To evaluate if clinical fluorescence imaging of IRDye800CW is feasible on our fluorescence optical mammography system by estimating detection limits assessed by breast-cancer-simulating phantom experiments. Phantoms (2.1 cm3, 0.9 cm3) with IRDye800CW concentrations of 0.5 to 120 nM were suspended in a 550 cm3 measurement cup containing 507 surface-mounted source and detector fibers. The cup was filled with optical matching fluid containing IRDye800CW concentrations of 0, 5, 10, or 20 nM. Tomographic fluorescence images were acquired by exciting IRDye800CW at 730 nm; wavelengths above 750 nm were filtered. Signal intensities were calculated over a volume of interest corresponding to the size and location of the phantom in the reconstructed images. Correlations (R2) were calculated, and detection limits with associated upper 95% prediction interval were estimated. Between-day reproducibility was assessed with intraclass correlation coefficients (ICC). Fluorescent intensities were strongly correlated with phantom IRDye800CW concentrations (R2∶0.983 to 0.999). IRDye800CW detection limits ranged from 0.14 to 2.46 nM (upper 95% prediction limit 4.63 to 18.63 nM). ICC ranged from 0.88 to 1.00. The estimated detection limits for IRDye800CW were in the low-nanomolar range. These results support the start of clinical trials to evaluate the fluorescence optical mammography system using IRDye800CW labeled breast cancer targeting ligands.
Filtered backprojection (FBP) has been commonly used as an efficient and robust reconstruction technique in
tomographic X-ray imaging during the last decades. For standard geometries like circle or helix it is known how
to efficiently filter the data. However, for geometries with only few projection views or with a limited angular
range, the application of FBP algorithms generally provides poor results. In digital breast tomosynthesis (DBT)
these limitations give rise to image artifacts due to the limited angular range and the coarse angular sampling. In
this work, a generalized FBP algorithm is presented, which uses the filtered projection data of all acquired views
for backprojection along one direction. The proposed method yields a computationally efficient generalized FBP
algorithm for DBT, which provides similar image quality as iterative reconstruction techniques while preserving
the ability for region of interest reconstructions. To demonstrate the excellent performance of this method,
examples are given with a simulated breast phantom and the hardware BR3D phantom.
Digital breast tomosynthesis (DBT) allows a quasi-3D reconstruction of the breast with high in-plane and poor
depth resolution by the principles of limited angle tomography. The limited angular range and the coarse
angular sampling result in prominent streak artifacts arising from high-contrast structures such as calcifications.
These artifacts do not only degrade the image quality but also hold the risk of overlaying suspicious tissue
structure in neighbouring slices, which might therefore be overlooked. This work presents a second pass method
for correcting these kinds of high-contrast streak artifacts. In a first pass reconstruction the candidate highcontrast
calcifications are segmented and subtracted from the original projection data to generate a subsequent
artifact-free second pass reconstruction. The method is demonstrated in a simulation study using software breast
phantoms, which have been derived from segmented MRI data.
Using lasers with different wavelengths in diffuse optical tomography (spectral DOT) has the advantage that the concentrations of chromophores can be reconstructed quantitatively. In continuous wave spectral DOT, it is furthermore possible to distinguish between scattering and absorption. The choice of the laser wavelengths has a strong impact on how well the scattering parameter and chromophore concentrations can be determined. Current methods to optimize the set of wavelengths disregard the sensitivity of the reconstruction result to uncertainties in the absorption spectra of the chromophores. But since available absorption spectra show significant deviations, it seems to be necessary to take this into account. The wavelength optimization approach presented here is an extension to a method of Corlu et al. The original method optimizes the wavelength sets such that scattering parameters and chromophore concentrations can be separated optimally. We introduce an additional criterion that evaluates the dependence of reconstructed chromophore concentrations on deviations of the extinction coefficients. The wavelength sets found by the new approach are different from those determined with the original method. Reconstructions of simulated data show the effect of using various absorption spectra for reconstruction with different wavelength sets and illustrate the advantages of the new wavelength sets.
We present a method to enhance tumor detectability in breasts imaged with our optical fluorescence mammography
system. During a measurement, transmission data at 4 wavelengths and fluorescence data for excitation at 1 wavelength
are collected after injection of an optical contrast agent. The data are reconstructed into 3D images of the absorption and
fluorescence distributions. Combining those images enables the identification of various breast tissue compounds. Here,
we investigate the relevance of our method in phantom experiments.
