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Crombé A, Matcuk GR, Fadli D, Sambri A, Patel DB, Paioli A, Kind M, Spinnato P. Role of Imaging in Initial Prognostication of Locally Advanced Soft Tissue Sarcomas. Acad Radiol 2023; 30:322-340. [PMID: 35534392 DOI: 10.1016/j.acra.2022.04.003] [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: 02/21/2022] [Revised: 03/21/2022] [Accepted: 04/06/2022] [Indexed: 02/07/2023]
Abstract
BACKGROUND Although imaging is central in the initial staging of patients with soft tissue sarcomas (STS), it remains underused and few radiological features are currently used in practice for prognostication and to help guide the best therapeutic strategy. Yet, several prognostic qualitative and quantitative characteristics from magnetic resonance imaging (MRI) and positron emission tomography (PET) have been identified over these last decades. OBJECTIVE After an overview of the current validated prognostic features based on baseline imaging and their integration into prognostic tools, such as nomograms used by clinicians, the aim of this review is to summarize more complex and innovative MRI, PET, and radiomics features, and to highlight their role to predict indirectly (through histologic grade) or directly the patients' outcomes.
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Affiliation(s)
- Amandine Crombé
- Department of Diagnostic and Interventional Oncological Imaging, Institut Bergonié, Regional Comprehensive Cancer of Nouvelle-Aquitaine, 229, cours de l'Argonne, F-33076, Bordeaux, France; Department of musculoskeletal imaging, Pellegrin University Hospital, 2, place Amélie Raba-Léon, F-33000, Bordeaux, France; Models in Oncology (MONC) Team, INRIA Bordeaux Sud-Ouest, CNRS UMR 5251, Institut de Mathématiques de Bordeaux & Bordeaux University, 351 cours de la libération, F-33400 Talence, France.
| | - George R Matcuk
- Department of Imaging, Cedars-Sinai Medical Center, Los Angeles, California
| | - David Fadli
- Department of musculoskeletal imaging, Pellegrin University Hospital, 2, place Amélie Raba-Léon, F-33000, Bordeaux, France
| | - Andrea Sambri
- Alma Mater Studiorum, University of Bologna, Bologna, Italy; IRCCS Policlinico di Sant'Orsola, Bologna, Italy
| | - Dakshesh B Patel
- Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Anna Paioli
- Osteoncology Unit, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
| | - Michele Kind
- Department of Diagnostic and Interventional Oncological Imaging, Institut Bergonié, Regional Comprehensive Cancer of Nouvelle-Aquitaine, 229, cours de l'Argonne, F-33076, Bordeaux, France
| | - Paolo Spinnato
- Diagnostic and Interventional Radiology, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
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Prognostic Value of Pre-Treatment [18F]FDG PET/CT Texture Analysis in Undifferentiated Soft-Tissue Sarcoma. J Clin Med 2022; 12:jcm12010279. [PMID: 36615079 PMCID: PMC9821547 DOI: 10.3390/jcm12010279] [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: 10/25/2022] [Revised: 12/19/2022] [Accepted: 12/27/2022] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Undifferentiated soft-tissue sarcomas (USTS) are one of the most common sarcoma histotypes in adults. The standard of care is surgical excision plus adjuvant radiotherapy, while the use of perioperative chemotherapy is still controversial. The aim of this study was to investigate the value of pre-treatment [18F]FDG PET/CT conventional metrics and textural features in predicting disease-free survival (DFS) and overall survival (OS) in patients with USTS of the limbs and trunk. METHODS [18F]FDG PET/CT scans of 51 consecutive patients with locally advanced USTS were retrospectively evaluated. Conventional and textural PET parameters were analysed and tested as predictive factors for DFS and OS. RESULTS During a median follow up of 50.7 months, 23 (45.1%) and 29 (56.9%) patients had death or disease progression, respectively. Univariate analysis revealed a significant association for perioperative treatment, PET volumetric parameters and the textural feature GLCM_correlation with DFS and OS. In multivariate analysis, perioperative treatment and GLCM_correlation were the only independent factors, allowing stratification of the population into three different prognostic classes. CONCLUSION GLCM_correlation can identify USTS at high risk of relapse and death, thus helping to optimize the perioperative treatment of patients.
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Radiomics of Musculoskeletal Sarcomas: A Narrative Review. J Imaging 2022; 8:jimaging8020045. [PMID: 35200747 PMCID: PMC8876222 DOI: 10.3390/jimaging8020045] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 01/31/2022] [Accepted: 02/10/2022] [Indexed: 12/23/2022] Open
Abstract
Bone and soft-tissue primary malignant tumors or sarcomas are a large, diverse group of mesenchymal-derived malignancies. They represent a model for intra- and intertumoral heterogeneities, making them particularly suitable for radiomics analyses. Radiomic features offer information on cancer phenotype as well as the tumor microenvironment which, combined with other pertinent data such as genomics and proteomics and correlated with outcomes data, can produce accurate, robust, evidence-based, clinical-decision support systems. Our purpose in this narrative review is to offer an overview of radiomics studies dealing with Magnetic Resonance Imaging (MRI)-based radiomics models of bone and soft-tissue sarcomas that could help distinguish different histotypes, low-grade from high-grade sarcomas, predict response to multimodality therapy, and thus better tailor patients’ treatments and finally improve their survivals. Although showing promising results, interobserver segmentation variability, feature reproducibility, and model validation are three main challenges of radiomics that need to be addressed in order to translate radiomics studies to clinical applications. These efforts, together with a better knowledge and application of the “Radiomics Quality Score” and Image Biomarker Standardization Initiative reporting guidelines, could improve the quality of sarcoma radiomics studies and facilitate radiomics towards clinical translation.
