CXCR4-targeted and MMP-responsive iron oxide nanoparticles for enhanced magnetic resonance imaging

MRI offers high spatial resolution with excellent tissue penetration but it has limited sensitivity and the commonly administered contrast agents lack specificity. In this study, two sets of iron oxide nanoparticles (IONPs) were synthesized that were designed to selectively undergo copper-free click conjugation upon sensing of matrix metalloproteinase (MMP) enzymes, thereby leading to a self-assembled superparamagnetic nanocluster network with T2 signal enhancement properties. For this purpose, IONPs with bioorthogonal azide and alkyne surfaces masked by polyethylene glycol (PEG) layers tethered to CXCR4-targeted peptide ligands were synthesized and characterized. The IONPs were tested in vitro and T2 signal enhancements of around 160 % were measured when the IONPs were incubated with cells expressing MMP2/9 and CXCR4. Simultaneous systemic administration of the bioorthogonal IONPs in tumor-bearing mice demonstrated the signal-enhancing ability of these ‘smart’ self-assembling nanomaterials

Reverse classification accuracy: predicting segmentation performance in the absence of ground truth

When integrating computational tools such as au- tomatic segmentation into clinical practice, it is of utmost importance to be able to assess the level of accuracy on new data, and in particular, to detect when an automatic method fails. However, this is difficult to achieve due to absence of ground truth. Segmentation accuracy on clinical data might be different from what is found through cross-validation because validation data is often used during incremental method development, which can lead to overfitting and unrealistic performance expectations. Before deployment, performance is quantified using different metrics, for which the predicted segmentation is compared to a reference segmentation, often obtained manually by an expert. But little is known about the real performance after deployment when a reference is unavailable. In this paper, we introduce the concept of reverse classification accuracy (RCA) as a framework for predicting the performance of a segmentation method on new data. In RCA we take the predicted segmentation from a new image to train a reverse classifier which is evaluated on a set of reference images with available ground truth. The hypothesis is that if the predicted segmentation is of good quality, then the reverse classifier will perform well on at least some of the reference images. We validate our approach on multi-organ segmentation with different classifiers and segmentation methods. Our results indicate that it is indeed possible to predict the quality of individual segmentations, in the absence of ground truth. Thus, RCA is ideal for integration into automatic processing pipelines in clinical routine and as part of large-scale image analysis studies

Clinical translation of [18F]ICMT-11 for measuring chemotherapy-induced caspase 3/7 activation in breast and lung cancer

Background: Effective anticancer therapy is thought to involve induction of tumour cell death through apoptosis and/or necrosis. [18F]ICMT-11, an isatin sulfonamide caspase-3/7-specific radiotracer, has been developed for PET imaging and shown to have favourable dosimetry, safety, and biodistribution. We report the translation of [18F]ICMT-11 PET to measure chemotherapy-induced caspase-3/7 activation in breast and lung cancer patients receiving first-line therapy. Results: Breast tumour SUVmax of [18F]ICMT-11 was low at baseline and unchanged following therapy. Measurement of M30/M60 cytokeratin-18 cleavage products showed that therapy was predominantly not apoptosis in nature. While increases in caspase-3 staining on breast histology were seen, post-treatment caspase-3 positivity values were only approximately 1%; this low level of caspase-3 could have limited sensitive detection by [18F]ICMT-11-PET. Fourteen out of 15 breast cancer patients responded to first–line chemotherapy (complete or partial response); one patient had stable disease. Four patients showed increases in regions of high tumour [18F]ICMT-11 intensity on voxel-wise analysis of tumour data (classed as PADS); response was not exclusive to patients with this phenotype. In patients with lung cancer, multi-parametric [18F]ICMT-11 PET and MRI (diffusion-weighted- and dynamic contrast enhanced-MRI) showed that PET changes were concordant with cell death in the absence of significant perfusion changes. Conclusion: This study highlights the potential use of [18F]ICMT-11 PET as a promising candidate for non-invasive imaging of caspase3/7 activation, and the difficulties encountered in assessing early-treatment responses. We summarize that tumour response could occur in the absence of predominant chemotherapy-induced caspase-3/7 activation measured non-invasively across entire tumour lesions in patients with breast and lung cancer

Evaluation of the generalized gamma as a tool for treatment planning optimization

