Histogram analysis of breast diffusion kurtosis imaging: a comparison between readout-segmented and single-shot echo-planar imaging sequence
Original Article

Histogram analysis of breast diffusion kurtosis imaging: a comparison between readout-segmented and single-shot echo-planar imaging sequence

Cicheng Huang1#, Chenao Zhan2#, Yiqi Hu2, Ting Yin3, Robert Grimm4, Tao Ai2

1Center of Stomatology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; 2Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; 3MR Collaborations, Siemens Healthcare Ltd., Chengdu, China; 4MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany

Contributions: (I) Conception and design: T Ai; (II) Administrative support: T Yin, R Grimm; (III) Provision of study materials or patients: C Zhan; (IV) Collection and assembly of data: C Huang; (V) Data analysis and interpretation: C Huang, C Zhan; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.

#These authors contributed equally to this work.

Correspondence to: Tao Ai, MD, PhD. Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China. Email: aitao007@hotmail.com.

Background: Histogram analysis of the diffusion-weighted imaging (DWI) parameters is widely used to differentiate the breast lesions. However, histogram analysis of the diffusion-kurtosis imaging (DKI) parameters for the single-shot echo-planar imaging (ss-EPI) and readout-segmented echo planar imaging (rs-EPI) sequences has not been compared in breast cancer. Thus, this study is to investigate the diagnostic accuracy and reliability of the histogram parameters derived from the rs-EPI and ss-EPI sequences of DKI parameters in distinguishing between the benign and malignant breast lesions.

Methods: This single-center, retrospective cohort study enrolled 205 consecutive patients with breast lesions (65 benign and 140 malignant). The patients underwent breast magnetic resonance imaging (MRI) with a 3T scanner using the rs-EPI and ss-EPI sequences with 4 b values (0, 50, 1,000, and 2,000 s/mm2). The regions of interest (ROIs) were manually delineated for all the lesion images from both the sequences, and the histogram parameters were extracted from the apparent diffusion coefficient (ADC) and apparent diffusional kurtosis (Kapp) maps. Statistical analysis was performed using the Kolmogorov-Smirnov test, the student’s t-test, and the receiver operating characteristic (ROC) curves.

Results: The mean, 25th, 50th, 75th, and 100th percentiles, skewness, and kurtosis values derived from apparent diffusion for non-Gaussian distribution (Dapp) and Kapp maps showed good or excellent intra-observer agreement (ICC: 0.695 to 0.863).The mean and the 25th, 50th, 75th, and 100th percentile values for Dapp were significantly lower and the mean and the 25th, 50th, 75th, and 100th percentile values for Kapp were significantly higher in the malignant breast lesions compared with those in the benign breast lesions for both the rs-EPI and ss-EPI sequences (all P<0.05). The majority of the histogram Kapp and Dapp parameters (except skewness and kurtosis) for the benign and malignant lesions showed significant differences between the ss-EPI and the rs-EPI sequences (P<0.05). ROC curve analysis showed that the AUC values for the 75th percentile of Kapp (0.854 for rs-EPI, 0.844 for ss-EPI) and the 25th percentile of Dapp (0.866 for rs-EPI, 0.858 for ss-EPI) were highest for both DKI sequences. The diagnostic performance of the rs-EPI sequence was better than the ss-EPI sequence for all the histogram parameters except the skewness value of Dapp.

Conclusions: Histogram parameters from the rs-EPI sequence were more reliable and accurate in differentiating malignant and benign breast lesions than those from the ss-EPI sequence.

Keywords: Histogram parameters; diffusion-kurtosis MR imaging; readout-segmented

Submitted May 13, 2022. Accepted for publication Dec 01, 2022. Published online Jan 02 2023.

