarded as significantly associated with FNCLCC grade in some of the studies which investigated these features. Most other MRI features were not significant. CONCLUSION Several MRI features, such as tumor size, necrosis, peritumoral edema, peritumoral contrast enhancement, intratumoral contrast enhancement, and polycyclic/multilobulated tumor configuration may indicate the malignancy grade of STS. However, further studies are needed to gain consensus.
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Affiliation(s)
- Fabian Schmitz
- Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
| | - Sam Sedaghat
- Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany.
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Naghavi AO, Bryant JM, Kim Y, Weygand J, Redler G, Sim AJ, Miller J, Coucoules K, Michael LT, Gloria WE, Yang G, Rosenberg SA, Ahmed K, Bui MM, Henderson-Jackson EB, Lee A, Lee CD, Gonzalez RJ, Feygelman V, Eschrich SA, Scott JG, Torres-Roca J, Latifi K, Parikh N, Costello J. Habitat escalated adaptive therapy (HEAT): a phase 2 trial utilizing radiomic habitat-directed and genomic-adjusted radiation dose (GARD) optimization for high-grade soft tissue sarcoma. BMC Cancer 2024; 24:437. [PMID: 38594603 PMCID: PMC11003059 DOI: 10.1186/s12885-024-12151-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2023] [Accepted: 03/20/2024] [Indexed: 04/11/2024] Open
Abstract
BACKGROUND Soft tissue sarcomas (STS), have significant inter- and intra-tumoral heterogeneity, with poor response to standard neoadjuvant radiotherapy (RT). Achieving a favorable pathologic response (FPR ≥ 95%) from RT is associated with improved patient outcome. Genomic adjusted radiation dose (GARD), a radiation-specific metric that quantifies the expected RT treatment effect as a function of tumor dose and genomics, proposed that STS is significantly underdosed. STS have significant radiomic heterogeneity, where radiomic habitats can delineate regions of intra-tumoral hypoxia and radioresistance. We designed a novel clinical trial, Habitat Escalated Adaptive Therapy (HEAT), utilizing radiomic habitats to identify areas of radioresistance within the tumor and targeting them with GARD-optimized doses, to improve FPR in high-grade STS. METHODS Phase 2 non-randomized single-arm clinical trial includes non-metastatic, resectable high-grade STS patients. Pre-treatment multiparametric MRIs (mpMRI) delineate three distinct intra-tumoral habitats based on apparent diffusion coefficient (ADC) and dynamic contrast enhanced (DCE) sequences. GARD estimates that simultaneous integrated boost (SIB) doses of 70 and 60 Gy in 25 fractions to the highest and intermediate radioresistant habitats, while the remaining volume receives standard 50 Gy, would lead to a > 3 fold FPR increase to 24%. Pre-treatment CT guided biopsies of each habitat along with clip placement will be performed for pathologic evaluation, future genomic studies, and response assessment. An mpMRI taken between weeks two and three of treatment will be used for biological plan adaptation to account for tumor response, in addition to an mpMRI after the completion of radiotherapy in addition to pathologic response, toxicity, radiomic response, disease control, and survival will be evaluated as secondary endpoints. Furthermore, liquid biopsy will be performed with mpMRI for future ancillary studies. DISCUSSION This is the first clinical trial to test a novel genomic-based RT dose optimization (GARD) and to utilize radiomic habitats to identify and target radioresistance regions, as a strategy to improve the outcome of RT-treated STS patients. Its success could usher in a new phase in radiation oncology, integrating genomic and radiomic insights into clinical practice and trial designs, and may reveal new radiomic and genomic biomarkers, refining personalized treatment strategies for STS. TRIAL REGISTRATION NCT05301283. TRIAL STATUS The trial started recruitment on March 17, 2022.
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Affiliation(s)
- Arash O Naghavi
- Department of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.
| | - J M Bryant
- Department of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Youngchul Kim
- Department of Bioinformatics and Biostatistics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Joseph Weygand
- Department of Radiation Oncology and Applied Sciences, Geisel School of Medicine, Dartmouth College, Hanover, NH, USA
| | - Gage Redler
- Department of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Austin J Sim
- Department of Radiation Oncology, James Cancer Hospital, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA
| | - Justin Miller
- Department of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Kaitlyn Coucoules
- Department of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Lauren Taylor Michael
- Clinical Trials Office, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Warren E Gloria
- Department of Pathology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - George Yang
- Department of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Stephen A Rosenberg
- Department of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Kamran Ahmed
- Department of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Marilyn M Bui
- Department of Pathology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | | | - Andrew Lee
- Department of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Caitlin D Lee
- Department of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Ricardo J Gonzalez
- Department of Sarcoma, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Vladimir Feygelman
- Department of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Steven A Eschrich
- Department of Bioinformatics and Biostatistics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Jacob G Scott
- Translational Hematology and Oncology Research, Radiation Oncology Department, Cleveland Clinic, Cleveland, OH, USA
| | - Javier Torres-Roca
- Department of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Kujtim Latifi
- Department of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Nainesh Parikh
- Department of Diagnostic Imaging and Interventional Radiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - James Costello
- Department of Diagnostic Imaging and Interventional Radiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
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Vogin G, Lepage M, Salleron J, Cuenin M, Blum A, Gondim Teixeira PA. Evaluation of the Prognostic Value of Pretherapeutic Magnetic Resonance Imaging in Predicting Soft Tissue Sarcoma Radiation Response: A Retrospective Study from a Large Institutional Sarcoma Imaging Database. Cancers (Basel) 2024; 16:878. [PMID: 38473238 DOI: 10.3390/cancers16050878] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 02/10/2024] [Accepted: 02/13/2024] [Indexed: 03/14/2024] Open
Abstract
Background: RT-induced hyalinization/fibrosis was recently evidenced as a significant independent predictor for complete response to neoadjuvant radiotherapy (RT) and survival in patients with soft tissue sarcoma (STS). Purpose: Non-invasive predictive markers of histologic response after neoadjuvant RT of STS are expected. Materials and Methods: From May 2010 to April 2017, patients with a diagnosis of STS who underwent neoadjuvant RT for limb STS were retrieved from a single center prospective clinical imaging database. Tumor Apparent Diffusion Coefficients (ADC) and areas under the time-intensity perfusion curve (AUC) were compared with the histologic necrosis ratio, fibrosis, and cellularity in post-surgical specimens. Results: We retrieved 29 patients. The median ADC value was 134.3 × 10-3 mm2/s. ADC values positively correlated with the post-treatment tumor necrosis ratio (p = 0.013). Median ADC values were lower in patients with less than 50% necrosis and higher in those with more than 50% (120.3 × 10-3 mm2/s and 202.0 × 10-3 mm2/s, respectively (p = 0.020). ADC values higher than 161 × 10-3 mm2/s presented a 95% sensitivity and a 55% specificity for the identification of tumors with more than 50% tumor necrosis ratio. Tumor-to-muscle AUC ratios were associated with histologic fibrosis (p = 0.036). Conclusions: ADC and perfusion AUC correlated, respectively, with radiation-induced tumor necrosis and fibrosis.
