Role of Tomosynthesis in Assessing the Size of the Breast Lesion
Role of Tomosynthesis in Assessing the Size of the Breast Lesion
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Role of Tomosynthesis in assessing the size of the breast
Poster No.: C-1045
Congress: ECR 2012
Type: Scientific Exhibit
Authors: B. Raghavan
, M. Selvakumar
Keywords: Pathology, Outcomes analysis, Ultrasound, Mammography, Breast
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To assess the role of 3D tomosynthesis in the evaluation of the size of malignant breast
lesions and to compare it with the size in 2D, Ultrasound and final Histopatholgy.
This is a preliminary study to investigate the ability of 3D Tomosynthesis in assessing the
pre-operative size of malignant breast lesions in comparison to 2D digital mammogram
and sonographic imaging modalities, and in predicting the gold standard, pathological
Tumor size obtained by pathology which remains the gold standard has been compared
by many authors with X-ray mammography, Ultrasound and MR mammography. Many
studies have shown that X-ray mammogram is better than breast Ultrasound in predicting
the size of the lesion though ultrasound is faster, less expensive and widely available.
MRI appears to measure the lesion size slightly better than X-ray mammogram because
of the 3D presentation of a lesion when compared to other modalities, but remains a
costly investigation and is done less often than X-ray mammogram.
Accurate measurement of a primary invasive breast cancer is crucial for staging
and patient management, in particular with the increased use of breast-saving and
reconstructive surgery. Neo-adjuvant chemotherapy is now commonly employed based
on the pretreatment imaging size and the size assessment is also important in evaluating
residual tumor extent after preoperative treatment with cytostatic drugs. Hence it is
important to document the size of the lesion in order to categorize it in the appropriate
local staging to decide on the mode of therapy and also for follow-up .
3 D Tomosynthesis combined with 2D FFD mammograms in the combined mode is a
relatively new technique which offers better delineation of margin. Margin analysis of a
lesion forms the very basis of measuring the size of the lesions. 3D sectional analysis can
overcome the problems due to superimposition of tissues especially in dense breasts.
Methods and Materials
Our study was a retrospective study, collecting and examining data already held in
patient's files. The patients' consent was obtained initially at screening. The data was
collected between May and November 2011 and processed.
About 100 abnormal imaging studies by Diagnostic Full field Digital mammogram (Combo
view for 2D and 3D studies were done for all cases) and breast Ultrasound were reviewed.
From these , 62 patients who had malignancy proved by Tru-cut biopsy were included in
the study. These patients had been advised treatment based on these results. Of these,
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few were lost to follow-up and few had palliative chemotherapy.Such patients were not
included in the study.
The maximum size of the tumor in 47 patients was analysed in two views by 3D
tomosynthesis and compared to the size in tfinal HPE. Comparison of the tumor size in
US and 2D was also done.
All patients in our study had undergone Combo view Diagnostic Full field Digital
mammogram that includes 2D mammogram and 3D tomosynthesis. The mammographic
imaging protocol included cranio-caudal, medio-lateral oblique projections and
magnification projections, wherever required.
High-frequency grey-scale dedicated ultrasound examination of the breast was
performed. The size of the lesion was measured with a high frequency probe ranging
from7.3 Mhz to 13 MHz. When the size of the tumor was larger than the foot print of the
transducer lower frequency probe was used to get the edges of the mass within the frame.
All measurements were taken on the dedicated mammographic work-station with
callipers on the monitor. All magnification projections were excluded from the
The process of mammographic measurement of tumors in our study was modeled on
the work of Flanagan et al  , based on the fact that the size excluding the spiculations
correlated best with the post surgical measurement.
For each mammographic lesion two measurements were recorded perpendicular to each
other. Spicules have been excluded from the measurements in stellate lesions and the
measurements were taken from the thickest point of the spicules on each side which
represented the nucleus of the tumor.
Out of the two, the longest measurement of each lesion was taken into consideration.
Tumors were graded mammographically into nodular or stellate shape, and whether they
were found in fatty parenchyma or dense parenchyma.
