João Ricardo Maltez de Almeida1, André Boechat Gomes1, Thomas Pitangueira Barros2, Paulo Eduardo Fahel3, Mario de Souza Rocha4. 1. MD, Radiologist, Department of Diagnostic Imaging, Clínica de Assistência à Mulher - Grupo CAM, Salvador, BA, Brazil. 2. BMSc, Clínica de Assistência à Mulher - Grupo CAM, Department of Biomedicine, Escola Bahiana de Medicina e Saúde Pública - Campus Brotas, Salvador, BA, Brazil. 3. MD, Pathologist, Clínica de Assistência à Mulher - Grupo CAM, Salvador, BA, Brazil. 4. MD, PhD, Department of Medicine, Escola Bahiana de Medicina e Saúde Pública - Campus Brotas, Salvador, BA, Brazil.
Abstract
OBJECTIVE: To test the use of diffusion-weighted imaging (DWI) in stratifying suspicious breast lesions (BI-RADS 4), correlating them with histopathology. We also investigated the performance of DWI related to the main enhancement patterns (mass and non-mass) and tested its reproducibility. MATERIALS AND METHODS: Seventy-six patients presented 92 lesions during the sampling period. Two independent examiners reviewed magnetic resonance imaging studies, described the lesions, and determined the apparent diffusion coefficient (ADC) values. Differences among benign, indeterminate- to high-risk, and malignant findings, in terms of the ADCs, were assessed by analysis of variance. Using receiver operating characteristic (ROC) curves, we compared the performance of ADC values in masses and non-mass lesions, and tested the reproducibility of measurements by determining the coefficient of variation and smallest real difference. RESULTS: Among the 92 lesions evaluated, the histopathology showed that 37 were benign, 11 were indeterminate- to high-risk, and 44 were malignant. The mean ADC differed significantly among those histopathological groups, the value obtained for the malignant lesions (1.10 × 10-3 mm2/s) being significantly lower than that obtained for the other groups (p < 0.001). ROC curves demonstrated that DWI performed better when applied to masses than when applied to non-mass lesions (area under the curve, 0.88 vs. 0.67). Reproducibility was good (coefficient of variation, 7.03%; and smallest real difference, ± 0.242 × 10-3 mm2/s). CONCLUSION: DWI can differentiate between malignant and nonmalignant (benign or indeterminate- to high-risk) lesions, showing better performance for masses. Nevertheless, stratification based on histopathological criteria that are more refined has yet to be achieved.
OBJECTIVE: To test the use of diffusion-weighted imaging (DWI) in stratifying suspicious breast lesions (BI-RADS 4), correlating them with histopathology. We also investigated the performance of DWI related to the main enhancement patterns (mass and non-mass) and tested its reproducibility. MATERIALS AND METHODS: Seventy-six patients presented 92 lesions during the sampling period. Two independent examiners reviewed magnetic resonance imaging studies, described the lesions, and determined the apparent diffusion coefficient (ADC) values. Differences among benign, indeterminate- to high-risk, and malignant findings, in terms of the ADCs, were assessed by analysis of variance. Using receiver operating characteristic (ROC) curves, we compared the performance of ADC values in masses and non-mass lesions, and tested the reproducibility of measurements by determining the coefficient of variation and smallest real difference. RESULTS: Among the 92 lesions evaluated, the histopathology showed that 37 were benign, 11 were indeterminate- to high-risk, and 44 were malignant. The mean ADC differed significantly among those histopathological groups, the value obtained for the malignant lesions (1.10 × 10-3 mm2/s) being significantly lower than that obtained for the other groups (p < 0.001). ROC curves demonstrated that DWI performed better when applied to masses than when applied to non-mass lesions (area under the curve, 0.88 vs. 0.67). Reproducibility was good (coefficient of variation, 7.03%; and smallest real difference, ± 0.242 × 10-3 mm2/s). CONCLUSION: DWI can differentiate between malignant and nonmalignant (benign or indeterminate- to high-risk) lesions, showing better performance for masses. Nevertheless, stratification based on histopathological criteria that are more refined has yet to be achieved.