doi: 10.21037/qims-22-475

Introduction

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is the most widely used MR imaging sequence for identification breast lesions (1). However, the specificity of DCE-MRI varies from 37% to 97% in the diagnosis of breast lesions due to the background parenchymal enhancement and the overlap of the time intensity curves (2,3). Diffusion-weighted imaging (DWI) of the breast has gained clinical acceptance for being an effective adjunctive sequence to DCE-MRI, which is widely used to evaluate the morphological changes and assess the semi-quantitative kinetic parameters of the breast lesions (4-6). The apparent diffusion coefficient (ADC) estimates the diffusion behavior of the water molecules within the tissues in a conventional DWI based on the mono-exponential decay of the signal intensity (SI) (7,8). ADC is based on the Gaussian diffusion model, which assumes that the water molecules diffuse freely and uniformly in the tissues (9). However, the tissue microstructure is highly complex, and the DWI signal intensity decay plot deviates from a simple mono-exponential pattern as the b-value increases (10,11). Jensen et al. proposed the diffusion kurtosis imaging (DKI) method in 2005 to describe the non-Gaussian diffusion of the water molecules (12). DKI estimates the kurtosis or skewed distribution of water diffusion and diffusivity or the kurtosis-corrected diffusion coefficient (13,14). Several studies have demonstrated that DKI probes non-Gaussian movement of water molecules in tissue environments and the kurtosis value calculated by the DKI model through more advanced mathematical curve fitting presumably reflects the heterogeneity of cellular microstructure (15-18). Sun et al. demonstrated that DKI may be a noninvasive method to evaluate the effects of neoadjuvant chemotherapy for breast cancer (10).

Currently, single-shot echo-planar imaging (ss-EPI) is the most commonly used DWI sequence in clinical practice for breast tumor detection and characterization (19). However, ss-EPI is associated with susceptibility-induced geometric distortion and image blurring (20,21). Readout segmented echo-planar imaging (rs-EPI) is a multi-shot strategy that divides the k-space into multiple segments along the readout direction and can overcome the shortcomings of the ss-EPI technique (22). Several studies have demonstrated that the rs-EPI sequence provided significantly higher image quality and lesion conspicuity than the ss-EPI sequence (23,24). The major challenge faced with rs-EPI is a comparatively long scan time than that for single-shot echo-planar imaging. This can be explained by the higher actual resolution of the rs-EPI sequence compared with single-shot echo-planar imaging and the more efficient k-space coverage of single-shot echo-planar imaging (25).

Histogram analysis can be used to estimate intratumor heterogeneity and compare lesions because it describes the statistical information of the MRI parameters for the lesions (23). Histogram analysis of the MRI parameters from the ss-EPI sequence is a promising approach to differentiate the breast lesions and predict the risk of breast cancer recurrence (24,26). However, to our knowledge, histogram analysis of the DKI image parameters for the rs-EPI and ss-EPI sequences have not been compared in breast cancer. Therefore, the aim of the present study was to compare the diagnostic accuracy and reliability of the rs-EPI and ss-EPI sequences based on histogram analysis of the DKI parameters. We present the following article in accordance with the STARD reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-22-475/rc).

Methods

Study patients

The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). This educational review includes a statement on ethics approval and consent from the ethics committee of Tongji Hospital, Tongji Medical College, Huazhong University of Science. Written informed consent was received from each participant before participation in the study. 406 women with suspected breast lesions diagnosed as Breast Imaging reporting and Data System (BI-RADS) category 3 or higher at mammography or ultrasonography in our hospital were selected for breast MR imaging between May 2016 and March 2017. The inclusion criteria included: (I) 18 years or older; (II) no pregnancy or lactation. 387 patients were approached for inclusion in the study, and 342 consented to participate. The exclusion criteria included (I) poor image quality with severe susceptibility or motion artifacts; (II) previous treatment including radiotherapy or neoadjuvant chemotherapy for breast lesions before MRI; (III) absence of visible lesions on the b-1000 images of two DWI sequences; (IV) lesion size (minimum diameter) <5 mm on the b-1000 images of two DWI sequences; and (V) patients without histopathological results confirmed by surgery or needle biopsy within two weeks after breast MRI. Finally, 205 patients (mean age ± SD, 40.6±16.5 years; age range, 22–63 years) were enrolled in this study. The flowchart of this study is displayed on Figure 1.

Figure 1 Flow diagram of the study population. MRI, magnetic resonance imaging; DWI, diffusion-weighted imaging.

