Voxel-wise analysis: A powerful tool to predict radio-induced toxicity and potentially perform personalised planning in radiotherapy

Dose - volume histograms have been historically used to study the relationship between the planned radiation dose and healthy tissue damage. However, this approach considers neither spatial information nor heterogenous radiosensitivity within organs at risk, depending on the tissue. Recently, voxel-wise analyses have emerged in the literature as powerful tools to fully exploit three-dimensional information from the planned dose distribution. They allow to identify anatomical subregions of one or several organs in which the irradiation dose is associated with a given toxicity. These methods rely on an accurate anatomical alignment, usually obtained by means of a non-rigid registration. Once the different anatomies are spatially normalised, correlations between the three-dimensional dose and a given toxicity can be explored voxel-wise. Parametric or non-parametric statistical tests can be performed on every voxel to identify the voxels in which the dose is significantly different between patients presenting or not toxicity. Several anatomical subregions associated with genitourinary, gastrointestinal, cardiac, pulmonary or haematological toxicity have already been identified in the literature for prostate, head and neck or thorax irradiation. Voxel-wise analysis appears therefore first particularly interesting to increase toxicity prediction capability by identifying specific subregions in the organs at risk whose irradiation is highly predictive of specific toxicity. The second interest is potentially to decrease the radio-induced toxicity by limiting the dose in the predictive subregions, while not decreasing the dose in the target volume. Limitations of the approach have been pointed out.

Deep learning methods to generate synthetic CT from MRI in radiotherapy: A literature review

PURPOSE

In radiotherapy, MRI is used for target volume and organs-at-risk delineation for its superior soft-tissue contrast as compared to CT imaging. However, MRI does not provide the electron density of tissue necessary for dose calculation. Several methods of synthetic-CT (sCT) generation from MRI data have been developed for radiotherapy dose calculation. This work reviewed deep learning (DL) sCT generation methods and their associated image and dose evaluation, in the context of MRI-based dose calculation.

METHODS

We searched the PubMed and ScienceDirect electronic databases from January 2010 to March 2021. For each paper, several items were screened and compiled in figures and tables.

RESULTS

This review included 57 studies. The DL methods were either generator-only based (45% of the reviewed studies), or generative adversarial network (GAN) architecture and its variants (55% of the reviewed studies). The brain and pelvis were the most commonly investigated anatomical localizations (39% and 28% of the reviewed studies, respectively), and more rarely, the head-and-neck (H&N) (15%), abdomen (10%), liver (5%) or breast (3%). All the studies performed an image evaluation of sCTs with a diversity of metrics, with only 36 studies performing dosimetric evaluations of sCT.

CONCLUSIONS

The median mean absolute errors were around 76 HU for the brain and H&N sCTs and 40 HU for the pelvis sCTs. For the brain, the mean dose difference between the sCT and the reference CT was <2%. For the H&N and pelvis, the mean dose difference was below 1% in most of the studies. Recent GAN architectures have advantages compared to generator-only, but no superiority was found in term of image or dose sCT uncertainties. Key challenges of DL-based sCT generation methods from MRI in radiotherapy is the management of movement for abdominal and thoracic localizations, the standardization of sCT evaluation, and the investigation of multicenter impacts.

A functional genomics screen identifying blood cell development genes in Drosophila by undergraduates participating in a course-based research experience

Undergraduate students participating in the UCLA Undergraduate Research Consortium for Functional Genomics (URCFG) have conducted a two-phased screen using RNA interference (RNAi) in combination with fluorescent reporter proteins to identify genes important for hematopoiesis in Drosophila. This screen disrupted the function of approximately 3500 genes and identified 137 candidate genes for which loss of function leads to observable changes in the hematopoietic development. Targeting RNAi to maturing, progenitor, and regulatory cell types identified key subsets that either limit or promote blood cell maturation. Bioinformatic analysis reveals gene enrichment in several previously uncharacterized areas, including RNA processing and export and vesicular trafficking. Lastly, the participation of students in this course-based undergraduate research experience (CURE) correlated with increased learning gains across several areas, as well as increased STEM retention, indicating that authentic, student-driven research in the form of a CURE represents an impactful and enriching pedagogical approach.