We present a new method to reconstruct arbitrary large volumes in (fluorescence) diffuse optical tomography by
splitting the volume of reconstruction into sub-volumes. This allows to perform nonlinear reconstruction on large
grids with a larger number of measurement data and more grid nodes than conventional reconstruction schemes,
where images are reconstructed on a single grid. We investigate how the reconstructed spatial distributions of
diffusion and absorption coefficients using the new method depend on the size of the sub-volumes, compare the
convergence to the conventional nonlinear approach, and present an error estimation.
Using multiple lasers in continuous wave diffuse optical tomography has the advantages that scattering and absorption
can be distinguished, and that physiological parameters (chromophore concentrations) can be reconstructed. The choice
of the laser wavelengths is crucial to ensure a good separability of scattering and chromophores. Current methods to
optimize the wavelengths do not consider the sensitivity of the reconstruction result to deviations of extinction
coefficients of the chromophores. But since the available absorption spectra for the individual chromophores show
significant deviations, it seems to be necessary to take this into account when optimizing the wavelengths. The
wavelength optimization approach presented here is an extension of a method of Corlu et al. An additional criterion is
introduced, which evaluates the dependence of reconstructed chromophore concentrations on deviations of the
absorption coefficients. The wavelengths found by the new approach are compared to those resulting from the original
method. Reconstructions of simulated data show the effect of using various spectra for reconstruction with different
wavelength sets and illustrate the advantages of the new wavelength sets, leading to less crosstalk between the
chromophore concentrations and lower artifacts.
We developed an eight-channel scanning time-domain fluorescence mammograph capable of imaging the distribution of
a non-specific fluorescent contrast agent in the female breast, besides imaging intrinsic absorption and scattering
properties of healthy breast tissue and tumors. The apparatus is based on the PTB multi-channel laser pulse
mammograph, originally designed for measurements of absorption and scattering coefficients at four selected
wavelengths (&lgr; = 652 nm, 684 nm, 797nm, and 830 nm). It was upgraded for time-resolved detection of fluorescence,
excited at 735 nm by a ps diode laser with 10 mW output power and detected at wavelengths &lgr; ⩾ 780 nm. Cooled PMTs
with GaAs photocathodes are used to detect laser and fluorescence photons at five positions in transmission and three
positions in reflection. Measurements are performed with the breast being slightly compressed between two parallel
glass plates. The transmitting and receiving fiber bundles are scanned synchronously over the breast in steps of typically
2.5 mm. At each scan position, distributions of times of flight of laser photons are measured by time-correlated single
photon counting at eight detector positions, followed by measurements of distributions of times of arrival of
fluorescence photons. The performance of the fluorescence mammograph was investigated by using breast-like
phantoms with a fluorescent inhomogeneity with dye enrichment varying between 2:1 and 10:1 over background values.
We have carried out phantom studies for optimizing the design of a fluorescence mammograph employing time-domain
and cw measurements, for improving data analysis and methods of reconstruction. By scanning pulsed (100 fs) laser
radiation across a fluorescent, rectangular breast-like phantom with a spherical inhomogeneity simulating a tumor
bearing breast slightly compressed between two parallel glass plates, distributions of times of flight of laser and
fluorescence photons were measured in transmission and reflection for various detector arrangements. Absorption
coefficients and dye concentrations were reconstructed using perturbation solutions of the diffusion equation at the laser
and fluorescence wavelengths. We additionally employed a CCD camera to measure time-integrated intensity of
fluorescence and laser radiation transmitted through the phantom. The increased number of projection angles entering the
reconstruction improved spatial resolution. Further improvements were obtained when combined cw data and time-resolved
remission data were used in the reconstruction.
We report on the reconstruction of absorption and fluorescence from measured time-domain diffuse reflectance
and transmittance of laser and fluorescence radiation. Measurements were taken on slab-like, diffusely scattering
and fluorescent phantoms containing fluorescent inhomogeneities, using fs laser pulses (&lgr; = 730 nm) and time
correlated single photon counting. The source was scanned across the entrance face of the phantom, and at
each source position data were collected in transmission and reflection at various detector positions. These
measurements simulate in vivo data that will be obtained employing a scanning, time-domain fluorescence
mammograph, where the breast is gently compressed between two parallel glass plates, and source and detector
optical fibers scan synchronously at various source-detector offsets, allowing to record laser and fluorescence
mammograms.
The diffusion equations for the propagation of the laser and fluorescence radiation were solved in frequency
domain by the finite element method. Measured time-resolved phantom data were Fourier-transformed to frequency
domain prior to image reconstruction. Signal-to-noise ratios were high enough to use several data sets
simultaneously in the reconstruction process belonging to various modulation frequencies up to several hundred
MHz. To obtain the spatial distribution of the fluorescent contrast agent the Born approximation of the
fluorescence diffusion equation was used.
