Higher perfusion among breast malignant tumors than among breast benign lesions as demonstrated by diffusion-derived ‘vessel density’ (DDVD): a pilot study

Introduction

Magnetic resonance imaging (MRI) of the breast is the most sensitive imaging modality for detecting cancer. It is currently used as an adjunct to the standard diagnostic procedures of the breast, i.e., clinical examination, mammography and ultrasound (1,2). Angiogenesis constitutes a prerequisite for the growth of malignant tumors (MTs) beyond a certain size. An association between the degree of tumor malignancy and prognosis with microvessel density (MVD) and proliferative activity have been described (3-5). It has been consistently reported that breast MTs lesions have a denser microvessel network than fibroadenomas, while there was no difference between the number of vessels in the fibroadenoma and its adjacent stroma. Weidner et al. (4,5) reported that MVD in the area of the most intense neovascularization in invasive breast carcinoma is an independent and highly significant prognostic indicator for overall and relapse-free survival in patients with early-stage breast carcinoma. The number of microvessels in the areas of most intensive neovascularization in an invasive breast carcinoma can be an independent predictor of metastatic disease either in axillary lymph nodes or at distant sites or both. The higher the MVD, the better the nutritional tumor situation, which in turn facilitates tumor growth and poor prognosis (4-7). For contrast-enhanced (CE) MRI of the breast, established characteristics of MTs are a rapid enhancement, followed by a washout and pronounced enhancement in the tumor periphery, and sometimes the so-called rim enhancement is observed (8-10).

The MRI biomarker diffusion-derived ‘vessel density’ (DDVD) works on the principle that blood vessels including sub-pixel microvessels show high signal when there is no motion probing gradient (b=0 s/mm²) and low signal when even very low b-values diffusion gradients are applied (11-14). The clinical usefulness of DDVD as a straightforward diffusion imaging biomarker has been demonstrated in multiple studies (11-23). DDVD is a useful parameter for distinguishing livers with and without fibrosis, and livers with severer fibrosis tend to have even lower DDVD measurements than those with milder liver fibrosis (11,12). Chen et al. (16) described a proof-of-concept study that a combination of DDVD map and high b-value diffusion weighted imaging (DWI) identifies the existence and the size of penumbras in acute brain stroke. Zheng et al. (17) demonstrated that per unit micro-circulation of spleen as measured by DDVD is decreased in viral Hepatitis-B liver fibrosis patients. This is consistent with, for example, the report of Gitlin et al. (18) with analysis of patients with liver cirrhosis and portal hypertension. Among the patients, splenic blood flow, expressed as mL per 100 g of splenic tissue, was decreased. On the contrary, total splenic blood flow, calculated by multiplying specific splenic flow by spleen volume, was increased (18). Lu et al. (19) reported earlier clinical grades rectal carcinoma had a higher DDVD than those of the advanced clinical grades, which is consistent with the known clinical characteristics of rectal carcinomas. Wang et al. (20) reported endometrial carcinoma with Ki-67 high-proliferation or aggressive histological type had higher DDVD values than those with Ki-67 low-proliferation or non-aggressive histological type [area under the receiver operating characteristic curve (AUROC) for Ki-67 expression status: 0.842, AUROC for aggressiveness of histological type: 0.771]. Ni et al. (21) tested DDVD analysis for isocitrate dehydrogenase (IDH) genotyping in diffuse gliomas. DDVD was lower among IDH-mutant positive gliomas than among IDH-wildtype gliomas, with an AUROC of 0.823 for separating IDH-mutant positive gliomas from IDH-wildtype gliomas. DDVD was also positively associated with Ki-67 expression for gliomas (21). He et al. (22) and Li et al. (23) reported that DDVD analysis of the placenta allows separation of normal and early preeclampsia pregnancies, with substantially lower placenta DDVD among early preeclampsia patients, and this reflects the compromised perfusion of placenta in the preeclampsia pregnancy patients.

DDVD has the advantage that it does not involve contrast agent administration, the data acquisition is fast involving only two sets of DWI images. The goal of the current study is to explore where there is a DDVD pattern difference between MT and benign lesions (BL) of the breast. Breast cancer has surpassed lung cancer to be the most common cancer in the world, accounting for a severe global burden among women. A non-invasive technique to assess breast lesion perfusion is highly desired.

