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Prone-Supine Breast MRI Registration for Surgical Visualisation

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Abstract and Figures

The concept of multi-modal data fusion generally involves some facet of registration. However to truly distinguish the notion of "fusion" from conventional "registration" a n und erstanding o f representation and visualisation must be incorporated into the solution. This is a particularly critical issue in the case of breast data fusion as the representation of the breast changes considerably between d ifferent i maging techniques (for example the compressed shape in a mammogram compared with the prone shape of a typical breast MR image) and the conditions of the operating room. To address this, we introduce the idea of registering prone a cquired MRI images to a supine acquisition to generate a visual representation that is meaningful to the surgeon.
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Prone-Supine Breast MRI Registration for Surgical Visualisation
Christian Behrenbruch
1,2a
, Kostas Marias
1
,
Paul Armitage
1
, Niall Moore
2a
, Jane Clarke
2b
, Michael Brady
1
1
Medical Vision Laboratory (Robotics), Department of Engineering Science
Oxford University, Parks Rd, Oxford OX1 4AU, UK {cpb,jmb}@robots.ox.ac.uk
2a
Oxford Magnetic Resonance Imaging (OMRI), John Radcliffe Hospital, Headley Way,
Oxford OX3 9DU, UK /
2b
Department of Surgery, Churchill Hospital, Oxford OX3 7LJ, UK
Abstract.
The concept of multi-modal data fusion generally involves some facet of registration. However to truly
distinguish the notion of “fusion” from conventional “registration” an understanding of representation and
visualisation must be incorporated into the solution. This is a particularly critical issue in the case of breast data
fusion as the representation of the breast changes considerably between different imaging techniques (for
example the compressed shape in a mammogram compared with the prone shape of a typical breast MR image)
and the conditions of the operating room. To address this, we introduce the idea of registering prone acquired
MRI images to a supine acquisition to generate a visual representation that is meaningful to the surgeon.
1. Clinical Overview
One of the little-known facts about breast surgery is that minimal imaging data enters the operating room (OR).
Clearly, imaging data is a critical part of the screening, diagnosis and extended management of breast disease.
However in our experience of working with breast surgeons, imaging data is seldom used at the time of excision.
There are a number of reasons for this:
1. A large proportion of breast pathology is palpable and therefore image-guidance is usually not necessary to
localise the lesion in the OR.
2. The surgical removal of breast disease generally involves a limited range of options. A wide-local excision is
the most breast-conservative approach but is only suitable for certain classes of malignancy. Larger-scale
excision may be as localised as a breast quadrant (see Fig. 1) or as extensive as complete mastectomy.
3. The representation of the breast on the operating table is unlike that of most commonly used imaging
modalities. A considerable “mental transformation” is required to map the location of a feature identified in
imaging data to that of the supine (on the back) shape of the breast with better accuracy than a quadrant (having
said this, we are constantly astounded by the spatial visualisation abilities of surgeons).
Figure 1.
An illustration of how the breast is divided into quadrants (e.g. UOQ = upper/outer quadrant)
Although these considerations seem to reduce the complexity of decision making during surgery, there remains the
difficult issue of excision margins (and hence localisation). Certain classes of pathology are difficult to localise, as
the lesion may be impalpable. As many as 20% of patients have impalpable lesions and this number may increase as
mammography screening and other imaging techniques (e.g. MRI, nuclear medicine) successfully detect breast
disease at earlier stages of development. For the purposes of discussion, there are three main types of malignancy
that confound the localisation issue due to their impalpable or poorly differentiated nature:
1. Early-stage ductal carcinoma in-situ (DCIS) as the size of the lesion may be only a few mm rather than a
palpable “lump” and therefore difficult to detect. DCIS is difficult to diagnose with most imaging modalities
(for example contrast-enhanced MRI) but may be indicated by microcalcifications in an X-ray mammogram.
2. Multifocal/multicentric disease where the pathology consists of several “lobules” of malignancy connected
together in a poorly differentiated cluster.
3. Diffuse or fleshy lesions (typical of some kinds of carcinoma) which may be quite extensive but difficult to
differentiate from normal tissue in a clinical assessment.
In addition, it may be useful to provide the surgeon with some idea of the extent to which chemotherapy has
influenced the dimensions of a lesion. This is particularly true for cases where adjuvant chemotherapy has been
prescribed for large (several cm), inoperable tumours to minimise adenosis (swelling) for improving the
effectiveness of surgery. Lesions that intersect several quadrants of the breast but have been shrunk by chemotherapy
may also require larger margins to account for residual pathology in surrounding tissue.
2. An “Atlas” of Breast Pathology
Our previous research in breast registration has involved developing techniques for temporal mammogram matching
[1,2], MRI/X-ray mammography data fusion [3,4] and chemotherapy assessment with contrast-enhanced MRI [5,6].
