Dosimetric implications of kidney anatomical volume changes in Lu-DOTATATE therapy.

Introduction: This study aims to evaluate the use of CT-based whole kidney parenchyma (WKP) segmentation in Lu-DOTATATE dosimetry. Specifically, it investigates whether WKP volumes change during treatment and evaluates the accuracy of applying a single delineated WKP volume for dosimetry. Furthermore, it aims to determine the cause of WKP volume changes-whether caused by radiation or amino acid infusion-by comparing them with spleen volume changes as a marker for radiation-induced alterations.

Evaluation of reconstruction methods and image noise levels concerning visual assessment of simulated liver lesions in In-octreotide SPECT imaging.

Background: Early cancer detection is crucial for patients' survival. The image quality in In-octreotide SPECT imaging could be improved by using Monte Carlo (MC)-based reconstruction. The aim of this observational study was to determine the detection rate of simulated liver lesions for MC-based ordered subset expectation maximization (OSEM) reconstruction compared to conventional attenuation-corrected OSEM reconstruction.

Optimizing the Schedule of PARP Inhibitors in Combination with Lu-DOTATATE: A Dosimetry Rationale.

Lu-DOTATATE for neuroendocrine tumours is considered a low-toxicity treatment and may therefore be combined with other pharmaceuticals to potentiate its efficacy. One approach is to add a poly-[ADP-ribose]-polymerase (PARP) inhibitor to decrease the ability of tumour cells to repair Lu-induced DNA damage. To decrease the risk of side effects, the sequencing should be optimized according to the tumour-to-normal tissue enhanced dose ratio ().

ACTIVITY CONCENTRATION ESTIMATION IN AUTOMATED KIDNEY SEGMENTATION BASED ON CONVOLUTION NEURAL NETWORK METHOD FOR 177LU-SPECT/CT KIDNEY DOSIMETRY.

For 177Lu-DOTATATE treatments, dosimetry based on manual kidney segmentation from computed tomography (CT) is accurate but time consuming and might be affected by misregistration between CT and SPECT images. This study develops a convolution neural network (CNN) for automated kidney segmentation that accurately aligns CT segmented volume of interest (VOI) to the kidneys in SPECT images. The CNN was trained with SPECT/CT images performed over the abdominal area of 137 patients treated with 177Lu-DOTATATE.

EVALUATION OF THE SPATIAL RESOLUTION IN MONTE CARLO-BASED SPECT/CT RECONSTRUCTION OF 111IN-OCTREOTIDE IMAGES.

The purpose was to evaluate the spatial resolution in 111In-octreotide single-photom emission computed tomography (SPECT)/computed tomography (CT) imaging following reconstructions with three different ordered subset expectation maximizations (OSEM) reconstruction algorithms; attenuation corrected (AC) OSEM, AC OSEM with resolution recovery (ACRR OSEM) and Monte Carlo-based OSEM reconstruction (MC OSEM). SPECT/CT imaging of a triple line phantom containing 111In in air and water was performed. The spatial resolution, represented by the full width at half maximum (FWHM) of a line profile, was determined for each line, for X and Y direction and for all reconstructions.

Deep learning-based digitization of prostate brachytherapy needles in ultrasound images.

Purpose: To develop, and evaluate the performance of, a deep learning-based three-dimensional (3D) convolutional neural network (CNN) artificial intelligence (AI) algorithm aimed at finding needles in ultrasound images used in prostate brachytherapy.

Methods: Transrectal ultrasound (TRUS) image volumes from 1102 treatments were used to create a clinical ground truth (CGT) including 24422 individual needles that had been manually digitized by medical physicists during brachytherapy procedures. A 3D CNN U-net with 128 × 128 × 128 TRUS image volumes as input was trained using 17215 needle examples.

Deep-Learning Generation of Synthetic Intermediate Projections Improves Lu SPECT Images Reconstructed with Sparsely Acquired Projections.