Implication of heat shock proteins in rotavirus entry into Reh cells

The mechanisms of rotavirus entry into the target cell are described as a multi-step event in which the virions are bound to sialic acid (SA), followed by interaction with heat shock cognate protein 70 (Hsc70), some integrins and protein disulfide isomerase (PDI). However, the cell surface receptor molecules facilitating the entry of tumor cell-adapted rotavirus are not completely characterized. Using infection blocking assays with antibodies to some heat shock proteins (HSPs) and also some inhibitors of these cellular proteins, we were able to identify the cell surface Hsp90, Hsp70, Hsc70, Hsp60, Hsp40, PDI and integrin β3 as receptors of tumor cell-adapted rotavirus in Reh cells. Furthermore, the results also indicated that these rotavirus receptors are associated with lipid microdomains (rafts). Our findings provide evidence that rotavirus tropism for these human acute lymphocytic leukemia cells is explained by the relatively high expression of some HSPs in rafts. The results shown here encourage further research aim at evaluating the potential use of rotaviruses as an oncolytic agent for the treatment of some cancers. Keywords: heat shock proteins; rotavirus; cell receptor; cancer; oncolytic virus.

Thiol/disulfide exchange occurs in rotavirus structural proteins during contact with intestinal villus cell surface

Protein disulfide isomerase (PDI) is an enzyme that catalyzes disulfide bond reduction or formation and rearrangements of disulfide bridges, and also functions as a chaperone. During entry of some of the viruses PDI participates in thiol-disulfide exchange. Previous reports show that rotavirus entry is interfered by impermeant thiol/disulfide exchange inhibitors and antibodies against PDI. Our objective was to assess the interaction between PDI and triple-layered particles (TLPs) from rotavirus strains ECwt and RRV and from a human rotavirus isolate (HI) during the early steps of virus entry in a system of isolated small intestinal villi. Purified soluble PDI was incubated with either isolated intestinal villi or cell membrane-enriched fractions in the presence or absence of thiol/disulfide inhibitors such as bacitracin, DTNB or N- ethylmaleimide followed by the assessment of the PDI interactions with TLPs and rotavirus structural proteins in terms of their redox state changes. Soluble and membrane-bound PDI was found to interact with TLPs from all the rotaviruses assayed and also with the isolated structural proteins represented by the recombinant rVP5* (a tryptic cleavage product of VP4), rVP6 and the native VP7. PDI interaction with TLPs and rotavirus structural proteins was decreased by the presence of thiol/disulfide exchange inhibitors. Interactions of cell membrane-enriched fractions with TLPs produced rearrangements in the disulfide bridges of rotavirus structural proteins. We conclude that PDI interacts with rotavirus virions through redox reactions that could facilitate the rotavirus entry into the host cell. Keywords: cell surface PDI; thiol-disulfide exchange; rotavirus TLPs; virus entry; bacitracin; DTNB.

Nintedanib in patients with progressive fibrosing interstitial lung diseases-subgroup analyses by interstitial lung disease diagnosis in the INBUILD trial: a randomised, double-blind, placebo-controlled, parallel-group trial

BACKGROUND

The INBUILD trial investigated the efficacy and safety of nintedanib versus placebo in patients with progressive fibrosing interstitial lung diseases (ILDs) other than idiopathic pulmonary fibrosis (IPF). We aimed to establish the effects of nintedanib in subgroups based on ILD diagnosis.

