Additive value of texture analysis based on breast MRI for distinguishing between benign and malignant non-mass enhancement in premenopausal women

Table 4 Statistically significant texture features in the FMC method of contrast phases

Dynamic enhanced phases	Texture parameters	Z value	p value	Algorithm model
2nd phase	S (5,5) Correlat^a	− 2.467	0.01	COM
3rd phase	Perc.99%	− 2.20	0.03	Histogram
	Mean	− 2.32	0.02	Histogram
	Perc.50%	− 2.28	0.02	Histogram
	Perc.90%	− 2.40	0.02	Histogram
5th phase	Perc.99%	− 2.29	0.02	Histogram
	Perc.90%^a	− 2.55	0.01	Histogram
	Perc.50%	− 2.31	0.02	Histogram
	Mean	− 2.31	0.02	Histogram
	Teta 3	− 2.05	0.04	ARM
	S (4, − 4) Correlat^a	− 2.41	0.02	COM
	S (5, − 5) Correlat	− 2.51	0.01	COM
	Variance	− 2.02	0.04	GRM

FMC, methods included Fisher coefficient, mutual information, classification error probability, and average correlation coefficients algorithms;
^aData, the statistically significant texture features in the multiple regression analysis, which would be input into the combined diagnosis model to distinguish between benign and malignant NME

ISSN: 1471-2342