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Etchebehere E, Munhoz RR, Casali A, Etchebehere M. PET/CT in soft tissue sarcomas. Nucl Med Mol Imaging 2022. [DOI: 10.1016/b978-0-12-822960-6.00115-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
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Hack RI, Becker AS, Bode-Lesniewska B, Exner GU, Müller DA, Ferraro DA, Warnock GI, Burger IA, Britschgi C. When SUV Matters: FDG PET/CT at Baseline Correlates with Survival in Soft Tissue and Ewing Sarcoma. Life (Basel) 2021; 11:life11090869. [PMID: 34575018 PMCID: PMC8468558 DOI: 10.3390/life11090869] [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: 07/23/2021] [Revised: 08/20/2021] [Accepted: 08/20/2021] [Indexed: 01/19/2023] Open
Abstract
Introduction: The role of positron-emission tomography/computed-tomography (PET/CT) in the management of sarcomas and as a prognostic tool has been studied. However, it remains unclear which metric is the most useful. We aimed to investigate if volume-based PET metrics (Tumor volume (TV) and total lesions glycolysis (TLG)) are superior to maximal standardized uptake value (SUVmax) and other metrics in predicting survival of patients with soft tissue and bone sarcomas. Materials and Methods: In this retrospective cohort study, we screened over 52′000 PET/CT scans to identify patients diagnosed with either soft tissue, bone or Ewing sarcoma and had a staging scan at our institution before initial therapy. We used a Wilcoxon signed-rank to assess which PET/CT metric was associated with survival in different patient subgroups. Receiver-Operating-Characteristic curve analysis was used to calculate cutoff values. Results: We identified a total of 88 patients with soft tissue (51), bone (26) or Ewing (11) sarcoma. Median age at presentation was 40 years (Range: 9–86 years). High SUVmax was most significantly associated with short survival (defined as <24 months) in soft tissue sarcoma (with a median and range of SUVmax 12.5 (8.8–16.0) in short (n = 18) and 5.5 (3.3–7.2) in long survival (≥24 months) (n = 31), with (p = 0.001). Similar results were seen in Ewing sarcoma (with a median and range of SUVmax 12.1 (7.6–14.7) in short (n = 6) and 3.7 (3.5–5.5) in long survival (n = 5), with (p = 0.017). However, no PET-specific metric but tumor-volume was significantly associated (p = 0.035) with survival in primary bone sarcomas (with a median and range of 217 cm3 (186–349) in short survival (n = 4) and 60 cm3 (22–104) in long survival (n = 19), with (p = 0.035). TLG was significantly inversely associated with long survival only in Ewing sarcoma (p = 0.03). Discussion: Our analysis shows that the outcome of soft tissue, bone and Ewing sarcomas is associated with different PET/CT metrics. We could not confirm the previously suggested superiority of volume-based metrics in soft tissue sarcomas, for which we found SUVmax to remain the best prognostic factor. However, bone sarcomas should probably be evaluated with tumor volume rather than FDG PET activity.
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Affiliation(s)
- Ruben I. Hack
- Department of Nuclear Medicine, University Hospital Zürich, University of Zürich, 8091 Zürich, Switzerland; (R.I.H.); (D.A.F.)
| | - Anton S. Becker
- Department of Interventional and Diagnostic Radiology, University Hospital Zürich, University of Zürich, 8091 Zürich, Switzerland;
| | - Beata Bode-Lesniewska
- Institute of Pathology and Molecular Pathology, University Hospital Zürich, University of Zürich, 8091 Zürich, Switzerland;
| | | | - Daniel A. Müller
- Balgrist University Hospital Zürich, Forchstrasse 340, 8008 Zürich, Switzerland;
| | - Daniela A. Ferraro
- Department of Nuclear Medicine, University Hospital Zürich, University of Zürich, 8091 Zürich, Switzerland; (R.I.H.); (D.A.F.)
| | | | - Irene A. Burger
- Department of Nuclear Medicine, University Hospital Zürich, University of Zürich, 8091 Zürich, Switzerland; (R.I.H.); (D.A.F.)
- Department of Nuclear Medicine, Kantonsspital Baden, 5404 Baden, Switzerland
- Correspondence:
| | - Christian Britschgi
- Department of Medical Oncology and Hematology, University Hospital Zürich, University of Zürich, 8091 Zürich, Switzerland;
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Yang Y, Ma X, Wang Y, Ding X. Prognosis prediction of extremity and trunk wall soft-tissue sarcomas treated with surgical resection with radiomic analysis based on random survival forest. Updates Surg 2021; 74:355-365. [PMID: 34003477 DOI: 10.1007/s13304-021-01074-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Accepted: 04/29/2021] [Indexed: 02/05/2023]
Abstract
Many researches have applied machine learning methods to find associations between radiomic features and clinical outcomes. Random survival forests (RSF), as an accurate classifier, sort all candidate variables as the rank of importance values. There was no study concerning on finding radiomic predictors in patients with extremity and trunk wall soft-tissue sarcomas using RSF. This study aimed to determine associations between radiomic features and overall survival (OS) by RSF analysis. To identify radiomic features with important values by RSF analysis, construct predictive models for OS incorporating clinical characteristics, and evaluate models' performance with different method. We collected clinical characteristics and radiomic features extracted from plain and contrast-enhanced computed tomography (CT) from 353 patients with extremity and trunk wall soft-tissue sarcomas treated with surgical resection. All radiomic features were analyzed by Cox proportional hazard (CPH) and followed RSF analysis. The association between radiomics-predicted risks and OS was assessed by Kaplan-Meier analysis. All clinical features were screened by CPH analysis. Prognostic clinical and radiomic parameters were fitted into RSF and CPH integrative models for OS in the training cohort, respectively. The concordance indexes (C-index) and Brier scores of both two models were evaluated in both training and testing cohorts. The model with better predictive performance was interpreted with nomogram and calibration plots. Among all 86 radiomic features, there were three variables selected with high importance values. The RSF on these three features distinguished patients with high predicted risks from patients with low predicted risks for OS in the training set (P < 0.001) using Kaplan-Meier analysis. Age, lymph node involvement and grade were incorporated into the combined models for OS (P < 0.05). The C-indexes in both two integrative models fluctuated above 0.80 whose Brier scores maintained less than 15.0 in the training and testing datasets. The RSF model performed little advantages over the CPH model that the calibration curve of the RSF model showed favorable agreement between predicted and actual survival probabilities for the 3-year and 5-year survival prediction. The multimodality RSF model including clinical and radiomic characteristics conducted high capacity in prediction of OS which might assist individualized therapeutic regimens. Level III, prognostic study.
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Affiliation(s)
- Yuhan Yang
- West China School of Medicine, Sichuan University, No.17 People's South Road, Chengdu, 610041, Sichuan, China
| | - Xuelei Ma
- State Key Laboratory of Biotherapy, Department of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Guoxue Road, Chengdu, 610041, China.