The aims of this study were to decrease the Lu-SPECT acquisition time by reducing the number of projections and to circumvent image degradation by adding deep-learning-generated synthesized projections. We constructed a deep convolutional U-net-shaped neural network for generation of synthetic intermediate projections (CUSIPs). The number of SPECT investigations was 352 for training, 37 for validation, and 15 for testing.

Bone Marrow Absorbed Doses and Correlations with Hematologic Response During Lu-DOTATATE Treatments Are Influenced by Image-Based Dosimetry Method and Presence of Skeletal Metastases.

This study aimed to compare different image-based methods for bone marrow dosimetry and study the dose-response relationship during treatment with Lu-DOTATATE in patients with and without skeletal metastases. This study included 46 patients with advanced neuroendocrine tumors treated with at least 2 fractions of Lu-DOTATATE at Sahlgrenska University Hospital. High- and low-uptake compartments were automatically outlined in planar images collected at 2, 24, 48, and 168 h after injection.

Segmentation of Whole-Body Images into Two Compartments in Model for Bone Marrow Dosimetry Increases the Correlation with Hematological Response in Lu-DOTATATE Treatments.

Background: In Lu-DOTATATE treatments, bone marrow (BM) is one of the most important organs at risk. The authors previously developed an image-based two-compartment method for BM dosimetry, showing a significant correlation between absorbed dose to BM and hematological toxicity in Lu-DOTATATE treatments. In the present study, they aimed to further evaluate this BM dosimetry method by finding optimal settings for dividing the whole body into two compartments; in terms of minimizing the coefficient of variation (CV) for the individual absorbed doses and studying its correlation to the BM response.

A novel planar image-based method for bone marrow dosimetry in (177)Lu-DOTATATE treatment correlates with haematological toxicity.

Background: (177)Lu-DOTATATE is a valuable treatment option for patients with advanced neuroendocrine tumours overexpressing somatostatin receptors. Though well tolerated in general, bone marrow toxicity can, besides renal exposure, become dose limiting and affect the ability to sustain future therapies. The aim of this study was to develop a novel planar image-based method for bone marrow dosimetry and evaluate its correlation with haematological toxicity during (177)Lu-DOTATATE treatment.

Model-integrated estimation of normal tissue contamination for cancer SNP allelic copy number data.

SNP allelic copy number data provides intensity measurements for the two different alleles separately. We present a method that estimates the number of copies of each allele at each SNP position, using a continuous-index hidden Markov model. The method is especially suited for cancer data, since it includes the fraction of normal tissue contamination, often present when studying data from cancer tumors, into the model.

Robust assignment of cancer subtypes from expression data using a uni-variate gene expression average as classifier.

Background: Genome wide gene expression data is a rich source for the identification of gene signatures suitable for clinical purposes and a number of statistical algorithms have been described for both identification and evaluation of such signatures. Some employed algorithms are fairly complex and hence sensitive to over-fitting whereas others are more simple and straight forward. Here we present a new type of simple algorithm based on ROC analysis and the use of metagenes that we believe will be a good complement to existing algorithms.

Persistent malignant stem cells in del(5q) myelodysplasia in remission.

Background: The in vivo clinical significance of malignant stem cells remains unclear.

Methods: Patients who have the 5q deletion (del[5q]) myelodysplastic syndrome (interstitial deletions involving the long arm of chromosome 5) have complete clinical and cytogenetic remissions in response to lenalidomide treatment, but they often have relapse. To determine whether the persistence of rare but distinct malignant stem cells accounts for such relapses, we examined bone marrow specimens obtained from seven patients with the del(5q) myelodysplastic syndrome who became transfusion-independent while receiving lenalidomide treatment and entered cytogenetic remission.

Combined gene expression and genomic profiling define two intrinsic molecular subtypes of urothelial carcinoma and gene signatures for molecular grading and outcome.

In the present investigation, we sought to refine the classification of urothelial carcinoma by combining information on gene expression, genomic, and gene mutation levels. For these purposes, we performed gene expression analysis of 144 carcinomas, and whole genome array-CGH analysis and mutation analyses of FGFR3, PIK3CA, KRAS, HRAS, NRAS, TP53, CDKN2A, and TSC1 in 103 of these cases. Hierarchical cluster analysis identified two intrinsic molecular subtypes, MS1 and MS2, which were validated and defined by the same set of genes in three independent bladder cancer data sets.

