Correlative study between ADC value and grading of invasive breast cancer

Studying breast carcinoma is of great importance as it is the commonest female malignancy. Accurate preoperative assessment of disease characteristics and prognosis would be of great help in the diagnosis and treatment planning of breast cancer. The aim of this study was to evaluate the role of the apparent diffusion coefficient (ADC) value in detecting the grading of invasive breast carcinoma prior to management. There was a significant difference between the mean ADC value of tumors of grade I and III (p = 0.001) and between grade I and II (p = 0.002). However, there was no significant difference between grade II and III (p = 0.979). High ADC values were associated with low-grade tumors. The mean ADC value of 0.93 × 10–3 mm2/s showed sensitivity 98%, specificity 100%, PPV 100%, NPV 83.3%, accuracy 98.2%, AUC = 0.994, and 95% confidence interval of 0.978 to 1.000. DWI is a contrast-free modality that allows for both morphological and quantitative analysis. ADC value may not be the proper modality to determine the prognosis of breast cancer due to overlap values, yet it could be a good discriminator between low- and high-grade tumors and hence predictor of breast cancer cells that would respond to chemotherapy.


Background
Breast cancer is considered the second leading cause of cancer-related death and the highest number of newly recognized cases of cancer in women. Precise preoperative evaluation of disease characteristics and prognosis would be of enormous help in the management of breast cancer. Noninvasive diagnosis by means of in vivo imaging is turning to be of more significance for the diagnosis and treatment of breast cancer [1].
Dynamic contrast-enhanced breast MR imaging is now considered as the most precise imaging procedure for diagnosis of breast cancer; nevertheless, it gives no definitive information about tumor cellularity, which is well-known to be a vital indicator of tumor grade. Therefore, there has been a growing interest in the use of diffusion-weighted breast imaging for its potential to advance the diagnosis of breast lesions at the expense of a little increase in the examination time and with no need for intravenous contrast material injection [2].
Diffusion-weighted MRI detects the biologic characteristics of tissue and gives unique data regarding the cellularity and the status of molecular content of water. Moreover, it has a privilege of short exam duration with no need to use contrast medium [3].
The ADC is a q value that can be quantified measuring signal attenuation being influenced by microscopic motion, including molecular diffusion of water as well as blood microcirculation [4].
In the current study, we evaluated the impact of interpreting apparent diffusion coefficient (ADC) value as a prognostic factor that can predict the grading of invasive breast carcinoma before deciding the options of management.

Methods
This study was a prospective analysis, approved by the ethics committee at our institute during the period from December 2015 to December 2018. Tumor grading was established by mean of open surgical or a core needle biopsy (considered as the standard reference).

Patients
It included 156 patients that were referred from general surgery department and they were subjected to primary sonomammogram evaluation and MRI scanning including pre-contrast, dynamic post-contrast as well as diffusion-weighted sequences prior to biopsy.

Inclusion criteria
Patients proved to have invasive breast carcinoma that requires further advanced pathological analysis for grading.
Exclusion criteria -Cases that received neoadjuvant chemotherapy.
-Cases that lacked pathological confirmation.
-Cases proved to be benign.
-Solid masses less than 1 cm or complex masses that presented with small solid component (The ADC value could not be evaluated).

MR imaging
MRI was performed for the breasts using 1.5 Tesla magnet scanners by two devices (Intera and Achieva, Philips medical system). All patients were examined in the prone position using a dedicated phased array breast coil with eight channels. Total study time ranged from 30 to 45 min. No sedation was used.

Post-processing and image analysis
Magnetic resonance images were reviewed by two radiologists (the first with 10 years of experience and the second with 6 years of experience) in the same setting and the final diagnosis was reached by their agreement (in consensus).
Post-processing image subtraction was obtained using the software subtraction function available on the work station.
Qualitative and quantitative analysis of the examined masses were done as follows:

I-Qualitative analysis:
Restricted diffusion was determined by visualization of abnormal bright signal intensity that became enhanced with increasing b values (0 → 850 → 1000 → 1500) at "diffusion-weighted" (DW) images. The ADC map presented intermediate/low signal intensity (SI) that corresponded to the abnormality (Figs. 1 and 2).

II-Quantitative analysis:
The ADC values were measured manually by applying ROI at areas of bright SI on DW images and intermediate/ low SI on ADC maps, aiming to cover as much as possible of the lesion, avoiding cystic/necrotic areas (Figs. 3 and 4).

Histological analysis
Nottingham combined histologic grade was used for assessment of histological grades of invasive ductal carcinoma, NOS using a numerical scoring system for tubule formation, pleomorphism and mitotic count. The total score could range from 3 to 9, with a total score of 3-5 representatives of grade 1, a total score of 6 or 7 representatives of grade 2, and a total score of 8 or 9 representatives of grade 3 (Table 1) [5].

Statistical analysis
Data were coded and entered using the statistical package SPSS (Statistical Package for the Social Sciences) version 23. Data were summarized using mean, standard deviation, median, minimum and maximum in quantitative data and using frequency (count) and relative frequency (percentage) for categorical data. Comparisons between quantitative variables were done using the nonparametric Kruskal-Wallis and Mann-Whitney tests [6]. ROC curve was constructed with area under curve analysis performed to detect the best cutoff value of ADC for the detection of high-grade tumors. P values less than 0.05 were considered statistically significant.