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Affiliation(s)
- Guillaume Vogin
- Department of Radiation Therapy, Institut de Cancérologie de Lorraine, 6 Avenue de Bourgogne, 54519 Vandœuvre-lès-Nancy, France
- Centre François Baclesse, Centre National de Radiothérapie du Luxembourg, BP436, L-4005 Esch-sur-Alzette, Luxembourg
- UMR 7365 CNRS-UL IMoPA, Biopôle de l'Université de Lorraine, Campus Brabois Santé, 9 Avenue de la Forêt de Haye, BP 20199, 54505 Vandœuvre-lès-Nancy, France
| | - Matthias Lepage
- Guilloz Imaging Department, University Hospital Center of Nancy, 29 Avenue du Maréchal de Lattre de Tassigny, 54035 Nancy, France
| | - Julia Salleron
- Biostatistics Unit, Institut de Cancérologie de Lorraine, 6 Avenue de Bourgogne, 54519 Vandœuvre-lès-Nancy, France
| | - Mathilde Cuenin
- Department of Radiation Therapy, Institut de Cancérologie de Lorraine, 6 Avenue de Bourgogne, 54519 Vandœuvre-lès-Nancy, France
| | - Alain Blum
- Guilloz Imaging Department, University Hospital Center of Nancy, 29 Avenue du Maréchal de Lattre de Tassigny, 54035 Nancy, France
| | - Pedro Augusto Gondim Teixeira
- Guilloz Imaging Department, University Hospital Center of Nancy, 29 Avenue du Maréchal de Lattre de Tassigny, 54035 Nancy, France
- Université de Lorraine, IADI, Inserm U1254, Bâtiment Recherche CHRU de Nancy Brabois, 5 Rue du Morvan, 54500 Vandœuvre-lès-Nancy, France
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5
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Danzer MF, Eveslage M, Görlich D, Noto B. A statistical framework for planning and analysing test-retest studies of repeatability. Stat Methods Med Res 2024; 33:295-308. [PMID: 38298010 DOI: 10.1177/09622802241227959] [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: 02/02/2024]
Abstract
There is an increasing number of potential quantitative biomarkers that could allow for early assessment of treatment response or disease progression. However, measurements of such biomarkers are subject to random variability. Hence, differences of a biomarker in longitudinal measurements do not necessarily represent real change but might be caused by this random measurement variability. Before utilizing a quantitative biomarker in longitudinal studies, it is therefore essential to assess the measurement repeatability. Measurement repeatability obtained from test-retest studies can be quantified by the repeatability coefficient, which is then used in the subsequent longitudinal study to determine if a measured difference represents real change or is within the range of expected random measurement variability. The quality of the point estimate of the repeatability coefficient, therefore, directly governs the assessment quality of the longitudinal study. Repeatability coefficient estimation accuracy depends on the case number in the test-retest study, but despite its pivotal role, no comprehensive framework for sample size calculation of test-retest studies exists. To address this issue, we have established such a framework, which allows for flexible sample size calculation of test-retest studies, based upon newly introduced criteria concerning assessment quality in the longitudinal study. This also permits retrospective assessment of prior test-retest studies.
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Affiliation(s)
- Moritz Fabian Danzer
- Institute of Biostatistics and Clinical Research, University of Münster, Münster, Germany
| | - Maria Eveslage
- Institute of Biostatistics and Clinical Research, University of Münster, Münster, Germany
| | - Dennis Görlich
- Institute of Biostatistics and Clinical Research, University of Münster, Münster, Germany
| | - Benjamin Noto
- Institute of Biostatistics and Clinical Research, University of Münster, Münster, Germany
- Clinic for Radiology, University Hospital Münster, Münster, Germany
- Department of Nuclear Medicine, University Hospital Münster, Münster, Germany
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Lee CY, Petronek MS, Monga V, Miller BJ, Milhem MM, Magnotta VA, Allen BG. T 2* Imaging Assessment of Neoadjuvant Radiation Therapy Combined With Pharmacological Ascorbate in Extremity Soft-Tissue Sarcomas: A Pilot Study. THE IOWA ORTHOPAEDIC JOURNAL 2023; 43:60-69. [PMID: 38213860 PMCID: PMC10777695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 01/13/2024]
Abstract
Background Extremity soft-tissue sarcomas (STS) are commonly treated with neoadjuvant radiation therapy followed by surgical resection. However, the pathological near-complete response rate is low (9-25%). Noninvasive imaging assessment that predicts treatment response before and during treatment is desirable to optimize treatment regimens. This pilot study aimed to investigate the application of a quantitative MRI parameter, T2*, in assessing neoadjuvant radiation therapy combined with pharmacological ascorbate in extremity STS. Methods This prospective cohort study included seven patients diagnosed with extremity STS and scheduled to receive neoadjuvant radiation therapy combined with pharmacological ascorbate. T2* maps were obtained from each patient before treatment (baseline MRI), two weeks after initiating treatment (on-treatment MRI), and before surgery (pre-surgery MRI). The T2* values within the tumor region were transformed into z-scores with respect to the normal- appearing tissue region. The voxel-wise z-scores within the tumor region were thresholded to generate masks representing significantly high (z-score>1.96) and low z-score (z-score<-1.96) voxels. The means of the total z-scores and within each of the significantly high and low z-score mask were computed. Their correlations with percent necrosis from pathological examination were evaluated using Spearman's rank correlation coefficient r. A correlation was considered as moderate or strong when r is higher than 0.6 and 0.8, respectively. A correlation was considered as fair or weak when r is below 0.6. Results For the baseline and on-treatment MRIs, the means of the significantly high z-scores of the T2* measurements showed moderate correlations with percent necrosis (r = 0.68 and 0.6; p = 0.11 and 0.24). For the pre-surgery MRI, the means of the total and significantly high z-scores showed strong correlations with percent necrosis (r = 0.8 and 0.9; p = 0.13 and 0.08). Tumor volume and baseline MRI-based percent necrosis showed fair or weak correlations (r = 0.3-0.54; p = 0.24-0.68). Conclusion T2* measurements prior to treatment, two weeks after initiating treatment, and before surgery showed moderate to strong correlations with percent necrosis. These results support the potential for using T2* mapping to predict and assess response to neoadjuvant radiation therapy combined with pharmacological ascorbate in extremity STS. Level of Evidence: IV.