A continuous-index hidden Markov jump process for modeling DNA copy number data.

The number of copies of DNA in human cells can be measured using array comparative genomic hybridization (aCGH), which provides intensity ratios of sample to reference DNA at genomic locations corresponding to probes on a microarray. In the present paper, we devise a statistical model, based on a latent continuous-index Markov jump process, that is aimed to capture certain features of aCGH data, including probes that are unevenly long, unevenly spaced, and overlapping. The model has a continuous state space, with 1 state representing a normal copy number of 2, and the rest of the states being either amplifications or deletions.

Estimating the total rate of DNA replication using branching processes.

Increasing the knowledge of various cell cycle kinetic parameters, such as the length of the cell cycle and its different phases, is of considerable importance for several purposes including tumor diagnostics and treatment in clinical health care and a deepened understanding of tumor growth mechanisms. Of particular interest as a prognostic factor in different cancer forms is the S phase, during which DNA is replicated. In the present paper, we estimate the DNA replication rate and the S phase length from bromodeoxyuridine-DNA flow cytometry data.

Estimating the variation in S phase duration from flow cytometric histograms.

A stochastic model for interpreting BrdUrd DNA FCM-derived data is proposed. The model is based on branching processes and describes the progression of the DNA distribution of BrdUrd-labelled cells through the cell cycle. With the main focus on estimating the S phase duration and its variation, the DNA replication rate is modelled by a piecewise linear function, while assuming a gamma distribution for the S phase duration.

Permissive roles of hematopoietin and cytokine tyrosine kinase receptors in early T-cell development.

Although several cytokines have been demonstrated to be critical regulators of development of multiple blood cell lineages, it remains disputed to what degree they act through instructive or permissive mechanisms. Signaling through the FMS-like tyrosine kinase 3 (FLT3) receptor and the hematopoietin IL-7 receptor alpha (IL-7Ralpha) has been demonstrated to be of critical importance for sustained thymopoiesis. Signaling triggered by IL-7 and thymic stromal lymphopoietin (TSLP) is dependent on IL-7Ralpha, and both ligands have been implicated in T-cell development.

Estimating the distribution of the G(2) phase duration from flow cytometric histograms.

A mathematical model, based on branching processes, is proposed to interpret BrdUrd DNA FCM-derived data. Our main interest is in determining the distribution of the G(2) phase duration. Two different model classes involving different assumptions on the distribution of the G(2) phase duration are considered.

On the characterization of dynamic supramolecular systems: a general mathematical association model for linear supramolecular copolymers and application on a complex two-component hydrogen-bonding system.

A general mathematical model for the characterization of the dynamic (kinetically labile) association of supramolecular assemblies in solution is presented. It is an extension of the equal K (EK) model by the stringent use of linear algebra to allow for the simultaneous presence of an unlimited number of different units in the resulting assemblies. It allows for the analysis of highly complex dynamic equilibrium systems in solution, including both supramolecular homo- and copolymers without the recourse to extensive approximations, in a field in which other analytical methods are difficult.

Regression analysis and modelling of data acquisition for SELDI-TOF mass spectrometry.

Motivation: Pre-processing of SELDI-TOF mass spectrometry data is currently performed on a largel y ad hoc basis. This makes comparison of results from independent analyses troublesome and does not provide a framework for distinguishing different sources of variation in data.

Results: In this article, we consider the task of pooling a large number of single-shot spectra, a task commonly performed automatically by the instrument software.

Continuous-index hidden Markov modelling of array CGH copy number data.

Motivation: In recent years, a range of techniques for analysis and segmentation of array comparative genomic hybridization (aCGH) data have been proposed. For array designs in which clones are of unequal lengths, are unevenly spaced or overlap, the discrete-index view typically adopted by such methods may be questionable or improved.

Results: We describe a continuous-index hidden Markov model for aCGH data as well as a Monte Carlo EM algorithm to estimate its parameters.