| | - Yixi Wang
- West China School of Medicine, Sichuan University, No.17 People's South Road, Chengdu, 610041, Sichuan, China
| | - Xinyan Ding
- West China School of Medicine, Sichuan University, No.17 People's South Road, Chengdu, 610041, Sichuan, China
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Harrison DJ, Chi YY, Tian J, Hingorani P, Mascarenhas L, McCowage GB, Weigel BJ, Venkatramani R, Wolden SL, Yock TI, Rodeberg DA, Hayes-Jordan AA, Teot LA, Spunt SL, Meyer WH, Hawkins DS, Shulkin BL, Parisi MT. Metabolic response as assessed by 18 F-fluorodeoxyglucose positron emission tomography-computed tomography does not predict outcome in patients with intermediate- or high-risk rhabdomyosarcoma: A report from the Children's Oncology Group Soft Tissue Sarcoma Committee. Cancer Med 2020; 10:857-866. [PMID: 33340280 PMCID: PMC7897958 DOI: 10.1002/cam4.3667] [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: 08/06/2020] [Revised: 10/01/2020] [Accepted: 10/26/2020] [Indexed: 11/07/2022] Open
Abstract
BACKGROUND Strategies to optimize management in rhabdomyosarcoma (RMS) include risk stratification to assign therapy aiming to minimize treatment morbidity yet improve outcomes. This analysis evaluated the relationship between complete metabolic response (CMR) as assessed by 18 F-fluorodeoxyglucose positron emission tomography-computed tomography (FDG-PET) imaging and event-free survival (EFS) in intermediate-risk (IR) and high-risk (HR) RMS patients. METHODS FDG-PET imaging characteristics, including assessment of CMR and maximum standard uptake values (SUVmax) of the primary tumor, were evaluated by central review. Institutional reports of SUVmax were used when SUVmax values could not be determined by central review. One hundred and thirty IR and 105 HR patients had FDG-PET scans submitted for central review or had SUVmax data available from institutional report at any time point. A Cox proportional hazards regression model was used to evaluate the relationship between these parameters and EFS. RESULTS SUVmax at study entry did not correlate with EFS for IR (p = 0.32) or HR (p = 0.86) patients. Compared to patients who did not achieve a CMR, EFS was not superior for IR patients who achieved a CMR at weeks 4 (p = 0.66) or 15 (p = 0.46), nor for HR patients who achieved CMR at week 6 (p = 0.75) or 19 (p = 0.28). Change in SUVmax at week 4 (p = 0.21) or 15 (p = 0.91) for IR patients or at week 6 (p = 0.75) or 19 (p = 0.61) for HR patients did not correlate with EFS. CONCLUSION Based on these data, FDG-PET does not appear to predict EFS in IR or HR-RMS. It remains to be determined whether FDG-PET has a role in predicting survival outcomes in other RMS subpopulations.
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Affiliation(s)
| | | | - Jing Tian
- University of Florida, Gainesville, FL, USA
| | - Pooja Hingorani
- University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Leo Mascarenhas
- Children's Hospital Los Angeles and University of Southern California Keck School of Medicine, Los Angeles, CA, USA
| | | | - Brenda J Weigel
- University of Minnesota/Masonic Cancer Center, Minneapolis, MN, USA
| | - Rajkumar Venkatramani
- Baylor College of Medicine/Dan L Duncan Comprehensive Cancer Center, Houston, TX, USA
| | | | - Torunn I Yock
- Massachusetts General Hospital Cancer Center, Boston, MA, USA
| | | | | | | | - Sheri L Spunt
- Lucile Packard Children's Hospital Stanford University, Palo Alto, CA, USA
| | - William H Meyer
- University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
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Metastasis risk prediction model in osteosarcoma using metabolic imaging phenotypes: A multivariable radiomics model. PLoS One 2019; 14:e0225242. [PMID: 31765423 PMCID: PMC6876771 DOI: 10.1371/journal.pone.0225242] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2019] [Accepted: 10/21/2019] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Osteosarcoma (OS) is the most common primary bone tumor affecting humans and it has extreme heterogeneity. Despite modern therapy, it recurs in approximately 30-40% of patients initially diagnosed with no metastatic disease, with the long-term survival rates of patients with recurrent OS being generally 20%. Thus, early prediction of metastases in OS management plans is crucial for better-adapted treatments and survival rates. In this study, a radiomics model for metastasis risk prediction in OS was developed and evaluated using metabolic imaging phenotypes. METHODS AND FINDINGS The subjects were eighty-three patients with OS, and all were treated with surgery and chemotherapy for local control. All patients underwent a pretreatment 18F-FDG-PET scan. Forty-five features were extracted from the tumor region. The incorporation of features into multivariable models was performed using logistic regression. The multivariable modeling strategy involved cross validation in the following four steps leading to final prediction model construction: (1) feature set reduction and selection; (2) model coefficients computation through train and validation processing; and (3) prediction performance estimation. The multivariable logistic regression model was developed using two radiomics features, SUVmax and GLZLM-SZLGE. The trained and validated multivariable logistic model based on probability of endpoint (P) = 1/ (1+exp (-Z)) was Z = -1.23 + 1.53*SUVmax + 1.68*GLZLM-SZLGE with significant p-values (SUVmax: 0.0462 and GLZLM_SZLGE: 0.0154). The final multivariable logistic model achieved an area under the curve (AUC) receiver operating characteristics (ROC) curve of 0.80, a sensitivity of 0.66, and a specificity of 0.88 in cross validation. CONCLUSIONS The SUVmax and GLZLM-SZLGE from metabolic imaging phenotypes are independent predictors of metastasis risk assessment. They show the association between 18F-FDG-PET and metastatic colonization knowledge. The multivariable model developed using them could improve patient outcomes by allowing aggressive treatment in patients with high metastasis risk.
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Lim HJ, Johnny Ong CA, Tan JWS, Ching Teo MC. Utility of positron emission tomography/computed tomography (PET/CT) imaging in the evaluation of sarcomas: A systematic review. Crit Rev Oncol Hematol 2019; 143:1-13. [DOI: 10.1016/j.critrevonc.2019.07.002] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2018] [Accepted: 07/02/2019] [Indexed: 12/14/2022] Open
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Abstract
INTRODUCTION Soft tissue sarcomas (STS) are highly fluorine-18-fluorodeoxyglucose (F-FDG)-avid tumours. PET seems to be effective for the assessment of the extent of disease. However, the use of PET to stratify STS into different risk histotypes still remains controversial. Our aim was to evaluate F-FDG uptake in different STS types and to assess the prognostic value of the maximum standardized uptake value (SUVmax). PATIENTS AND METHODS We reviewed 50 adult patients with primary high-grade STS of the extremities with a preoperative PET. Overall survival and local recurrence were analysed. RESULTS The mean SUVmax was 12.9 (range: 2.2-33.4). All cases of myxoid liposarcoma and all cases of synovial sarcoma had SUVmax of less than 10.3. A better overall survival and local recurrence were observed in patients with SUVmax of less than 10.3 (P=0.005 and 0.046, respectively). CONCLUSION SUVmax seems to be specific among different STS histotypes. PET does not seem to be useful in myxoid liposarcoma as well as synovial sarcoma as these tumours seem to have a low uptake of glucose. SUVmax might also be included as a prognostic factor.
