Abstract
Objectives
To perform a systematic review regarding the developments in the field of radiomics in lymphoma. To evaluate the quality of included articles by the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2), the phases classification criteria for image mining studies, and the radiomics quality scoring (RQS) tool.
Methods
We searched for eligible articles in the MEDLINE/PubMed and EMBASE databases using the terms “radiomics”, “texture” and “lymphoma”. The included studies were divided into two categories: diagnosis-, therapy response- and outcome-related studies. The diagnosis-related studies were evaluated using the QUADAS-2; all studies were evaluated using the phases classification criteria for image mining studies and the RQS tool by two reviewers.
Results
Forty-five studies were included; thirteen papers (28.9%) focused on the differential diagnosis of primary central nervous system lymphoma (PCNSL) and glioblastoma (GBM). Thirty-two (71.1%) studies were classified as discovery science according to the phase classification criteria for image mining studies. The mean RQS score of all studies was 14.2% (ranging from 0.0 to 40.3%), and 23 studies (51.1%) were given a score of < 10%.
Conclusion
The radiomics features could serve as diagnostic and prognostic indicators in lymphoma. However, the current conclusions should be interpreted with caution due to the suboptimal quality of the studies. In order to introduce radiomics into lymphoma clinical settings, the lesion segmentation and selection, the influence of the pathological pattern and the extraction of multiple modalities and multiple time points features need to be further studied.
Key Points
• The radiomics approach may provide useful information for diagnosis, prediction of the therapy response, and outcome of lymphoma.
• The quality of published radiomics studies in lymphoma has been suboptimal to date.
• More studies are needed to examine lesion selection and segmentation, the influence of pathological patterns, and the extraction of multiple modalities and multiple time point features.
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Abbreviations
- AUC:
-
Area under the curve
- CT:
-
Computed tomography
- DLBCL:
-
Diffuse large B cell lymphoma
- GBM:
-
Glioblastoma
- HL:
-
Hodgkin’s lymphoma
- MRI:
-
Magnetic resonance imaging
- NHL:
-
Non-Hodgkin’s lymphoma
- PCNSL:
-
Primary central nervous system lymphoma
- PET:
-
Positron emission tomography
- QUADAS-2:
-
The Quality Assessment of Diagnostic Accuracy Studies-2
- RQS:
-
Radiomics quality scoring
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This study has received funding from the Key Projects of the Ministry of Science and Technology (grant 2017YFC0113304).
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The scientific guarantor of this publication is Rong Tian, PhD.
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Wang, H., Zhou, Y., Li, L. et al. Current status and quality of radiomics studies in lymphoma: a systematic review. Eur Radiol 30, 6228–6240 (2020). https://doi.org/10.1007/s00330-020-06927-1
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DOI: https://doi.org/10.1007/s00330-020-06927-1