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Affiliation(s)
- Chu-Yu Lee
- Department of Radiology, University of Iowa, Iowa City, Iowa, USA
| | - Michael S. Petronek
- Department of Radiation Oncology, Free Radical and Radiation Biology Program, University of Iowa Hospitals and Clinics, Iowa City, Iowa, USA
| | - Varun Monga
- Department of Internal Medicine, Division of Hematology and Oncology, University of Iowa Hospitals and Clinics, Iowa City, Iowa, USA
| | - Benjamin J. Miller
- Department of Orthopedics and Rehabilitation, University of Iowa Hospitals and Clinics, Iowa City, Iowa, USA
| | - Mohammed M. Milhem
- Department of Internal Medicine, Division of Hematology and Oncology, University of Iowa Hospitals and Clinics, Iowa City, Iowa, USA
| | | | - Bryan G. Allen
- Department of Radiation Oncology, Free Radical and Radiation Biology Program, University of Iowa Hospitals and Clinics, Iowa City, Iowa, USA
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Fokkinga E, Hernandez-Tamames JA, Ianus A, Nilsson M, Tax CMW, Perez-Lopez R, Grussu F. Advanced Diffusion-Weighted MRI for Cancer Microstructure Assessment in Body Imaging, and Its Relationship With Histology. J Magn Reson Imaging 2023. [PMID: 38032021 DOI: 10.1002/jmri.29144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 10/30/2023] [Accepted: 10/31/2023] [Indexed: 12/01/2023] Open
Abstract
Diffusion-weighted magnetic resonance imaging (DW-MRI) aims to disentangle multiple biological signal sources in each imaging voxel, enabling the computation of innovative maps of tissue microstructure. DW-MRI model development has been dominated by brain applications. More recently, advanced methods with high fidelity to histology are gaining momentum in other contexts, for example, in oncological applications of body imaging, where new biomarkers are urgently needed. The objective of this article is to review the state-of-the-art of DW-MRI in body imaging (ie, not including the nervous system) in oncology, and to analyze its value as compared to reference colocalized histology measurements, given that demonstrating the histological validity of any new DW-MRI method is essential. In this article, we review the current landscape of DW-MRI techniques that extend standard apparent diffusion coefficient (ADC), describing their acquisition protocols, signal models, fitting settings, microstructural parameters, and relationship with histology. Preclinical, clinical, and in/ex vivo studies were included. The most used techniques were intravoxel incoherent motion (IVIM; 36.3% of used techniques), diffusion kurtosis imaging (DKI; 16.7%), vascular, extracellular, and restricted diffusion for cytometry in tumors (VERDICT; 13.3%), and imaging microstructural parameters using limited spectrally edited diffusion (IMPULSED; 11.7%). Another notable category of techniques relates to innovative b-tensor diffusion encoding or joint diffusion-relaxometry. The reviewed approaches provide histologically meaningful indices of cancer microstructure (eg, vascularization/cellularity) which, while not necessarily accurate numerically, may still provide useful sensitivity to microscopic pathological processes. Future work of the community should focus on improving the inter-/intra-scanner robustness, and on assessing histological validity in broader contexts. LEVEL OF EVIDENCE: NA TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Ella Fokkinga
- Biomedical Engineering, Track Medical Physics, Delft University of Technology, Delft, The Netherlands
- Radiomics Group, Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain
| | - Juan A Hernandez-Tamames
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
- Department of Imaging Physics, Delft University of Technology, Delft, The Netherlands
| | - Andrada Ianus
- Champalimaud Research, Champalimaud Foundation, Lisbon, Portugal
| | - Markus Nilsson
- Department of Diagnostic Radiology, Clinical Sciences Lund, Lund, Sweden
| | - Chantal M W Tax
- Cardiff University Brain Research Imaging Center (CUBRIC), School of Physics and Astronomy, Cardiff University, Cardiff, United Kingdom
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Raquel Perez-Lopez
- Radiomics Group, Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain
| | - Francesco Grussu
- Radiomics Group, Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain
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8
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van Ravensteijn SG, Nederkoorn MJL, Wal TCP, Versleijen-Jonkers YMH, Braam PM, Flucke UE, Bonenkamp JJ, Schreuder BHW, van Herpen CML, de Wilt JHW, Desar IME, de Rooy JWJ. The Prognostic Relevance of MRI Characteristics in Myxofibrosarcoma Patients Treated with Neoadjuvant Radiotherapy. Cancers (Basel) 2023; 15:2843. [PMID: 37345181 DOI: 10.3390/cancers15102843] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 05/14/2023] [Accepted: 05/17/2023] [Indexed: 06/23/2023] Open
Abstract
To improve local control, neoadjuvant radiotherapy (nRT) followed by surgery is the standard of care in myxofibrosarcoma (MFS) because of its infiltrative growth pattern. Nevertheless, local recurrence rates are high. Data on prognostic factors for poor clinical outcomes are lacking. This retrospective study thus investigates the prognostic relevance of magnetic resonance imaging (MRI) characteristics before and after nRT in 40 MFS patients, as well as their association with disease-free survival (DFS) and overall survival (OS). A vascular pedicle, defined as extra-tumoral vessels at the tumor periphery, was observed in 12 patients (30.0%) pre-nRT and remained present post-nRT in all cases. Patients with a vascular pedicle had worse DFS (HR 5.85; 95% CI 1.56-21.90; p = 0.009) and OS (HR 9.58; 95% CI 1.91-48.00; p = 0.006). An infiltrative growth pattern, referred to as a tail sign, was observed in 22 patients (55.0%) pre-nRT and in 19 patients (47.5%) post-nRT, and was associated with worse DFS post-nRT (HR 6.99; 95% CI 1.39-35.35; p = 0.019). The percentage of tumor necrosis estimated by MRI was increased post-nRT, but was not associated with survival outcomes. The presence of a tail sign or vascular pedicle on MRI could support the identification of patients at risk for poor clinical outcomes after nRT.
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Affiliation(s)
- Stefan G van Ravensteijn
- Department of Medical Oncology, Radboud University Medical Centre, 6525 GA Nijmegen, The Netherlands
| | - Maikel J L Nederkoorn
- Department of Medical Oncology, Radboud University Medical Centre, 6525 GA Nijmegen, The Netherlands
| | - Tom C P Wal
- Department of Medical Oncology, Radboud University Medical Centre, 6525 GA Nijmegen, The Netherlands
| | | | - Pètra M Braam
- Department of Radiotherapy, Radboud University Medical Centre, 6525 GA Nijmegen, The Netherlands
| | - Uta E Flucke
- Department of Pathology, Radboud University Medical Centre, 6525 GA Nijmegen, The Netherlands
| | - Johannes J Bonenkamp
- Department of Surgery, Radboud University Medical Centre, 6525 GA Nijmegen, The Netherlands
| | - Bart H W Schreuder
- Department of Orthopedics, Radboud University Medical Centre, 6525 GA Nijmegen, The Netherlands
| | - Carla M L van Herpen
- Department of Medical Oncology, Radboud University Medical Centre, 6525 GA Nijmegen, The Netherlands
| | - Johannes H W de Wilt
- Department of Surgery, Radboud University Medical Centre, 6525 GA Nijmegen, The Netherlands
| | - Ingrid M E Desar
- Department of Medical Oncology, Radboud University Medical Centre, 6525 GA Nijmegen, The Netherlands
| | - Jacky W J de Rooy
- Department of Radiology, Radboud University Medical Centre, 6525 GA Nijmegen, The Netherlands
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9
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Neves R, Perez BDD, Tindall T, Fernandez NS, Panek R, Wilne S, Suri M, Whitehouse W, Jagani S, Dandapani M, Dineen RA, Glazebrook C. Whole-body MRI for cancer surveillance in ataxia-telangiectasia: A qualitative study of the perspectives of people affected by A-T and their families. Health Expect 2023; 26:1358-1367. [PMID: 36929011 PMCID: PMC10154855 DOI: 10.1111/hex.13756] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Revised: 01/21/2023] [Accepted: 03/03/2023] [Indexed: 03/18/2023] Open
Abstract
BACKGROUND/OBJECTIVES Ataxia-telangiectasia (A-T) is a complex inherited disease associated with an increased risk of malignancy. Surveillance guidelines have demonstrated significant health benefits in other cancer predisposition syndromes. However, evidence-based guidelines for cancer screening are not currently used in the United Kingdom for people affected by A-T. This study aims to understand how people with A-T and their parents feel about cancer surveillance using whole-body magnetic resonance imaging (MRI) to inform the future development of cancer surveillance guidelines. DESIGN/METHODS We conducted semistructured interviews with people affected by A-T. Data were analysed inductively using thematic analysis. RESULTS Nine parents of children with A-T and four adults with A-T were interviewed. Five main themes emerged from the data, including (1) cancer screening was considered invaluable with the perceived value of early detection highlighted; (2) the cancer fear can increase anxiety; (3) the perceived limitations around current practice, with the responsibility for monitoring falling too strongly on parents and patients; (4) the need for effective preparation for cancer screening, including clear communication and (5) the challenges associated with MRI screening, where specific recommendations were made for improving the child's experience. CONCLUSION This study suggests that stakeholders are positive about the perceived advantages of a cancer screening programme. Ongoing support and preparation techniques should be adopted to maximise adherence and minimise adverse psychosocial outcomes. PATIENT OR PUBLIC CONTRIBUTION People with A-T and parents of people with A-T were actively involved in this study by giving their consent to be interviewed. An independent parent representative contributed to the study, supporting the research team in interpreting and commenting on the appropriateness of the language used in this report.