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Rhu J, Hyun SH, Lee KH, Jo SJ, Lee KW, Park JB, Kim SJ. Maximum standardized uptake value on 18F-fluorodeoxyglucose positron emission tomography/computed tomography improves outcome prediction in retroperitoneal liposarcoma. Sci Rep 2019; 9:6605. [PMID: 31036901 PMCID: PMC6488597 DOI: 10.1038/s41598-019-43215-5] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2018] [Accepted: 04/05/2019] [Indexed: 12/26/2022] Open
Abstract
While 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) has been investigated in extremity sarcomas, there is no evidence on its usefulness in retroperitoneal sarcoma. This study was designed to evaluate the usefulness of 18F-FDG PET/CT in predicting aggressiveness of retroperitoneal liposarcoma. Patients experienced surgery for retroperitoneal liposarcoma from November 2007 to February 2018 and underwent preoperative 18F-FDG PET/CT were included. Preoperative maximum standardized uptake value (SUVmax) was calculated. To evaluate the predictability of SUVmax for Fédération Nationale des Centres de Lutte Contre le Cancer (FNCLCC) grade 3, receiver operating characteristics (ROC) curve analysis was performed. To analyze whether SUVmax can be a risk factor for prognosis, multivariable Cox regression was performed including potential risk factors regarding operation and histopathology. A total of 133 patients were included. ROC curve showed area under the curve of 0.877 (P < 0.001), with a cut-off point of 4.5 SUVmax showing 85.7% sensitivity and 78.3% specificity. Cox analyses showed that SUVmax > 4.5 was a significant factor for recurrence-free survival (HR = 2.148, CI 1.301-3.546, P = 0.003) and overall survival (HR = 5.052, CI 1.854-13.766, P = 0.002). SUVmax is highly predictive of FNCLCC grade 3 and SUVmax > 4.5 can be used as a prognostic factor before obtaining the histopathology.
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Affiliation(s)
- Jinsoo Rhu
- Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Seung Hyup Hyun
- Department of Nuclear Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Kyung-Han Lee
- Department of Nuclear Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Sung Jun Jo
- Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Kyo Won Lee
- Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Jae Berm Park
- Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Sung Joo Kim
- Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
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Spraker MB, Wootton LS, Hippe DS, Ball KC, Peeken JC, Macomber MW, Chapman TR, Hoff MN, Kim EY, Pollack SM, Combs SE, Nyflot MJ. MRI Radiomic Features Are Independently Associated With Overall Survival in Soft Tissue Sarcoma. Adv Radiat Oncol 2019; 4:413-421. [PMID: 31011687 PMCID: PMC6460235 DOI: 10.1016/j.adro.2019.02.003] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2018] [Accepted: 02/12/2019] [Indexed: 11/21/2022] Open
Abstract
PURPOSE Soft tissue sarcomas (STS) represent a heterogeneous group of diseases, and selection of individualized treatments remains a challenge. The goal of this study was to determine whether radiomic features extracted from magnetic resonance (MR) images are independently associated with overall survival (OS) in STS. METHODS AND MATERIALS This study analyzed 2 independent cohorts of adult patients with stage II-III STS treated at center 1 (N = 165) and center 2 (N = 61). Thirty radiomic features were extracted from pretreatment T1-weighted contrast-enhanced MR images. Prognostic models for OS were derived on the center 1 cohort and validated on the center 2 cohort. Clinical-only (C), radiomics-only (R), and clinical and radiomics (C+R) penalized Cox models were constructed. Model performance was assessed using Harrell's concordance index. RESULTS In the R model, tumor volume (hazard ratio [HR], 1.5) and 4 texture features (HR, 1.1-1.5) were selected. In the C+R model, both age (HR, 1.4) and grade (HR, 1.7) were selected along with 5 radiomic features. The adjusted c-indices of the 3 models ranged from 0.68 (C) to 0.74 (C+R) in the derivation cohort and 0.68 (R) to 0.78 (C+R) in the validation cohort. The radiomic features were independently associated with OS in the validation cohort after accounting for age and grade (HR, 2.4; P = .009). CONCLUSIONS This study found that radiomic features extracted from MR images are independently associated with OS when accounting for age and tumor grade. The overall predictive performance of 3-year OS using a model based on clinical and radiomic features was replicated in an independent cohort. Optimal models using clinical and radiomic features could improve personalized selection of therapy in patients with STS.
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Affiliation(s)
- Matthew B. Spraker
- Department of Radiation Oncology, Washington University in St. Louis, St. Louis, Missouri
| | - Landon S. Wootton
- Department of Radiation Oncology, University of Washington, Seattle, Washington
| | - Daniel S. Hippe
- Department of Radiology, University of Washington, Seattle, Washington
| | - Kevin C. Ball
- Aurora St. Luke's Medical Center, Department of Diagnostic Radiology, Milwaukee, Wisconsin
| | - Jan C. Peeken
- Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Institute of Innovative Radiation therapy, Department of Radiation Sciences, Helmholtz Zentrum München, Neuherberg, Germany
- Deutsches Konsortium für Translationale Krebsforschung, Munich, Germany
| | - Meghan W. Macomber
- Department of Radiation Oncology, University of Washington, Seattle, Washington
| | - Tobias R. Chapman
- Beth Israel Deaconess Medical Center, Department of Radiation Oncology, Harvard Medical School, Boston, Massachusetts
| | - Michael N. Hoff
- Department of Radiology, University of Washington, Seattle, Washington
| | - Edward Y. Kim
- Department of Radiation Oncology, University of Washington, Seattle, Washington
| | - Seth M. Pollack
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
- Division of Medical Oncology, University of Washington, Seattle, Washington
| | - Stephanie E. Combs
- Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Matthew J. Nyflot
- Department of Radiation Oncology, University of Washington, Seattle, Washington
- Department of Radiology, University of Washington, Seattle, Washington
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Vallières M, Serban M, Benzyane I, Ahmed Z, Xing S, El Naqa I, Levesque IR, Seuntjens J, Freeman CR. Investigating the role of functional imaging in the management of soft-tissue sarcomas of the extremities. PHYSICS & IMAGING IN RADIATION ONCOLOGY 2018; 6:53-60. [PMID: 33458389 PMCID: PMC7807871 DOI: 10.1016/j.phro.2018.05.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/14/2017] [Revised: 04/06/2018] [Accepted: 05/08/2018] [Indexed: 11/16/2022]
Abstract
Background and purpose In this work, we validate a texture-based model computed from positron emission tomography (PET) and magnetic resonance imaging (MRI) for the prediction of lung metastases in soft-tissue sarcomas (STS). We explore functional imaging at different treatment time points and evaluate the feasibility of radiotherapy dose painting as a potential treatment strategy for patients with higher metastatic risk. Materials and methods We acquired fluorodeoxyglucose (FDG)-PET, fluoromisonidazole (FMISO)-PET, diffusion weighting (DW)-MRI and dynamic contrast enhanced (DCE)-MRI data for 18 patients with extremity STS before, during, and after pre-operative radiotherapy. We tested the lung metastases prediction model using pre-treatment images. We evaluated the feasibility of dose painting using volumetric arc therapy (VMAT) via treatment re-planning with a prescription of 50 Gy to the planning target volume (PTV50Gy) and boost doses of 60 Gy to the FDG hypermetabolic gross tumour volume (GTV60Gy) and 65 Gy to the low-perfusion DCE-MRI hypoxic GTV contained within the GTV60Gy (GTV65Gy). Results The texture-based model for lung metastases prediction reached an area under the curve (AUC), sensitivity, specificity and accuracy of 0.71, 0.75, 0.85 and 0.82, respectively. Dose painting resulted in adequate coverage and homogeneity in the re-planned treatments: D95% to the PTV50Gy, GTV60Gy and GTV65Gy were 50.0 Gy, 60.3 Gy and 65.4 Gy, respectively. Conclusions Textural biomarkers extracted from FDG-PET and MRI could be useful to identify STS patients that might benefit from dose escalation. The feasibility of treatment planning with double boost levels to intratumoural GTV functional sub-volumes was established.