METHODS

The INBUILD trial was a randomised, double-blind, placebo-controlled, parallel group trial done at 153 sites in 15 countries. Participants had an investigator-diagnosed fibrosing ILD other than IPF, with chest imaging features of fibrosis of more than 10% extent on high resolution CT (HRCT), forced vital capacity (FVC) of 45% or more predicted, and diffusing capacity of the lung for carbon monoxide (DLco) of at least 30% and less than 80% predicted. Participants fulfilled protocol-defined criteria for ILD progression in the 24 months before screening, despite management considered appropriate in clinical practice for the individual ILD. Participants were randomly assigned 1:1 by means of a pseudo-random number generator to receive nintedanib 150 mg twice daily or placebo for at least 52 weeks. Participants, investigators, and other personnel involved in the trial and analysis were masked to treatment assignment until after database lock. In this subgroup analysis, we assessed the rate of decline in FVC (mL/year) over 52 weeks in patients who received at least one dose of nintedanib or placebo in five prespecified subgroups based on the ILD diagnoses documented by the investigators: hypersensitivity pneumonitis, autoimmune ILDs, idiopathic non-specific interstitial pneumonia, unclassifiable idiopathic interstitial pneumonia, and other ILDs. The trial has been completed and is registered with ClinicalTrials.gov, number NCT02999178.

FINDINGS

Participants were recruited between Feb 23, 2017, and April 27, 2018. Of 663 participants who received at least one dose of nintedanib or placebo, 173 (26%) had chronic hypersensitivity pneumonitis, 170 (26%) an autoimmune ILD, 125 (19%) idiopathic non-specific interstitial pneumonia, 114 (17%) unclassifiable idiopathic interstitial pneumonia, and 81 (12%) other ILDs. The effect of nintedanib versus placebo on reducing the rate of FVC decline (mL/year) was consistent across the five subgroups by ILD diagnosis in the overall population (hypersensitivity pneumonitis 73·1 [95% CI -8·6 to 154·8]; autoimmune ILDs 104·0 [21·1 to 186·9]; idiopathic non-specific interstitial pneumonia 141·6 [46·0 to 237·2]; unclassifiable idiopathic interstitial pneumonia 68·3 [-31·4 to 168·1]; and other ILDs 197·1 [77·6 to 316·7]; p=0·41 for treatment by subgroup by time interaction). Adverse events reported in the subgroups were consistent with those reported in the overall population.

INTERPRETATION

The INBUILD trial was not designed or powered to provide evidence for a benefit of nintedanib in specific diagnostic subgroups. However, its results suggest that nintedanib reduces the rate of ILD progression, as measured by FVC decline, in patients who have a chronic fibrosing ILD and progressive phenotype, irrespective of the underlying ILD diagnosis.

FUNDING

Boehringer Ingelheim.

4D in vivo quantification of ankle joint space width using dynamic MRI

Spatio-temporal evolution of joint space width (JSW) during motion is of great importance to help with making early treatment plans for degenerative joint diseases like osteoarthritis (OA). These diseases can affect people of all ages leading to an acceleration of joint degeneration and to limitations in the activities of daily living. However, only a few studies have attempted to quantify the JSW from moving joints. In this paper, we present a generic pipeline to accurately determine the changes of the JSW during the joint motion cycle. The key idea is to combine spatial information of static MRI with temporal information of low-resolution (LR) dynamic MRI sequences via an intensity-based registration framework, leading to a high-resolution (HR) temporal reconstruction of the joint. This allows the temporal JSW to be measured in the HR domain using an Eulerian approach for solving partial differential equations (PDEs) inside a deforming inter-bone area where the HR reconstructed bone segmentations are considered as temporal Dirichlet boundaries. The proposed approach has been applied and evaluated on in vivo MRI data of five healthy children to non-invasively quantify the spatio-temporal evolution of the JSW of the ankle (tibiotalar joint) during the entire dorsi-plantar flexion motion cycle. Promising results were obtained, showing that this pipeline can be useful to perform large-scale studies containing subjects with OA for different joints like ankle and knee.

Voxel-based identification of local recurrence sub-regions from pre-treatment PET/CT for locally advanced head and neck cancers

Background

Overall, 40% of patients with a locally advanced head and neck cancer (LAHNC) treated by chemoradiotherapy (CRT) present local recurrence within 2 years after the treatment. The aims of this study were to characterize voxel-wise the sub-regions where tumor recurrence appear and to predict their location from pre-treatment ¹⁸F-fluorodeoxyglucose (FDG) positron emission tomography (PET) images.

