|Year : 2020 | Volume
| Issue : 1 | Page : 320-325
The role of diffusion magnetic resonance imaging in evaluation of suspicious breast lesions
Mohamed A Maaly1, Safaa A.E. Mohamed1, Mahmoud A Abdella2
1 Department of Diagnostic Radiology, Faculty of Medicine, Menoufia University, Menoufia, Egypt
2 Department of Diagnostic Radiology, Diagnostic Radiology at Ministry of Health, Al Bagour General Hospital, Menoufia, Egypt
|Date of Submission||25-Jul-2018|
|Date of Decision||24-Aug-2018|
|Date of Acceptance||28-Aug-2018|
|Date of Web Publication||25-Mar-2020|
Mahmoud A Abdella
Shebien Elkom, Menoufia 33667
Source of Support: None, Conflict of Interest: None
The aim was to evaluate the role of diffusion-weighted (DW) MRI with apparent diffusion coefficient (ADC) value measurement in differentiating benign from malignant breast lesions.
DW imaging is a potential resource as a coadjutant of MRI in the differentiation between benign and malignant lesions.
Patients and methods
This prospective study included 30 patients with suspicious breast lesions in mammography and/or ultrasound study from April 2017 to April 2018. Patients had undergone dynamic contrast-enhanced MRI and DW imaging before their biopsy. ADC value was calculated by placing region-of-interest over required area in DW-MRI at b value 1000 s/mm2. The sensitivity and specificity of DW-MRI were determined for comparison with histological results.
The study included 30 cases, where 21 were malignant and nine were benign. Significant results were obtained between ADC values of benign and malignant lesions (P < 0.001). The mean ADC for benign lesions was 1.10 × 10-3 mm2/s, whereas mean ADC for malignant lesions was 1.63 × 10-3 mm2/s. Cut-off level of ADC was 1.03 × 10-3 mm2/s. DW-MRI achieved a sensitivity of 62% and a specificity of 88% for differentiating benign and malignant lesions.
DW imaging is a potential resource as a coadjutant of MRI in the differentiation between benign and malignant breast lesions.
Keywords: b value, breast lesions, diffusion-weighted imaging, magnetic resonance imaging
|How to cite this article:|
Maaly MA, Mohamed SA, Abdella MA. The role of diffusion magnetic resonance imaging in evaluation of suspicious breast lesions. Menoufia Med J 2020;33:320-5
|How to cite this URL:|
Maaly MA, Mohamed SA, Abdella MA. The role of diffusion magnetic resonance imaging in evaluation of suspicious breast lesions. Menoufia Med J [serial online] 2020 [cited 2020 Jun 6];33:320-5. Available from: http://www.mmj.eg.net/text.asp?2020/33/1/320/281276
| Introduction|| |
Breast cancer is considered a common malignancy and a cause of cancer death worldwide. Despite the improvements in detection of breast cancer with widespread application of mammography and breast ultrasound, differentiation between benign and malignant breast lesions is considered a difficult diagnostic problem.
Early detection of breast cancer by screening with mammography has the potential to decrease mortality, but it can also lead to overdiagnosis and overtreatment. Although screening can early detect nonpalpable tumors, the harms of unnecessary treatment of over diagnosed tumors could reduce any potential benefits.
Ultrasound has a considerable role in breast imaging and management today. Previously, the role of breast ultrasound was limited to discerning whether a lesion was solid or cystic and detection of the presence of microcalcifications. Recently, breast ultrasound has a very important function in breast diagnostic workup, including not only its capacity as an imaging modality in itself but also as a means of undertaking various types of needle biopsy interventions. However, the main limitation of US is its operator-dependent nature.
MRI is an established supplementary technique to mammography and ultrasound for evaluation of suspicious breast lesions, and it has a higher sensitivity over both mammography and ultrasound.
Diffusion-weighted MRI (DW-MRI) is an advanced MRI technique, which allows the mapping of in-vivo water diffusion processes in a noninvasive manner; it has a higher sensitivity and specificity in detecting suspicious breast lesions than routine MRI.
