Myxofibrosarcoma: clinical and prognostic value of MRI features

: Myxofibrosarcoma is one of the most common soft tissue sarcomas in the elderly. It is characterized by an extremely high rate of local recurrence, higher than other soft tissue tumors, and a relatively low risk of distant metastases.Magnetic resonance imaging (MRI) is the imaging modality of choice for the assessment of myxofibrosarcoma and plays a key role in the preoperative setting of these patients.MRI features associated with high risk of local recurrence are: high myxoid matrix content (water-like appearance of the lesions), high grade of contrast enhancement, presence of an infiltrative pattern (“tail sign”). On the other hand, MRI features associated with worse sarcoma specific survival are: large size of the lesion, deep location, high grade of contrast enhancement. Recognizing the above-mentioned imaging features of myxofibrosarcoma may be helpful to stratify the risk for local recurrence and disease-specific survival. Moreover, the surgical planning should be adjusted according to the MRI features

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Treatment-Induced Pathologic Necrosis: A Predictor of Local Recurrence and Survival in Patients Receiving Neoadjuvant Therapy for High-Grade Extremity Soft Tissue Sarcomas

Journal of Clinical Oncology ◽

10.1200/jco.2001.19.13.3203 ◽

2001 ◽

Vol 19 (13) ◽

pp. 3203-3209 ◽

Cited By ~ 218

Author(s):

Fritz C. Eilber ◽

Gerald Rosen ◽

Jeffery Eckardt ◽

Charles Forscher ◽

Scott D. Nelson ◽

...

Keyword(s):

Overall Survival ◽

Soft Tissue ◽

Local Recurrence ◽

Neoadjuvant Therapy ◽

Independent Predictor ◽

Survival Rates ◽

Soft Tissue Sarcomas ◽

High Grade ◽

Recurrence Rates ◽

Pathologic Assessment

PURPOSE: To determine whether treatment-induced pathologic necrosis correlates with local recurrence and overall survival in patients who receive neoadjuvant therapy for high-grade extremity soft tissue sarcomas. PATIENTS AND METHODS: Four hundred ninety-six patients with intermediate- to high-grade extremity soft tissue sarcomas received protocol neoadjuvant therapy. All patients underwent surgical resection after neoadjuvant therapy and had pathologic assessment of tumor necrosis in the resected specimens. RESULTS: The 5- and 10-year local recurrence rates for patients with ≥ 95% pathologic necrosis were significantly lower (6% and 11%, respectively) than the local recurrence rates for patients with less than 95% pathologic necrosis (17% and 23%, respectively). The 5- and 10-year survival rates for the patients with ≥ 95% pathologic necrosis were significantly higher (80% and 71%, respectively) than the survival rates for the patients with less than 95% pathologic necrosis (62% and 55%, respectively). Patients with less than 95% pathologic necrosis were 2.51 times more likely to develop a local recurrence and 1.86 times more likely to die of their disease as compared with patients with ≥ 95% pathologic necrosis. The percentage of patients who achieved ≥ 95% pathologic necrosis increased to 48% with the addition of ifosfamide as compared with 13% of the patients in all the other protocols combined. CONCLUSION: Treatment-induced pathologic necrosis is an independent predictor of both local recurrence and overall survival in patients who receive neoadjuvant therapy for high-grade extremity soft tissue sarcomas. A complete pathologic response (≥ 95% pathologic necrosis) correlated with a significantly lower rate of local recurrence and improved overall survival.

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Brainstem glioma: Prediction of histopathologic grade based on conventional MR imaging

The Neuroradiology Journal ◽

10.1177/1971400917743099 ◽

2017 ◽

Vol 31 (1) ◽

pp. 10-17 ◽

Cited By ~ 4

Author(s):

Yashar Moharamzad ◽

Morteza Sanei Taheri ◽

Farhad Niaghi ◽

Elham Shobeiri

Keyword(s):

Logistic Regression ◽

Mr Imaging ◽

Contrast Enhancement ◽

Binary Logistic Regression ◽

Binary Logistic Regression Analysis ◽

Low Grade ◽

Imaging Features ◽

High Grade ◽

Post Contrast ◽

Mri Features

Objective The objective of this article is to investigate the association between specific MR imaging findings and histopathologic grading (low-grade vs. high-grade) of brainstem gliomas (BSGs). Methods Sixty-two males and 34 females (mean (standard deviation, SD) age of 24.61 (17.20) years, range = 3 to 70 years) with histologically diagnosed BSG underwent conventional 1.5 T MR imaging, which included T1-weighted (T1W), T2W, and post-contrast T1W sequences. There were 39 children (mean age of 9.38 years) and 57 adults (mean age of 35 years). A binary logistic regression analysis was used to explore associations between MRI features and histopathological grade of the BSG. Results Binary logistic regression revealed that necrosis (adjusted odds ratio (OR) = 16.07; 95% confidence interval (CI) = 3.20 to 80.52; p = 0.001) and inhomogeneous contrast enhancement (adjusted OR = 8.04; 95% CI = 1.73 to 37.41; p = 0.008) as significant predictors of high-grade BSG. The equation (Nagelkerke R2 = 0.575) is Logit ( p high-grade BSG) = (2.77 × necrosis) + (2.08 × heterogeneous contrast enhancement) – 3.13. Sensitivity and specificity values were respectively 66.7% and 96.0% for necrosis and 85.7% and 65.9% for inhomogeneous contrast-enhancing lesions. In the pediatric age group, only inhomogeneous contrast enhancement (adjusted OR = 40; 95% CI = 3.95 to 445.73; p = 0.002) was a significant predictor for high-grade BSG. Conclusion Conventional MR imaging features such as necrosis and inhomogeneous contrast enhancement in adults and heterogeneous contrast enhancement in children suggest high-grade BSG.