Materials and methods

Twenty-six patients with local failure after treatment were included in this study. Local recurrence volume was identified by co-registering pre-treatment and recurrent PET/CT images using a customized rigid registration algorithm. A large set of voxel-wise features were extracted from pre-treatment PET to train a random forest model allowing to predict local recurrence at the voxel level.

Results

Out of 26 expert-assessed registrations, 15 provided enough accuracy to identify recurrence volumes and were included for further analysis. Recurrence volume represented on average 23% of the initial tumor volume. The MTV with a threshold of 50% of SUVmax plus a 3D margin of 10 mm covered on average 89.8% of the recurrence and 96.9% of the initial tumor. SUV and MTV alone were not sufficient to identify the area of recurrence. Using a random forest model, 15 parameters, combining radiomics and spatial location, were identified, allowing to predict the recurrence sub-regions with a median area under the receiver operating curve of 0.71 (range 0.14–0.91).

Conclusion

As opposed to regional comparisons which do not bring enough evidence for accurate prediction of recurrence volume, a voxel-wise analysis of FDG-uptake features suggested a potential to predict recurrence with enough accuracy to consider tailoring CRT by dose escalation within likely radioresistant regions.

Multi T1-weighted contrast MRI with fluid and white matter suppression at 1.5 T

INTRODUCTION

The fluid and white matter suppression sequence (FLAWS) provides two T1-weighted co-registered datasets: a white matter (WM) suppressed contrast (FLAWS1) and a cerebrospinal fluid (CSF) suppressed contrast (FLAWS2). FLAWS has the potential to improve the contrast of the subcortical brain regions that are important for Deep Brain Stimulation surgery planning. However, to date FLAWS has not been optimized for 1.5 T. In this study, the FLAWS sequence was optimized for use at 1.5 T. In addition, the contrast-enhancement properties of FLAWS image combinations were investigated using two voxel-wise FLAWS combined images: the division (FLAWS-div) and the high contrast (FLAWS-hc) image.

METHODS

FLAWS sequence parameters were optimized for 1.5 T imaging using an approach based on the use of a profit function under constraints for brain tissue signal and contrast maximization. MR experiments were performed on eleven healthy volunteers (age 18-30). Contrast (CN) and contrast to noise ratio (CNR) between brain tissues were measured in each volunteer. Furthermore, a qualitative assessment was performed to ensure that the separation between the internal globus pallidus (GPi) and the external globus pallidus (GPe) is identifiable in FLAWS1.

RESULTS

The optimized set of sequence parameters for FLAWS at 1.5 T provided contrasts similar to those obtained in a previous study at 3 T. The separation between the GPi and the GPe was clearly identified in FLAWS1. The CN of FLAWS-hc was higher than that of FLAWS1 and FLAWS2, but was not different from the CN of FLAWS-div. The CNR of FLAWS-hc was higher than that of FLAWS-div.

CONCLUSION

Both qualitative and quantitative assessments validated the optimization of the FLAWS sequence at 1.5 T. Quantitative assessments also showed that FLAWS-hc provides an enhanced contrast compared to FLAWS1 and FLAWS2, with a higher CNR than FLAWS-div.

[MRI-based radiotherapy planning]

