Mizue Suzuki^{1}, Masako Kataoka^{1}, Mami Iima^{1}, Shotaro Kanao^{1}, Kanae Kawai Miyake^{1}, Rena Sakaguchi^{1}, Ayami Ohno Kishimoto^{1}, Maya Honda^{1}, Tadakazu Kondo^{2}, Tatsuki Kataoka^{3}, Takaki Sakurai^{3}, Masakazu Toi^{4}, and Kaori Togashi^{1}

^{1}Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan, ^{2}Department of Hematology and Oncology, Graduate School of Medicine, Kyoto University, Kyoto, Japan, ^{3}Department of Diagnostic Pathology, Graduate School of Medicine, Kyoto University, Kyoto, Japan, ^{4}Department of Breast Surgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan

### Synopsis

Since breast hematological malignancies
show various image findings, it is not easy to differentiate them from breast
cancer using conventional MRI. Non-Gaussian diffusion MRI is a relatively new
method using multi b values from low to high, reflecting the interaction of
water molecules with tissue features. We compared non-Gaussian parameters of
breast hematological malignancies and breast cancer to investigate the
advantage of non-Gaussian diffusion imaging. Our preliminary results
suggest potential advantage of kurtosis as a marker of cellular structure and
usefulness in differential diagnosis between breast hematological malignancies
and breast cancer.

**Introduction**

Although breast hematological
malignancies (lymphoma and leukemia) and invasive breast cancer sometimes show
similar MR image findings^{1}, hematological malignancies have
different biological and histological characteristics from breast cancer and
the management strategy is considerably different. Thus, the accurate imaging
diagnosis of hematological malignancies prior to biopsies warranted for
appropriate management and early systemic evaluation for staging.
Dynamic contrast-enhanced MRI (DCE-MRI) findings
were various and the considerable overlap of apparent diffusion coefficient (ADC)
values between breast hematological malignancies and breast cancer has been
reported in previous studies^{1-3}. Hence combination of DCE-MRI and
diffusion weighted image (DWI) is not sufficient enough to provide accurate
differential diagnosis.
Non-Gaussian diffusion MRI can provide
detailed information, such as tissue microstructure beyond ADC. One can
quantify the degree of non-Gaussian diffusion of water molecules with Kurtosis
model, and it is supposed to reflect the interaction of water molecules with
tissue features, especially cell membranes^{4}. Hematological
malignancies possess high cellular density, with characteristic small round
cell in lymphoma. Since such information on tissue microstructure would be
helpful for diagnosis, we hypothesized that non-Gaussian diffusion parameters,
particularly kurtosis, could be useful for differential diagnosis. Thus, the
purpose of this study was to investigate the advantage of non-Gaussian
diffusion imaging for differential diagnosis between breast hematological
malignancies and breast cancer. **Materials and methods**

**Patients** 115 female patients were enrolled between May 2013 and March 2015. All
of them had breast hematological malignancies or breast cancer, which were
diagnosed by histopathologic analysis on initial biopsy. All patients had
breast mass larger than 10mm on MR images, where we defined region of interest
(ROI). The characteristics of patients and mass lesions are summarized in Table
1.
**DWI image acquisition protocol and estimated
non-Gaussian parameters** Each
patient underwent a bilateral breast MR imaging with a 3T MR machine (Tim Trio;
Siemens Healthcare, Erlangen, Germany) using a 16-channel breast array coil. DW
images were acquired with 16 b values ranging from 5 to 2500 sec/mm^{2}.
As for non-Gaussian diffusion parameters, theoretical ADC at b value
of 0 sec/mm^{2} (ADC_{0}) and kurtosis (K) were
estimated from DWI images with multi b values, using the kurtosis model^{5}.
The following formula was used to estimate ADC_{0} and K.
S/S_{0} = {exp [-2b ADC_{0} + K (b ADC_{0})^{2}/3]
+ NCF }^{1/2}
Here S_{0} is the theoretical signal acquired at b=0 and NCF
(noise correction factor) is a parameter which characterizes the intrinsic
non-Gaussian noise contribution within images. A synthetic ADC (sADC) was also calculated by using b values of 200 and 1500 sec/mm^{2} (sADC_{200-1500}),
as well as standard ADC by using b values of 0 and 800 sec/mm^{2} (ADC_{0-800}).
**Image analysis**
Firstly, ROIs were placed on
the largest mass for each patient. Then, non-Gaussian parameters (ADC_{0} and K), sADC_{200-1500} and ADC_{0-800}
were calculated as mean value in the ROIs. Then, those values of
hematological malignancies were compared with those of breast cancer. The parametric
maps were also generated for each ROI. All the analysis were performed using MATLAB (MathWorks, Natick, MA, USA). **Results**

The parametric maps of
breast mass (K, ADC_{0}) of lymphoma are shown in Figure 1, showing moderately homogeneous pattern. The
peripheral area of the tumor shows high K and low ADC_{0} values
reflecting high cellularity, while the central area shows relatively low K and
high ADC_{0} values reflecting comparative low cellularity. Taken
together, it suggests heterogeneity of the lesion.
The
mean value of K was slightly higher in hematological malignancies than that in
breast cancer (Figure 2). The mean values of sADC_{200-1500} and ADC_{0-800}
were slightly lower in hematological malignancies than in breast cancer,
although the overlap was observed between both groups (Figure 3, 4). **Discussion**

These
results agree with our hypothesis that non-Gaussian diffusion parameters,
particularly kurtosis could be helpful for differential diagnosis between
breast hematological malignancies and breast cancer. Because non-Gaussian
diffusion MRI can reflect microstructure of the lesions, K is considered to reflect
high cellular density characteristic to tumor cells in breast hematological
malignancies. K is also considered to reflect structural complexity, such as proliferation

^{6}.
Considering overlap between both groups, combining it with other parameters
which reflect other characteristic such as homogeneity over the entire lesion
may lead to increasing diagnostic accuracy of MRI.
Although the data size is limited due to
the rarity of breast hematological malignancies, our preliminary results suggest
potential advantage of kurtosis as a marker of cellular structure and
usefulness in differential diagnosis between breast hematological malignancies
and breast cancer.

**Conclusion**

Non-Gaussian diffusion parameter, kurtosis (K) can
be a helpful index for differential diagnosis between hematological
malignancies in breast and breast cancer. ### Acknowledgements

No acknowledgement found.### References

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