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Affiliation(s)
- Martin Vallières
- Medical Physics Unit, McGill University, Cedars Cancer Centre, McGill University Health Centre – Glen Site, 1001 boulevard Décarie, Montréal, QC H4A 3J1, Canada
- Corresponding author.
| | - Monica Serban
- Medical Physics Unit, McGill University, Cedars Cancer Centre, McGill University Health Centre – Glen Site, 1001 boulevard Décarie, Montréal, QC H4A 3J1, Canada
| | - Ibtissam Benzyane
- Medical Physics Unit, McGill University, Cedars Cancer Centre, McGill University Health Centre – Glen Site, 1001 boulevard Décarie, Montréal, QC H4A 3J1, Canada
| | - Zaki Ahmed
- Medical Physics Unit, McGill University, Cedars Cancer Centre, McGill University Health Centre – Glen Site, 1001 boulevard Décarie, Montréal, QC H4A 3J1, Canada
| | - Shu Xing
- Medical Physics Unit, McGill University, Cedars Cancer Centre, McGill University Health Centre – Glen Site, 1001 boulevard Décarie, Montréal, QC H4A 3J1, Canada
| | - Issam El Naqa
- Department of Radiation Oncology, Physics Division, University of Michigan, 519 W. Williman St. Argus Bldg, Ann Arbor, MI 48103-4943, USA
| | - Ives R. Levesque
- Medical Physics Unit, McGill University, Cedars Cancer Centre, McGill University Health Centre – Glen Site, 1001 boulevard Décarie, Montréal, QC H4A 3J1, Canada
- Research Institute of the McGill University Health Centre, 1001 boulevard Décarie, Montréal, QC H4A 3J1, Canada
| | - Jan Seuntjens
- Medical Physics Unit, McGill University, Cedars Cancer Centre, McGill University Health Centre – Glen Site, 1001 boulevard Décarie, Montréal, QC H4A 3J1, Canada
- Research Institute of the McGill University Health Centre, 1001 boulevard Décarie, Montréal, QC H4A 3J1, Canada
| | - Carolyn R. Freeman
- Research Institute of the McGill University Health Centre, 1001 boulevard Décarie, Montréal, QC H4A 3J1, Canada
- Department of Radiation Oncology, Cedars Cancer Centre, McGill University Health Centre – Glen Site, 1001 boulevard Décarie, Montréal, QC H4A 3J1, Canada
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Macpherson RE, Pratap S, Tyrrell H, Khonsari M, Wilson S, Gibbons M, Whitwell D, Giele H, Critchley P, Cogswell L, Trent S, Athanasou N, Bradley KM, Hassan AB. Retrospective audit of 957 consecutive 18F-FDG PET-CT scans compared to CT and MRI in 493 patients with different histological subtypes of bone and soft tissue sarcoma. Clin Sarcoma Res 2018; 8:9. [PMID: 30116519 PMCID: PMC6086048 DOI: 10.1186/s13569-018-0095-9] [Citation(s) in RCA: 57] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2017] [Accepted: 02/26/2018] [Indexed: 12/22/2022] Open
Abstract
Background The use of 18F-FDG PET–CT (PET–CT) is widespread in many cancer types compared to sarcoma. We report a large retrospective audit of PET–CT in bone and soft tissue sarcoma with varied grade in a single multi-disciplinary centre. We also sought to answer three questions. Firstly, the correlation between sarcoma sub-type and grade with 18FDG SUVmax, secondly, the practical uses of PET–CT in the clinical setting of staging (during initial diagnosis), restaging (new baseline prior to definitive intervention) and treatment response. Finally, we also attempted to evaluate the potential additional benefit of PET–CT over concurrent conventional CT and MRI. Methods A total of 957 consecutive PET–CT scans were performed in a single supra-regional centre in 493 sarcoma patients (excluding GIST) between 2007 and 2014. We compared, PET–CT SUVmax values in relation to histology and FNCCC grading. We compared PET–CT findings relative to concurrent conventional imaging (MRI and CT) in staging, restaging and treatment responses. Results High-grade (II/III) bone and soft tissue sarcoma correlated with high SUVmax, especially undifferentiated pleomorphic sarcoma, leiomyosarcoma, translocation induced sarcomas (Ewing, synovial, alveolar rhabdomyosarcoma), de-differentiated liposarcoma and osteosarcoma. Lower SUVmax values were observed in sarcomas of low histological grade (grade I), and in rare subtypes of intermediate grade soft tissue sarcoma (e.g. alveolar soft part sarcoma and solitary fibrous tumour). SUVmax variation was noted in malignant peripheral nerve sheath tumours, compared to the histologically benign plexiform neurofibroma, whereas PET–CT could clearly differentiate low from high-grade chondrosarcoma. We identified added utility of PET–CT in addition to MRI and CT in high-grade sarcoma of bone and soft tissues. An estimated 21% overall potential benefit was observed for PET–CT over CT/MRI, and in particular, in ‘upstaging’ of high-grade disease (from M0 to M1) where an additional 12% of cases were deemed M1 following PET–CT. Conclusions PET–CT in high-grade bone and soft tissue sarcoma can add significant benefit to routine CT/MRI staging. Further prospective and multi-centre evaluation of PET–CT is warranted to determine the actual predictive value and cost-effectiveness of PET–CT in directing clinical management of clinically complex and heterogeneous high-grade sarcomas.