We have demonstrated that it is possible to “fuse” features visible in X-ray mammography and MRI as well as
quantify the effects of chemotherapy. The result is a breast “atlas” that is the combination of temporal and multi-
modal pathological indicators. The geometrical reference frame we have used is the prone-acquired MRI scan. An
example is shown in Figure 2 where a mammographically visible lesion is localised in an MRI volume.
Figure 2.
A sample “atlas” showing the results of X-ray mammography/MRI fusion using [4].
However the problem of presenting this cumulated information to the surgeon remains. Although visualisations like
Figure 2 are useful to the surgeon as they illustrate the quadrant location of the lesion, it would be better if this
model could be transformed to a breast shape consistent with the surgical positioning of the patient.
3. Prone-Supine Registration
Our approach to the issue of breast surgical visualisation has incorporated a radiological aspect, a registration
component and a simple deformation model. In addition to a conventional prone-acquired contrast-enhanced MRI
acquisition, we have taken a relatively low resolution scan of the patient lying supine using the MRI body coil to get
an idea of the shape of the breasts as they would appear in the OR (Figure 3). This is not quite an exact shape
because the patient’s arms rest behind the head as opposed to perpendicularly when in the OR, however we attempt
to compensate slightly for this at a later stage in the process.
The registration process is simple and represents a preliminary approach to the problem:
1. Rotation of the body-coil acquired data set by 180
o
to align the prone and the supine data.
2. Segmentation of the skin in both acquisitions using a simple threshold and iso-contour detection. A threshold-
based segmentation is quite robust in the case of MRI as the signal background of T1-weighted images is easy
to differentiate from tissue.
3. A global rigid/affine transformation is computed using a variation of the iterated closest point algorithm, ICP
[7] on the skin data. This is mainly to align the thoracic component of the image.
4. The breast in each image is segmented using coronal re-slicing of the volume and a region growth algorithm.
By growing each breast through successive slices and looking for the point at which the two largest regions
merge, the location of the sternum (and hence the chest wall) is approximated. The sternum is used to separate
the left and right breast for registration.
5. Non-rigid registration driven by the skin surface, utilising a tensor B-spline mesh [8] to compute the
deformation. We do not currently use any internal landmarks or features to drive the registration.
6. As mentioned previously, the shape of the breast in the supine-acquired MRI scan is slightly different to the
OR shape due to the location of the patient’s arms (the breasts are pulled more upright). To visually compensate
for this, surface matching points are re-weighted towards the thorax and spline bending energy can be adjusted
to implement a degree of “pstosis” (or sag).
The application of non-rigid registration based purely on a breast surface match is certainly an over-simplification of
the problem. Ideally, one would include internal landmarks to properly control the deformation. However the
difference in resolution between the two acquisitions and the gravitational compression of tissue in the supine
position makes it difficult to compare the internal characteristics of the breast. Our justification for demonstrating
this registration concept based on a surface match derives from our initial objective of localising the position of the
supine-deformed lesion to quadrant accuracy only.
Figure 3.
Slices from prone and supine MRI acquisitions at approximately the same location (supine is resliced in
the saggital plan for clarity). Whilst the main structural characteristics of the breast appear similar, internal tissue
registration is difficult due to the difference in resolution between the breast and body coil acquisition and the large
compressive deformation.
4. Preliminary Results
We have performed an initial study on two patient cases with impalpable lesions. The purpose of this experiment
was to convince clinicians that there might be value in acquiring the additional supine MRI scan for relevant cases
(and hence build a database for future research). Figure 4 shows the results of a case with a highly localised (2-
3mm) lesion that was detected during mammography screening and fused to the MRI volume using the technique
described in [4]. This was quite a challenging case as the lesion was located quite deeply in the quadrant and may
have resulted in inter-quadrant margins when excised. Although it is difficult to validate the lesion location against
the excision specimen, the lesion remained quadrant-consistent after deformation and histology confirmed the
presence of DCIS in approximately the indicated area.
Figure 4.
A) illustrates the prone position of the patient in the breast coil. B) several renderings of the lesion
location in the prone shape. C) The supine deformation of the breast.
A) B) C)
Prone
Supine
As mentioned earlier, there is a need to incorporate some kind of provision for the slight difference in pstosis
between the supine MRI and OR breast shape. By re-weighting the matched surface points towards the thorax and
changing the spline bending energy it is possible to introduce a small amount of additional pstosis and produce a
visualisation more consistent with the surgical shape of the breast. This is illustrated in Figure 5, showing the
motion of the lesion with respect to the simulated pstosis.
Figure 5.
Adjustment of the spline bending energy characteristics to simulate pstosis.