Purpose: The aim of that work is to study the theoretical behavior and merits of the Generalized Gamma (generalized dose response gradient) as well as to investigate the usefulness of this concept in practical radiobiological treatment planning.Methods: In this study, the treatment planning system RayStation 1.9 (Raysearch Laboratories AB, Stockholm, Sweden) was used. Furthermore, radiobiological models that provide the tumor control probability (TCP), normal tissue complication probability (NTCP), complication-free tumor control probability (P+) and the Generalized Gamma were employed. The Generalized Gammas of TCP and NTCP, respectively were calculated for given heterogeneous dose distributions to different organs in order to verify the TCP and NTCP computations of the treatment planning system. In this process, a treatment plan was created, where the target and the organs at risk were included in the same ROI in order to check the validity of the system regarding the objective function P+ and the Generalized Gamma. Subsequently, six additional treatment plans were created with the target organ and the organs at risk placed in the same or different ROIs. In these plans, the mean dose was increased in order to investigate the behavior of dose change on tissue response and on Generalized Gamma before and after the change in dose. By theoretically calculating these quantities, the agreement of different theoretical expressions compared to the values that the treatment planning system provides could be evaluated. Finally, the relative error between the real and approximate response values using the Poisson and the Probit models, for the case of having a target organ consisting of two compartments in a parallel architecture and with the same number of clonogens could be investigated and quantified. Results: The computations of the RayStation regarding the values of the Generalized Gamma and the objective function (P+) were verified by using an independent software. Furthermore, it was proved that after a small change in dose, the organ that is being affected most is the organ with the highest Generalized Gamma. Apart from that, the validity of the theoretical expressions that describe the change in response and the associated Generalized Gamma was verified but only for the case of small change in dose. Especially for the case of 50% TCP and NTCP, the theoretical values (ΔPapprox.) and those calculated by the RayStation show close agreement, which proves the high importance of the D50 parameter in specifying clinical response levels. Finally, the presented findings show that the behavior of ΔPapprox. looks sensible because, for both of the models that were used (Poisson and Probit), it significantly approaches the real ΔP around the region of 37% and 50% response. The present study managed to evaluate the mathematical expression of Generalized Gamma for the case of non-uniform dose delivery and the accuracy of the RayStation to calculate its values for different organs. Conclusion: A very important finding of this work is the establishment of the usefulness and clinical relevance of Generalized Gamma. That is because it gives the planner the opportunity to precisely determine which organ will be affected most after a small increase in dose and as a result an optimal treatment plan regarding tumor control and normal tissue complications can be found

Nine Months of Hybrid Intradialytic Exercise Training Improves Ejection Fraction and Cardiac Autonomic Nervous System Activity.

Cardiovascular disease is the most common cause of death in hemodialysis (HD) patients. Intradialytic aerobic exercise training has a beneficial effect on cardiovascular system function and reduces mortality in HD patients. However, the impact of other forms of exercise on the cardiovascular system, such as hybrid exercise, is not clear. Briefly, hybrid exercise combines aerobic and strength training in the same session. The present study examined whether hybrid intradialytic exercise has long-term benefits on left ventricular function and structure and the autonomous nervous system in HD patients. In this single-group design, efficacy-based intervention, twelve stable HD patients (10M/2F, 56 ± 19 years) participated in a nine-month-long hybrid intradialytic training program. Both echocardiographic assessments of left ventricular function and structure and heart rate variability (HRV) were assessed pre, during and after the end of the HD session at baseline and after the nine-month intervention. Ejection Fraction (EF), both assessed before and at the end of the HD session, appeared to be significantly improved after the intervention period compared to the baseline values (48.7 ± 11.1 vs. 58.8 ± 6.5, p = 0.046 and 50.0 ± 13.4 vs. 56.1 ± 3.4, p = 0.054 respectively). Regarding HRV assessment, hybrid exercise training increased LF and decreased HF (p p > 0.05). In conclusion, long-term intradialytic hybrid exercise training was an effective non-pharmacological approach to improving EF and the cardiac autonomous nervous system in HD patients. Such exercise training programs could be incorporated into HD units to improve the patients' cardiovascular health

Development and evaluation of machine learning in whole-body magnetic resonance imaging for detecting metastases in patients with lung or colon cancer: a diagnostic test accuracy study.

