Traditional bone atlas modelling is carried out using linear methods such as PCA. Such linear models use a
mean shape and principal modes to represent the atlas. A new shape, which is a high dimensional data vector,
is then described using this mean and a weighted combination of the principal modes. The use of alternate
methods for modelling statistical atlases have not been explored very much. Recently, there has been a lot of
new work in the areas of multilinear modelling and nonlinear modelling. They present new ways of modelling
high dimensional data. In this work, we compare and contrast several linear, multilinear and nonlinear methods
for bone atlas modelling.
We present a framework to estimate the missing anatomical details from a partial CT scan with the help
of statistical shape models. The motivating application is periacetabular osteotomy (PAO), a technique for
treating developmental hip dysplasia, an abnormal condition of the hip socket that, if untreated, may lead to
osteoarthritis. The common goals of PAO are to reduce pain, joint subluxation and improve contact pressure
distribution by increasing the coverage of the femoral head by the hip socket. While current diagnosis and
planning is based on radiological measurements, because of significant structural variations in dysplastic hips,
a computer-assisted geometrical and biomechanical planning based on CT data is desirable to help the surgeon
achieve optimal joint realignments. Most of the patients undergoing PAO are young females, hence it is usually
desirable to minimize the radiation dose by scanning only the joint portion of the hip anatomy. These partial
scans, however, do not provide enough information for biomechanical analysis due to missing iliac region. A
statistical shape model of full pelvis anatomy is constructed from a database of CT scans. The partial volume is
first aligned with the statistical atlas using an iterative affine registration, followed by a deformable registration
step and the missing information is inferred from the atlas. The atlas inferences are further enhanced by the
use of X-ray images of the patient, which are very common in an osteotomy procedure. The proposed method is
validated with a leave-one-out analysis method. Osteotomy cuts are simulated and the effect of atlas predicted
models on the actual procedure is evaluated.
Purpose: Brachytherapy (radioactive seed insertion) has emerged as one of the most effective treatment options
for patients with prostate cancer, with the added benefit of a convenient outpatient procedure. The main
limitation in contemporary brachytherapy is faulty seed placement, predominantly due to the presence of intra-operative
edema (tissue expansion). Though currently not available, the capability to intra-operatively monitor
the seed distribution, can make a significant improvement in cancer control. We present such a system here.
Methods: Intra-operative measurement of edema in prostate brachytherapy requires localization of inserted
radioactive seeds relative to the prostate. Seeds were reconstructed using a typical non-isocentric C-arm, and
exported to a commercial brachytherapy delivery system. Technical obstacles for 3D reconstruction on a non-isocentric
C-arm include pose-dependent C-arm calibration; distortion correction; pose estimation of C-arm
images; seed reconstruction; and C-arm to TRUS registration.
Results: In precision-machined hard phantoms with 40-100 seeds and soft tissue phantoms with 45-87 seeds,
we correctly reconstructed the seed implant shape with an average 3D precision of 0.35 mm and 0.24 mm,
respectively. In a DoD Phase-1 clinical trial on 6 patients with 48-82 planned seeds, we achieved intra-operative
monitoring of seed distribution and dosimetry, correcting for dose inhomogeneities by inserting an average of
4.17 (1-9) additional seeds. Additionally, in each patient, the system automatically detected intra-operative seed
migration induced due to edema (mean 3.84 mm, STD 2.13 mm, Max 16.19 mm).
Conclusions: The proposed system is the first of a kind that makes intra-operative detection of edema (and
subsequent re-optimization) possible on any typical non-isocentric C-arm, at negligible additional cost to the
existing clinical installation. It achieves a significantly more homogeneous seed distribution, and has the potential
to affect a paradigm shift in clinical practice. Large scale studies and commercialization are currently underway.
C-arm fluoroscopy is modelled as a perspective projection, the parameters of which are estimated through a calibration
procedure. It has been universally accepted that precise intra-procedural calibration is a prerequisite for
accurate quantitative C-arm fluoroscopy guidance. Calibration, however, significantly adds to system complexity,
which is a major impediment to clinical practice. We challenge the status quo by questioning the assumption that
precise intra-procedural C-arm calibration is really necessary. Using our theoretical framework, we derive upper
bounds on the effect of mis-calibration on various algorithms like C-arm tracking, 3D reconstruction and surgical
guidance in virtual fluoroscopy - some of the most common techniques in intra-operative fluoroscopic guidance.
To derive bounds as a function of mis-calibration, we model the error using an a.ne transform. This is fairly
intuitive, since small amounts of mis-calibration result in predictably linear transformation of the reconstruction
space. Experiments indicate the validity of this approximation even for 50 mm mis-calibrations.
C-arm images suffer from pose dependant distortion, which needs to be corrected for intra-operative quantitative
3D surgical guidance. Several distortion correction techniques have been proposed in the literature, the current
state of art using a dense grid pattern rigidly attached to the detector. These methods become cumbersome
for intra-operative use, such as 3D reconstruction, since the grid pattern interferes with patient anatomy. The
primary contribution of this paper is a framework to statistically analyze the distortion pattern which enables
us to study alternate intra-operative distortion correction methods. In particular, we propose a new phantom
that uses very few BBs, and yet accurately corrects for distortion.
The high dimensional space of distortion pattern can be effectively characterized by principal component analysis
(PCA). The analysis shows that only first three eigen modes are significant and capture about 99% of the
variation. Phantom experiments indicate that distortion map can be recovered up to an average accuracy of
less than 0.1 mm/pixel with these three modes. With this prior statistical knowledge, a subset of BBs can
be sufficient to recover the distortion map accurately. Phantom experiments indicate that as few as 15 BBs
can recover distortion with average error of 0.17 mm/pixel, accuracy sufficient for most clinical applications.
These BBs can be arranged on the periphery of the C-arm detector, minimizing the interference with patient
anatomy and hence allowing the grid to remain attached to the detector permanently. The proposed method
is fast, economical, and C-arm independent, potentially boosting the clinical viability of applications such as
quantitative 3D fluoroscopic reconstruction.