Diffuse optical tomography is a non-invasive method aiming at the detection of breast cancer. The sensitivity and
specificity of the method can be increased if a fluorescent contrast agent is used that accumulates in malignant
lesions. Recently, Philips developed an optical scanner, where the patient is lying on a bed, with one breast
hanging freely in a cup containing an optical matching fluid. 507 optical fibers are mounted in the surface of
the measurement cup. The breast is illuminated sequentially by half of these fibers while the other half is used
to collect the light that is emanating from the breast. The system uses near-infrared light of continuous wave
solid-state lasers to illuminate the breast at four different wavelengths. A complete measurement takes less than
ten minutes and involves five breast scans: transmission data are collected for four wavelengths, and fluorescence
data for excitation at one wavelength. Here, we present the image reconstruction scheme and a novel method to
assess the system performance in terms of lesion detectability. This method uses a statistical significance test on
simulated data with and without a lesion. It allows the quantification of the detectability of lesions for different
size, position, or contrast of the lesion. It also allows to analyze the potential impact of system improvements
or to judge the performance of an image reconstruction algorithm.
Diffuse optical tomography (DOT) uses the transmission of near-infrared light through tissue to image absorption and scattering. Especially for mammography applications DOT might become of clinical use. In this work we present simulation results on the influence of noise on the detectability of lesions for the Philips mammoscope system. Noise can have a significant impact on the image quality. It can prevent the detection of even high contrast lesions. The influence of noise can be reduced by a proper treatment in the reconstruction algorithm. But it changes also the effective sampling pattern of the imaging system if noisy data are not used (or used with a lower weight). In the case of this optical tomography system this means that lesions are only detectable up to a certain depth. This depth depends on where the signal power gets close to the constant noise floor, and on the volume and contrast of the lesion. Our simulation results show that the detection of lesions with 10 mm diameter and 100% absorption contrast should be possible with the mammoscope system, even in the worst case where the lesion is located in the center of the breast.
Images reconstructed for transmission tomography with iterative Ordered Subsets Maximum Likelihood (OSML) algorithms have a higher signal-to-noise ratio than images reconstructed with filtered back-projection type algorithms. However, a drawback of OSML reconstruction is the requirement that a field-of-view (FOV) has to be reconstructed that covers the whole volume, which contributed to the absorption. In the case of a high resolution reconstruction, this demands a huge number of voxels. This paper presents a solution, how an iterative OSML reconstruction can be limited to a region of interest without loosing the advantages of a OSML reconstruction. Compared with a full FOV OSML reconstruction, the reconstruction speed mainly increases by the number of voxels, which are saved. In addition, less iterations are needed to achieve the same result.
High resolution images of coronary arteries are reconstructed with the algebraic reconstruction technique (ART) applied to cone-beam CT cardiac imaging.
Due to the motion of the heart during the scan, only data belonging to the same phase of the heart cycle can be used in the reconstruction process. Currently, all known analytical image reconstruction algorithms for this problem are approximate and do not take the cone-angle fully into account.
ART models the scanner geometry exactly and does not suffer from large-cone angles, which is especially important with the current trend in CT to use detectors with more and more rows and larger cone-angles.
In this study, the influence of the cardiac weighting function on image quality is investigated.
Cardiac ART (CART) is used to reconstruct images from clinical data obtained with current 16-row CT scanners. The results are compared to an analytical reconstruction method.
With the introduction of ultra-fast cone beam scanners, cardiac CT
imaging has become feasible. In order to achieve excellent image
quality, cardiac phases must be found during which the heart is
quasi-stationary. Electrocardiogram (ECG) information does not
always correspond to the exact motion-state of the heart, and
there is high patient variability with respect to the motion
pattern. The clinician has to select stable phases manually
without an exact knowledge about the patient-specific motion.
Therefore, several high-resolution volumes corresponding to
different phases have to be reconstructed, which is an inefficient
task.
In this contribution, a simple and efficient image-based technique
is introduced which is able to deliver patient-specific stable
cardiac phases in an automatic fashion. For this purpose, a
low-resolution 4D data set is reconstructed in advance. The most
stable phases are derived from this 4D data set by calculating the
similarity between subsequent positions in the cardiac cycle.
Information about the patient-specific motion of the heart can be
determined. High-resolution reconstructions are shown at the
automatically predicted phase points corresponding to systole and
diastole. The images are superior to images reconstructed at other
phase points.
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