Methods

The study was approved by the local institutional review board of Longgang Central Hospital of Shenzhen, China, and with informed consent obtained. The other participating institution was also informed of and consented to this study. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. Fifty-two consecutive patients had the prescribed MRI. Standard breast MRI protocol included T1 weighted imaging, T2 weighted imaging, fat-suppressed single-shot spin-echo echo-planar-imaging (EPI) sequence DWI data, and gadolinium CE imaging were sampled in the axial plane. For data from Hospital 1 (Peking University Shenzhen Hospital), MRI was performed using a 3 T MRI scanner (Ingenia, Philips Healthcare), with a sense breast 16-channel coil for radiofrequency signal transmission and reception. The DWI parameters included: repetition time (TR)/echo time (TE), 5,148.1/74.7 ms; field of view (FOV) 340 mm × 340 mm; 4 mm slice thickness; inter-slice gap: 0.8 mm; pixel size 0.966 mm × 0.966 mm; number of averages (NEX): 2; b-values: 0, 10, 800 s/mm². Hospital 1 enrolled 17 cases including: 13 invasive carcinomas (76.5%; median age 49 years, range 35–66 years, among them four completed chemotherapy), 2 ductal carcinomas in situ (11.8%; aged 34 and 47 years, with one completed chemotherapy), and 2 BLs (11.8%; aged 35 and 38 years). For data from Hospital 2 (Longgang District Maternity & Child Healthcare Hospital of Shenzhen), MRI was performed using a 1.5 T MRI scanner (Optima MR360, GE Healthcare), with a 4-channel breast array coil for radiofrequency transmission and reception. The DWI included: TR/TE, 7,111/43.6 ms; FOV 260 mm × 260 mm; 4 mm slice thickness; inter-slice gap: 1 mm; pixel size: 1.016 mm × 1.016 mm; NEX: 4; b-values: 0, 10, 1,000 s/mm². Hospital 2 enrolled 35 cases including: 9 invasive carcinomas (25.7%; median age 48 years, range 37–62 years, among them three were undergoing chemotherapy), one ductal carcinoma in situ (2.9%; age 42 years), 1 intraductal papillary carcinoma (2.9%; aged 67 years), three pyogenic mastitis cases (8.6%; median age 39 years), one granulomatous mastitis case (2.9%; aged 45 years), 11 fibroadenomas/adenosis cases (31.4%; median age 40 years, ranged 35–60 years), and 9 radiologically BLs without pathological confirmation (25.7%; median age 43 years, range: 32–59 years). For the 24 BLs from Hospital 2, one lesion, 9 lesions, 14 lesions, and one lesion were classified as Breast Imaging Reporting and Data System (BI-RADS) 2, BI-RADS 3, BI-RADS 4A, and BI-RADS 4B (the lesion was confirmed to be BL with follow-up), respectively.

This study focused on the analysis of DDVD data. DDVD value and DDVD pixelwise map (DDVDm) were computed using the following equations (11-14):

For region-of-interest (ROI) approach:

DDVDb0b10=Sb0ROIarea_b0−Sb10ROIarea_b10[unit:arbitraryunit(au)/pixel][1]

For DDVDm approach:

DDVDb0b10=Sb0−Sb10[unit:arbitraryunit(au)/pixel][2]

where S_b0 and S_b10 refer to the sum of signals within the selected ROI on b=0 and 10 s/mm² images, respectively. ROI_{area_b0} and ROI_{area_b10} refer to the ROI area (unit in pixels) on b=0 and 10 s/mm² images.

The quantification applied ROI-based analysis according to Eq. [1]. Contours were manually drawn on b=0 s/mm² covering the lesion, and adjusted with reference to anatomical images, excluding necrotic and cystic regions if existed. Visible vessels near the lesion were also excluded. The contours on b=0 s/mm² image were then fitted to the b=10 s/mm² diffusion weighted (DW) images. The contours were further adjusted manually. The contours for ROI analyses were drawn by a trainee radiologist and a trained engineering graduate, then an experienced radiologist checked the quality of the contours and finally consensuses were reached. As absolute magnetic resonance (MR) signal intensity is influenced by various factors, including B1 spatial inhomogeneity, coil loading, and receiver gain, etc., in this study the ratio of a lesion DDVD measure to a DDVD measure of the contralateral breast of similar site and expected similar tissue type was used to minimize these scaling factors.

DDVDr=DDVDofbreastlesionDDVDofcontralateralbreastofsimilarsite[3]

The mean of all included slice measurements was regarded as the value of the DWI scan (in some cases, the lesion was shown on only one slice), with the last step weighted by the ROI area of each slice.