Entities:
Keywords:
Breast neoplasms; Diffusion magnetic resonance imaging/methods; Magnetic resonance imaging; Neoplasms/pathology
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has become established
as the most sensitive method for breast cancer detection, with acceptable, albeit
low, specificity(. New techniques applied to MRI, such as
spectroscopy and diffusion-weighted imaging (DWI), have been producing encouraging
results and have expanded the field for oncology studies(. Nevertheless, the use of these techniques has not
yet achieved widespread clinical validation, because they are still considered
ancillary tools in the evaluation of suspicious findings(.Among the novel MRI procedures, DWI is regarded as one of the most promising methods
of screening for malignancy and evaluating treatment response(. It has been shown that malignant
neoplasms typically have lower apparent diffusion coefficients (ADCs) than do benign
growths and normal features, in part due to the restricted extracellular space
caused by the higher cell density in malignancies(. The measurement of ADCs might partially translate
this microscopic complexity into a manageable quantitative parameter that can be
used in order to distinguish among different biological tissues. In addition, most
modern scanners are capable of employing DWI, which has short acquisition times,
does not require the use of paramagnetic contrast medium, and, above all, has shown
a potential to improve the specificity of MRI(.The American College of Radiology Breast Imaging Reporting and Data System (BI-RADS)
classifies suspicious abnormalities as category 4 (BI-RADS 4), with a wide variation
in the risk of malignancy (> 2% to < 95%)(. As a consequence, BI-RADS 4 lesions require invasive
investigation, which results in a varied spectrum of findings-from simple,
nonproliferative changes to aggressive malignant tumors- leading to divergent
clinical practices. In addition, histology reports of nonmalignant proliferative
abnormalities with atypia and those with an indeterminate risk of malignancy usually
prompt physicians to investigate more aggressively, which results in a high number
of false-positive procedures(.In its latest edition, the BI-RADS stratifies suspicious (category 4) lesions into
three, narrower, subcategories (4A, 4B, and 4C), which respectively correspond to
increasing positive predictive values for malignancy(. The approach is not infallible, given that
positive predictive values vary according to prevalence(, and
the subcategorization is currently applicable only to mammography and ultrasound.
Because DWI provides information about the internal structure of living
tissue(, it might improve
the accuracy of DCEMRI by providing a better pathological correlation, which could
ultimately engender a valid stratification of BI-RADS 4 lesions by histopathological
subtype.Our study aimed to determine whether ADC values could be used in order to establish a
practical three-level histopathological classification of suspicious (BI-RADS 4)
findings as benign, indeterminate- to high-risk, or malignant. We further probed the
performance of DWI for mass and non-mass enhancement patterns, evaluating the
reproducibility of measurements between examiners (interobserver reliability).
MATERIALS AND METHODS
The subgroup of patients analyzed here was part of a larger cohort previously studied
for different purposes(. The present study stems from a
collaboration between an academic institution and a local private referral center
for women's healthcare. An independent review board approved the study (Report no.
518466) and waived informed consent. Between November 2009 and December 2013, we
performed 1973 breast MRI examinations at the private referral center. In 238
(12.1%) of those examinations, the lesion was classified as BI-RADS 4. All of the
subjects were female and ≥ 18 years of age.
Subjects and lesions
The study sample was defined according to the following inclusion criteria: DWI
had been part of the imaging protocol; the histopathological correlation was
available; the lesions were larger than 5.0 mm in diameter (foci were excluded);
two reviewers had categorized the examination as technically adequate; and the
DCE-MRI and DWI sequences had been properly restored. The examinations were
anonymized with an inbuilt tool available in the Advantage Windows workstation,
version 4.4 (GE Healthcare) and linked to a restricted version of the database
managed by the private facility. Eighty examinations were incompletely restored
or lost due to random computational storage problems (data corruption). Among
the remaining 158 examinations, 199 lesions were identified. Pathology findings
were unavailable for 89 lesions; 16 lesions were excluded due to field
inhomogeneity and movement artifacts; and 2 lesions were excluded because they
were considered too small. Therefore, the final study sample comprised a
collective total of 92 lesions in 76 patients.
