. 2022 Feb 14;28(6):624–634. doi: 10.3748/wjg.v28.i6.624

Table 1.

Summary of studies evaluating the role of radiomics in differentiating intraductal papillary mucinous neoplasms with advanced neoplasia

Ref.	n	Image type	No. of radiomic features	Best model	Performance training set
Hanania et al[19], United States, 2016	53	CECT	360	10 radiomic features	AUC: 0.82
Hanania et al[19], United States, 2016	53	CECT	360	10 radiomic features	SP: 85%, SP: 68%
Permuth et al[20], United States, 2016	38	CECT	112	14 radiomic features +blood 5 mi-RNAs	AUC: 0.92
Permuth et al[20], United States, 2016	38	CECT	112	14 radiomic features +blood 5 mi-RNAs	SN: 83%, SP: 89%
Attiyeh et al[21], United States, 2019	103	CECT	255	Radiomic + clinical features	AUC: 0.79
Attiyeh et al[21], United States, 2019	103	CECT	255	Radiomic + clinical features	SN: 71%, SP: 82%
Williams et al[22], United States, 2020	33	CECT	12	Radiomic features + cyst fluid protein markers	AUC: 0.88
Williams et al[22], United States, 2020	33	CECT	12	Radiomic features + cyst fluid protein markers	SN: 71%, SP: 92%
Hoffman et al[23], United States, 2017	18	MRI w/ DWI	N/A	Entropy	AUC: 0.86
Hoffman et al[23], United States, 2017	18	MRI w/ DWI	N/A	Entropy	SN: 100%; SP: 70%

HGD: High-grade dysplasia; LGD: Low-grade dysplasia; CECT: Contrast-enhanced computed tomography; MRI: Magnetic resonance imaging; mi-RNA: micro-RNA; DWI: Diffusion weighted imaging; AUC: Area under curve; SN: Sensitivity; SP: Specificity; NA: Not application.