For qualitative visual assessment according to Eq. [2], with the location reference to the T1 weighted, T2 weighted, and DW images but without reference to gadolinium contrast (CE) enhanced images, a potential lesion site was subjectively classified to have or do not have regional increased DDVD signal.

Statistical analysis was performed using GraphPad Prism Software (GraphPad Software Inc., San Diego, CA, USA). Comparisons were tested by Mann-Whitney U test. A P<0.05 was considered statistically significant.

Results

Quantitatively measured DDVD ratio (DDVDr) values are shown in Figure 1. While there were overlaps, breast MT tended to show higher DDVDr value than those of breast BL. A trend was noted that higher BI-RADS grade lesions had higher DDVDr value than those of lower BI-RADS grade lesions (Figure 1B). A tentative trend was also noted that, the patients completed chemotherapy (from Hospital 1, MT median: 4.951, post-chemotherapy MT median: 1.323) had lower DDVDr value than those of the patients under chemotherapy (from Hospital 2, MT median: 3.020, MT under-chemotherapy median: 1.937).

Figure 1 DDVDr value of breast tissues or breast lesions of the two-hospital data (A: data of Peking University Shenzhen Hospital; B: data of Longgang District Maternity & Child Healthcare Hospital of Shenzhen). A trend is seen that MTs tend to have a higher DDVDr value than those of BLs. P value was 0.121 for data in (A) (BL vs. MT comparison, post-chemotherapy patients not included for P value calculation), non-significant likely due to that there were only two BLs. P value was <0.0001 for data in (B) (all BLs were grouped together, patients under chemotherapy not included for P value calculation). Dots with “*” represent three cases being false negative for malignancy with visual assessment, while DDVDr results suggest two of them were likely to be MT. Dots with “^” represent two cases being false positive for malignancy with visual assessment. The false positive lesion in the case under chemotherapy is at the contralateral breast of an MT after chemotherapy, and was diagnosed as BI-RADS grade-3 nodule and under ultrasound surveillance. Dots with “#” represent two cases with lesion of visual high DDVD signal due to ‘T2 shine-through’. Dots with “i” represent four lesions showing high visual DDVD signal due to inflammatory change. According to DDVDr results, lesions with visual high DDVD signals due to ‘T2 shining through’ or due to inflammatory changes still tend to have DDVDr value lower than those of MT. Noted that, DDVDr values from different magnetic field strength and different scan parameters are not directly comparable (24). BI-RADS, Breast Imaging Reporting and Data System; BL, benign lesion; chemo, chemotherapy; DDVD, diffusion-derived ‘vessel density’; DDVDr, DDVD ratio; MT, malignant tumor.

Examples of breast DDVDm visualization are shown in Figures 2-7. Among the total 52 cases, 30 cases were judged to have ‘no suspicious increased regional vascularity’, while 22 cases were judged to have ‘suspicious increased regional vascularity’ in the lesion site.

Figure 2 A comparison of DDVDm of breast post-chemotherapy for MT (A-D, arrows) and breasts with treatment naïve MT (E-I, arrows). (A-I) represent 9 patients respectively. (A-D) Cases with breast MT post-treatment patients. (E-H) Cases with invasive carcinoma. (I) A case with ductal carcinoma in situ (arrows). (A,B,C,D,E3,F3,G3,H3,I3) DDVDm; (E3-I3) DDVDm shows apparent increased regional vascularity (arrows). (E1-I1) T2W images. (E2-I2) b=0 s/mm² DW images. (E4-I4) CE images 60 seconds post-gadolinium injection. CE, contrast-enhanced; DDVD, diffusion-derived ‘vessel density’; DDVDm, DDVD pixelwise map; DW, diffusion weighted; DWI, diffusion weighted imaging; MT, malignant tumor; T2W, T2 weighted.

Figure 3 DDVD imaging of two cases of breast invasive carcinoma (arrows). The tumor regions demonstrated higher DDVD signal (arrows). The high signal DDVD rim shown in (B7) is a typical sign for breast MT (8-10). (A1,B1) T2W images. (A2,B2) b=0 s/mm² DW images. (A3,B3) b=1,000 s/mm² DW images. (A4,B4) ADC_{b0b1, 000} maps. (A5,B5) Angiographic rendering of breast vessels based on the principle of DDVD while without an application of contrast agent, which endorses the principle of DDVD-based angiography (though an improvement in resolution is desired for breast angiography). (A6,B6) Angiographic rendering of breast vessels based on gadolinium enhanced MRI. (A7,B7) DDVDm. (A8,B8) CE images 60 seconds post-gadolinium injection. ADC, apparent diffusion coefficient; CE, contrast-enhanced; DDVD, diffusion-derived ‘vessel density’; DDVDm, DDVD pixelwise map; DW, diffusion weighted; DWI, diffusion weighted imaging; MRI, magnetic resonance imaging; MT, malignant tumor; T2W, T2 weighted.