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Affiliation(s)
- Renata Neves
- Radiological Sciences, Mental Health and Division of Clinical Neuroscience, University of Nottingham, Nottingham, UK.,Department of Radiology, Nottingham University Hospitals NHS Trust, Nottingham, UK
| | - Blanca de Dios Perez
- Division of Rehabilitation, Ageing and Wellbeing, Centre for Rehabilitation and Ageing Research, School of Medicine, University of Nottingham, Nottingham, UK
| | - Tierney Tindall
- Mental Health and Division of Clinical Neuroscience, School of Medicine, University of Nottingham, Nottingham, UK
| | | | - Rafal Panek
- Department of Medical Physics and Clinical Engineering, Nottingham University Hospitals NHS Trust, Nottingham, UK
| | - Sophie Wilne
- Department of Paediatric Oncology, Nottingham University Hospitals NHS Trust, Nottingham, UK
| | - Mohnish Suri
- Nottingham Clinical Genetics Service, Nottingham University Hospitals NHS Trust, Nottingham, UK
| | - William Whitehouse
- Division of Child Health, Obstetrics and Gynaecology, School of Medicine, University of Nottingham, Nottingham, UK
| | - Sumit Jagani
- Department of Radiology, Nottingham Children's Hospital, Nottingham University Hospitals NHS Trust, Nottingham, UK
| | - Madhumita Dandapani
- Children's Brain Tumour Research Centre, Medical School, University of Nottingham, Nottingham, UK
| | - Robert A Dineen
- Radiological Sciences, Mental Health and Division of Clinical Neuroscience, University of Nottingham, Nottingham, UK.,NIHR Nottingham Biomedical Research Centre, Nottingham, UK.,Division of Clinical Neuroscience, Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, UK
| | - Cris Glazebrook
- Institute of Mental Health, University of Nottingham, Nottingham, UK
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10
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Thrussell I, Winfield JM, Orton MR, Miah AB, Zaidi SH, Arthur A, Thway K, Strauss DC, Collins DJ, Koh DM, Oelfke U, Huang PH, O’Connor JPB, Messiou C, Blackledge MD. Radiomic Features From Diffusion-Weighted MRI of Retroperitoneal Soft-Tissue Sarcomas Are Repeatable and Exhibit Change After Radiotherapy. Front Oncol 2022; 12:899180. [PMID: 35924167 PMCID: PMC9343063 DOI: 10.3389/fonc.2022.899180] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 06/17/2022] [Indexed: 11/13/2022] Open
Abstract
Background Size-based assessments are inaccurate indicators of tumor response in soft-tissue sarcoma (STS), motivating the requirement for new response imaging biomarkers for this rare and heterogeneous disease. In this study, we assess the test-retest repeatability of radiomic features from MR diffusion-weighted imaging (DWI) and derived maps of apparent diffusion coefficient (ADC) in retroperitoneal STS and compare baseline repeatability with changes in radiomic features following radiotherapy (RT). Materials and Methods Thirty patients with retroperitoneal STS received an MR examination prior to treatment, of whom 23/30 were investigated in our repeatability analysis having received repeat baseline examinations and 14/30 patients were investigated in our post-treatment analysis having received an MR examination after completing pre-operative RT. One hundred and seven radiomic features were extracted from the full manually delineated tumor region using PyRadiomics. Test-retest repeatability was assessed using an intraclass correlation coefficient (baseline ICC), and post-radiotherapy variance analysis (post-RT-IMS) was used to compare the change in radiomic feature value to baseline repeatability. Results For the ADC maps and DWI images, 101 and 102 features demonstrated good baseline repeatability (baseline ICC > 0.85), respectively. Forty-three and 2 features demonstrated both good baseline repeatability and a high post-RT-IMS (>0.85), respectively. Pearson correlation between the baseline ICC and post-RT-IMS was weak (0.432 and 0.133, respectively). Conclusions The ADC-based radiomic analysis shows better test-retest repeatability compared with features derived from DWI images in STS, and some of these features are sensitive to post-treatment change. However, good repeatability at baseline does not imply sensitivity to post-treatment change.