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Affiliation(s)
- Ruth E Macpherson
- 1Oxford Sarcoma Service (OxSarc), Oxford University Hospitals Foundation Trust, Oxford, OX3 7LE UK.,2Department of Radiology, Oxford University Hospitals Foundation Trust, Oxford, OX3 7LE UK
| | - Sarah Pratap
- 1Oxford Sarcoma Service (OxSarc), Oxford University Hospitals Foundation Trust, Oxford, OX3 7LE UK.,3Department of Oncology, Churchill Hospital, Oxford University Hospitals Foundation Trust, Oxford, OX3 7LE UK
| | - Helen Tyrrell
- 3Department of Oncology, Churchill Hospital, Oxford University Hospitals Foundation Trust, Oxford, OX3 7LE UK
| | - Mehrdad Khonsari
- 2Department of Radiology, Oxford University Hospitals Foundation Trust, Oxford, OX3 7LE UK
| | - Shaun Wilson
- 1Oxford Sarcoma Service (OxSarc), Oxford University Hospitals Foundation Trust, Oxford, OX3 7LE UK.,5Department of Paediatric Oncology, Oxford University Hospitals Foundation Trust, Oxford, OX3 7LE UK
| | - Max Gibbons
- 1Oxford Sarcoma Service (OxSarc), Oxford University Hospitals Foundation Trust, Oxford, OX3 7LE UK.,4Nuffield Orthopaedic Centre, Oxford University Hospitals Foundation Trust, Oxford, OX3 7LE UK
| | - Duncan Whitwell
- 1Oxford Sarcoma Service (OxSarc), Oxford University Hospitals Foundation Trust, Oxford, OX3 7LE UK.,4Nuffield Orthopaedic Centre, Oxford University Hospitals Foundation Trust, Oxford, OX3 7LE UK
| | - Henk Giele
- 1Oxford Sarcoma Service (OxSarc), Oxford University Hospitals Foundation Trust, Oxford, OX3 7LE UK.,4Nuffield Orthopaedic Centre, Oxford University Hospitals Foundation Trust, Oxford, OX3 7LE UK
| | - Paul Critchley
- 1Oxford Sarcoma Service (OxSarc), Oxford University Hospitals Foundation Trust, Oxford, OX3 7LE UK.,4Nuffield Orthopaedic Centre, Oxford University Hospitals Foundation Trust, Oxford, OX3 7LE UK
| | - Lucy Cogswell
- 1Oxford Sarcoma Service (OxSarc), Oxford University Hospitals Foundation Trust, Oxford, OX3 7LE UK.,4Nuffield Orthopaedic Centre, Oxford University Hospitals Foundation Trust, Oxford, OX3 7LE UK
| | - Sally Trent
- 1Oxford Sarcoma Service (OxSarc), Oxford University Hospitals Foundation Trust, Oxford, OX3 7LE UK.,3Department of Oncology, Churchill Hospital, Oxford University Hospitals Foundation Trust, Oxford, OX3 7LE UK
| | - Nick Athanasou
- 1Oxford Sarcoma Service (OxSarc), Oxford University Hospitals Foundation Trust, Oxford, OX3 7LE UK.,4Nuffield Orthopaedic Centre, Oxford University Hospitals Foundation Trust, Oxford, OX3 7LE UK.,6NIHR Musculoskeletal Biomedical Research Unit (Sarcoma Theme), Sarcoma and TYA Unit of the NHS Oncology Department, and Sir William Dunn School of Pathology, University of Oxford, South Parks Road, Oxford, OX1 3RE UK
| | - Kevin M Bradley
- 1Oxford Sarcoma Service (OxSarc), Oxford University Hospitals Foundation Trust, Oxford, OX3 7LE UK.,2Department of Radiology, Oxford University Hospitals Foundation Trust, Oxford, OX3 7LE UK
| | - A Bassim Hassan
- 1Oxford Sarcoma Service (OxSarc), Oxford University Hospitals Foundation Trust, Oxford, OX3 7LE UK.,3Department of Oncology, Churchill Hospital, Oxford University Hospitals Foundation Trust, Oxford, OX3 7LE UK.,6NIHR Musculoskeletal Biomedical Research Unit (Sarcoma Theme), Sarcoma and TYA Unit of the NHS Oncology Department, and Sir William Dunn School of Pathology, University of Oxford, South Parks Road, Oxford, OX1 3RE UK
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16
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Clinical overview of the current state and future applications of positron emission tomography in bone and soft tissue sarcoma. Clin Transl Imaging 2017. [DOI: 10.1007/s40336-017-0236-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
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Platzek I, Beuthien-Baumann B, Schramm G, Maus J, Laniado M, Kotzerke J, van den Hoff J, Schuler M. FDG PET/MR in initial staging of sarcoma: Initial experience and comparison with conventional imaging. Clin Imaging 2017; 42:126-132. [DOI: 10.1016/j.clinimag.2016.11.016] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2016] [Revised: 11/10/2016] [Accepted: 11/28/2016] [Indexed: 12/15/2022]
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18
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Chen L, Wu X, Ma X, Guo L, Zhu C, Li Q. Prognostic value of 18F-FDG PET-CT-based functional parameters in patients with soft tissue sarcoma: A meta-analysis. Medicine (Baltimore) 2017; 96:e5913. [PMID: 28178131 PMCID: PMC5312988 DOI: 10.1097/md.0000000000005913] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Considering the clinical importance of high 5-year mortality, we performed a meta-analysis of maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) from F-FDG PET-CT for overall survival (OS) and progression-free survival (PFS) in patients with soft tissue sarcoma. METHODS The search and selection of eligible articles was conducted on PubMed and EMBASE. We applied hazard ratio (HR) and odd ratio (OR) to measure the correlation between SUVmax, MTV, and TLG with PFS and OS. The SUVmax was analyzed through subgroup in terms of histological grade and HR of posttreatment SUVmax was also assessed. RESULTS Eleven studies with 582 patients were included. The pooled HRs of pretreatment SUVmax were 2.40 (95% CI: 1.38-4.17) for OS and 2.20 (95% CI: 1.47-3.30) for PFS. The HRs in terms of OS were 3.20 (95% CI: 1.71-5.98) based on MTV and 5.20 (95% CI: 2.34-11.56) based on TLG. Meanwhile, the predict results of pretreatment SUVmax on OR remained significant and the HRs of posttreatment SUVmax were 2.25 (95% CI: 1.33-3.80) for OS and 2.87 (95% CI: 1.81-4.55) for PFS. CONCLUSIONS The pretreatment SUVmax, MTV, and TLG of F-FDG PET-CT showed significant prognostic value for OS and the PET-CT can be used in identifying high-risk patients about progression and survival. The analysis for posttreatment SUVmax suggested PET-CT as a promising equipment in monitoring therapy response.