Figure 4 DDVDm of two cases of breast inflammatory lesions (arrows). (A1,B1) T2 weighted images. (A2,B2) b=0 s/mm² DWIs. (A3,B3) b=1,000 s/mm² DWIs. (A4,B4) ADC_b0b1,000 maps. (A5,B5) DDVDm. (A6,B6) CE images 60 seconds post-gadolinium injection. ADC, apparent diffusion coefficient; CE, contrast-enhanced; DDVD, diffusion-derived ‘vessel density’; DDVDm, DDVD pixelwise map; DWI, diffusion weighted imaging; T2W, T2 weighted.

Figure 5 DDVDm of a case of breast invasive carcinoma. Due to the increase in vascular signal is limited visually, this case was not initially considered to be with MT based on DDVDm. However, this case’s DDVDr value resembles measures of MT. (A) T1 weighted image; (B) T2 weighted image; (C) b=0 s/mm² DWI (arrow: the tumor); (D) b=1,000 s/mm² DWI (arrow: the tumor); (E) DDVDm (arrow: the tumor); (F) CE images 60 seconds post-gadolinium injection, the tumor (arrow) showing high enhancement. CE, contrast-enhanced; DDVD, diffusion-derived ‘vessel density’; DDVDm, DDVD pixelwise map; DDVDr, DDVD ratio; DWI, diffusion weighted imaging; MT, malignant tumor; T1W, T1 weighted; T2W, T2 weighted.

Figure 6 Explanation of ‘T2 shine-through’ effect for DDVDm in two cases (A,B). For the benign lesion in (A) (arrows), DDVDm shows high signal, but CE image does not show increased gadolinium enhancement. This lesion’s DDVD high signal is considered to be due to ‘T2-shine-through’ which is also seen with liquid signal of gallbladder and simple cyst when liver DDVD is measured (14,24). This effect can be partially mitigated by using a very low second b-value for DDVD, such as b=1 or 2 s/mm² (13,24). The arrows in (B) denote a regenerative lymph node. CE images also show high perfusion for this node. The high DDVD of this node could be due to a combination of intrinsic high perfusion and the very high signal on b=0 s/mm² DWI. Thus, DDVD value should be interpreted with caution when a tissue is very bright on T2W image (and on b=0 s/mm² DWI), and particularly when there is a degree of misalignment between b=0 s/mm² DWI and the second b-value DWI. One such example is the CSF signal inside the spinal canal (14), which commonly shows artificially high signal on DDVDm. (A1,B1) T2W images. (A2,B2) b=0 s/mm² DWIs. (A3,B3) b=10 s/mm² DWIs. (A4,B4) b=1,000 s/mm² DWIs. (A5,B5) DDVDm. (A6,B6) CE images 60 seconds post-gadolinium injection. BL, benign lesion; CE, contrast-enhanced; CSF, cerebrospinal fluid; DDVD, diffusion-derived ‘vessel density’; DDVDm, DDVD pixelwise map; DWI, diffusion weighted imaging; T2W, T2 weighted.

Figure 7 Examples of 6 cases with breast BLs (arrows), no suspicious increased vascularity is noted on DDVDm. (A-F) represent 6 patients respectively. (A1,B1,C1,D1,E1,F1) T2W images. (A2,B2,C2,D2,E2,F2) DWIs. (A3,B3,C3,D3,E3,F3) DDVDm. (A4,B4,C4,D4,E4,F4) CE image 60 seconds post-gadolinium injection. BL, benign lesion; CE, contrast-enhanced; DDVD, diffusion-derived ‘vessel density’; DDVDm, DDVD pixelwise map; DWI, diffusion weighted imaging; T2W, T2 weighted.

For lesions subjectively assessed without ‘suspicious increased vascularity’ (n=30), 19 cases (63.3%, 19/30) were with BL, 8 cases (26.7%, 8/30) were MT patients post- or under-chemotherapy, and three lesions (10%, 3/30) were MT. Among these three MT cases without increased vascularity, one case was considered to demonstrate DDVD signal not high enough for MT (Figure 4), and another case had a small MT lesion. However, for these three false negative cases for malignancy with visual assessment, DDVDr results suggest two of them were likely to be MT (Figure 1).