5. Discussion and Conclusion
There is little doubt that the registration approach presented in this article is a considerable simplification over what
would be necessary to implement a clinically usable tool. Part of our objective in this initial evaluation was to
address the issue of data fusion visualisation in the surgical context and to improve the surgeon’s visibility of the
potential benefits of data fusion with respect to patients with impalpable tumours. We hypothesise that if the prone-
supine registration/deformation framework were robustly quadrant conservative, this would already be useful to the
surgeon.
In order to achieve this it is likely that a more sophisticated approach based on truly volumetric models with
material constraints and control over the internal deformation would be required. The difficulty with such models is
the extreme variability of tissue characteristics between patients and hence “calibration” problems are likely to arise.
There is no doubt, however, that advancements in rotationally invariant non-linear FEM tissue models (for example
[9,10]) could be used as the basis of such a scheme. We advocate, however, that free-form models (for example
based on a gravitationally influenced breast rotation) are perhaps not the best solution and that by using a supine-
acquired MRI in a registration context, a suitable model may be better constrained.
Acknowledgements
C. Behrenbruch wishes to acknowledge the Association of Commonwealth Universities for doctoral funding. M.
Brady and P. Armitage acknowledge the EPSRC. K. Marias is sponsored by Cancerkin, Royal Free Hospital.
References
[1] K. Marias, C.P. Behrenbruch, M. Brady, et al., A, “Non-rigid Registration of Temporal Mammogram Pairs via a
Combination of Boundary and Internal Landmarks”,
In proc. of IWDM ‘00
, Toronto, Canada, June 2000 (Kluwer)
[2] K. Marias, C.P. Behrenbruch, J.M. Brady, et al., “Quantifying mammographic changes in temporal HRT sequences”,
In proc. of MIUA ’00
, University College London, United Kingdom, July 2000
[3] C.P. Behrenbruch, K. Marias, P.A. Armitage, et al., “The Generation of Simulated Mammograms from Contrast-
Enhanced MRI for Surgical Planning and Postoperative Assessment”,
IWDM ‘00
, Toronto, Canada, June 2000
(Kluwer)
[4] C.P. Behrenbruch, K. Marias, P.A. Armitage, et al., “Mammography-MRI 2D/3D Data Fusion for Breast Pathology
Assessment”,
In proc. of MICCAI ‘00
, Pittsburgh, USA, Springer, October 2000
[5] C.P. Behrenbruch, P.A. Armitage, M. Brady, et al., “Non-Rigid Registration of Contrast-Enhanced MRI to Quantify
Chemotherapy Response in Breast Cancer for Histological Comparison”,
In Proc. ISMRM ’01
, Glasgow, April 2001
[6] N. Moore, C. Behrenbruch, C. Hardingham, et al., “3D Non-Rigid Matching of Contrast-Enhanced MRI to Assess
Chemotherapy Response in Breast Cancer”,
European Congress of Radiology 2001
, Vienna, Austria, March 2001
[7] Besl, P. and McKay, N. , A method for registration of 3-D shapes.
IEEE Trans. PAMI
, 14, pp239-256, 1992
[8] Declerck, J., Feldmar, J., Goris, M.L et al, Automatic Registration and Alignment on a Template of Cardiac Stress &
Rest SPECT Images.
Mathematical Methods in Biomedical Image Analysis
, pp212-221, 1996
[9] Azar, F.S., Metaxas, D.N., Schnall, M.D. (2000) A Finite Element Model of the Breast for Predicting Mechanical
Deformation During Biopsy Procedures.
IEEE Workshop on Mathematical Methods in Biomedical Image Analysis
.
[10] Picinbono, G., Delingette, H., Ayache, N. (2000) Real-Time Large Displacement Elasticity for Surgery Simulation:
Non-linear Tensor-Mass Model.
In proc. of MICCAI ‘00
, Pittsburgh, USA, Springer, October 2000
... In this study, we aim for a maximum difference in the order of 10%, or at most two times the elasticity variation among FEM-simulated elasticity values. Image registration techniques based on image intensities could be used for small deformations [108], but do not work in cases with large deformations such as the alignment from prone to supine configurations [12]. ...
... 12: Test setup for force measurements of cylinders and stepper motors. ...
... Behrenbruch et al. 281 started by rotating one of the surfaces by 180° to ensure a first overlap. Then, the skin is segmented and a coarse alignment is achieved by applying a variant of the ICP algorithm to the results of the segmentation. ...
... Behrenbrunch et al. 281 2001 Physical Registration of MRI data in supine and prone positions with nonlinear biomechanical models, optimizing the breast tissue materials parameters and the gravitational force direction Schuler et al. 284 2006 Nonphysical Matching of images of a pendant and a compressed breast, using ICP and weighting the symmetric closest points correspondence Lee et al. 286 2010 Dual Combination of FFD and physical models to restrict impossible deformations Ong et al. 287 2010 Nonphysical Correspondence of deformed/undeformed surfaces with potential energy fields and isocontours Joo et al. 291 2013 ...
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