MRI acquisition
All examinations were performed with patients in the prone position in a single
1.5-T MRI scanner (Signa Excite HDxT; GE Healthcare, Waukesha, WI, USA), with an
8-channel phased-array bilateral breast coil. In our protocol, the DWI sequence
comes last, immediately after the contrast-enhanced sequences, and consists of
single-shot echo-planar acquisition in the axial plane (repetition time/echo
time, 11.7/96; number of excitations, 8; matrix size, 256 × 224; field of
view, 340 × 340 mm; slice thickness, 3.5 mm; intersection gap, 0.5 mm),
together with array spatial sensitivity encoding technique parallel imaging.
Diffusion gradients are applied in six directions with b = 0 and 750
s/mm2. The remaining sequences-T1-weighted fast spin-echo;
T2-weighted fat-suppressed fast spin-echo; and post-contrast dynamic T1-weighted
fat-suppressed images using Volume Image Breast Assessment (VIBRANT) technique
(GE Health-care), after an intravenous bolus injection of gadoterate meglumine
(Dotarem, 0.1 mmol/kg of bodyweight; Guerbet, Roissy, France)-are all acquired
in the sagittal plane. If the patient is compliant, we also obtain a
single-phase late axial isotropic fat-suppressed T1-weighted sequence using
VIBRANT. The detailed parameters of our protocol can be accessed in previous
publications(.
Image assessment
The restored examinations were anonymized and kept in an offline Advantage
Windows workstation, version 4.4 (GE Healthcare), with the FuncTool software
package (GE Healthcare) and full post-processing capability. Two radiologists
with at least five years of experience and 1000 breast MRI readings to their
credit, who were blinded to all clinical and pathological data, independently
reassessed the images, with subsequent consensual analysis of discordant cases.
They were instructed to evaluate the standard acquisitions
(non-contrast-enhanced and DCE-MRI sequences) and to correlate the suspicious
findings with the corresponding areas of high signal intensity on DWI sequences.
Gray-scale ADC maps were generated based on the following equation:where b = 750 s/mm2; S
is the geometric mean of the individual b = 750
s/mm2 images obtained with DWI; and
S is the b = 0
s/mm2. At least two circular or oval regions of interest (ROIs)
were manually placed on the suspicious areas, including a minimum of four
pixels, with independent averages calculated to test interobserver variability.
Pathological evaluation
In the restricted version of our electronic database, histopathological reports,
most of them produced at our facility, were available for all of the
examinations evaluated. We consulted with an experienced pathologist
subspecializing in breast diseases and devised a three-level histological
classification with practical clinical implications(. The pathologist reviewed the reports and
stratified the lesions in the following manner: benign (nonproliferative and
proliferative lesions without atypia); indeterminate- to high-risk
(proliferative lesions with atypia and those of unknown malignant potential,
pending a larger tissue sample, which comprise papillary and complex sclerosing
lesions); and malignant (any type of invasive carcinoma or in
situ ductal carcinoma). In samples with mixed pathological
features, the most clinically relevant finding would dictate the stratification
(e.g., fibrocystic changes with concurrent atypical hyperplasia would be
included in the indeterminate- to high-risk group and lobular neoplasia mixed
with invasive lobular carcinoma would be included in the malignant group).Biological specimens were obtained by surgical excision, core biopsies being
performed with a spring-loaded reusable core biopsy system device (Bard Magnum;
Bard Biopsy Systems, Tempe, AZ, USA), using 14-gauge needles, and
vacuum-assisted biopsies being performed with a 9-gauge probe (ATEC; Suros
Surgical Systems, Indianapolis, IN, USA). All diagnoses of indeterminate- to
high-risk lesions were eventually confirmed by surgery. For practical and
financial reasons, when there was good imaging correlation with MRI,
preoperative localization and biopsy procedures were preferably guided by
mammography or ultrasound. Therefore, direct MRI guidance was used in only three
preoperative localizations and one vacuum-assisted biopsy.All of the participants with biopsy-negative lesions that were not explored
further by surgery were followed clinically and through imaging studies for at
least two years. When there was radiological-pathological discordance after the
biopsy, surgical excision was performed, and the result of the investigation was
categorized accordingly.