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Affiliation(s)
- Linyan Chen
- State Key Laboratory of Biotherapy and Cancer Center
| | - Xin Wu
- Department of Head and Neck Cancer, Cancer Center, West China Hospital, Sichuan University, Chengdu, PR China
| | - Xuelei Ma
- State Key Laboratory of Biotherapy and Cancer Center
| | - Linghong Guo
- State Key Laboratory of Biotherapy and Cancer Center
| | - Chenjing Zhu
- State Key Laboratory of Biotherapy and Cancer Center
| | - Qingfang Li
- State Key Laboratory of Biotherapy and Cancer Center
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Li YJ, Dai YL, Cheng YS, Zhang WB, Tu CQ. Positron emission tomography (18)F-fluorodeoxyglucose uptake and prognosis in patients with bone and soft tissue sarcoma: A meta-analysis. EUROPEAN JOURNAL OF SURGICAL ONCOLOGY 2016; 42:1103-14. [PMID: 27189833 DOI: 10.1016/j.ejso.2016.04.056] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2016] [Revised: 04/04/2016] [Accepted: 04/08/2016] [Indexed: 02/05/2023]
Abstract
PURPOSE To investigate the prognostic significance of (18)F-FDG PET imaging in patients with bone and soft tissue sarcoma, a meta-analysis was conducted. METHODS Comprehensive literature searches were performed in PubMed, Embase, Web of Science and Cochrane Library. Pooled hazard ratio (HR) values were calculated to assess the correlations of pre-chemotherapy SUV (SUV1), post-chemotherapy SUV (SUV2), SUV Ratio, total lesion glycolysis (TLG) and metabolic tumor volume (MTV) with event-free survival (EFS) and overall survival (OS). RESULTS Twenty-three studies with 1261 patients were identified. The combined HRs for EFS were 1.84 (95% CI: 1.54-2.20) for SUV1, 2.92 (95% CI: 2.15-3.97) for SUV2, 1.90 (95% CI: 1.43-2.52) for SUV Ratio, 3.01 (95% CI: 1.36-6.67) for TLG and 2.32 (95% CI: 1.44-3.75) for MTV. The pooled HRs for OS were 1.85 (95% CI: 1.49-2.30) for SUV1, 2.00 (95% CI: 1.39-2.88) for SUV2, 2.20 (95% CI: 1.18-4.10) for SUV Ratio, 6.19 (95% CI: 2.17-17.66) for TLG and 2.67 (95% CI: 1.52-4.68) for MTV. Besides, high SUV1 was found to be significantly associated with higher rate of metastasis (RR 5.55, 95% CI: 2.75-11.18) and local recurrence (RR 1.87 95% CI: 1.28-2.72). CONCLUSION (18)F-FDG PET parameters of SUV1, SUV2, SUV Ratio, TLG and MTV may have effective prognostic significance for patients with bone and soft tissue sarcoma. (18)F-FDG PET imaging may be a promising tool to help predict survival outcomes of these patients.
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Affiliation(s)
- Y-J Li
- Department of Orthopedics, West China Hospital, Sichuan University, Chengdu, PR China; Department of Cancer Center, West China Hospital, Sichuan University, Chengdu, PR China.
| | - Y-L Dai
- College of Computer Science, Sichuan Normal University, Chengdu, PR China
| | - Y-S Cheng
- Department of Orthopedics, West China Hospital, Sichuan University, Chengdu, PR China
| | - W-B Zhang
- Department of Orthopedics, West China Hospital, Sichuan University, Chengdu, PR China
| | - C-Q Tu
- Department of Orthopedics, West China Hospital, Sichuan University, Chengdu, PR China.
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Kubo T, Furuta T, Johan MP, Ochi M. Prognostic significance of (18)F-FDG PET at diagnosis in patients with soft tissue sarcoma and bone sarcoma; systematic review and meta-analysis. Eur J Cancer 2016; 58:104-11. [PMID: 26990930 DOI: 10.1016/j.ejca.2016.02.007] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2015] [Revised: 01/25/2016] [Accepted: 02/09/2016] [Indexed: 01/08/2023]
Abstract
PURPOSE The usefulness of (18)F-fluorodeoxyglucose positron emission tomography ((18)F-FDG PET) for the survival prognosis in soft tissue sarcoma (STS) and bone sarcoma (BS) is controversial. The objective of this systematic review was to provide an up-to-date and unprecedented summary of the prognostic value of (18)F-FDG PET at diagnosis in STS and BS. METHODS Studies evaluating pre-treatment (18)F-FDG PET for overall survival of STS and BS were systematically searched for in MEDLINE, EMBASE, and Web of Science. Comparative analyses of the pooled hazard ratios (HR) of overall survival were performed between patients with high and low maximum standardised uptake value (SUVmax). The quality of study designs was evaluated using the Newcastle-Ottawa scale (NOS) for quality assessment of cohort studies. P < 0.05 was defined as statistically significant. RESULTS A total of six studies comprising 514 patients with STS and BS were considered for the meta-analysis. The pooled HR for overall survival was 1.22 (95% confidence interval: 1.03-1.46), suggesting that high SUVmax predicts a significantly shorter overall survival period than low SUVmax (P = 0.03). Additional subgroup analyses using patients with STS alone showed that high SUVmax might predict poorer overall survival than low SUVmax (P = 0.004), although only two studies consisting of 96 patients were included. The overall quality of the included studies evaluated by the NOS assessment was adequate. CONCLUSION (18)F-FDG PET at diagnosis provides a very useful predictive tool for patients with STS and BS.
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Affiliation(s)
- Tadahiko Kubo
- Department of Orthopaedic Surgery, Graduate School of Biomedical Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan.
| | - Taisuke Furuta
- Department of Orthopaedic Surgery, Graduate School of Biomedical Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan.
| | - Muhammad P Johan
- Department of Orthopaedic Surgery, Graduate School of Biomedical Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan.
| | - Mitsuo Ochi
- Department of Orthopaedic Surgery, Graduate School of Biomedical Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan.
