Diagnostic value of magnetic resonance imaging radiomics and machine-learning in grading soft tissue sarcoma: a mini-review on the current state
Soft tissue sarcomas (STS) are a heterogeneous group of rare malignant tumors. Tumor grade might be underestimated in biopsy due to intratumoral heterogeneity. This mini-review aims to present the current state of predicting malignancy grades of STS through radiomics, machine learning, and deep lear...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
January 2025
|
| In: |
Academic radiology
Year: 2025, Jahrgang: 32, Heft: 1, Pages: 311-315 |
| ISSN: | 1878-4046 |
| DOI: | 10.1016/j.acra.2024.08.035 |
| Online-Zugang: | Verlag, kostenfrei, Volltext: https://doi.org/10.1016/j.acra.2024.08.035 Verlag, kostenfrei, Volltext: https://www.sciencedirect.com/science/article/pii/S1076633224005981 
|
| Verfasserangaben: | Fabian Schmitz, Sam Sedaghat |
MARC
| LEADER | 00000naa a2200000 c 4500 | ||
|---|---|---|---|
| 001 | 1931684073 | ||
| 003 | DE-627 | ||
| 005 | 20250724081550.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 250724s2025 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1016/j.acra.2024.08.035 |2 doi | |
| 035 | |a (DE-627)1931684073 | ||
| 035 | |a (DE-599)KXP1931684073 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rda | ||
| 041 | |a eng | ||
| 084 | |a 33 |2 sdnb | ||
| 100 | 1 | |a Schmitz, Fabian |e VerfasserIn |0 (DE-588)1357675372 |0 (DE-627)1918585210 |4 aut | |
| 245 | 1 | 0 | |a Diagnostic value of magnetic resonance imaging radiomics and machine-learning in grading soft tissue sarcoma |b a mini-review on the current state |c Fabian Schmitz, Sam Sedaghat |
| 264 | 1 | |c January 2025 | |
| 300 | |b Illustrationen | ||
| 300 | |a 5 | ||
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a Computermedien |b c |2 rdamedia | ||
| 338 | |a Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Online verfügbar: 10. September 2024, Artikelversion: 16. Januar 2025 | ||
| 500 | |a Gesehen am 24.07.2025 | ||
| 520 | |a Soft tissue sarcomas (STS) are a heterogeneous group of rare malignant tumors. Tumor grade might be underestimated in biopsy due to intratumoral heterogeneity. This mini-review aims to present the current state of predicting malignancy grades of STS through radiomics, machine learning, and deep learning on magnetic resonance imaging (MRI). Several studies investigated various machine-learning and deep-learning approaches in T2-weighted (w) images, contrast-enhanced (CE) T1w images, and DWI/ADC maps with promising results. Combining semantic imaging features, radiomics features, and deep-learning signatures in machine-learning models has demonstrated superior predictive performances compared to individual feature sources. Furthermore, incorporating features from both tumor volume and peritumor region is beneficial. Especially random forest and support vector machine classifiers, often combined with the least absolute shrinkage and selection operator (LASSO) and/or synthetic minority oversampling technique (SMOTE), did show high area under the curve (AUC) values and accuracies in existing studies. | ||
| 650 | 4 | |a Deep learning | |
| 650 | 4 | |a Machine learning | |
| 650 | 4 | |a MRI | |
| 650 | 4 | |a Radiomics | |
| 650 | 4 | |a Soft tissue sarcoma | |
| 700 | 1 | |a Sedaghat, Sam |d 1986- |e VerfasserIn |0 (DE-588)1074259270 |0 (DE-627)831927860 |0 (DE-576)441954480 |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Academic radiology |d Philadelphia, PA [u.a.] : Elsevier, 1994 |g 32(2025), 1 vom: Jan., Seite 311-315 |h Online-Ressource |w (DE-627)331018667 |w (DE-600)2050425-1 |w (DE-576)271497602 |x 1878-4046 |7 nnas |a Diagnostic value of magnetic resonance imaging radiomics and machine-learning in grading soft tissue sarcoma a mini-review on the current state |