Statistical analysis
We collected data on age, lesion size, main enhancement pattern (mass or
non-mass), and ADC values (for the breast parenchyma and lesions), as well as
histopathological results, which were categorized in three groups (benign,
indeterminate- to high-risk, and malignant). Data are reported as absolute and
relative frequencies, measures of central tendency (means and medians), and
measures of dispersion-standard deviations (SDs) and interquartile ranges
(IQRs)-when appropriate.Data related to participant ages and lesion sizes were checked for normality,
and, because the null hypothesis was rejected, we used the Kruskal-Wallis test
with Dunn's pairwise post hoc comparisons. We also used the
Shapiro-Wilk test to determine the distribution of ADC values
(p = 0.17), and Levene's robust test to determine groupwise
homoscedasticity (p = 0.33), subsequently applying analysis of
variance with Scheffé correction. The ADC values for the breast
parenchyma also did not deviate significantly from the standard normal
distribution (p = 0.10) and were compared with those of lesions
by paired t-test. We then used analysis of variance to assess the differences in
ADCs between mass and non-mass enhancement patterns among the histopathological
groups. Receiver operating characteristic (ROC) curves were generated to compare
the performance of DWI in using the enhancement pattern to differentiate
malignant lesions from indeterminate- to high-risk or benign (hereafter
collectively referred to as nonmalignant) lesions. The area under the curve
(AUC), with a 95% confidence interval (95% CI), was calculated for each pattern.
We also applied Pearson's chi-square test to determine whether mass and non-mass
enhancement patterns were independently linked to any particular
histopathological group. The reproducibility of ADC values was determined by
calculating the coefficient of variation between the examiners(. We calculated the smallest
real difference, which is similar to the Bland-Altman limits of
agreement( and
provides a measure of the relevant change(.Considering a total sample size of 92, a calculated effect size of 0.39, and a
variance roughly equal to 0.37, we estimated the post hoc power
of the study for its primary objective to be greater than 90%. We acknowledge
that, for a small number of patients, there was more than one result (1.21
lesions per subject). Nevertheless, those few correlated outcomes are not
expected to have significant impact on our results, as previously
indicated( and as
suggested by a cursory sensitivity analysis with robust standard errors. All
computations were performed with Stata statistical software, version 12.0
(StataCorp LP; College Station, TX, USA), except for the power calculations, for
which we used G*Power, version 3.1.9.2 (Faul, Erdfelder, Lang and Buchner, 2006,
2009). Values of p < 0.05 were considered statistically
significant for two-tailed tests.
RESULTS
Of the 92 lesions evaluated, 37 (40.2%) were categorized as benign, 11 (12.0%) were
categorized as indeterminate- to high-risk, and 44 (47.8%) were categorized as
malignant. The histopathological results were mostly related to material obtained
from surgical excisions, corresponding to 68 (73.9%) of the specimens, whereas the
remaining material was obtained from core-needle biopsies and vacuum-assisted
biopsies, which accounted for 20 (21.7%) and 4 (4.4%) of the specimens,
respectively. There were no significant differences among the various tissue
acquisition techniques in terms of the pathological results (p =
0.456). The overall median age of the patients was 51 years (IQR, 42-59 years), and
the median lesion size was 1.6 cm (IQR, 1.0-3.7 cm). As can be seen in Table 1, there were no significant differences
among groups in terms of patient age (p = 0.229), although the
groups differed significantly in terms of lesion size, which was greatest in the
malignant group (p = 0.006). The median lesion size was comparable
between the benign and indeterminate- to high-risk groups, which could not be
distinguished by pairwise comparison (p = 0.182).