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Affiliation(s)
- Imogen Thrussell
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
- Department of Radiology, The Royal Marsden National Health Service (NHS) Foundation Trust, Sutton, United Kingdom
| | - Jessica M. Winfield
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
- Department of Radiology, The Royal Marsden National Health Service (NHS) Foundation Trust, Sutton, United Kingdom
| | - Matthew R. Orton
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
- Department of Radiology, The Royal Marsden National Health Service (NHS) Foundation Trust, Sutton, United Kingdom
| | - Aisha B. Miah
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
- Sarcoma Unit, The Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom
| | - Shane H. Zaidi
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
- Sarcoma Unit, The Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom
| | - Amani Arthur
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
- Department of Radiology, The Royal Marsden National Health Service (NHS) Foundation Trust, Sutton, United Kingdom
| | - Khin Thway
- Sarcoma Unit, The Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom
- Department of Histopathology, The Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom
| | - Dirk C. Strauss
- Department of Surgery, The Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom
| | - David J. Collins
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
- Department of Radiology, The Royal Marsden National Health Service (NHS) Foundation Trust, Sutton, United Kingdom
| | - Dow-Mu Koh
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
- Department of Radiology, The Royal Marsden National Health Service (NHS) Foundation Trust, Sutton, United Kingdom
| | - Uwe Oelfke
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
| | - Paul H. Huang
- Division of Molecular Pathology, The Institute of Cancer Research, London, United Kingdom
| | - James P. B. O’Connor
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
- Division of Cancer Sciences, University of Manchester, Manchester, United Kingdom
- Department of Radiology, The Christie Hospital, Manchester, United Kingdom
| | - Christina Messiou
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
- Department of Radiology, The Royal Marsden National Health Service (NHS) Foundation Trust, Sutton, United Kingdom
| | - Matthew D. Blackledge
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
- Department of Radiology, The Royal Marsden National Health Service (NHS) Foundation Trust, Sutton, United Kingdom
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11
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Arthur A, Johnston EW, Winfield JM, Blackledge MD, Jones RL, Huang PH, Messiou C. Virtual Biopsy in Soft Tissue Sarcoma. How Close Are We? Front Oncol 2022; 12:892620. [PMID: 35847882 PMCID: PMC9286756 DOI: 10.3389/fonc.2022.892620] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Accepted: 05/31/2022] [Indexed: 12/13/2022] Open
Abstract
A shift in radiology to a data-driven specialty has been unlocked by synergistic developments in imaging biomarkers (IB) and computational science. This is advancing the capability to deliver "virtual biopsies" within oncology. The ability to non-invasively probe tumour biology both spatially and temporally would fulfil the potential of imaging to inform management of complex tumours; improving diagnostic accuracy, providing new insights into inter- and intra-tumoral heterogeneity and individualised treatment planning and monitoring. Soft tissue sarcomas (STS) are rare tumours of mesenchymal origin with over 150 histological subtypes and notorious heterogeneity. The combination of inter- and intra-tumoural heterogeneity and the rarity of the disease remain major barriers to effective treatments. We provide an overview of the process of successful IB development, the key imaging and computational advancements in STS including quantitative magnetic resonance imaging, radiomics and artificial intelligence, and the studies to date that have explored the potential biological surrogates to imaging metrics. We discuss the promising future directions of IBs in STS and illustrate how the routine clinical implementation of a virtual biopsy has the potential to revolutionise the management of this group of complex cancers and improve clinical outcomes.
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Affiliation(s)
- Amani Arthur
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, Sutton, United Kingdom
| | - Edward W. Johnston
- Sarcoma Unit, The Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom
| | - Jessica M. Winfield
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, Sutton, United Kingdom
- Sarcoma Unit, The Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom
| | - Matthew D. Blackledge
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, Sutton, United Kingdom
| | - Robin L. Jones
- Sarcoma Unit, The Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom
- Division of Clinical Studies, The Institute of Cancer Research, London, United Kingdom
| | - Paul H. Huang
- Division of Molecular Pathology, The Institute of Cancer Research, Sutton, United Kingdom
| | - Christina Messiou
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, Sutton, United Kingdom
- Sarcoma Unit, The Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom
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12
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Rodriguez JD, Selleck AM, Abdel Razek AAK, Huang BY. Update on MR Imaging of Soft Tissue Tumors of Head and Neck. Magn Reson Imaging Clin N Am 2021; 30:151-198. [PMID: 34802577 DOI: 10.1016/j.mric.2021.06.019] [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: 11/16/2022]
Abstract
This article reviews soft tissue tumors of the head and neck following the 2020 revision of WHO Classification of Soft Tissue and Bone Tumours. Common soft tissue tumors in the head and neck and tumors are discussed, along with newly added entities to the classification system. Salient clinical and imaging features that may allow for improved diagnostic accuracy or to narrow the imaging differential diagnosis are covered. Advanced imaging techniques are discussed, with a focus on diffusion-weighted and dynamic contrast imaging and their potential to help characterize soft tissue tumors and aid in distinguishing malignant from benign tumors.
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Affiliation(s)
- Justin D Rodriguez
- Department of Radiology, Duke University, 2301 Erwin Rd, Durham, NC 27705, USA
| | - A Morgan Selleck
- Department of Otolaryngology/Head and Neck Surgery, University of North Carolina Hospitals, 170 Manning Drive, CB 7070, Physicians Office Building, Rm G190A, Chapel Hill, NC 27599, USA
| | | | - Benjamin Y Huang
- Department of Radiology, UNC School of Medicine, 101 Manning Drive, CB#7510, Chapel Hill, NC 27599, USA.
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13
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Kousi E, Messiou C, Miah A, Orton M, Haas R, Thway K, Hopkinson G, Zaidi S, Smith M, Barquin E, Moskovic E, Fotiadis N, Strauss D, Hayes A, Schmidt MA. Descriptive analysis of MRI functional changes occurring during reduced dose radiotherapy for myxoid liposarcomas. Br J Radiol 2021; 94:20210310. [PMID: 34545764 PMCID: PMC9328045 DOI: 10.1259/bjr.20210310] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
OBJECTIVES Myxoid liposarcomas (MLS) show enhanced response to radiotherapy due to their distinctive vascular pattern and therefore could be effectively treated with lower radiation doses. This is a descriptive study to explore the use of functional MRI to identify response in a uniform cohort of MLS patients treated with reduced dose radiotherapy. METHODS 10 patients with MLS were imaged pre-, during, and post-radiotherapy receiving reduced dose radiotherapy and the response to treatment was histopathologically assessed post-radiotherapy. Apparent diffusion coefficient (ADC), T2* relaxation time, volume transfer constant (Ktrans), initial area under the gadolinium curve over 60 s (IAUGC60) and (Gd) were estimated for a central tumour volume. RESULTS All parameters showed large inter- and intrasubject variabilities. Pre-treatment (Gd), IAUGC60 and Ktrans were significantly different between responders and non-responders. Post-radiotherapy reductions from baseline were demonstrated for T2*, (Gd), IAUGC60 and Ktrans for responders. No statistically significant ADC differences were demonstrated between the two response groups. Significantly greater early tumour volume reductions were observed for responders. CONCLUSIONS MLS are heterogenous lesions, characterised by a slow gradual contrast-agent uptake. Pre-treatment vascular parameters, early changes to tumour volume, vascular parameters and T2* have potential in identifying response to treatment. The delayed (Gd) is a suitable descriptive parameter, relying simply on T1 measurements. Volume changes precede changes in MLS functionality and could be used to identify early response. ADVANCES IN KNOWLEDGE MLS are are characterised by slow gradual contrast-agent uptake. Measurement of the delayed contrast-agent uptake (Gd) is simple to implement and able to discriminate response.