DW-MRI can provide information about the physiological properties of the tissue in addition to morphology and perfusion that are reported by conventional and MRI. DWI displays the random motion of in-voxel water molecules and also has been introduced to provide a more specific biophysiological characterization of suspicious breast lesions in MRI. Several publications suggest the use of DWI and its quantification using the apparent diffusion coefficient (ADC) values as an additive measure with the aim to improve the specificity of breast MRI.
The objective of this study was to evaluate the role of DWI with ADC value measurement in differentiating benign from malignant breast lesions.
| Patients and Methods|| |
This prospective study included 30 women (age range: 29–68 years) who underwent breast DW-MRI from April 2017 to April 2018 at National Cancer Institute (NCI) because of suspicious findings on mammography and/or breast ultrasound. The sources of specimens for histological examination were surgical excision and core needle biopsy. All patients had DW-MRI before the biopsy or surgical procedure.
An informed consent was obtained before persons were included in the study. Approval from the local research ethical committee was obtained.
Dynamic contrast-enhanced (DCE) MRI was performed with high field strength 1.5 Tesla closed MRI Philips Achieva using dedicated double breast coil (Philips Healthcare, Andover, MA, US). Coronal T1-weighted spin echo sequence was carried out for localization purpose and followed by plain sequences using T1-weighted fast spin echo sequence (TR = 491 ms and TE = 10 ms), in addition to T2-weighted fast spin echo sequence (TR = 4841 ms, TE = 120 ms) in axial orientation. DWI was performed before the DCE-MRI acquisition using a DW echo-planar imaging sequence with parallel imaging; number of excitations, 2; slice thickness, 4.5 mm; and gap, 0. Diffusion gradients were applied with b = 0 and 1000 s/mm2. Respiratory triggering was used for better resolution. A bolus of gadolinium dimeglumine (Gd-DTPA) was injected manually intravenously at a dose of 0.1 mmol/kg followed by saline flush to ensure that contrast-enhanced images could be obtained immediately after contrast agent injection. Dynamic T1 WIs were then performed using gradient echo T1-weighted image with fat suppression.
Image interpretation started similar to conventional breast MRI. If a lesion was visualized in the dynamic scan, it had to be identified in the corresponding slice of the diffusion-weighted images (DWIs). As a second step, a region-of-interest (ROI) was drawn in the center of the lesion on the b-1000 DWI and copied to the ADC map. The scanner software provided the mean value within the ROI which was automatically calculated when the ROI was drawn and equals the ADC value (multiplied by 10−3 mm2/s). A small ROI was used in the area near the tumor edge to achieve the greatest accuracy.
Subtraction images were first examined to detect the presence or absence of lesion enhancement. In case of lesion enhancement, the corresponding nonsubtracted precontrast and postcontrast images in each time point were viewed together, and lesion interpretation took place as whether it was a focus, mass, or non-mass-like enhancement.
Dynamic behavior of the mass with evaluation of the % of enhancement as well as the shape of time/signal intensity curve (type I, type II, or type III) was studied. DWIs and ADC maps are then examined regarding the signal intensity and the mean ADC of each lesion. MRI BI-RADS classification was applied for each lesion based on the combination of morphologic and kinetic criteria. Findings were correlated with histopathological result.
Data were fed to the computer using IBM (SPSS Inc., Chicago, Illinois, USA) software package, version 20.0. Receiver operating characteristic curve analyses were performed to assess the diagnostic performance of the ADC values in tumor characterization and determine suitable ADC cut-off points to separate benign and malignant lesions. The results were expressed by applying ranges, means ± SD, Fisher exact test, Student's t-test, and P (probability) values. Accuracy was represented using the terms sensitivity and specificity.
| Results|| |
The present study included 30 female patients; their age ranged between 29 and 68 years, with mean age of 48 years old. The mean age of the patients with benign lesions is 39.1 years old. The mean age of the patients with malignant lesions is 51.8 years. The age of patients is younger in cases with benign lesions.
All 30 patients enrolled in this study successfully underwent DW-MRI for their suspicious breast findings and had a histopathological correlation. There were 21 malignant lesions, including sixteen invasive ductal carcinomas, two invasive lobular carcinomas, two phylloids tumor, and one mucinous adenocarcinoma. There were nine benign lesions, four fibroadenomas, three granulomatous mastitis, one galactocele, and one traumatic fat necrosis.