Table 1
Characteristics of the patients and lesion enhancement patterns by
histological group.
Characteristic
Benign
Indeterminate-to high-risk
Malignant
p*
Proportion of total
40.2%
12.0%
47.8%
—
Age, in years †
47 (32-55)
53 (40-73)
54 (43-62)
0.229
Lesion size, in cm †
1.3 (0.9-2.5)
0.9 (0.8-1.5)
2.2 (1.5-4.7)
0.006
Enhancement pattern ‡
0.967
Mass
17 (41.5)
5 (12.2)
19 (46.3)
—
Non-mass
20 (39.2)
6 (11.8)
25 (49.0)
—
Kruskal-Wallis test for age and lesion size; Pearson's chi-square test
for enhancement patterns.
Median (interquartile range).
Number of lesions (proportion of enhancement pattern).
Characteristics of the patients and lesion enhancement patterns by
histological group.Kruskal-Wallis test for age and lesion size; Pearson's chi-square test
for enhancement patterns.Median (interquartile range).Number of lesions (proportion of enhancement pattern).The overall ADC value (mean ± SD) for the breast parenchyma and lesions was
1.83 ± 0.30 × 10-3 mm2/s and 1.25 ± 0.034
× 10-3 mm2/s, respectively (p <
0.001). There were also significant differences among the groups in terms of the
mean ADC, which was lowest (1.10 ± 0.309 × 10-3
mm2/s) in the malignant group (p < 0.001),
although it was similar between the benign and indeterminate- to high-risk groups
(pairwise comparison, p = 0.972). Table 2 provides detailed descriptive data on ADC values by pathological
group and specific diagnosis. Figures 1 and
2 show examples of lesions considered
suspicious on the basis of their imaging characteristics (BI-RADS 4 lesions) but
with distinct histopathology.
Table 2
ADC values by histological group and specific pathological result, in
relation to the 1.21 x 10 3 mm2/s cut-off point, among the 92 lesions
evaluated.
ADC
< 1.21
x 10-3 mm2/s
≥
1.21 x 10-3 mm2/s
Group
Number of lesions
Mean ± SD
N
%*
N
%*
Benign
37
1.38 ± 0.25
11
29.7
26
70.3
Adenosis
4
1.35 ± 0.19
1
25.0
3
75.0
Fibrocystic
changes
4
1.41 ± 0.31
2
50.0
2
50.0
Ductal ectasia
2
1.68 ± 0.32
0
0
2
100.0
Fibroadenoma
12
1.47 ± 0.27
2
17.0
10
83.0
Fibrosis
5
1.28 ± 0.07
0
0
5
100.0
Hypervascularity†
1
1.15
1
100.0
0
0
Usual ductal
hyperplasia
4
1.25 ± 0.15
2
50.0
2
50.0
Inflammation
3
1.12 ± 0.07
3
100.0
0
0
Pseudoangiomatous
stromal hyperplasia
2
1.58 ± 0.30
0
0
2
100.0
Indeterminate- to high-risk
11
1.41 ± 0.37
3
27.3
8
72.7
Atypical
hyperplasia
1
1.29
0
0
1
100.0
Complex sclerosing
lesion
1
1.05
1
100.0
0
0
Papillary lesion
9
1.46 ± 0.38
2
22.0
7
78.0
Malignant
44
1.10 ± 0.31
31
70.5
13
29.6
Invasive ductal
carcinoma
22
0.96 ± 0.21
21
95.5
1
4.5
Invasive lobular
carcinoma
6
1.15 ± 0.17
3
50.0
3
50.0
Neuroendocrine
carcinoma
2
0.96 ± 0.63
1
50.0
1
50.0
Invasive mucinous
carcinoma
2
1.83 ± 0.53
0
0
2
100.0
In
situ ductal carcinoma
12
1.23 ± 0.23
6
50.0
6
50.0
Percentages may not total 100, because of rounding.