| 773 | 1 | 8 | |g volume:32 |g year:2025 |g number:1 |g month:01 |g pages:311-315 |g extent:5 |a Diagnostic value of magnetic resonance imaging radiomics and machine-learning in grading soft tissue sarcoma a mini-review on the current state |
| 856 | 4 | 0 | |u https://doi.org/10.1016/j.acra.2024.08.035 |x Verlag |x Resolving-System |z kostenfrei |3 Volltext |
| 856 | 4 | 0 | |u https://www.sciencedirect.com/science/article/pii/S1076633224005981 |x Verlag |z kostenfrei |3 Volltext |
| 951 | |a AR | ||
| 992 | |a 20250724 | ||
| 993 | |a Article | ||
| 994 | |a 2025 | ||
| 998 | |g 1074259270 |a Sedaghat, Sam |m 1074259270:Sedaghat, Sam |d 910000 |d 911400 |e 910000PS1074259270 |e 911400PS1074259270 |k 0/910000/ |k 1/910000/911400/ |p 2 |y j | ||
| 998 | |g 1357675372 |a Schmitz, Fabian |m 1357675372:Schmitz, Fabian |d 910000 |d 911400 |e 910000PS1357675372 |e 911400PS1357675372 |k 0/910000/ |k 1/910000/911400/ |p 1 |x j | ||
| 999 | |a KXP-PPN1931684073 |e 474937850X | ||
| BIB | |a Y | ||
| SER | |a journal | ||
| JSO | |a {"type":{"bibl":"article-journal","media":"Online-Ressource"},"note":["Online verfügbar: 10. September 2024, Artikelversion: 16. Januar 2025","Gesehen am 24.07.2025"],"origin":[{"dateIssuedKey":"2025","dateIssuedDisp":"January 2025"}],"title":[{"title":"Diagnostic value of magnetic resonance imaging radiomics and machine-learning in grading soft tissue sarcoma","subtitle":"a mini-review on the current state","title_sort":"Diagnostic value of magnetic resonance imaging radiomics and machine-learning in grading soft tissue sarcoma"}],"id":{"eki":["1931684073"],"doi":["10.1016/j.acra.2024.08.035"]},"recId":"1931684073","relHost":[{"language":["eng"],"part":{"volume":"32","extent":"5","pages":"311-315","year":"2025","text":"32(2025), 1 vom: Jan., Seite 311-315","issue":"1"},"title":[{"title":"Academic radiology","title_sort":"Academic radiology","subtitle":"official journal of the Association of University Radiologists, the Society of Chairs of Academic Radiology Departments, the Association of Program Directors in Radiology, the American Alliance of Academic Chief Residents in Radiology, the Alliance of Medical Student Educators in Radiology, the Radiology Research Alliance, the Radiology Alliance for Health Services Research, and the Medical Image Computing and Computer-Assisted Intervention Society"}],"pubHistory":["1.1994 -"],"origin":[{"publisher":"Elsevier ; Assoc. of University Radiologists","dateIssuedKey":"1994","dateIssuedDisp":"1994-","publisherPlace":"Philadelphia, PA [u.a.] ; Oak Brook, Ill."}],"note":["Gesehen am 18.04.17"],"type":{"bibl":"periodical","media":"Online-Ressource"},"disp":"Diagnostic value of magnetic resonance imaging radiomics and machine-learning in grading soft tissue sarcoma a mini-review on the current stateAcademic radiology","physDesc":[{"extent":"Online-Ressource"}],"recId":"331018667","id":{"eki":["331018667"],"zdb":["2050425-1"],"issn":["1878-4046"]}}],"name":{"displayForm":["Fabian Schmitz, Sam Sedaghat"]},"physDesc":[{"extent":"5 S.","noteIll":"Illustrationen"}],"person":[{"role":"aut","given":"Fabian","family":"Schmitz","display":"Schmitz, Fabian"},{"family":"Sedaghat","display":"Sedaghat, Sam","given":"Sam","role":"aut"}],"language":["eng"]} | ||
| SRT | |a SCHMITZFABDIAGNOSTIC2025 | ||