The sonographic measurements were undertaken by measurement calipers incorporated
into the ultrasound units. Measurements were taken in different ways depending on the
growth pattern of the tumor and included:
1. From break to break in the tissue plane in diffuse masses where the tumor
disrupts the natural breast architecture.
2. The hypo-echoic nucleus of the tumor in the case of circumscribed, nodular
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3. The largest diameter in stellate lesions which includes micro-lobulations and
branch patterns but excludes radiating hyper-echoic straight lines.
Surgical pathology breast specimens were processed according to a standard protocol.
Each breast excision or mastectomy specimen was serially sectioned and fixed in
formalin overnight. The tumor was then measured in three dimensions, to the nearest
millimeter, and submitted for microscopic evaluation.
In general, the gross measurement of the tumor was used for staging.
However, if the microscopic tumor measurement of the largest dimension was
substantially greater than the largest gross measurement (eg due to microscopic tumor
extension into surrounding tissues), or substantially smaller than the gross measurement
(eg due to adjacent dense fibrocystic change), the microscopic measurement was utilized
for staging. The largest diameter was used for depicting the HPE.
Categorical data were presented by frequency with percentage and it was analyzed
by using Chi-square and Fisher exact test. Karl Pearson's co-efficient of correlation
was used for relationship. Bland altman plot was used for measurement of each
modalities and linear regression plot with 95% confidence interval was used to analyze
the performance of each modality in Fatty / Dense Breasts and Nodular/ Stellate lesion.
All the analysis was done by using SPSS 14.0 version, A p value less than 0.05 was
considered as significant.
Images for this section:
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Fig. 1: 40years female presented with focal nodularity of the left breast. On combo view,
the breast appears heterogenously dense(BIRADS 3)in nature and no measurable lesion
was detected in 2D mammogram. 3D tomosynthesis revealed a nodular lesion.
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Fig. 2: 45 years female patient presented with nodularity of left breast. on combo view,the
breast appears fatty (BIRADS 2).On 2D a stellate lesion was seen corresponding to the
palpable nodularity.3D tomosynthesis picked up an additional stellate lesion.
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The maximum number of women in our study was between 40-50 years, (fig 3) and age
ranged from less than 30 to more than 70 years.
Out of our 62 cases 12 cases were not measurable in 2D mammography (fig 4). 15 cases
who had undergone preoperative chemotherapy, radiotherapy or lost on follow up were
considered as histopathologically non measurable lesions (fig 4).
Only 8% of our tumor load was contributed by lobular carcinoma and 3% by malignant
phylloides (fig 5).
Based on the BIRADS classification for breast tissue density 49% of our lesions (23 out
of 47 lesions) were seen in fatty breasts (BIRADS 1,2) and 51% of our lesions(24 out of
47 lesions) were seen in dense breasts (BIRADS 3,4) (fig 6). 62% of lesions were stellate
and 38% of lesions were nodular in nature (fig 7).
Bland altman was used for the measurement of agreement between each modality. The
confidence interval was high (0.858- 0.963) for 2D digital mammography in comparison
to 3D tomosynthesis (0.808- 0.952) and ultrasonography (0.585- 0.908) (Table 1, fig
8-10). The 95% confidence index was high for 2D and 3D. It was lower for Ultrasound.
In measurable lesions 2D performed better than 3D.
Estimate 95% CI
2D 0.927 0.858- 0.963
3D 0.907 0.808- 0.952
USG 0.813 0.585- 0.908
With Linear regression plots, 2D and 3D mammography showed high prediction interval
for lesions in fatty breast than in dense breast and
in comparison with 2D mammography, 3D mammography had high prediction interval in
dense breast lesions .
Both 2D and 3D showed high prediction interval for nodular lesions than stellate lesions
and 3D mammography was superior in predicting stellate lesions than nodular lesions in
comparison to 2D mammography.
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Ultrasonography had better prediction index for nodular lesions ,especially in fatty breast .
However it was not superior to 2D or 3D mammography. It had poor predictability in dense
breasts and for stellate lesions.(Table2)
Table - 2
LINEAR REGRESSION ANALYSIS with 95% INDIVIDUAL PREDICTION INTERVAL-
2D .94 .74 .67 .93
3D .94 .75 .69 .91
US .87 .86 .43 .87
Majority of our lesions were between 2-5 cms i.e local Stage 2 disease and we had very
few less than 1 cms lesion (Fig 11).