Description provided by the pathologist after correlation with the MRI
findings.
Figure 1
Contrast-enhanced sagittal T1-weighted fat-saturated MRI scan
(A) showing a 0.8-cm focal enhancement considered
suspicious (arrow) and its representation on axial DWI (marked with an
ROI), which displays an ADC of 1.30 × 10-3
mm2/s. Photomicrograph (B) of a specimen
obtained by vacuum-assisted biopsy showing dense fibrous stroma on
greater magnification (hematoxylin-eosin staining).
Figure 2
Contrast-enhanced sagittal T1-weighted fat-saturated MRI scan
(A) showing a 1.6-cm round mass (arrow), with irregular
margins, and the corresponding DWI (marked with an ROI), with an ADC of
0.74 × 10-3 mm2/s. Photomicrograph
(B) of a specimen obtained by ultrasound-guided core
biopsy showing clusters of malignant, high nuclear grade (grade 3)
epithelial cells and lymphocytic infiltrate on greater magnification
(hematoxylin-eosin staining).
ADC values by histological group and specific pathological result, in
relation to the 1.21 x 10 3 mm2/s cut-off point, among the 92 lesions
evaluated.Percentages may not total 100, because of rounding.Description provided by the pathologist after correlation with the MRI
findings.Contrast-enhanced sagittal T1-weighted fat-saturated MRI scan
(A) showing a 0.8-cm focal enhancement considered
suspicious (arrow) and its representation on axial DWI (marked with an
ROI), which displays an ADC of 1.30 × 10-3
mm2/s. Photomicrograph (B) of a specimen
obtained by vacuum-assisted biopsy showing dense fibrous stroma on
greater magnification (hematoxylin-eosin staining).Contrast-enhanced sagittal T1-weighted fat-saturated MRI scan
(A) showing a 1.6-cm round mass (arrow), with irregular
margins, and the corresponding DWI (marked with an ROI), with an ADC of
0.74 × 10-3 mm2/s. Photomicrograph
(B) of a specimen obtained by ultrasound-guided core
biopsy showing clusters of malignant, high nuclear grade (grade 3)
epithelial cells and lymphocytic infiltrate on greater magnification
(hematoxylin-eosin staining).Among the histopathological groups, the two main enhancement patterns were
proportionally distributed and showed discrepant ADC values (Figure 3). Only the lesions with mass enhancement could be
reliably stratified (p < 0.001), the pairwise comparisons
showing that the malignant group differed from the benign and indeterminate- to
high-risk groups (p = 0.001 and p = 0.059,
respectively). On the basis of the ADC values, it was not possible to separate the
non-mass enhancement patterns into malignant and nonmalignant types
(p = 0.071), although the AUCs indicated that the ADC performed
significantly better in that regard for the mass enhancement patterns (Figure 4).
Figure 3
ADC values of masses (dark gray boxes) and non-mass enhancement (white
boxes), stratified by histological group, black circles indicating
extreme values. Significantly lower median ADCs (central lines in box
plots) are observed for malignant masses (p <
0.001). Lesions with non-mass enhancement could not be confidently
differentiated by their ADC values (p = 0.071).
Figure 4
ROC curves for mass and non-mass enhancement patterns. The AUC, which
corresponds to the probability of correctly classifying a lesion as
malignant or nonmalignant (benign or indeterminate- to high-risk),
indicated that ADC values perform better when applied to masses (AUC,
0.88) than when applied to nonmass enhancement (AUC, 0.67), the
difference being statistically significant (p =
0.029).