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Affiliation(s)
- Evanthia Kousi
- MRI unit, The Royal Marsden NHS Foundation Trust and The Institute of Cancer Research, London, UK
| | - Christina Messiou
- Radiology department, The Royal Marsden NHS Foundation Trust, London, UK
| | - Aisha Miah
- Sarcoma Unit, The Royal Marsden NHS Foundation Trust, London, UK
| | - Matthew Orton
- MRI unit, The Royal Marsden NHS Foundation Trust and The Institute of Cancer Research, London, UK
| | - Rick Haas
- Sarcoma Unit, Department of Radiotherapy, The Netherlands Cancer Institute, Amsterdam, The Netherlands.,Department of Radiotherapy, Leiden University Medical Center, Leiden, The Netherlands
| | - Khin Thway
- Molecular pathology, The Royal Marsden NHS Foundation Trust, London, UK
| | - Georgina Hopkinson
- MRI unit, The Royal Marsden NHS Foundation Trust and The Institute of Cancer Research, London, UK
| | - Shane Zaidi
- Sarcoma Unit, The Royal Marsden NHS Foundation Trust, London, UK
| | - Myles Smith
- Sarcoma Unit, The Royal Marsden NHS Foundation Trust, London, UK
| | | | - Eleanor Moskovic
- Radiology department, The Royal Marsden NHS Foundation Trust, London, UK
| | - Nicos Fotiadis
- Department of Interventional Radiology, The Royal Marsden NHS Foundation trust, London, UK
| | - Dirk Strauss
- Sarcoma/Melanoma Unit, The Royal Marsden NHS Foundation Trust, London, UK
| | - Andrew Hayes
- Sarcoma/Melanoma Unit, The Royal Marsden NHS Foundation Trust, London, UK
| | - Maria A Schmidt
- MRI unit, The Royal Marsden NHS Foundation Trust and The Institute of Cancer Research, London, UK
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14
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Wang C, Padgett KR, Su MY, Mellon EA, Maziero D, Chang Z. Multi-parametric MRI (mpMRI) for treatment response assessment of radiation therapy. Med Phys 2021; 49:2794-2819. [PMID: 34374098 DOI: 10.1002/mp.15130] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Revised: 06/23/2021] [Accepted: 06/28/2021] [Indexed: 11/11/2022] Open
Abstract
Magnetic resonance imaging (MRI) plays an important role in the modern radiation therapy (RT) workflow. In comparison with computed tomography (CT) imaging, which is the dominant imaging modality in RT, MRI possesses excellent soft-tissue contrast for radiographic evaluation. Based on quantitative models, MRI can be used to assess tissue functional and physiological information. With the developments of scanner design, acquisition strategy, advanced data analysis, and modeling, multiparametric MRI (mpMRI), a combination of morphologic and functional imaging modalities, has been increasingly adopted for disease detection, localization, and characterization. Integration of mpMRI techniques into RT enriches the opportunities to individualize RT. In particular, RT response assessment using mpMRI allows for accurate characterization of both tissue anatomical and biochemical changes to support decision-making in monotherapy of radiation treatment and/or systematic cancer management. In recent years, accumulating evidence have, indeed, demonstrated the potentials of mpMRI in RT response assessment regarding patient stratification, trial benchmarking, early treatment intervention, and outcome modeling. Clinical application of mpMRI for treatment response assessment in routine radiation oncology workflow, however, is more complex than implementing an additional imaging protocol; mpMRI requires additional focus on optimal study design, practice standardization, and unified statistical reporting strategy to realize its full potential in the context of RT. In this article, the mpMRI theories, including image mechanism, protocol design, and data analysis, will be reviewed with a focus on the radiation oncology field. Representative works will be discussed to demonstrate how mpMRI can be used for RT response assessment. Additionally, issues and limits of current works, as well as challenges and potential future research directions, will also be discussed.
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Affiliation(s)
- Chunhao Wang
- Department of Radiation Oncology, Duke University, Durham, North Carolina, USA
| | - Kyle R Padgett
- Department of Radiation Oncology, University of Miami, Miami, Florida, USA.,Department of Radiology, University of Miami, Miami, Florida, USA
| | - Min-Ying Su
- Department of Radiological Sciences, University of California, Irvine, California, USA.,Department of Medical Imaging and Radiological Sciences, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Eric A Mellon
- Department of Radiation Oncology, University of Miami, Miami, Florida, USA
| | - Danilo Maziero
- Department of Radiation Oncology, University of Miami, Miami, Florida, USA
| | - Zheng Chang
- Department of Radiation Oncology, Duke University, Durham, North Carolina, USA
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15
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Gennaro N, Reijers S, Bruining A, Messiou C, Haas R, Colombo P, Bodalal Z, Beets-Tan R, van Houdt W, van der Graaf WTA. Imaging response evaluation after neoadjuvant treatment in soft tissue sarcomas: Where do we stand? Crit Rev Oncol Hematol 2021; 160:103309. [PMID: 33757836 DOI: 10.1016/j.critrevonc.2021.103309] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Revised: 02/15/2021] [Accepted: 03/03/2021] [Indexed: 12/16/2022] Open
Abstract
Soft tissue sarcomas (STS) represent a broad family of rare tumours for which surgery with radiotherapy represents first-line treatment. Recently, neoadjuvant chemo-radiotherapy has been increasingly used in high-risk patients in an effort to reduce surgical morbidity and improve clinical outcomes. An adequate understanding of the efficacy of neoadjuvant therapies would optimise patient care, allowing a tailored approach. Although response evaluation criteria in solid tumours (RECIST) is the most common imaging method to assess tumour response, Choi criteria and functional and molecular imaging (DWI, DCE-MRI and 18F-FDG-PET) seem to outperform it in the discrimination between responders and non-responders. Moreover, the radiologic-pathology correlation of treatment-related changes remains poorly understood. In this review, we provide an overview of the imaging assessment of tumour response in STS undergoing neoadjuvant treatment, including conventional imaging (CT, MRI, PET) and advanced imaging analysis. Future directions will be presented to shed light on potential advances in pre-surgical imaging assessments that have clinical implications for sarcoma patients.
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Affiliation(s)
- Nicolò Gennaro
- Humanitas Research and Cancer Center, Dept. of Radiology, Rozzano, Italy; Humanitas University, Dept. of Biomedical Sciences, Pieve Emanuele, Italy; The Netherlands Cancer Institute, Dept. of Radiology, Amsterdam, the Netherlands.
| | - Sophie Reijers
- The Netherlands Cancer Institute, Dept. of Surgical Oncology, Amsterdam, the Netherlands
| | - Annemarie Bruining
- The Netherlands Cancer Institute, Dept. of Radiology, Amsterdam, the Netherlands
| | - Christina Messiou
- The Royal Marsden NHS Foundation Trust, Dept. Of Radiology Sarcoma Unit, Sutton, United Kingdom; The Institute of Cancer Research, Sutton, United Kingdom
| | - Rick Haas
- The Netherlands Cancer Institute, Dept. of Radiation Oncology, Amsterdam, the Netherlands; Leiden University Medical Center, Dept. of Radiation Oncology, the Netherlands
| | | | - Zuhir Bodalal
- The Netherlands Cancer Institute, Dept. of Radiology, Amsterdam, the Netherlands; GROW School for Oncology and Developmental Biology, Maastricht University, Maastricht, the Netherlands
| | - Regina Beets-Tan
- The Netherlands Cancer Institute, Dept. of Radiology, Amsterdam, the Netherlands; GROW School for Oncology and Developmental Biology, Maastricht University, Maastricht, the Netherlands; Danish Colorectal Cancer Center South, Vejle University Hospital, Institute of Regional Health Research, University of Southern Denmark, Denmark
| | - Winan van Houdt
- The Netherlands Cancer Institute, Dept. of Surgical Oncology, Amsterdam, the Netherlands
| | - Winette T A van der Graaf
- The Netherlands Cancer Institute, Dept. of Medical Oncology, Amsterdam, the Netherlands; Erasmus MC Cancer Institute, Dept. of Medical Oncology, Erasmus University Medical Center, Rotterdam, the Netherlands
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16
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Manikis GC, Nikiforaki K, Lagoudaki E, de Bree E, Maris TG, Marias K, Karantanas AH. Differentiating low from high-grade soft tissue sarcomas using post-processed imaging parameters derived from multiple DWI models. Eur J Radiol 2021; 138:109660. [PMID: 33756189 DOI: 10.1016/j.ejrad.2021.109660] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Revised: 02/14/2021] [Accepted: 03/15/2021] [Indexed: 01/18/2023]
Abstract
PURPOSE To investigate and histopathologically validate the role of model selection in the design of novel parametric meta-maps towards the discrimination of low from high-grade soft tissue sarcomas (STSs) using multiple Diffusion Weighted Imaging (DWI) models. METHODS DWI data of 28 patients were quantified using the mono-exponential, bi-exponential, stretched-exponential and the diffusion kurtosis model. Akaike Weights (AW) were calculated from the corrected Akaike Information Criteria (AICc) to select the most suitable model for every pixel within the tumor volume. Pseudo-colorized classification maps were then generated to depict model suitability, hypothesizing that every single model underpins different tissue properties and cannot solely characterize the whole tumor. Single model parametric maps were turned into meta-maps using the classification map and a histological validation of the model suitability results was conducted on several subregions of different tumors. Several histogram metrics were calculated from all derived maps before and after model selection, statistical analysis was conducted using the Mann-Whitney U test, p-values were adjusted for multiple comparisons and performance of all statistically significant metrics was evaluated using the Receiver Operator Characteristic (ROC) analysis. RESULTS The histologic analysis on several tumor subregions confirmed model suitability results on these areas. Only 3 histogram metrics, all derived from the meta-maps, were found to be statistically significant in differentiating low from high-grade STSs with an AUC higher than 89 %. CONCLUSION Embedding model selection in the design of the diffusion parametric maps yields to histogram metrics of high discriminatory power in grading STSs.
