What morphological MRI features enable differentiation of low-grade from high-grade soft tissue sarcoma?

Boudabbous, Sana; Hamard, Marion; Saïji, Essia; Gorican, K; Poletti, Pierre–Alexandre; Becker, Minerva; Neroladaki, Angeliki

doi:10.1259/bjro.20210081

Cited by 4 publications

(2 citation statements)

References 39 publications

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“…In patients with lower rectal cancer, the intralesional tumor heterogeneity and therapeutic response can be predicted by diffusion-weighted MRI (DWI) [17]. Also, diagnostic MRI can be used to score heterogeneity in soft tissue sarcoma und identify them as high-or lowgrade soft tissue sarcomas [18]. A direct co-registration of DWI and histology in non-small cell lung cancer showed that an estimation of the local spatial tumor cell density can be performed based on DWI data [19].…”

Section: Imaging Markers For Intralesional Heterogeneitymentioning

confidence: 99%

Imaging-based characterization of tumoral heterogeneity for personalized cancer treatment

Haag,

Hertel,

Tharmaseelan

et al. 2023

Rofo

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With personalized tumor therapy, understanding and addressing the heterogeneity of malignant tumors is becoming increasingly important. Heterogeneity can be found within one lesion (intralesional) and between several tumor lesions emerging from one primary tumor (interlesional). The heterogeneous tumor cells may show a different response to treatment due to their biology, which in turn influences the outcome of the affected patients and the choice of therapeutic agents. Therefore, both intra- and interlesional heterogeneity should be addressed at the diagnostic stage. While genetic and biological heterogeneity are important parameters in molecular tumor characterization and in histopathology, they are not yet addressed routinely in medical imaging. This article summarizes the recently established markers for tumor heterogeneity in imaging as well as heterogeneous/mixed response to therapy. Furthermore, a look at emerging markers is given. The ultimate goal of this overview is to provide comprehensive understanding of tumor heterogeneity and its implications for radiology and for communication with interdisciplinary teams in oncology. Key points:

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Section: Imaging Markers For Intralesional Heterogeneitymentioning

confidence: 99%

Imaging-based characterization of tumoral heterogeneity for personalized cancer treatment

Haag,

Hertel,

Tharmaseelan

et al. 2023

Rofo

View full text Add to dashboard Cite

show abstract

“…Standard interpretation of STTs is based on a conventional MR sequence of T1-and T2-weighted images (T1-WI, T2-WI) and contrast-enhanced (CE)-T1-WI if contrast media is available. STTs with larger size, lobular contours, and heterogeneous components on conventional MRI are more likely to be malignant tumors, but there is no definite diagnostic qualitative criteria for diagnosis of soft tissue sarcoma because diverse subtype of soft tissue sarcoma can show various imaging findings [3][4][5]. Recently, advanced imaging techniques such as diffusion-weighted imaging (DWI), dynamic contrast-enhanced imaging, and MR spectroscopy are combined to acquire functional information including cellularity, vascularity, or metabolism [6].…”

Section: Introductionmentioning

confidence: 99%

Ensemble learning-based radiomics with multi-sequence magnetic resonance imaging for benign and malignant soft tissue tumor differentiation

Lee

Jung

et al. 2023

PLoS ONE

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Many previous studies focused on differentiating between benign and malignant soft tissue tumors using radiomics model based on various magnetic resonance imaging (MRI) sequences, but it is still unclear how to set up the input radiomic features from multiple MRI sequences. Here, we evaluated two types of radiomics models generated using different feature incorporation strategies. In order to differentiate between benign and malignant soft tissue tumors (STTs), we compared the diagnostic performance of an ensemble of random forest (R) models with single-sequence MRI inputs to R models with pooled multi-sequence MRI inputs. One-hundred twenty-five STT patients with preoperative MRI were retrospectively included and consisted of training (n = 100) and test (n = 25) sets. MRI included T1-weighted (T1-WI), T2-weighted (T2-WI), contrast-enhanced (CE)-T1-WI, diffusion-weighted images (DWIs, b = 800 sec/mm2) and apparent diffusion coefficient (ADC) maps. After tumor segmentation on each sequence, 100 original radiomic features were extracted from each sequence image and divided into three-feature sets: T features from T1- and T2-WI, CE features from CE-T1-WI, and D features from DWI and ADC maps. Four radiomics models were built using Lasso and R with four combinations of three-feature sets as inputs: T features (R-T), T+CE features (R-C), T+D features (R-D), and T+CE+D features (R-A) (Type-1 model). An ensemble model was built by soft voting of five, single-sequence-based R models (Type-2 model). AUC, sensitivity, specificity, and accuracy of each model was calculated with five-fold cross validation. In Type-1 model, AUC, sensitivity, specificity, and accuracy were 0.752, 71.8%, 61.1%, and 67.2% in R-T; 0.756, 76.1%, 70.4%, and 73.6% in R-C; 0.750, 77.5%, 63.0%, and 71.2% in R-D; and 0.749, 74.6%, 61.1%, and 68.8% R-A models, respectively. AUC, sensitivity, specificity, and accuracy of Type-2 model were 0.774, 76.1%, 68.5%, and 72.8%. In conclusion, an ensemble method is beneficial to incorporate features from multi-sequence MRI and showed diagnostic robustness for differentiating malignant STTs.

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New trends in the surgical management of soft tissue sarcoma: The role of preoperative biopsy

Pavlidis¹,

Pavlidis²

2023

World J Clin Oncol

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What morphological MRI features enable differentiation of low-grade from high-grade soft tissue sarcoma?

Cited by 4 publications

References 39 publications

Imaging-based characterization of tumoral heterogeneity for personalized cancer treatment

Imaging-based characterization of tumoral heterogeneity for personalized cancer treatment

Ensemble learning-based radiomics with multi-sequence magnetic resonance imaging for benign and malignant soft tissue tumor differentiation

New trends in the surgical management of soft tissue sarcoma: The role of preoperative biopsy

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