ADC values of masses (dark gray boxes) and non-mass enhancement (white
boxes), stratified by histological group, black circles indicating
extreme values. Significantly lower median ADCs (central lines in box
plots) are observed for malignant masses (p <
0.001). Lesions with non-mass enhancement could not be confidently
differentiated by their ADC values (p = 0.071).ROC curves for mass and non-mass enhancement patterns. The AUC, which
corresponds to the probability of correctly classifying a lesion as
malignant or nonmalignant (benign or indeterminate- to high-risk),
indicated that ADC values perform better when applied to masses (AUC,
0.88) than when applied to nonmass enhancement (AUC, 0.67), the
difference being statistically significant (p =
0.029).On the basis of data previously published(, we employed an ADC cut-off point of 1.21 ×
10-3 mm2/s, values lower than that being considered
diagnostic of malignancy. Thus, 31 (70.5%) of the 44 lesions in the malignant group
were classified as malignancies, whereas 26 (70.3%) of the 37 lesions in the benign
group showed an ADC above the cut-off point, as did 8 (72.7%) of those in the
indeterminate-to high-risk group (Table
2).The interobserver variability for ADC measurements was considered small, with a mean
difference between examiners of ± 0.123 × 10-3
mm2/s (SD of ± 0.019 × 10-3
mm2/s) and an overall coefficient of variation of 7.03%. To be considered
relevant, a discrepancy between any two measurements had to be outside the limits of
± 0.242 × 10-3 mm2/s, according to the smallest
real difference calculated. The examiners produced only three such pairs of
measurements.
DISCUSSION
Our results support the notion that DWI can be used in order to differentiate between
malignant tumors and nonmalignant abnormalities. However, benign and indeterminate-
to high-risk subtypes were indistinguishable in our sample, precluding a more
detailed classification based on histopathological features. The interobserver
variability for ADC values was small, given that only three pairs of measurements
were considered substantially discordant.We found that the mean ADC was lower for any type of lesion than for the normal
breast parenchyma. In the present study, the mean ADC was lowest in the malignant
group, a finding supported by those of previous studies(. A
review article authored by Tsushima et al.( showed that DWI performs well in the diagnosis of breast
cancer, with a pooled sensitivity and specificity of 0.89 and 0.77, respectively,
similar to that shown by Qu et al.( in a more recent meta-analysis. In the present study, DWI
performed similarly-with an estimated accuracy (AUC) of 0.88-although only for mass
enhancement patterns. However, the AUC estimated for non-mass enhancement patterns
was less than optimal (0.67), comparable to the 0.70 reported for such patterns by
Imamura et al.( and virtually
identical to the 0.66 estimated by Partridge et al.(. One plausible explanation for the discrepancy
between the mass and non-mass enhancement patterns is that, in the latter pattern,
normal breast parenchyma is typically intermingled with pathological tissue,
inevitably leading to averaged ADC measurements, even if multiple ROIs are
evaluated.There have been few studies concerning DWI analysis of more detailed histological
subgroups(. Parsian et al.( distinguished high-risk findings
from benign breast lesions by their mean ADCs after a false-positive MRI
classification (BIRADS 4 or 5). Nevertheless, the authors did not find a
statistically significant difference between high-risk and malignant
lesions(. This is in contradistinction to our findings,
because we observed a substantial overlap between the nonmalignant subtypes (benign
and indeterminate- to high-risk lesions) in term of the ADCs, which were clearly
distinct from those of malignant lesions. That might be explained by differences in
the histopathological classification. In order to achieve a practical, clinically
meaningful categorization, we grouped high-risk atypical lesions together with those
of indeterminate malignant potential, because both usually elicit further
investigation. In addition, we identified a small number of proliferative changes
with atypia and no lobular neoplasia (atypical lobular hyperplasia or lobular
carcinoma in situ). Nevertheless, in our indeterminate- to high-risk group, the mean
ADC was quite close to that reported by Parsian et al.(-a difference of only 0.05 ×
10-3 mm2/s-whereas, in our benign and malignant groups, it
was substantially lower than the values reported by those authors.A number of ADC cut-off points have been tested, for a variety of purposes(. In a study
previously conducted by our group(, we used a balanced cut-off point of 1.21 ×
10-3 mm2/s to separate malignant from nonmalignant
findings, thus correctly classifying approximately 70% of the lesions. We
acknowledge that adopting a higher ADC cut-off point would be a better strategy to
safely avoid more aggressive investigation of BI-RADS 4 findings. In our sample, all
lesions with ADC values above 1.74 × 10-3 mm2/s were
determined to be nonmalignant, except for one mucinous carcinoma (ADC, 2.20 ×
10-3 mm2/s), which corresponded to 7.6% of the findings.