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Affiliation(s)
- Georgios C Manikis
- Department of Radiology, Medical School-University of Crete, Heraklion, Greece; Computational BioMedicine Laboratory, Institute of Computer Science, Foundation for Research and Technology-Hellas (FORTH), Heraklion, Greece.
| | - Katerina Nikiforaki
- Department of Radiology, Medical School-University of Crete, Heraklion, Greece; Computational BioMedicine Laboratory, Institute of Computer Science, Foundation for Research and Technology-Hellas (FORTH), Heraklion, Greece.
| | - Eleni Lagoudaki
- Department of Pathology, University Hospital of Crete, Heraklion, Greece.
| | - Eelco de Bree
- Department of Surgical Oncology, University of Crete, Heraklion, Greece.
| | - Thomas G Maris
- Department of Radiology, Medical School-University of Crete, Heraklion, Greece; Computational BioMedicine Laboratory, Institute of Computer Science, Foundation for Research and Technology-Hellas (FORTH), Heraklion, Greece.
| | - Kostas Marias
- Computational BioMedicine Laboratory, Institute of Computer Science, Foundation for Research and Technology-Hellas (FORTH), Heraklion, Greece; Department of Electrical & Computer Engineering, Hellenic Mediterranean University, Crete, Heraklion, Greece.
| | - Apostolos H Karantanas
- Department of Radiology, Medical School-University of Crete, Heraklion, Greece; Computational BioMedicine Laboratory, Institute of Computer Science, Foundation for Research and Technology-Hellas (FORTH), Heraklion, Greece; Department of Medical Imaging, University Hospital, Heraklion, Greece.
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17
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Kalisvaart GM, Bloem JL, Bovée JVMG, van de Sande MAJ, Gelderblom H, van der Hage JA, Hartgrink HH, Krol ADG, de Geus-Oei LF, Grootjans W. Personalising sarcoma care using quantitative multimodality imaging for response assessment. Clin Radiol 2021; 76:313.e1-313.e13. [PMID: 33483087 DOI: 10.1016/j.crad.2020.12.009] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Accepted: 12/17/2020] [Indexed: 01/18/2023]
Abstract
Over the last decades, technological developments in the field of radiology have resulted in a widespread use of imaging for personalising medicine in oncology, including patients with a sarcoma. New scanner hardware, imaging protocols, image reconstruction algorithms, radiotracers, and contrast media, enabled the assessment of the physical and biological properties of tumours associated with response to treatment. In this context, medical imaging has the potential to select sarcoma patients who do not benefit from (neo-)adjuvant treatment and facilitate treatment adaptation. Due to the biological heterogeneity in sarcomas, the challenge at hand is to acquire a practicable set of imaging features for specific sarcoma subtypes, allowing response assessment. This review provides a comprehensive overview of available clinical data on imaging-based response monitoring in sarcoma patients and future research directions. Eventually, it is expected that imaging-based response monitoring will help to achieve successful modification of (neo)adjuvant treatments and improve clinical care for these patients.
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Affiliation(s)
- G M Kalisvaart
- Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands.
| | - J L Bloem
- Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - J V M G Bovée
- Department of Pathology, Leiden University Medical Center, Leiden, the Netherlands
| | - M A J van de Sande
- Department of Orthopaedics, Leiden University Medical Center, Leiden, the Netherlands
| | - H Gelderblom
- Department of Medical Oncology, Leiden University Medical Center, Leiden, the Netherlands
| | - J A van der Hage
- Department of Surgery, Leiden University Medical Center, Leiden, the Netherlands
| | - H H Hartgrink
- Department of Surgery, Leiden University Medical Center, Leiden, the Netherlands
| | - A D G Krol
- Department of Radiation Oncology. Leiden University Medical Center, Leiden, the Netherlands
| | - L F de Geus-Oei
- Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands; Biomedical Photonic Imaging Group, University of Twente, Enschede, the Netherlands
| | - W Grootjans
- Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
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Palm RF, Jim HSL, Boulware D, Johnstone PAS, Naghavi AO. Using the revised Edmonton symptom assessment scale during neoadjuvant radiotherapy for retroperitoneal sarcoma. Clin Transl Radiat Oncol 2020; 22:22-28. [PMID: 32181374 PMCID: PMC7063105 DOI: 10.1016/j.ctro.2020.02.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2019] [Revised: 02/20/2020] [Accepted: 02/25/2020] [Indexed: 01/22/2023] Open
Abstract
Patent-reported outcomes guide managment for retroperitoneal sarcoma. All patients completed treatment uninterrupted with improvements in anxiety and pain. Symptom reporting helps personalize patient care in the era of precision medicine.
Background and purpose Retroperitoneal sarcoma (RPS) is a rare, complex disease requiring multidisciplinary management. We have previously reported that use of the Revised Edmonton Symptom Assessment Scale (ESAS-r-CSS) allows for proactive symptom management, and we sought to report the results of ESAS-r-CSS screening during pre-operative radiotherapy (RT) for a cadre of patients with RPS. Materials and methods We reviewed records of 47 patients with RPS evaluated at our institution between 2015 and 2018. Of this group, 29 non-metastatic patients were treated with definitive intent neoadjuvant RT with at least 2 weekly ESAS-r-CSS reports. A generalized estimating equation model was used to compare 13 symptoms during weekly on-treatment visits compared to baseline scores at week 1 of RT. Additionally, covariate effects of age, gender, dose, tumor size and location were assessed. Results The population was predominantly male (66%) with median age of 65 years, KPS of 90, and tumor size of 12.8 cm. ESAS scores significantly decreased for anxiety at week 3 (P = 0.01), and pain at week 5 (P = 0.01). Worse constipation was reported at week 2 (P = 0.02). In an exploratory covariate analysis, female gender, age, high dose, and larger tumor size were associated with worse ESAS scores across all time points. Conclusion Patient reporting of symptoms during radiotherapy through weekly ESAS-r-CSS facilitates timely management in patients with this unique tumor type. Expectant care during RT offers the opportunity to minimize symptom progression or treatment interruptions in a population that generally has worsening side effects.