For lesions subjectively assessed with ‘suspicious increased vascularity’ (n=22), 14 (63.6%) were MT, four were inflammatory lesions (18.2%), two (9.1%, 2/22) were BL but with ‘T2 shine-through’. ‘T2 shine-through’ refers to a lesion that has very high signal on T2 weighted image and on b=0 s/mm² DW image, and this resulted in high DDVD signal that might not reflect true increased vascularity (Figure 6). One ‘false positive’ high DDVD lesion (4.5%, 1/22) was finally diagnosed as mixed fibroadenoma but also with high perfusion as evaluated with gadolinium enhanced sequence. One ‘false positive’ high DDVD lesion (4.5%, 1/22) in a post-chemotherapy patient was diagnosed as BI-RADS grade-3 nodule in a breast contralateral to an earlier breast MT, and this nodule was under ultrasound surveillance. According to DDVDr results, lesions due to inflammatory changes still tended to have DDVDr value lower than those of MT (Figure 1).

Discussion

With both qualitative and quantitative analyses, this study shows a trend that breast BL had a lower DDVD value than that of breast MT. However, there were still overlaps between breast BL and MT in DDVD visual appearance or values. The initial false negative rate (for malignancy) was 10% (3/30) for visual assessment. After exclusion of cases of breast inflammatory lesions (n=4) and cases associated with ‘T2 shine-through’ (n=2), the initial false positive rate (for malignancy) was 12.5% (2/16) for visual assessment. It is expected that, together with other morphological images and clinical history and physical exam results (such as those for inflammatory lesions), DDVD results may aid the diagnosis of MT when regional DDVD is high. On the other hand, when there is no increase in regional DDVD, then the confidence for a negative result or for the diagnosis of BL may be improved. These results are consistent with many earlier reports. In an ultrasound study, Madjar et al. (25) reported that a cutoff value of >3 (number of) tumor vessels was characteristic of breast MT with a sensitivity of 89% and a specificity of 92%. Chao et al. (26) reported significantly higher values of vessel number and pulsatility index in breast MT than in BL. CE ultrasound also showed breast MT had an increased range of enhancement (27,28). On the other hand, some benign nonneoplastic breast lesions such as fibroadenomas, papillomas, hyperplasias and inflammatory changes may also exhibit avid angiogenesis (9,29). Meanwhile, breast MTs of low perfusion status are also reported (30). Some ductal carcinoma in situ of low-level could rely on healthy peripheral blood vessels to provide necessary nutrients. For some MTs, the immune system of the body can produce dynamic changes of reverse infiltration, forming an immune response zone around the lesion and inhibiting the formation of peripheral microvessels (31).

Intensity of angiogenesis is a strong independent predictor of relapse-free survival in patients with breast cancer (32-34). Neoadjuvant chemotherapy is accepted as a primary treatment for inoperable or locally advanced breast cancer before definitive surgery. Non-invasive imaging assessment of tumor perfusion has been used before the initiation of treatment or during treatment to predict the treatment response of neoadjuvant chemotherapy and other regional treatments (35-37). The ability of DDVD to quantitatively measure tissue perfusion in relative terms has been demonstrated. In healthy subjects, perfusion computed tomography (CT) and radioisotope imaging consistently showed that the overall perfusion is similar between the liver and spleen (24), and our study shows DDVD_liver was measured approximately similar to DDVD_spleen (24). DDVD analysis demonstrates the liver parenchyma has an age-dependent decrease of micro-perfusion (38). This agrees with the known physiological age-dependent reduction in liver blood flow. Both liver and spleen DDVD measures for women were larger than those of men, which is also consistent with the known gender difference in perfusion volume of the organs (17,38). With the advancement of pregnancy and the continuing growth of the placenta, the placental parenchyma became more fibrotic, calcium deposits and infarction occurred. A negative correlation between placenta DDVD with gestational age has been consistently demonstrated (22,23,39). In a recent analysis, when a TE of 59 ms (TR =1,600 ms, free breathing acquisition) and b=0, 2 mm²/s were used for the DDVD calculation of 26 cases of hepatocellular carcinomas (HCCs), the mean DDVD_HCC/DDVD_liver ratio was 1.42. This value agrees well with the literature results showing perfusion-CT blood volume ratio of HCC to liver (blood volume_HCC/blood volume_liver) median value being 1.38 (40). Yao et al. (41) used DDVD to evaluate parotid gland pleomorphic adenomas (PAs), MTs, and Warthin’s tumors. It was noted that DDVD ratios of both MTs to PA and Warthin’s tumors to PA were very similar to the mean ratio of computed tomography measured blood volume of these tumors. The current study shows breast lesions under- chemotherapy or post-chemotherapy had much reduced DDVD signal compared with treatment naive lesions. Moreover, lesions completed chemotherapy had lower DDVDr values than those of the lesions still under chemotherapy (Figure 1). Thus, DDVD imaging may have the potential to be used to predict the treatment response of neoadjuvant chemotherapy and other regional treatments for breast cancers.