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Predictors of Local Recurrence in High-grade Soft Tissue Sarcomas: Hydrogen Peroxide as a Local Adjuvant

Orthopedics ◽

10.3928/01477447-20130122-24 ◽

2013 ◽

Vol 36 (2) ◽

pp. e207-e215 ◽

Cited By ~ 4

Author(s):

Adam N. Wooldridge ◽

Gregory P. Kolovich ◽

Martha K. Crist ◽

Joel L. Mayerson ◽

Thomas J. Scharschmidt

Keyword(s):

Hydrogen Peroxide ◽

Soft Tissue ◽

Local Recurrence ◽

Soft Tissue Sarcomas ◽

High Grade

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The effect of local recurrence on survival time in adult high-grade soft tissue sarcomas

Journal of Clinical Epidemiology ◽

10.1016/0895-4356(89)90083-8 ◽

1989 ◽

Vol 42 (2) ◽

pp. 105-110 ◽

Cited By ~ 56

Author(s):

Lawrence J. Emrich ◽

Wlodzimierz Ruka ◽

Deborah L. Driscoll ◽

Constantine P. Karakousis

Keyword(s):

Soft Tissue ◽

Local Recurrence ◽

Survival Time ◽

Soft Tissue Sarcomas ◽

High Grade

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What Are Risk Factors for Local Recurrence of Deep High-grade Soft-tissue Sarcomas?

Clinical Orthopaedics and Related Research ◽

10.1007/s11999-011-2017-5 ◽

2011 ◽

Vol 470 (3) ◽

pp. 700-705 ◽

Cited By ~ 23

Author(s):

Chigusa Sawamura ◽

Seiichi Matsumoto ◽

Takashi Shimoji ◽

Taisuke Tanizawa ◽

Keisuke Ae

Keyword(s):

Risk Factors ◽

Soft Tissue ◽

Local Recurrence ◽

Soft Tissue Sarcomas ◽

High Grade

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Myxoinflammatory Fibroblastic Sarcoma: Review and Update

Archives of Pathology & Laboratory Medicine ◽

10.5858/arpa.2017-0219-ra ◽

2017 ◽

Vol 141 (11) ◽

pp. 1503-1507 ◽

Cited By ~ 6

Author(s):

David R. Lucas

Keyword(s):

Soft Tissue ◽

Local Recurrence ◽

Soft Tissue Tumor ◽

High Rate ◽

High Grade ◽

Clinicopathologic Features ◽

Molecular Features ◽

Microscopic Features ◽

Myxoinflammatory Fibroblastic Sarcoma ◽

Low Rate

Myxoinflammatory fibroblastic sarcoma is a rare soft tissue tumor with most occurring in the distal extremities of adult patients. It has a high rate of local recurrence and a low rate of metastasis. Because it may appear benign on clinical examination, and because the microscopic features are generally underrecognized, it is often inadequately treated and misdiagnosed. In this review, based upon experience and that of the literature, the intent is to highlight salient clinicopathologic features, detail the broad microscopic spectrum including high-grade aggressive variants, review the molecular features, and discuss its relation to hemosiderotic fibrolipomatous tumor.

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Predicting distant metastases in soft-tissue sarcomas from PET-CT scans using constrained hierarchical multi-modality feature learning

Physics in Medicine and Biology ◽

10.1088/1361-6560/ac3d17 ◽

2021 ◽

Author(s):

Yige Peng ◽

Lei Bi ◽

Ashnil Kumar ◽

Michael Fulham ◽

David Dagan Feng ◽

...

Keyword(s):

Soft Tissue ◽

Imaging Modality ◽

Soft Tissue Sarcomas ◽

Feature Learning ◽

Distant Metastases ◽

P Value ◽

Imaging Features ◽

Tumor Delineation ◽

Positron Emission ◽

Pet Ct

Abstract Objective: Positron emission tomography-computed tomography (PET-CT) is regarded as the imaging modality of choice for the management of soft-tissue sarcomas (STSs). Distant metastases (DM) are the leading cause of death in STS patients and early detection is important to effectively manage tumors with surgery, radiotherapy and chemotherapy. In this study, we aim to early detect DM in patients with STS using their PET-CT data. Approach: We derive a new convolutional neural network (CNN) method for early DM detection. The novelty of our method is the introduction of a constrained hierarchical multi-modality feature learning approach to integrate functional imaging (PET) features with anatomical imaging (CT) features. In addition, we removed the reliance on manual input, e.g., tumor delineation, for extracting imaging features. Main results: Our experimental results on a well-established benchmark PET-CT dataset show that our method achieved the highest accuracy (0.896) and AUC (0.903) scores when compared to the state-of-the-art methods (unpaired student’s t-test p-value < 0.05). Significance: Our method could be an effective and supportive tool to aid physicians in tumor quantification and in identifying image biomarkers for cancer treatment.

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