Characterization of breast masses as benign or malignant at 3.0T MRI with whole-lesion histogram analysis of the apparent diffusion coefficient

Suo, Shiteng; Zhang, Kebei; Cao, Mengqiu; Suo, Xinjun; Hua, Jia; Geng, Xueqing; Chen, Jie; Zhuang, Zhiguo; Ji, Xiang; Lü, Qing; Wang, He; Xu, Jianrong

doi:10.1002/jmri.25043

Cited by 93 publications

(101 citation statements)

References 36 publications

(93 reference statements)

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“…On the other hand, high grade HCC usually showing hypercellularity, necrosis, or cystic change was rare. Suo et al also reported that the mean, minimum, maximum, and 10th, 25th, 50th, 75th, and 90th percentile ADCs were significantly lower, while skewness and entropy ADCs were significantly higher in malignant lesions compared with benign ones in breast tumor [19]. The results reflected hypercellularity and pathological heterogeneity.…”

Section: Discussionmentioning

confidence: 99%

3D analysis of apparent diffusion coefficient histograms in hepatocellular carcinoma: correlation with histological grade

et al. 2017

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BackgroundTo evaluate the usefulness of differentiation of histological grade in hepatocellular carcinoma (HCC) using three-dimensional (3D) analysis of apparent diffusion coefficient (ADC) histograms retrospectively.MethodsThe subjects consisted of 53 patients with 56 HCCs. The subjects included 12 well-differentiated, 35 moderately differentiated, and nine poorly differentiated HCCs. Diffusion-weighted imaging (b-values of 100 and 800 s/mm2) were obtained within 3 months before surgery. Regions of interest (ROIs) covered the entire tumor. The data acquired from each slice were summated to derive voxel-by-voxel ADCs for the entire tumor. The following parameters were derived from the ADC histogram: mean, standard deviation, minimum, maximum, mode, percentiles (5th, 10th, 25th, 50th, 75th, and 90th), skew, and kurtosis. These parameters were analyzed according to histological grade. After eliminating steatosis lesions, these parameters were re-analyzed.ResultsA weak correlation was observed in minimum ADC and 5th percentile for each histological grade (r = –0.340 and r = –0.268, respectively). The minimum ADCs of well, moderately, and poorly differentiated HCC were 585 ± 388, 411 ± 278, and 235 ± 102 × 10−6 mm2/s, respectively. Minimum ADC showed significant differences among tumor histological grades (P = 0.009). The minimum ADC of poorly differentiated HCC and that of combined well and moderately differentiated HCC were 236 ± 102 and 437 ± 299 × 10−6 mm2/s. The minimum ADC of poorly differentiated HCC was significantly lower than that of combined well and moderately differentiated HCC (P = 0.001). The sensitivity and specificity, when a minimum ADC of 400 × 10−6 mm2/s or lower was considered to be poorly differentiated HCC, were 100 and 54%, respectively. After exclusion of the effect of steatosis, the sensitivity and specificity did not change, although the statistical differences became strong (P < 0.0001).ConclusionMinimum ADC was most useful to differentiate poorly differentiated HCC in 3D analysis of ADC histograms.

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Section: Discussionmentioning

confidence: 99%

3D analysis of apparent diffusion coefficient histograms in hepatocellular carcinoma: correlation with histological grade

et al. 2017

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“…4,6 Entropy equals 0 if all values are the same and increases as the data distribution becomes more irregular. 26 The malignant tumours in our population displayed a tendency for higher entropies as compared with the benign ones, although a considerable degree of overlap between the two types of lesions precluded statistical significance. This is mainly the reason why the diagnostic accuracy of ADC entropy was found to be substantially inferior to that of the whole-lesion mean ADC value.…”

Section: -34mentioning

confidence: 66%

“…[21][22][23][24][25][26] This may be attributable to breast tumour heterogeneity, with the most aggressive part being located anywhere within the tumour volume, whereas ADC is traditionally measured as the average value within a region of interest just a single-slice thick.…”