The lesions were categorized according to Breast Imaging-Reporting and Data System (BI-RADS) based on their sonomammographic features: four lesions were categorized as BI-RADS III, and they were proved to be benign; nine lesions were categorized as BI-RADS IV, where four were proved to be benign and five lesions were proved to be malignant; and 17 lesions were categorized as BI-RADS V, and they were proved to be malignant. BI-RADS system has a significant role in differentiation between malignant and benign lesion (P = 0.0001). Incidence of malignancy increased with lesions with BI-RADS IV or BI-RADS V category [Table 1].
|Table 1: Describes the relation between Breast Imaging-Reporting and Data System categorization of the lesion in relation to type of lesions|
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All patients were referred for MRI examination. The dynamic behavior of the mass was evaluated, with evaluation of the percentage of enhancement as well as the shape of time/signal intensity curve (type I, type II, or type III). Comparing the enhancement kinetics with the final diagnosis revealed that all lesions with progressive enhancement curve (type I) proved to be benign, all lesions with washout curve (type III) proved to be malignant, and 50% of lesions with plateau curve (type II) proved to be malignant. The dynamic behavior of the lesions has significant role in differentiation between malignant and benign lesion (P = 0.001) [Table 2].
|Table 2: Describes the relation between dynamic enhancement curves of the lesions and type of lesions|
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By DWI, the lesions were classified according to their diffusion criteria as restricted or facilitated. ADC value was calculated by placing ROI over required area in DW-MRI at b value 1000 s/mm2. Most benign lesions had facilitated diffusion (88.9%), with the mean ADC for benign lesions of 1.63 × 10−3 mm2/s [Figure 1], and most malignant lesions had restricted diffusion (90.5%), with the mean ADC for malignant lesions of 1.10 × 10−3 mm2/s [Figure 2], with significant difference between malignant and benign lesion (P = 0.00001). The mean ADC for malignant masses was lower than the mean ADC for benign lesions at b value 1000 s/mm2 [Table 3].
|Table 3: Describes the relation between mean apparent diffusion coefficient value, diffusion criteria of lesions and type of lesions|
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|Figure 1: A representative case of benign breast lesion: Granulomatous mastitis (in a 32-year-old patient). (a) MRI axial T2W1 of the left breast mainly the central portion shows sizable ill-defined area of heterogeneous signal intensity (white arrow). (b) MRI axial Short-TI Inversion Recovery (STIR) of the lesion shows increased signal intensity. (c and d) Diffusion-weighted imaging and the corresponding ADC map respectively showed heterogeneous diffusion restriction of the lesion with average ADC value of 1.6 × 10-3 mm2/s. (e) Postcontrast MRI shows area of nonmass enhancement with type II time intensity curve. ADC, apparent diffusion coefficient.|
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|Figure 2: A representative case of malignant breast lesion: invasive ductal carcinoma (in a 48-year-old patient). (a) MRI axial T2W1 showing hypointense spiculated lesion with ill-defined outlines at the upper outer quadrant of the left breast (white arrow). (b) MRI axial STIR of the lesion shows increased signal intensity. (c and d) Diffusion-weighted imaging and the corresponding ADC map respectively showed restricted diffusion of the lesion with average ADC value of 0.87 × 10-3 mm2/s. (e) Postcontrast MRI with subtraction images showing heterogeneous enhancement with type III time intensity curve. ADC, apparent diffusion coefficient.|
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Cut-off level of ADC was 1.03 × 10−3 mm2/s. DW-MRI achieved a sensitivity of 62% and a specificity of 88% for differentiating between benign and malignant lesions [Figure 3].
|Figure 3: Receiver operating characteristic curve of apparent diffusion coefficient (ADC) to calculate cut-off point.|
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| Discussion|| |
DCE-MRI of the breast has a high sensitivity for breast cancer detection and has recently been shown to be the most sensitive breast screening technique.
DWI has recently been reported to demonstrate usefulness in differentiating benign from malignant breast lesions.
In addition, using DWI and ADC values are useful in differentiating benign from malignant breast masses and in the detection of breast cancer without administration of contrast medium. Hence, DWI could be a promising tool in screening for breast cancer without using contrast medium, especially for patients with renal dysfunction or previous reactions to contrast agents and will relieve the cost of examination.