MRI acquisition

The breast MRI examinations were performed on a 3T MRI scanner (MAGNETOM Skyra, Siemens Healthcare) equipped with a dedicated bilateral 16-channel phased-array breast coil. The MR imaging was performed with the patient in a prone position using the following sequences: (I) axial fat-saturated T2-weighted imaging (T2WI); (II) single-shot echo-planar imaging (ss-EPI); (III) readout-segmented echo-planar imaging (rs-EPI); (IV) axial T1-weighted DCE-MRI. The parameters of the sequences are shown in Table 1.The ss-EPI and rs-EPI sequences were applied with 4 b values (0, 50, 1,000, and 2,000 s/mm2).

Table 1

Imaging protocol for T2-weighted imaging, diffusion-weighted imaging, and dynamic contrast-enhanced MRI

Parameters T2-weighted DWI sequences DCE-MRI
ss-EPI rs-EPI
Repetition time (ms) 3,700 5,000 5,000 5.40
Echo time (ms) 101 96 68 2.46
Field of view (mm2) 320×320 169×280 169×280 270×320
Voxel size (mm3) 1×1×4 1.5×1.5×5 1.5×1.5×5 1×1×1.5
Flip angle (°) 137 180 180 10
Slice thickness (mm) 4 5 5 1.5
Parallel imaging GRAPPA2 GRAPPA2 GRAPPA2 GRAPPA2 + CAIPIRINHA2
b-value (s/mm2) – 0, 50, 1,000, 2,000 0, 50, 1,000, 2,000 –
Readout segments – – 5 –
Averages – 5 1 –
Acquisition time (min) 2:06 4:35 4:27 5:57

MRI, magnetic resonance imaging; DWI, diffusion-weighted imaging; ss-EPI, single-shot echo-planar imaging; rs-EPI, readout-segmented echo planar imaging; DCE-MRI, dynamic contrast-enhanced magnetic resonance imaging; GRAPPA, generalized autocalibrating partially parallel acquisition; CAIPIRINHA, controlled aliasing in parallel imaging results in higher acceleration; mm, millimeter.

Image analysis

All the imaging datasets were analyzed with the prototype software, Body Diffusion Toolbox (version 0.2.2, Siemens Healthcare). The apparent diffusion for non-Gaussian distribution (Dapp) and the apparent diffusional kurtosis (Kapp) values were calculated for both the DWI sequences using the following equation:

ln[S(b)]=ln[S(0)]−bDapp+16b2Dapp2Kapp+O(b3)

Where S(b) is the signal intensity at the echo time, Dapp is the apparent diffusion for non-Gaussian distribution, and Kapp is the apparent diffusional kurtosis; Where S(b) represents the DWI signal intensity at a particular b value; S(0) represents the baseline signal at b=0; b represents the degree of diffusion weighting applied to calculate Dapp and Kapp; and O(b3) represents the fit error associated with the measurements (11).

Two experienced radiologists with 10 years (reader 1) and 7 years (reader 2) of experience in DW imaging of the breast independently evaluated all the images simultaneously. Disagreement between the two observers was resolved in consensus. The readers were blinded to patient clinical histories, histopathologic diagnoses, and sequence information. Two-dimensional regions of interest (ROIs) were manually delineated on the rs-EPI images with a b value of 1,000 s/mm2. Freehand ROIs (>200 mm2 quasi-circular area) were drawn along the outer edge of the lesions. The areas with sizeable cystic necrosis, calcifications, or blood vessels were avoided by referring to the corresponding T2WI and DCE-MRI images. The same ROIs were copied to the ss-EPI images and the parametric maps. Histogram parameters including the mean, 25th, 50th, 75th and 100th percentiles, skewness, and kurtosis were recorded for all the ROIs and compared.

Statistical analysis

SPSS version 20.0 (SPSS, Chicago, IL, USA) and MedCalc version 12.0 (MedCalc Software, Mariakerke, Belgium) software were used for the statistical analysis. The data with normal distribution were analyzed using the Kolmogorov-Smirnov test. Inter-class agreements for the histogram parameter measurements by the two readers were assessed by calculating the intra-class correlation coefficients (ICCs) (27). ICC values less than 0.4 were considered poor; ICC values between 0.40 to 0.59 were considered fair; ICC values between 0.60 to 0.74 were considered good, and ICC values greater than 0.75 were considered excellent (28).