This cut-off point is close to the arithmetic mean of the values reported by other
authors, which have ranged from 1.60 to 1.81 × 10-3
mm2/s. Spick et al.(
also stated that DWI might obviate the need for MRI-guided biopsies. In their study,
34.5% of the false-positive procedures would have been avoided, without
false-negatives, if a cut-off point of 1.58 × 10-3
mm2/s had been adopted.The reproducibility of measurements in the present study was considered good, because
the mean difference was small and the coefficient of variation was below 10%. The
discordance was considered clinically relevant, based on the smallest real
difference, in only three cases. This finding is supportive of those of other
authors, who have reported high or very high interobserver reliability of ADC
measurements when trained examiners were involved(.To our knowledge, this is the first study aiming to stratify suspicious-only (BI-RADS
4) lesions by DWI according to detailed histopathological features, thus avoiding
the simple benign vs. malignant dichotomy. By doing so, we were able to devise
different recommendations according to the primary biopsy results: biopsy-proven
benign lesions could be followed by imaging methods; indeterminate- to high-risk
findings would require additional clinical and pathological correlation, because
they might be upgraded after analysis of tissue samples that are more
representative; and malignancies could be treated without delay.This study has some limitations. Our objective was to stratify BI-RADS 4 lesions
according to tissue characteristics, with comprehensive clinical implications.
Therefore, to simulate the three subcategories already established for other imaging
methods (4A, 4B, and 4C), we grouped findings with indeterminate malignant potential
together with those categorized as high-risk. This strategy led to different
histological subtypes (ranging from typically benign to atypical) being grouped
together while a more definitive pathological evaluation was pending. As a
consequence, the variability of ADC measurements in that group could have been
increased. In addition, in our sample, there were relatively few high-risk findings
and no lobular neoplasias. We also understand that, because this was a single-center
study, with examiners routinely discussing cases seen in their daily clinical
practice, the high level of interobserver agreement was to be expected.In summary, we have demonstrated that DWI performs well in differentiating malignant
lesions from nonmalignant abnormalities even in the challenging subgroup of patients
with suspicious (BI-RADS 4) lesions. A more detailed stratification based on ADC
values of representative histopathological characteristics might be feasible,
although studies involving larger samples would be needed.
Authors: Pascal A T Baltzer; Matthias Benndorf; Matthias Dietzel; Mieczyslaw Gajda; Ingo B Runnebaum; Werner A Kaiser Journal: AJR Am J Roentgenol Date: 2010-06 Impact factor: 3.959
Authors: Savannah C Partridge; Wendy B DeMartini; Brenda F Kurland; Peter R Eby; Steven W White; Constance D Lehman Journal: AJR Am J Roentgenol Date: 2009-12 Impact factor: 3.959
Authors: Savannah C Partridge; Christiane D Mullins; Brenda F Kurland; Michael D Allain; Wendy B DeMartini; Peter R Eby; Constance D Lehman Journal: AJR Am J Roentgenol Date: 2010-06 Impact factor: 3.959
Authors: Stephane Zervoudis; George Iatrakis; Eirini Tomara; Anastasia Bothou; George Papadopoulos; George Tsakiris Journal: World J Clin Oncol Date: 2014-08-10
Authors: João Ricardo Maltez de Almeida; André Boechat Gomes; Thomas Pitangueiras Barros; Paulo Eduardo Fahel; Mário de Seixas Rocha Journal: Radiol Bras Date: 2016 May-Jun