Results
One hundred fifty-six patients were included in this study, their age ranged from 26 to 67 years (mean age 47.62 ± 10.36).
Analysis of the diffusion-weighted images and comparison of the mean ADC value with the pathological grade of the tumor was done.
All the included carcinomas (100%) showed persistent high signal on DWI with low to intermediate signal on ADC map (i.e., restricted diffusion).
There was a significant difference between the mean ADC value of tumors of grade I and III (p = 0.001) and  between grade I and II (p = 0.002). However, there was no significant difference between grade II and III (p = 0.979). Moreover, ROC curve analysis of the data revealed that using the ADC value of 0.79 × 10 -3 mm 2 /s as a cutoff value to differentiate between grade III from grades I and II yielded a sensitivity, specificity, PPV, NPV, and accuracy of 83.3%, 52.3%, 32.3%, 91.0%, and 58.9%, respectively, AUC = 0.647, and 95% confidence interval of 0.498 to 0.795. The use of mean ADC value of 0.93 × 10 -3 mm 2 /s as a cutoff value to differentiate between grades II and III from grade I showed better statistical indices (sensitivity 98%, specificity 100%, PPV 100%, NPV 83.3%, and accuracy 98.2% AUC = 0.994, and 95% confidence interval of 0.978 to 1.000) and enhanced the performance of the ADC value in the assessment of the tumor cellularity of the induced breast carcinoma (Tables 2 and 3- Figs. 5 and 6).

Discussion
Breast carcinoma shows various molecular characteristics and differences in biological behavior, clinical progress, and prognosis [7].
Precise assessment of disease characteristics and prognosis preoperatively would be of extreme importance in the diagnosis and treatment planning of breast cancer [8].
The role of breast MRI has been greatly increasing and it is becoming rather mandatory for preoperative assessment of patients because of its accurate valuable information regarding the characteristics, extent, and number of breast lesions.
The rapid growth of cancer is coupled with a change of both anabolism and catabolism affecting its growth and changing the intracellular and extracellular environment. Functional MR imaging techniquessuch as diffusion-weighted imaging (DWI) and the measured apparent diffusion coefficient (ADC)-are helpful to detect such changes coupled with tumor proliferation [9].
However, Belli et al. [7] and Costantini et al. [4] reported a slightly higher mean ADC value measuring 1.02 × 10 − 3 mm 2 /s and 1.03 × 10 − 3 mm 2 /s, respectively. This is probably because both Belli et al. [7] and Costantini et al. [4] studies included ductal carcinoma in situ among their investigated cases, while our study specifically included only invasive carcinomas which were more likely to have lower ADC values than the non-invasive forms.
ADC values ranged from 0.50 to 1.10 × 10 − 3 mm 2 /s in our study and so, it did not exceed the cutoff value between benign and malignant breast lesions set by previous studies, such as Sharma et al. [9] who estimated a cutoff ADC value of 1.23 × 10 -3 mm 2 /s, and Tan et al. [15] who found that the cutoff ADC values for benign and malignant lesions were 1.21 × 10 -3 mm 2 /s for b = 500 s/mm 2 and 1.22 × 10 -3 mm2/s for b = 1000 s/mm 2 , respectively.
The relation between the mean ADC value and the histological grade of the detected breast carcinoma was studied in the current work. We found that there was a significant inverse relation between them, meaning that tumors with higher grade showed lower ADC values when compared with those of lower grade (p = 0.001).
This was consistent with the previous researches done by of Belli et al. [7], Abdel Razek et al. [16], Costantini et al. [4], and Gouhar et al. [11] who had reached the same conclusion.  Our results agreed also with Sharma et al. [9], Guo et al. [17], Hatakenaka et al. [18], and Matsubayashi et al. [14] who reported a significant correlation between the ADC value and the tumor cellularity.
On the other side, Park et al. [12] and Tan et al. [15] stated that no significant correlation was found between ADC values and tumor grades.
Also, Yoshikawa et al. [19] research which included 27 breast cancer patients, 24 of which were invasive ductal carcinoma, found that the mean ADC of breast cancer did not significantly correlate with cancer cellularity.
However, it differs from the results obtained by Costantini et al. [4] who reported that the mean ADC values for grade I, II, and III tumors were 1.25 × 10 − 3 mm 2 /s, 1.02 × 10 − 3 mm 2 /s, and 0.92 × 10 − 3 mm 2 /s, respectively. This variation may be attributed to the discrepancy in the sample size and the MRI technique specially the use of different b values.
We found a significant difference between the mean ADC value of tumors of grade I and III (p = 0.001) and between grade I and II (p = 0.002). However, there was no significant difference between grades II and III (p = 0.979).
This was different from the results of Gouhar et al. [11], who reported that there was a significant difference in the mean ADC value of tumors of grade II and III (p = 0.003), and no significant difference between grade I and II (p = 0.054), we think the difference was due to the difference in the b values used as Gouhar et al. used only two b values (0 and 1000).
Analysis of our data revealed that using the ADC value 0.79 × 10 − 3 mm 2 /s as a cutoff value between grade III and grades I and II has a sensitivity, specificity, PPV, NPV, and accuracy of 83.3%, 52.3%, 32.3%, 91.0%, and 58.9%, respectively. On the other hand, using the ADC value of 0.93 × 10 − 3 mm 2 /s as a cutoff value between grade I and grades II and III has a sensitivity, specificity, PPV, NPV, and accuracy of 98%, 100%, 100%, 83.3%, and 98.2%, respectively. Yet, we have to admit that our study was limited by the uneven distribution of the different histological grades which is due to the limited number of grade I and grade III tumors included.

Conclusion
ADC value could be a good discriminator between lowand high-grade tumors and hence predictor of breast cancer cells that would respond to chemotherapy.