Section: Discussionmentioning

confidence: 99%

“…Suo et al 26 (JMRI) (April 2016) recently showed in their study that entropy in malignant lesions is higher than the entropy in benign masses with statistical significance (p 5 0.001). However, the DWI sequence was performed with a higher b-value of 600 s mm 22 , whereas in our study, the higher b-value was 1300 s mm 22 .…”

Section: -34mentioning

confidence: 94%

“…Although comparison of single-slice with multislice whole-lesion ADC results was not the purpose of this study, the high specificity may suggest that a volumetric analysis of each lesion, instead of the single section-based measurement, may better depict the morphologic heterogeneity of breast lesions, which is mainly attributable to the fact that multislice whole-lesion ADC calculation eliminates the source of single-slice sampling errors deriving from tumour heterogeneity. 26 However, a further study comparing single-slice with multislice whole-lesion ADC should be performed providing accurate results.…”

Section: -34mentioning

confidence: 99%

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Whole-lesion apparent diffusion coefficient (ADC) metrics as a marker of breast tumour characterization—comparison between ADC value and ADC entropy

Bougias¹,

Ghiatas²,

Priovolos³

et al. 2016

The British Journal of Radiology

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Objective: To prospectively assess the role of wholelesion apparent diffusion coefficient (ADC) metrics in the characterization of breast tumours by comparing ADC value with ADC entropy. Methods: 49 patients with 53 breast lesions underwent phased-array breast coil 1.5-T MRI. Two radiologists experienced in breast MRI, blinded to the final diagnosis, reviewed the ADC maps and placed a volume of interest on all slices including each lesion on the ADC map to obtain whole-lesion mean ADC value and ADC entropy. The mean ADC value and ADC entropy in benign and malignant lesions were compared by the Mann-Whitney U-test. Receiver-operating characteristic analysis was performed to assess the sensitivity and specificity of the two variables in the characterization of the breast lesions. Results: The benign (n 5 19) and malignant lesions (n 5 34) had mean diameters of 20.8 mm (10.1-31.5 mm) and 26.4 mm (10.5-42.3 mm), respectively. The mean ADC value of the malignant lesions was significantly lower than that of the benign ones (0.87 3 10 23 vs , the sensitivity and specificity for diagnosing malignancy became optimal (97.1% and 93.7, respectively) with an area under the curve (AUC) of 0.975. With regard to ADC entropy, the sensitivity and specificity at a cut-off of 5.18 were 67.6 and 68.7%, respectively, with an AUC of 0.664. Conclusion: Whole-lesion mean ADC could be a helpful index in the characterization of suspicious breast lesions, with higher sensitivity and specificity than ADC entropy. Advances in knowledge: Two separate parameters of the whole-lesion histogram were compared for their diagnostic accuracy in characterizing breast lesions. Mean ADC was found to be able to characterize breast lesions, whereas entropy proved to be unable to differentiate benign from malignant breast lesions. It is, however, likely that entropy may distinguish these two groups if a larger cohort were used, or the fact that this may be influenced by the molecular subtypes of breast cancers included.

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Radiomics based on ultrasound images for diagnosis of minimal breast cancer

2023

J of Clinical Ultrasound

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Characterization of breast masses as benign or malignant at 3.0T MRI with whole-lesion histogram analysis of the apparent diffusion coefficient

Abstract: These results suggest that whole-lesion ADC histogram analysis may facilitate the differentiation between benign and malignant breast mass lesions.

Cited by 93 publications

References 36 publications

3D analysis of apparent diffusion coefficient histograms in hepatocellular carcinoma: correlation with histological grade

3D analysis of apparent diffusion coefficient histograms in hepatocellular carcinoma: correlation with histological grade

Whole-lesion apparent diffusion coefficient (ADC) metrics as a marker of breast tumour characterization—comparison between ADC value and ADC entropy

Radiomics based on ultrasound images for diagnosis of minimal breast cancer

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