OBJECTIVES: Whole-body magnetic resonance imaging (WB-MRI) has been demonstrated to be efficient and cost-effective for cancer staging. The study aim was to develop a machine learning (ML) algorithm to improve radiologists' sensitivity and specificity for metastasis detection and reduce reading times. MATERIALS AND METHODS: A retrospective analysis of 438 prospectively collected WB-MRI scans from multicenter Streamline studies (February 2013-September 2016) was undertaken. Disease sites were manually labeled using Streamline reference standard. Whole-body MRI scans were randomly allocated to training and testing sets. A model for malignant lesion detection was developed based on convolutional neural networks and a 2-stage training strategy. The final algorithm generated lesion probability heat maps. Using a concurrent reader paradigm, 25 radiologists (18 experienced, 7 inexperienced in WB-/MRI) were randomly allocated WB-MRI scans with or without ML support to detect malignant lesions over 2 or 3 reading rounds. Reads were undertaken in the setting of a diagnostic radiology reading room between November 2019 and March 2020. Reading times were recorded by a scribe. Prespecified analysis included sensitivity, specificity, interobserver agreement, and reading time of radiology readers to detect metastases with or without ML support. Reader performance for detection of the primary tumor was also evaluated. RESULTS: Four hundred thirty-three evaluable WB-MRI scans were allocated to algorithm training (245) or radiology testing (50 patients with metastases, from primary 117 colon [n = 117] or lung [n = 71] cancer). Among a total 562 reads by experienced radiologists over 2 reading rounds, per-patient specificity was 86.2% (ML) and 87.7% (non-ML) (-1.5% difference; 95% confidence interval [CI], -6.4%, 3.5%; P = 0.39). Sensitivity was 66.0% (ML) and 70.0% (non-ML) (-4.0% difference; 95% CI, -13.5%, 5.5%; P = 0.344). Among 161 reads by inexperienced readers, per-patient specificity in both groups was 76.3% (0% difference; 95% CI, -15.0%, 15.0%; P = 0.613), with sensitivity of 73.3% (ML) and 60.0% (non-ML) (13.3% difference; 95% CI, -7.9%, 34.5%; P = 0.313). Per-site specificity was high (>90%) for all metastatic sites and experience levels. There was high sensitivity for the detection of primary tumors (lung cancer detection rate of 98.6% with and without ML [0.0% difference; 95% CI, -2.0%, 2.0%; P = 1.00], colon cancer detection rate of 89.0% with and 90.6% without ML [-1.7% difference; 95% CI, -5.6%, 2.2%; P = 0.65]). When combining all reads from rounds 1 and 2, reading times fell by 6.2% (95% CI, -22.8%, 10.0%) when using ML. Round 2 read-times fell by 32% (95% CI, 20.8%, 42.8%) compared with round 1. Within round 2, there was a significant decrease in read-time when using ML support, estimated as 286 seconds (or 11%) quicker (P = 0.0281), using regression analysis to account for reader experience, read round, and tumor type. Interobserver variance suggests moderate agreement, Cohen κ = 0.64; 95% CI, 0.47, 0.81 (with ML), and Cohen κ = 0.66; 95% CI, 0.47, 0.81 (without ML). CONCLUSIONS: There was no evidence of a significant difference in per-patient sensitivity and specificity for detecting metastases or the primary tumor using concurrent ML compared with standard WB-MRI. Radiology read-times with or without ML support fell for round 2 reads compared with round 1, suggesting that readers familiarized themselves with the study reading method. During the second reading round, there was a significant reduction in reading time when using ML support

Embryonic Stem Cell-Derived L1 Overexpressing Neural Aggregates Enhance Recovery after Spinal Cord Injury in Mice

An obstacle to early stem cell transplantation into the acutely injured spinal cord is poor survival of transplanted cells. Transplantation of embryonic stem cells as substrate adherent embryonic stem cell-derived neural aggregates (SENAs) consisting mainly of neurons and radial glial cells has been shown to enhance survival of grafted cells in the injured mouse brain. In the attempt to promote the beneficial function of these SENAs, murine embryonic stem cells constitutively overexpressing the neural cell adhesion molecule L1 which favors axonal growth and survival of grafted and imperiled cells in the inhibitory environment of the adult mammalian central nervous system were differentiated into SENAs and transplanted into the spinal cord three days after compression lesion. Mice transplanted with L1 overexpressing SENAs showed improved locomotor function when compared to mice injected with wild-type SENAs. L1 overexpressing SENAs showed an increased number of surviving cells, enhanced neuronal differentiation and reduced glial differentiation after transplantation when compared to SENAs not engineered to overexpress L1. Furthermore, L1 overexpressing SENAs rescued imperiled host motoneurons and parvalbumin-positive interneurons and increased numbers of catecholaminergic nerve fibers distal to the lesion. In addition to encouraging the use of embryonic stem cells for early therapy after spinal cord injury L1 overexpression in the microenvironment of the lesioned spinal cord is a novel finding in its functions that would make it more attractive for pre-clinical studies in spinal cord regeneration and most likely other diseases of the nervous system

Evidence of Increased Muscle Atrophy and Impaired Quality of Life Parameters in Patients with Uremic Restless Legs Syndrome

BACKGROUND: Restless Legs Syndrome is a very common disorder in hemodialysis patients. Restless Legs Syndrome negatively affects quality of life; however it is not clear whether this is due to mental or physical parameters and whether an association exists between the syndrome and parameters affecting survival. METHOD#ENTITYSTARTX003BF;LOGY/PRINCIPAL FINDINGS: Using the Restless Legs Syndrome criteria and the presence of Periodic Limb Movements in Sleep (PLMS/h >15), 70 clinically stable hemodialysis patients were assessed and divided into the RLS (n = 30) and non-RLS (n = 40) groups. Physical performance was evaluated by a battery of tests: body composition by dual energy X ray absorptiometry, muscle size and composition by computer tomography, while depression symptoms, perception of sleep quality and quality of life were assessed through validated questionnaires. In this cross sectional analysis, the RLS group showed evidence of thigh muscle atrophy compared to the non-RLS group. Sleep quality and depression score were found to be significantly impaired in the RLS group. The mental component of the quality of life questionnaire appeared significantly diminished in the RLS group, reducing thus the overall quality of life score. In contrast, there were no significant differences between groups in any of the physical performance tests, body and muscle composition. CONCLUSIONS: The low level of quality of life reported by the HD patients with Restless Legs Syndrome seems to be due mainly to mental health and sleep related aspects. Increased evidence of muscle atrophy is also observed in the RLS group and possibly can be attributed to the lack of restorative sleep