The present study has shown that the mean age of patients presenting with breast lesions was 48 years. The age range was 29–68 years. The mean age of patients with benign lesions is 39.1 years and for those with malignant lesions is 51.8 years. The age of patients is younger in cases with benign lesions. It agreed with a study by Lalitha, which included 200 patients (199 female patients and one male patient) between the ages of 16 and 80 years, and the mean age was 48 years.
According to the present study, the most frequent malignant lesion was infiltrating ductal carcinoma, which represented 53.3%, whereas the most frequent benign lesion was fibroadenoma, which represented 13.3%.
On the contrary, the study by Min et al. on 52 women (age range: 20–86 years) who underwent breast DW-MRI between March 2008 and March 2010 showed in the breast lesions survey that invasive ductal carcinoma accounted for 50% and fibroadenoma accounted for 19.2%.
Our studied cases were classified according to the diffusion pattern in the detected lesions into two groups: group 1 includes 20 (66.7%) cases that showed restricted diffusion and group 2 includes the remaining 10 (33.3%) cases that showed no significant diffusion restriction.
According to the ADC values, our findings for lesions showed that the best ADC cut-off value to differentiate between benign and malignant lesions was 1.03 × 10−3 mm2/s. Malignancy exhibited lower mean ADC values compared with those of benign lesions, being 1.10 × 10−3 and 1.63 × 10−3 mm2/s, respectively.
The most common benign mass was fibroadenoma; this agrees with the finding of Partridge et al.. They found that malignant masses had a mean ADC of 1.25 ± 0.29 × 10−3 mm2/s, and benign masses had a mean of 1.74 ± 0.46 × 10-3 mm2/s.
Chen et al. in a meta-analysis of 964 breast lesions (615 malignant, 349 benign) from 13 studies found that the mean ADC values of malignancy ranged from 0.87 to 1.36 × 10−3 mm2/s. The mean ADC values of benign lesions ranged from 1.00 to 1.82 × 10−3 mm2/s. The cut-off values differentiating malignant and benign lesions ranged from 0.90 to 1.76 × 10−3 mm2/s, and the sensitivity and specificity ranged from 63 to 100% and 46 to 97%, respectively.
Balzer et al. stated that the mean ADC was significantly lower for malignant lesions (1.05 ± 0.33 × 10–3 mm2/s) as compared with benign lesions (1.63 ± 0.42 × 10–3 mm2/s), with threshold value of the ADC of 1.23 × 10–3 mm2/s.
Matsubayashi et al. found the mean ADC for malignant lesions, namely, IDC, was 0.915 ± 0.151 × 10−3 mm2/s.
Pereira et al. stated that the mean ADC was significantly lower for malignant lesions (0.92 ± 0.26 × 10–3 mm2/s) as compared with benign lesions (1.50 ± 0.34 × 10–3 mm2/s).
In their study of 41 women, Sonmez et al. founded the threshold value of the ADC was 1.0 × 10–3 mm2/s; its sensitivity was demonstrated as 95%, specificity as 100%, positive predictive as 100%, negative predictive as 94% and accuracy rate as 97%.
The correlation between the findings of DWI and histopathological results of different breast lesions showed the value of this sequence as an additive tool that augments the results of dynamic MRI and increases the overall specificity of the study. This fact gains a wide agreement with a large number of studies.
The present study had some limitations. First, the comparison of our results with other studies was somewhat problematic because of differences in patient selection criteria, number of patients, and examination techniques.
In addition, our series is relatively small, and further studies should consider increasing the sample number to improve the statistical power for precise evaluation of DWI.
Despite these limitations, the present study revealed that DWI of the breast provides additional information to characterize focal breast lesions in a fast and easy way.
Thus, by combining ADC measurements and dynamic studies with interpretation of enhancement patterns, the latter known to have good sensitivity but variable specificity for characterizing lesions, the overall accuracy of MRI can be increased, reducing unnecessary invasive procedures. Nevertheless, further studies with larger populations are needed to confirm the use of DWI in the evaluation of breast lesions.
| Conclusion|| |
DWI is a potential resource as a coadjutant of MRI in the differentiation between benign and malignant lesions. DWI should be included as a routine modality when examining any breast lesion by MRI.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Figure 1], [Figure 2], [Figure 3]
[Table 1], [Table 2], [Table 3]