The Student’s t-test was used to compare the histogram parameters of MK and MD from the ss-EPI and rs-EPI sequences for the benign and malignant lesions, respectively, and the differences in the histogram parameters of Dapp and Kapp between the benign and malignant breast lesions in the ss-EPI or the rs-EPI sequences. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic accuracy of the histogram parameters in differentiating the malignant lesions from the benign lesions. The area under the receiver operating characteristic (AUC), sensitivity, and specificity values were estimated for all the histogram parameters of Dapp and Kapp using the ROC curves. The differences in the AUC values between the ss-EPI and rs-EPI sequences were compared for all the histogram parameters. P<0.05 was considered statistically significant.

Results

Basic clinicopathologic characteristics of the included study subjects

Among the 205 breast lesions confirmed by histopathology, 65 (32%) were benign and 140 (68%) were malignant. The histologic types of the breast lesions are shown in Table 2. The ss-EPI and rs-EPI images of two representative cases with benign and malignant breast lesions are shown in Figure 2.

Table 2

Histological types of 205 breast lesions

Groups Histological types Number
Benign (N=65) Fibroadenoma 45
Adenosis 11
Fibrous epithelial tumor 1
Benign phyllode tumor 2
Intraductal papilloma 6
Malignant (N=140) Invasive ductal carcinoma 116
Invasive lobular carcinoma 3
Ductal carcinomas in situ 16
Malignant phyllode tumor 5
Figure 2 Representative images of a 42-year-old patient (A-F) with a malignant breast lesion (invasive ductal carcinoma) and a 36-year-old patient (G-L) with a benign breast lesion (benign phyllode tumor). The reference DWI (b=1,000 s/mm2) images (A,G), Kapp images (B,H), Dapp images (C,I) are based on the rs-EPI sequence. The reference DWI (b=1,000 s/mm2) images (D,J), Kapp images (E,K) and Dapp images (F,L) are based on the ss-EPI sequence. DWI, diffusion-weighted imaging; Kapp, apparent diffusional kurtosis; Dapp, apparent diffusion coefficient; rs-EPI, readout-segmented echo planar imaging; ss-EPI, single-shot echo-planar imaging.

Histogram analysis shows significant differences in the DKI parameters between malignant and benign breast lesions

In both the DKI sequences, the inter-reader agreement was excellent for the histogram parameters such as the mean and the 25th, 50th, 75th, and 100th percentiles of Dapp and Kapp (ICC: 0.776 to 0.863), and good for skewness and kurtosis of Dapp and Kapp (ICC: 0.695 to 0.734).

The histogram analysis showed significant differences in the DKI parameters between the benign and the malignant lesions for both sequences (Table 3 and Figure 3). The malignant breast lesions showed significantly lower mean and 25th, 50th, 75th, and 100th percentiles of the Dapp values and significantly higher mean and 25th, 50th, 75th and 100th percentiles of the Kapp values compared with the benign breast lesions for both the sequences (all P<0.05). The skewness values of Dapp and Kapp were significantly higher for the malignant breast lesions than for the benign breast lesions (P<0.05). The kurtosis values of Dapp and Kapp showed no difference between the benign and malignant breast lesions for both DWI sequences (P>0.05).

Table 3

Comparisons of the histogram parameters between benign and malignant breast lesions in ss-EPI and rs-EPI sequence

