Role of locoregional therapies in the wake of systemic therapy.

The Role of Artificial Intelligence in Interventional Oncology: A Primer.

AIM
To evaluate vascular endothelial growth factor (VEGF) and tryptase in hepatocellular cancer (HCC) before and after trans-arterial chemoembolization (TACE).


METHODS
VEGF and tryptase serum concentrations were assessed from 71 unresectable HCC patients before and after hepatic TACE performed by binding DC-Beads(®) to doxorubicin. VEGF levels were examined for each serum sample using the Quantikine Human VEGF-enzyme-linked immuno-absorbent assay (ELISA), whereas tryptase serum concentrations were assessed for each serum sample by means of fluoro-enzyme immunoassay (FEIA) using the Uni-CAP100 tool. Differences between serum VEGF and tryptase values before and after TACE were evaluated using Student t test. Person's correlation was used to assess the degree of association between the two variables.


RESULTS
VEGF levels and serum tryptase in HCC patients before TACE had a mean value and standard deviation (SD) of 114.31 ± 79.58 pg/mL and 8.13 ± 3.61 μg/L, respectively. The mean levels and SD of VEGF levels and serum tryptase in HCC patients after TACE were 238.14 ± 109.41 pg/mL and 4.02 ± 3.03 μg/L. The changes between the mean values of concentration of VEGF and tryptase before treatment and after treatment was statistically significant (P < 0.000231 and P < 0.00124, by Wilcoxon-Mann-Whitney respectively). A significant correlation between VEGF levels before and after TACE and between tryptase levels before and after TACE was demonstrated (r = 0.68, P = 0.003; r = 0.84, P = 0.000 respectively).


CONCLUSION
Our pilot results suggest that the higher serum VEGF levels and the lower tryptase levels following TACE may be potential biomarkers changing in response to therapy.

Vascular endothelial growth factor and tryptase changesafter chemoembolization in hepatocarcinoma patients

We investigate links between the so-called Stein’s density approach in dimension one and some functional and concentration inequalities. We show that measures having a finite first moment and a density with connected support satisfy a weighted Poincare inequality with the weight being the Stein kernel, that indeed exists and is unique in this case. Furthermore, we prove weighted log-Sobolev and asymmetric Brascamp–Lieb type inequalities related to Stein kernels. We also show that existence of a uniformly bounded Stein kernel is sufficient to ensure a positive Cheeger isoperimetric constant. Then we derive new concentration inequalities. In particular, we prove generalized Mills’ type inequalities when a Stein kernel is uniformly bounded and sub-gamma concentration for Lipschitz functions of a variable with a sub-linear Stein kernel. More generally, when some exponential moments are finite, the Laplace transform of the random variable of interest is shown to bounded from above by the Laplace transform of the Stein kernel. Along the way, we prove a general lemma for bounding the Laplace transform of a random variable, that may be of independent interest. We also provide density and tail formulas as well as tail bounds, generalizing previous results that where obtained in the context of Malliavin calculus.

Weighted Poincaré inequalities, concentration inequalities and tail bounds related to Stein kernels in dimension one

We investigate the links between the so-called Stein's density approach in
dimension one and some functional and concentration inequalities. We show that
measures having a finite first moment and a density with connected support
satisfy a weighted Poincar\'e inequality with the weight being the Stein
kernel. Furthermore we prove asymmetric Brascamp-Lieb type inequalities related
to the Stein kernel. We also show that existence of a uniformly bounded Stein
kernel is sufficient to ensure a positive Cheeger isoperimetric constant. Then
we derive new concentration inequalities. In particular, we prove generalized
Mills' type inequalities when the Stein kernel is uniformly bounded and
sub-gamma concentration for Lipschitz functions of a variable with sub-linear
Stein kernel. When some exponential moments are finite, a general concentration
inequality is then expressed in terms of Legendre-Fenchel transform of the
Laplace transform of the Stein kernel. Along the way, we prove a general lemma
for bounding the Laplace transform of a random variable, that should be very
useful in many other contexts when deriving concentration inequalities.
Finally, we provide density and tail formulas as well as tail bounds,
generalizing previous results that where obtained in the context of Malliavin
calculus.

Weighted Poincar\'e inequalities, concentration inequalities and tail bounds related to the behavior of the Stein kernel in dimension one

The impact of antiangiogenic therapy combined with Transarterial Chemoembolization on enhancement based quantitative tumor response assessment in patients with hepatocellular carcinoma

This work addresses multi-class liver tissue classification from multi-parameter MRI in patients with hepatocellular carcinoma (HCC), and is among the first to do so. We propose a structured prediction framework to simultaneously classify parenchyma, blood vessels, viable tumor tissue, and necrosis, which overcomes limitations related to classifying these tissue classes individually and consecutively. A novel classification framework is introduced, based on the integration of multi-scale shape and appearance features to initiate the classification, which is iteratively refined by augmenting the feature space with both structured and rotationally invariant label context features. We study further the topic of rotationally invariant label context feature representations, and introduce a method for this purpose based on computing the energies of the spherical harmonic decompositions computed at different frequencies and radii. We test our method on full 3D multi-parameter MRI volumes from 47 patients with HCC and achieve promising results.

/pdf/liver-tissue-classification-in-patients-with-hepatocellular-1px8fii4rk.pdf

Liver tissue classification in patients with hepatocellular carcinoma by fusing structured and rotationally invariant context representation.

We use the Malliavin calculus to prove a new abstract concentration inequality result for zero mean, Malliavin differentiable random variables which admit densities. We demonstrate the applicability of the result by deriving two new concrete concentration inequalities, one relating to an integral functional of a fractional Brownian motion process, and the other relating to the centered maximum of a finite sum of Normal random variables. These concentration inequalities are, to the best of our knowledge, largely unattainable via existing methods other than those which are the subject of this paper.

/pdf/concentration-inequalities-via-malliavin-calculus-with-341b2lehxo.pdf

Concentration inequalities via Malliavin calculus with applications

The described implementations relate to systems, methods, and apparatuses for generating regions of interest ( 214 ) from imaging data ( 212 ). Specifically, the regions of interest are generated for tracking treatment efficacy in a more consistent and repeatable manner. The regions of interest can be generated from contrast medium and non-contrast medium enhanced scans ( 102 ) of a patient. Voxel data derived from the scans can be collected and distributed according to respective intensity values in order to identify mode voxels ( 116, 118, 120 ) for particular ranges ( 128 ) of intensities. Regions of interest ( 110, 112, 114 ) can then be generated for each identified mode voxel, and standard deviations for the regions of interest can be determined. One or more thresholds can be derived from the determined standard deviations in order to further filter the intensity values and identify filtered groups of voxels to be the resulting regions of interest.

Systems, methods, and apparatuses for generating regions of interest from voxel mode based thresholds

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The impact of antiangiogenic therapy combined with Transarterial Chemoembolization on enhancement based quantitative tumor response assessment in patients with hepatocellular carcinoma

Liver tissue classification in patients with hepatocellular carcinoma by fusing structured and rotationally invariant context representation.

Concentration inequalities via Malliavin calculus with applications

Systems, methods, and apparatuses for generating regions of interest from voxel mode based thresholds