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Andersen KF, Fuglo HM, Rasmussen SH, Petersen MM, Loft A. Volume-Based F-18 FDG PET/CT Imaging Markers Provide Supplemental Prognostic Information to Histologic Grading in Patients With High-Grade Bone or Soft Tissue Sarcoma. Medicine (Baltimore) 2015; 94:e2319. [PMID: 26705220 PMCID: PMC4697986 DOI: 10.1097/md.0000000000002319] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
The aim of the study is to assess the prognostic value of different volume-based calculations of tumor metabolic activity in the initial assessment of patients with high-grade bone sarcomas (BS) and soft tissue sarcomas (STS) using F-18 FDG PET/CT.A single-site, retrospective study from 2002 to 2012 including 92 patients with histologically verified high-grade BS (N = 37) or STS (N = 55). All patients underwent a pretreatment F-18 FDG PET/CT scan. Clinical data were registered. Measurements of the accuracy of metabolic tumor volume with a preset threshold of 40% of the maximum standardized uptake value of primary tumor (MTV40%) and total lesion glycolysis (TLG) as prognostic variables and identification of optimal discriminating cut-off values were performed through ROC curve analysis. Patients were grouped according to the cut-off values. All deaths were considered an event in survival analysis. Kaplan-Meier survival estimates and log-rank test were used to compare the degree of equality of survival distributions. Prognostic variables with related hazard ratios (HR) were assessed using Cox proportional hazards regression analysis.Forty-one of 92 patients died during follow-up (45%; 12 BS and 29 STS). Average survival for included patients was 6.5 years (95% CI 5.8-7.3 years) and probability of 5-year survival was 52%. There was a high-significant accuracy of TLG and MTV40% as prognostic variables when looking on all patients and during subgroup analysis. AUCs were higher for TLG than for MTV40%. TLG above optimal cut-off value was the only variable which was independently prognostic for survival throughout multivariate regression analysis of all included patients (P = 0.01, HR 4.78 [95% CI 1.45-15.87]) and subgroup analysis (BS: P = 0.04, HR 11.11 [95% CI 1.09-111.11]; STS: P < 0.05, HR 3.37 [95% CI 1.02-11.11]). No significant results were demonstrated for MTV40%.Volume-based F-18 FDG PET/CT imaging markers in terms of pretreatment estimation of TLG provide supplemental prognostic information to histologic grading, with significant independent properties for prediction of overall survival in patients with high-grade BS or STS.
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Affiliation(s)
- Kim Francis Andersen
- From the Department of Clinical Physiology, Nuclear Medicine & PET (KFA, SHR, AL); and Department of Orthopedic Surgery, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark (HMF, MMP)
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Andersen KF, Fuglo HM, Rasmussen SH, Petersen MM, Loft A. Semi-Quantitative Calculations of Primary Tumor Metabolic Activity Using F-18 FDG PET/CT as a Predictor of Survival in 92 Patients With High-Grade Bone or Soft Tissue Sarcoma. Medicine (Baltimore) 2015; 94:e1142. [PMID: 26181552 PMCID: PMC4617075 DOI: 10.1097/md.0000000000001142] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
To assess the prognostic value of primary tumor metabolic activity in patients with high-grade bone sarcomas (BS) or soft tissue sarcomas (STS) using F-18 FDG PET/CT. A single-site, retrospective study including 92 patients with high-grade BS or STS. Pretreatment F-18 FDG PET/CT scan was performed. Clinical data were registered. Accuracy of maximum standardized uptake value of primary tumor (SUVmax) and tumor-to-background (T/B) uptake ratio as prognostic variables and identification of cut-off values to group patients were determined. Kaplan-Meier survival estimates and log-rank test were used to compare survival distributions. Prognostic variables were assessed using Cox proportional hazards regression analysis. Forty-one of 92 patients died during follow-up (45%). Average survival was 6.5 years (95% CI 5.8-7.3 years) and probability of 5-year survival was 52%. Accuracy of SUVmax and T/B uptake ratio as prognostic variables in all patients and during subgroup analysis of patients with STS was significant. No significant results for AUCs were registered in patients with BS. Surgery was independently prognostic for survival throughout multivariate regression analysis of all patients (P = 0.001, HR 3.84) and subgroup analysis (BS: P = 0.02, HR 11.62; STS: P = 0.005, HR 4.13). SUVmax was significant as prognostic variable in all patients (P = 0.02, HR 3.66) and in patients with STS (P = 0.007, HR 3.75). No significant results were demonstrated for T/B uptake ratio. Estimation of primary tumor metabolic activity with pretherapeutic SUVmax using F-18 FDG PET/CT demonstrates independent properties beyond histologic grading for prediction of survival in patients with high-grade STS, but not with high-grade BS.
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Affiliation(s)
- Kim Francis Andersen
- From the Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, Copenhagen University Hospital (KFA, SHR, AL); and Department of Orthopedic Surgery, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark (HMF, MMP)
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Vallières M, Freeman CR, Skamene SR, El Naqa I. A radiomics model from joint FDG-PET and MRI texture features for the prediction of lung metastases in soft-tissue sarcomas of the extremities. Phys Med Biol 2015; 60:5471-96. [PMID: 26119045 DOI: 10.1088/0031-9155/60/14/5471] [Citation(s) in RCA: 560] [Impact Index Per Article: 62.2] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
This study aims at developing a joint FDG-PET and MRI texture-based model for the early evaluation of lung metastasis risk in soft-tissue sarcomas (STSs). We investigate if the creation of new composite textures from the combination of FDG-PET and MR imaging information could better identify aggressive tumours. Towards this goal, a cohort of 51 patients with histologically proven STSs of the extremities was retrospectively evaluated. All patients had pre-treatment FDG-PET and MRI scans comprised of T1-weighted and T2-weighted fat-suppression sequences (T2FS). Nine non-texture features (SUV metrics and shape features) and forty-one texture features were extracted from the tumour region of separate (FDG-PET, T1 and T2FS) and fused (FDG-PET/T1 and FDG-PET/T2FS) scans. Volume fusion of the FDG-PET and MRI scans was implemented using the wavelet transform. The influence of six different extraction parameters on the predictive value of textures was investigated. The incorporation of features into multivariable models was performed using logistic regression. The multivariable modeling strategy involved imbalance-adjusted bootstrap resampling in the following four steps leading to final prediction model construction: (1) feature set reduction; (2) feature selection; (3) prediction performance estimation; and (4) computation of model coefficients. Univariate analysis showed that the isotropic voxel size at which texture features were extracted had the most impact on predictive value. In multivariable analysis, texture features extracted from fused scans significantly outperformed those from separate scans in terms of lung metastases prediction estimates. The best performance was obtained using a combination of four texture features extracted from FDG-PET/T1 and FDG-PET/T2FS scans. This model reached an area under the receiver-operating characteristic curve of 0.984 ± 0.002, a sensitivity of 0.955 ± 0.006, and a specificity of 0.926 ± 0.004 in bootstrapping evaluations. Ultimately, lung metastasis risk assessment at diagnosis of STSs could improve patient outcomes by allowing better treatment adaptation.
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Affiliation(s)
- M Vallières
- Medical Physics Unit, McGill University, 845 Rue Sherbrooke O, Montreal QC H3A 0G4, Canada
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