Variables ss-EPI rs-EPI
Benign lesions Malignant lesions P Benign lesions Malignant lesions P
Histogram Kapp
   Mean 0.77±0.19 0.98±0.14 <0.01 0.65±0.19 0.89±0.14 <0.01
   25th 0.72±0.17 0.89±0.14 <0.01 0.59±0.18 0.80±0.14 <0.01
   50th 0.77±0.19 0.98±0.16 <0.01 0.66±0.19 0.89±0.16 <0.01
   75th 0.82±0.22 1.08±0.20 <0.01 0.72±0.20 0.98±0.20 <0.01
   100th 1.04±0.34 1.41±0.73 <0.01 0.92±0.30 1.31±0.43 <0.01
   Skewness −0.24±1.20 −0.01±1.10 0.03 −0.43±1.06 0.01±1.15 <0.01
   Kurtosis 5.13±3.82 4.53±3.28 0.29 5.18±2.85 4.93±4.34 0.43
Histogram Dapp
   Mean 1.68±0.39 1.21±0.28 <0.01 1.66±0.34 1.23±0.27 <0.01
   25th 1.57±0.39 1.06±0.26 <0.01 1.54±0.35 1.08±0.23 <0.01
   50th 1.67±0.39 1.18±0.28 <0.01 1.65±0.35 1.20±0.26 <0.01
   75th 1.78±0.39 1.34±0.32 <0.01 1.77±0.35 1.35±0.31 <0.01
   100th 2.27±0.63 1.90±0.50 <0.01 2.36±0.57 1.89±0.49 <0.01
   Skewness 0.40±0.78 0.80±0.85 <0.01 0.48±0.84 0.73±0.71 <0.01
   Kurtosis 4.32±2.45 4.29±2.55 0.48 4.63±3.14 3.95±1.93 0.07

Data are expressed as mean ± standard deviation. ss-EPI, single-shot echo-planar imaging; rs-EPI, readout-segmented echo planar imaging; Kapp, apparent diffusional kurtosis; Dapp, apparent diffusion for non-Gaussian distribution.

Figure 3 Boxplots show the histogram analysis of the mean values and the 25th, 50th, 75th, and 100th percentiles of (A-E) apparent diffusional kurtosis (Kapp) and (F-J) apparent diffusion coefficient (Dapp) of the benign and malignant breast lesions based on the ss-EPI and rs-EPI sequence. * in figure represents the statistical difference. Kapp, apparent diffusional kurtosis; Dapp, apparent diffusion for non-Gaussian distribution; ss-EPI, single-shot echo-planar imaging; rs-EPI, readout-segmented echo planar imaging.

The histogram analysis showed significant differences in the mean and the 25th, 50th, 75th, and 100th percentiles of Dapp and Kapp between the ss-EPI and rs-EPI sequences for both benign and malignant breast lesions (all P<0.05; Table 4). Furthermore, the skewness of Dapp values between the ss-EPI and rs-EPI sequences were significantly different for both benign and the malignant breast lesions (P<0.05; Table 4).

Table 4

Comparisons of the histogram parameters between ss-EPI and rs-EPI sequence for breast lesions

Variables Benign lesion (n=65) Malignant lesion (n=140)
ss-EPI rs-EPI P ss-EPI rs-EPI P
Histogram Kapp
   Mean 0.77±0.19 0.65±0.19 <0.01 0.98±0.14 0.89±0.14 <0.01
   25th 0.72±0.17 0.59±0.18 <0.01 0.89±0.14 0.80±0.14 <0.01
   50th 0.77±0.19 0.66±0.19 <0.01 0.98±0.16 0.89±0.16 <0.01
   75th 0.82±0.22 0.72±0.20 <0.01 1.08±0.20 0.98±0.20 <0.01
   100th 1.04±0.34 0.92±0.30 <0.01 0.92±0.30 1.31±0.43 <0.01
   Skewness −0.24±1.20 −0.43±1.06 0.14 -0.01±1.10 0.01±1.15 0.33
   Kurtosis 5.13±3.82 5.18±2.85 0.11 4.53±3.28 4.93±4.34 <0.01
Histogram Dapp
   Mean 1.68±0.39 1.66±0.34 <0.01 1.21±0.28 1.23±0.27 <0.01
   25th 1.57±0.39 1.54±0.35 <0.01 1.06±0.26 1.08±0.23 <0.01
   50th 1.67±0.39 1.65±0.35 <0.01 1.18±0.28 1.20±0.26 <0.01
   75th 1.78±0.39 1.77±0.35 <0.01 1.34±0.32 1.35±0.31 <0.01
   100th 2.27±0.63 2.36±0.57 <0.01 1.90±0.50 1.89±0.49 <0.01
   Skewness 0.40±0.78 0.48± 0.84 <0.01 0.80±0.85 0.73±0.71 <0.01
   Kurtosis 4.32±2.45 4.63±3.14 0.06 4.29±2.55 3.95±1.93 <0.01

Data are expressed as mean ± standard deviation. ss-EPI, single-shot echo-planar imaging; rs-EPI, readout-segmented echo planar imaging; Kapp, apparent diffusional kurtosis; Dapp, apparent diffusion for non-Gaussian distribution.