MRI-based radiotherapy planning is a topical subject due to the introduction of a new generation of treatment machines combining a linear accelerator and a MRI. One of the issues for introducing MRI in this task is the lack of information to provide tissue density information required for dose calculation. To cope with this issue, two strategies may be distinguished from the literature. Either a synthetic CT scan is generated from the MRI to plan the dose, or a dose is generated from the MRI based on physical underpinnings. Within the first group, three approaches appear: bulk density mapping assign a homogeneous density to different volumes of interest manually defined on a patient MRI; machine learning-based approaches model local relationship between CT and MRI image intensities from multiple data, then applying the model to a new MRI; atlas-based approaches use a co-registered training data set (CT-MRI) which are registered to a new MRI to create a pseudo CT from spatial correspondences in a final fusion step. Within the second group, physics-based approaches aim at computing the dose directly from the hydrogen contained within the tissues, quantified by MRI. Excepting the physics approach, all these methods generate a synthetic CT called "pseudo CT", on which radiotherapy planning will be finally realized. This literature review shows that atlas- and machine learning-based approaches appear more accurate dosimetrically. Bulk density approaches are not appropriate for bone localization. The fastest methods are machine learning and the slowest are atlas-based approaches. The less automatized are bulk density assignation methods. The physical approaches appear very promising methods. Finally, the validation of these methods is crucial for a clinical practice, in particular in the perspective of adaptive radiotherapy delivered by a linear accelerator combined with an MRI scanner.

Abstract P5-09-08: Molecular evaluation of Peruvian patients with hereditary breast cancer reveals a novel germline mutation in BRCA1

Background

Breast cancer is the leading cancer in women worldwide, while in Peru is the second most frequent cancer with a high incidence of triple negative breast cancers (21%). There is no previous information about BRCA1/BRCA2 mutations in Peruvian high-risk breast cancer patients. Prior studies from International diagnostic laboratories only presented results of our population as a pooled Hispanic data. Our aim was to characterize mutations in BRCA1/BRCA2 genes in Peruvian patients with breast cancer with hereditary patterns.

Methods

We evaluated mutations in BRCA1/BRCA2 genes by Sanger sequencing and large genomic rearrangements by multiplex ligation-dependent probe amplification (MLPA) in 18 families with hereditary breast cancer criteria identified at the Breast Unit of Oncosalud-AUNA (Lima-Peru). Molecular analysis was done in the facilities of Genetics and Molecular Biology Center at the San Martin de Porres University (Lima-Peru).

Results

Sequencing identified 4 pathogenic mutations in 4/18 families, three previously detected (BRCA1: c.302-1G&gt;C y c.815_824dup10; BRCA2: c.5946delT) and a novel germline mutation in exon 15 of BRCA1 (c.4647_4648dupAA, ClinVar SCV000256598.1) producing a frameshift variant. MLPA revealed 2 amplifications in exon 7 (duplication and triplication) in BRCA1 in unrelated patients with potential pathogenic effects, one of this co-existed with the BRCA2: c.5946delT mutation. In addition, three variants of uncertain significance were found (c.140G&gt;T, in exon 5 of BRCA1 and c.464G&gt;A and c.938C&gt;T in exon 5 and 10 of BRCA2, respectively).

Conclusions

After a comprehensive evaluation we found an alteration rate of 27.8% (5/18) in BRCA1/BRCA2 in families with criteria for hereditary breast cancer. We reported BRCA1 c.4647_4648dupAA as a novel mutation. Further studies including a larger sample size of Peruvian patients should evaluate the prevalence or founder effect of this mutation in our population.

Citation Format: Ponce J, Vigil C, Araujo JM, Castañeda C, Calderon G, Buleje JL, Acosta O, Danos P, Huaman F, Guevara-Fujita ML, Aguilar A, Pinto JA, Gomez HL, Fujita R. Molecular evaluation of Peruvian patients with hereditary breast cancer reveals a novel germline mutation in BRCA1 [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P5-09-08.

Recent advancements in toxicity prediction following prostate cancer radiotherapy

In external beam radiotherapy for prostate cancer limiting toxicities for dose escalation are bladder and rectum toxicities. Normal tissue complication probability models aim at quantifying the risk of developping adverse events following radiotherapy. These models, originally proposed in the context of uniform irradiation, have evolved to implementations based on the state-of-the-art classification methods which are trained using empirical data. Recently, the use of image processing techniques combined with population analysis methods has led to a new generation of models to understand the risk of normal tissue complications following radiotherapy. This paper overviews those methods in the case of prostate cancer radiation therapy and propose some lines of future research.