There are some limitations to this study. This is a preliminary study with limited sample size. Factors such as patient age and menstrual cycle were not considered. While a trend could be noted that breast DDVD high signal lesions were associated with higher gadolinium enhancement, the precise relationship between DDVD value and gadolinium enhancement pattern has not been studied due to the limited sample size of this study. Breast lesions’ gadolinium enhancement is related to the factors such as blood volume, blood flow speed, and permeability of the regional vasculature. Besides the MRI scan parameters, DDVD is more related to the blood volume of lesions (13,24). Since the morphology and distribution of neovascularization in benign and malignant small breast masses can overlap, accordingly the current study showed a total separation of BL and MT purely based on DDVD was not possible, and DDVD based diagnosis was more of a suggestive rather than confirmatory nature. Moreover, DDVDm has a lower spatial resolution than those of morphological images, thus DDVD is not meant to detect small lesions. In the differential diagnosis, a comprehensive evaluation should be performed by combining medical history and other imaging methods, while this study only considered DDVD assessment. In this study, ‘suspicious increased regional vascularity’ was subjectively evaluated, and should be better clarified in the further with more studies, probably with the help of a comprehensive pictorial image database. The patients were scanned with two MRI scanners at two hospitals. The data from Hospital 1 were scanned using 3 T scanner with a spatial resolution of 0.966 mm × 0.966 mm × 4.0 mm, while the data from Hospital 2 were scanned using 1.5 T scanner with a spatial resolution of 1.016 mm × 1.016 mm × 4.0 mm. These two datasets had notably different TE values (TE for Hospital 1, 74.7 ms; TE for Hospital 2, 43.6 ms). As noted, DDVDm of Hospital 1 had better visual quality than DDVDm of Hospital 2. Another issue which could be potentially resolved is the ‘T2 shine-through’. It is noted that T2 contribution to DDVD measure is affected by the T2 length of the issue and the 2nd b-value for DDVD calculation, and T2 contribution is partially mitigated when a very low 2nd b-value is adopted (13,24,42). The 2nd b-value was 10 s/mm² for DDVD in this study. It is possible that a 2nd b-value of 1 or 2 s/mm² would help to mitigate T2 contribution. However, for many of the clinical MRI scanners, the lowest non-zero b-value is 10 s/mm². More advanced DWI sequences, such as ZOOMit (zonal oblique multislice) technique and multiplexed sensitivity-encoding (MUSE) technique, can be applied to improve DWI quality. Our recent liver study showed that there are EPI image distortion differences between DWI_b0 (where the diffusion gradient is ‘off’) and DWI_b10 (where the diffusion gradient is ‘on’) (43). Compared with traditional EPI DWI used in the current study, turbo spin echo DWI can reduce image geometric distortions (44,45). This approach can be tested in the future.

Conclusions

In conclusion, DDVD imaging can provide information on vascularity changes associated with breast lesions, it has the potential to be used as a supplementary diagnostic technique for differentiating benign and malignant breast masses. DDVD measures of tumor angiogenesis can also be potentially important for non-invasive imaging monitoring of tumor perfusion before and during the treatment to predict the treatment response. With the integration of DDVDm into breast MRI, the number of gadolinium-CE scans may be saved in a substantial proportion of patients, particularly for patients with larger lesions.

Acknowledgments

None.

Footnote

Data Sharing Statement: Available at https://qims.amegroups.com/article/view/10.21037/qims-2026-1-0446/dss

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2026-1-0446/coif). Y.X.J.W. serves as an Editor-in-Chief of Quantitative Imaging in Medicine and Surgery. Y.X.J.W. is the founder of Yingran Medicals Ltd., which develops medical image-based diagnostics software. The metric DDVD is associated with a granted China patent (ZL201910125747.2, inventorship). The other authors have no conflicts of interest to declare.

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. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the local institutional review board of Longgang Central Hospital of Shenzhen, China, and all the study participants provided informed consent. The other participating institution was also informed of and consented to this 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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