The diagnostic performance of the DKI parameters from the rs-EPI sequence is superior to those from the ss-EPI sequence

The results of the ROC curve analysis to distinguish the malignant and the benign breast lesions based on the histogram parameters are shown in Table 5 and Figure 4. The AUC values were higher for all the histogram parameters in the rs-EPI sequence compared with the ss-EPI sequence except for the skewness value of Dapp, but the differences were not statistically significant (all P>0.05). The AUC values were highest for the 75th percentile of Kapp (0.854 for rs-EPI, 0.844 for ss-EPI) and 25th percentile of Dapp (0.866 for rs-EPI, 0.858 for ss-EPI) among all the histogram parameters for both the DWI sequences.

Table 5

Comparisons of ROC analyses of the histogram parameters between ss-EPI and rs-EPI sequence

Variables ss-EPI rs-EPI
Sensitivity (%) Specificity (%) AUC Sensitivity (%) Specificity (%) AUC
Histogram Kapp
   Mean 76 77 0.822 94 68 0.850
   25th 73 75 0.797 86 77 0.842
   50th 68 88 0.829 93 72 0.853
   75th 79 82 0.844 92 72 0.854
   100th 79 72 0.786 87 68 0.812
   Skewness 51 71 0.593 64 68 0.644
   Kurtosis 58 54 0.543 54 72 0.611
Histogram Dapp
   Mean 74 82 0.835 87 69 0.850
   25th 78 83 0.858 91 71 0.866
   50th 93 62 0.839 79 80 0.855
   75th 68 85 0.812 81 74 0.831
   100th 56 74 0.678 66 80 0.751
   Skewness 38 86 0.622 60 60 0.597
   Kurtosis 40 68 0.518 69 46 0.561

ROC, receiver operating characteristic; ss-EPI, single-shot echo-planar imaging; rs-EPI, readout-segmented echo planar imaging; Kapp, apparent diffusional kurtosis; Dapp, apparent diffusion for non-Gaussian distribution; AUC, area under the curve.

Figure 4 Receiver operating characteristic curves show the diagnostic accuracy of the histogram values of the (A) Kapp and (B) Dapp parameters from the ss-EPI and rs-EPI sequence. Kapp, apparent diffusional kurtosis; Dapp, apparent diffusion for non-Gaussian distribution; ss-EPI, single-shot echo-planar imaging; rs-EPI, readout-segmented echo planar imaging.

Discussion

The ICC values demonstrated good or excellent interclass agreement between the two readers, thereby confirming the reliability of our results. In this study, we performed histogram analysis of the DKI parameters (Dapp and Kapp) based on the ss-EPI and rs-EPI sequences for the benign and malignant breast lesions. The results demonstrated that most of the histogram parameters for the Dapp and Kapp values based on both the DWI sequences showed significant differences between the benign and the malignant breast lesions. Furthermore, the benign and malignant breast lesions showed significant differences between the ss-EPI and the rs-EPI sequence for the histogram parameters. ROC curve analysis demonstrated that the diagnostic accuracy of the histogram parameters for the Dapp and Kapp values based on the rs-EPI sequence was significantly higher compared with those from the ss-EPI sequence.

This is the first study to compare the histogram parameters between the ss-EPI and rs-EPI sequences for the breast lesions. The histogram parameters can accurately describe the intrinsic characteristics of the lesions and highlight small but important differences between the benign and malignant lesions without a requirement for additional imaging (29). Previous studies have reported histogram parameters of the breast lesions based on the ss-EPI sequence may provide better diagnostic performance for diagnosis (24,30). Furthermore, Kim et al. demonstrated that the image quality from the rs-EPI sequence was superior to that from the ss-EPI sequence (31). However, differences in the histogram parameters for the breast lesions between the two sequences have not been reported previously.