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Affiliation(s)
- Russell F Palm
- Department of Radiation Oncology, H. Lee Moffitt Cancer Center, Tampa, FL, USA
| | - Heather S L Jim
- Health Outcomes and Behavior Department, H. Lee Moffitt Cancer Center, Tampa, FL, USA
| | - David Boulware
- Department of Biostatistics, H. Lee Moffitt Cancer Center, Tampa, FL, USA
| | - Peter A S Johnstone
- Department of Radiation Oncology, H. Lee Moffitt Cancer Center, Tampa, FL, USA
| | - Arash O Naghavi
- Department of Radiation Oncology, H. Lee Moffitt Cancer Center, Tampa, FL, USA
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Blackledge MD, Winfield JM, Miah A, Strauss D, Thway K, Morgan VA, Collins DJ, Koh DM, Leach MO, Messiou C. Supervised Machine-Learning Enables Segmentation and Evaluation of Heterogeneous Post-treatment Changes in Multi-Parametric MRI of Soft-Tissue Sarcoma. Front Oncol 2019; 9:941. [PMID: 31649872 PMCID: PMC6795696 DOI: 10.3389/fonc.2019.00941] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2019] [Accepted: 09/06/2019] [Indexed: 01/12/2023] Open
Abstract
Background: Multi-parametric MRI provides non-invasive methods for response assessment of soft-tissue sarcoma (STS) from non-surgical treatments. However, evaluation of MRI parameters over the whole tumor volume may not reveal the full extent of post-treatment changes as STS tumors are often highly heterogeneous, including cellular tumor, fat, necrosis, and cystic tissue compartments. In this pilot study, we investigate the use of machine-learning approaches to automatically delineate tissue compartments in STS, and use this approach to monitor post-radiotherapy changes. Methods: Eighteen patients with retroperitoneal sarcoma were imaged using multi-parametric MRI; 8/18 received a follow-up imaging study 2-4 weeks after pre-operative radiotherapy. Eight commonly-used supervised machine-learning techniques were optimized for classifying pixels into one of five tissue sub-types using an exhaustive cross-validation approach and expert-defined regions of interest as a gold standard. Final pixel classification was smoothed using a Markov Random Field (MRF) prior distribution on the final machine-learning models. Findings: 5/8 machine-learning techniques demonstrated high median cross-validation accuracies (82.2%, range 80.5-82.5%) with no significant difference between these five methods. One technique was selected (Naïve-Bayes) due to its relatively short training and class-prediction times (median 0.73 and 0.69 ms, respectively on a 3.5 GHz personal machine). When combined with the MRF-prior, this approach was successfully applied in all eight post-radiotherapy imaging studies and provided visualization and quantification of changes to independent STS sub-regions following radiotherapy for heterogeneous response assessment. Interpretation: Supervised machine-learning approaches to tissue classification in multi-parametric MRI of soft-tissue sarcomas provide quantitative evaluation of heterogeneous tissue changes following radiotherapy.
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Affiliation(s)
- Matthew D. Blackledge
- Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
| | - Jessica M. Winfield
- Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
- Department of Radiology, The Royal Marsden NHS Foundation Trust, Sutton, United Kingdom
| | - Aisha Miah
- Sarcoma Unit, Department of Radiotherapy and Physics, The Royal Marsden NHS Foundation Trust, London, United Kingdom
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
| | - Dirk Strauss
- Department of Surgery, The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Khin Thway
- Sarcoma Unit, Department of Radiotherapy and Physics, The Royal Marsden NHS Foundation Trust, London, United Kingdom
- Department of Histopathology, The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Veronica A. Morgan
- Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
- Department of Radiology, The Royal Marsden NHS Foundation Trust, Sutton, United Kingdom
| | - David J. Collins
- Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
- Department of Radiology, The Royal Marsden NHS Foundation Trust, Sutton, United Kingdom
| | - Dow-Mu Koh
- Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
- Department of Radiology, The Royal Marsden NHS Foundation Trust, Sutton, United Kingdom
| | - Martin O. Leach
- Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
- Department of Radiology, The Royal Marsden NHS Foundation Trust, Sutton, United Kingdom
| | - Christina Messiou
- Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
- Department of Radiology, The Royal Marsden NHS Foundation Trust, Sutton, United Kingdom
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Ren C, Zou Y, Zhang X, Li K. Diagnostic value of diffusion-weighted imaging-derived apparent diffusion coefficient and its association with histological prognostic factors in breast cancer. Oncol Lett 2019; 18:3295-3303. [PMID: 31452808 PMCID: PMC6704298 DOI: 10.3892/ol.2019.10651] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2019] [Accepted: 06/26/2019] [Indexed: 12/17/2022] Open
Abstract
Diffusion-weighted imaging (DWI) has been proven to be effective in detecting breast malignancies and has been widely implemented for breast imaging. However, the exact association between certain DWI biomarkers and well-known prognostic factors remains to be fully elucidated. By studying the association between the apparent diffusion coefficient (ADC) and prognostic factors, the present study aimed to explore the diagnostic value and prognostic potential of the ADC in breast lesions. The study included 539 female subjects with histopathologically confirmed breast lesions who underwent DWI of the breast tissue. The diagnoses comprised 307 subjects with malignant breast tumors and 232 with benign breast tumors. The maximum ADC and mean ADC (ADCmean) values of the breast lesions were calculated. For malignant tumors, the association between ADC and major prognostic factors, including histological grade, nuclear grade and lymph node status, as well as estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER-2) and proliferation marker protein Ki-67.(Ki-67) status, were evaluated. The ADCmean demonstrated the best diagnostic performance in distinguishing between malignant and benign lesions. With the optimum cut-off value at 1.30×10−3 mm2/sec, ADCmean had a sensitivity and specificity of 84.1 and 90.2%, respectively. In those patients with malignant breast lesions, a decreased ADC was associated with breast lesions with high nuclear and histological grades, and lymph node-positive, ER-negative, PR-negative and HER-2-negative status, and Ki-67 ≥14%. In conclusion, the ADC is a useful imaging biomarker for differentiating between benign and malignant breast tumors. The marked association between the ADC and prognostic factors also demonstrated its value in evaluating the malignancy of breast lesions.
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Affiliation(s)
- Congcong Ren
- Department of Radiology, Women's Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310006, P.R. China
| | - Yu Zou
- Department of Radiology, Women's Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310006, P.R. China
| | - Xiaodan Zhang
- Department of Radiology, Women's Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310006, P.R. China
| | - Kui Li
- Department of Radiology, Women's Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310006, P.R. China
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