All modalities under-estimated the size of the lesion with respect to HPE.HPE has also
been reported to under predict the tumor margin ,according to some studies , due to
tissue shrinkage of the surrounding parenchyma in formalin.
Table - 3
numbers mean in cms
Under measuring 21 .882D
Over measuring 11 .57
Under measuring 35 .713D
Over measuring 9 .59
Under measuring 33 1.15USG
Over measuring 11 .50
Our study being a preliminary study had less numbers and the entire range of malignant
pathology could not be captured.
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Our study population is derived from opportunistic screening and is not population based.
This gives us lesser cases in the stage1 disease and in early breast cancers less than 1
cm where the performance of 3D Tomosynthesis is reported to be superior.
Images for this section:
Fig. 3: Age distribution
Fig. 4: Measurable and non measurable lesions
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Fig. 5: Histopathology distribution.
Fig. 6: Distribution of breast parenchymal density
Fig. 7: Distribution of morphology (nodular/stellate)of the lesion.
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Fig. 8: 2D-HPE consistency analysis
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Fig. 9: 3D-HPE consistency analysis
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Fig. 10: USG-HPE consistency analysis
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Fig. 11: Size and stagewise distribution of lesions
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Better predictability of sizes by Mammogram (2D and 3D) with respect to HPE was seen
in our study (Table 1 and fig 8-10) and that correlates well with other studies also .
Cases in which the lesions are not measurable with 2D mammogram due to
superimposition of dense glandular parenchyma, tomosynthesis proves to be the better
modality for measurement (fig1 and 2), however if the lesion is measurable in 2D digital
mammography, it is superior to 3D tomosynthesis. This is probably because though 3D
tomosynthesis gives better margin characterization, each 1 mm section gives only part
of the marginal information whereas 2D mammogram gives summated information of the
Ultrasound has a greater ability to demonstrate lesion characteristics when a
mammographic lesion is obscured by dense overlying tissue or if the lesion is only
evident as a radiographic distortion. This is partly due to the ability of transducer to
be maneuvered through multiple planes to acquire multiple views and dimensions. The
results of our study demonstrate that sonography was less useful than mammography in
predicting histological tumor size because most of our lesions were stellate in nature and
are usually characterized by posterior acoustic shadowing on sonography, corresponding
to associated desmoplasia in and around the lesion.The shadowing obscures the
posterior border of the lesion, often making measurement in this longest diameter difficult.
Lobular cancer and associated DCIS are known to decrease the capability of imaging
to predict size when compared to histopathology. In our study we found decreased
predictablity by all modalities in 2 cases of lobular carcinoma which were T2 lesions and
3D tomosynthesis predictablity was closest to HPE. However T1 lesions co-related well
with HPE size in all 3 modalities.
Majority of the lesions were underpredicted with all the modalities. The average
underestimate of breast tumor size with 2D and 3D mammography was 0.88 cm and
0.71 cms respectively. The average underestimate produced by sonography was 1.15cm.
Alternatively, over-estimation of breast tumor size by medical imaging may lead to a
more radical approach at surgery. The average size of over estimation by 2D and 3D
mammography was 0.57 and 0.59cm respectively and 0.5 cm by sonography (Table 3).
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In this preliminary study 3D mammogram appears to be as reliable as 2D in predicting
tumor size especially in stellate lesions and dense breast parenchyma , if it is
measurable , whereas 2D is less reliable due to non-measurability, because of obscured
margins and superimposition of tissues. However more numbers with significant
distribution patterns in size and pathological categorization needs to be done.
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3. Bobbi Pritt et al; Influence of breast cancer histology on the relationship
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4. Tresserra F et al. Assessment of breast cancer size: sonographic and
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5. M. Kristoffersen Wiberg et al.Comparison of lesion size estimated by
dynamic MR imaging, mammography and histopathology in breast
neoplasms. Eur Radiol (2003) 13:1207-1212.
6. Fornvik, D, et al. Breast Tomosynthesis:Accuracy of tumor measurement
compared with digital mammography and ultrasonography. Acta Radiol 3;
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