This study showed that the malignant and the benign breast lesions were clearly distinguishable based on the mean values and the 25th, 50th, 75th, and the 100th percentiles of Dapp and Kapp in both the DWI sequences. The Dapp values were lower, and the Kapp values were higher in the malignant breast lesions compared with the benign lesions. These results were consistent with the previously reported findings, which demonstrated that the malignant tumors were more complex and heterogeneous than the benign lesions (2,32). Therefore, the movement of the water molecules in the malignant tumors was more restricted than the water molecules in the benign lesions. The 75th percentile of Kapp and the 25th percentile of Dapp yielded the highest AUC values in their respective histogram parameter groups for differentiating the benign breast lesions from the malignant breast lesions. These results were consistent with a previously reported analysis of the DKI histogram parameters (24). The lower percentiles of Dapp coupled with the higher percentiles of Kapp are characteristic features of aggressive lesions with relatively dense malignant cells. Furthermore, the 100th percentile of Kapp did not show superior diagnostic accuracy because the higher values are adversely affected by noise and adjacent structures (30).

In our study, histogram parameters, including the mean, median, 25th, 50th, 75th, and 100th percentile of Dapp and Kapp for the benign lesions, were significantly different from those for the malignant lesions based on the image data from both DKI sequences. Furthermore, the results of ROC curve analyses demonstrated that the diagnostic accuracies of all the histogram parameters, based on the rs-EPI sequence, were higher than the corresponding histogram parameters based on the ss-EPI sequence. These results may be related to the differences in the fat suppression quality between the two DKI sequences. Fat suppression quality is highly dependent on factors such as magnetic field homogeneity, coil sensitivity, air-tissue susceptibility differences and partial-volume effects from the intravoxel fat signals in the breast diffusion-weighted images (33). The conventional single-shot EPI acquisitions are performed using a single excitation with a gradient echo readout trajectory (34). However, long EPI readout and corresponding low bandwidth per pixel in the phase-encoding direction can cause susceptibility artifacts at the air-tissue interface and magnetic field homogeneity, especially at higher field strengths such as 3 Tesla (3T), which may lead to errors in breast quantitative measurements with the ss-EPI sequence (21). The rs-EPI sequence acquires several readout segments of k-space in the readout direction during each shot and significantly reduces the echo spacing by accelerating the k-space traversal along the phase-encoding direction (35). These effects significantly reduce the magnetic susceptibility artifacts and improve the fat suppression quality, which can affect the performance of breast DWI imaging. Therefore, the histogram parameters from the rs-EPI sequence were more reliable than those from the ss-EPI sequences for the breast lesions.

Our study has several limitations. Firstly, the pathological types of benign and malignant lesions were unevenly distributed and may have resulted in sample selection bias. Secondly, all the parameters in this study were calculated by manually drawing the ROIs, which can introduce errors. Therefore, in future research, automated segmentation of the ROIs may be more accurate. Thirdly, the optimal b-value for the DKI model remains to be confirmed for the breast lesions. Finally, we did not compare the parameters from the DKI model with ADC value and we need to explore it in future.

In conclusion, the histogram analysis of the DKI parameters demonstrated that the rs-EPI sequence was more reliable and accurate in differentiating malignant breast from benign breast lesions.

Acknowledgments

Funding: None.

Footnote

Reporting Checklist: The authors have completed the STARD reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-22-475/rc

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-22-475/coif). TY and RG are employees of Siemens Healthcare. However, Siemens Healthcare has no role in the design of the study, data analyses, or data interpretation. The data of this study was analyzed and controlled by authors who are not the employees of the medical industry. The other authors have no conflicts of interest to disclose.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). This educational review includes a statement on ethics approval and consent from the ethics committee of Tongji Hospital, Tongji Medical College, Huazhong University of Science. Written informed consent was received from each participant before participation in the study.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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Cite this article as: Huang C, Zhan C, Hu Y, Yin T, Grimm R, Ai T. Histogram analysis of breast diffusion kurtosis imaging: a comparison between readout-segmented and single-shot echo-planar imaging sequence. Quant Imaging Med Surg 2023;13(2):735-746. doi: 10.21037/qims-22-475

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