Identification of CT radiomic features robust to acquisition and segmentation variations for improved prediction of radiotherapy-treated lung cancer patient recurrence.

The primary objective of the present study was to identify a subset of radiomic features extracted from primary tumor imaged by computed tomography of early-stage non-small cell lung cancer patients, which remain unaffected by variations in segmentation quality and in computed tomography image acquisition protocol. The robustness of these features to segmentation variations was assessed by analyzing the correlation of feature values extracted from lesion volumes delineated by two annotators. The robustness to variations in acquisition protocol was evaluated by examining the correlation of features extracted from high-dose and low-dose computed tomography scans, both of which were acquired for each patient as part of the stereotactic body radiotherapy planning process. Among 106 radiomic features considered, 21 were identified as robust. An analysis including univariate and multivariate assessments was subsequently conducted to estimate the predictive performance of these robust features on the outcome of early-stage non-small cell lung cancer patients treated with stereotactic body radiation therapy. The univariate predictive analysis revealed that robust features demonstrated superior predictive potential compared to non-robust features. The multivariate analysis indicated that linear regression models built with robust features displayed greater generalization capabilities by outperforming other models in predicting the outcomes of an external validation dataset.

Faster clinical decisions in B-cell acute lymphoblastic leukaemia: A single flow cytometric 12-colour tube improves diagnosis and minimal residual disease follow-up.

Assessing minimal residual disease (MRD) in B-cell precursor acute lymphoblastic leukaemia (BCP-ALL) is essential for adjusting therapeutic strategies and predicting relapse. Quantitative polymerase chain reaction (qPCR) is the gold standard for MRD. Alternatively, flow cytometry is a quicker and cost-effective method that typically uses leukaemia-associated immunophenotype (LAIP) or different-from-normal (DFN) approaches for MRD assessment. This study describes an optimized 12-colour flow cytometry antibody panel designed for BCP-ALL diagnosis and MRD monitoring in a single tube. This method robustly differentiated hematogones and BCP-ALL cells using two specific markers: CD43 and CD81. These and other markers (e.g. CD73, CD66c and CD49f) enhanced the specificity of BCP-ALL cell detection. This innovative approach, based on a dual DFN/LAIP strategy with a principal component analysis method, can be used for all patients and enables MRD analysis even in the absence of a diagnostic sample. The robustness of our method for MRD monitoring was confirmed by the strong correlation (r = 0.87) with the qPCR results. Moreover, it simplifies and accelerates the preanalytical process through the use of a stain/lysis/wash method within a single tube (<2 h). Our flow cytometry-based methodology improves the BCP-ALL diagnosis efficiency and MRD management, offering a complementary method with considerable benefits for clinical laboratories.

Predictive clinical and dosimetric parameters for risk of relapse in early-stage non-small cell lung cancer treated by SBRT: A large single institution experience.

Purpose: To evaluate the impact of dosimetric parameters on efficacy of stereotactic body radiation therapy (SBRT) in early-stage non-small cell lung cancer (ES-NSCLC), using Hypofractionated Treatment Effects in the Clinic (HyTEC) reporting standards. Methods: From April 2010 to December 2020, 497 patients who received SBRT for ES-NSCLC at the University Hospital of Liège were retrospectively enrolled. A total dose of 40 to 60 Gy in 3-5 fractions (72-180 Gy biologically effective dose with an α/ß ratio of 10 (BED10)) was prescribed to the 80 % isodose line of the PTV. Potential clinical and dosimetric predictors of recurrence, overall survival (OS) and disease specific survival (DSS) were evaluated using univariate and multivariate analyses. Results: After a median follow-up of 32 months (range 3-143 months), the local control and disease-free survival (DFS) rates at 3 years were 91 % (95 % CI: 90 %-93 %) and 75 % (95 % CI: 73 %-77 %), respectively. The median OS was 41.6 months and the median DSS was not reached. On multivariate analysis, a higher gross tumor volume (GTV) Dmax (BED10) (cut-off 198 Gy) and a larger percent of the GTV receiving ≥110 % of the prescribed dose were predictive of a better local control, only GTV volume was correlated with DSS and no parameter was correlated with OS and regional or distant recurrences. Conclusion: Lung SBRT for ES-NSCLC in 3 to 5 fractions resulted in high local control rates. A higher percent of GTV receiving ≥110 % of the prescribed dose and a higher GTV Dmax (BED10) seem to allow a better local control.

Multicentric development and evaluation of [18F]FDG PET/CT and CT radiomic models to predict regional and/or distant recurrence in early-stage non-small cell lung cancer treated by stereotactic body radiation therapy.

PURPOSE: To develop machine learning models to predict regional and/or distant recurrence in patients with early-stage non-small cell lung cancer (ES-NSCLC) after stereotactic body radiation therapy (SBRT) using [18F]FDG PET/CT and CT radiomics combined with clinical and dosimetric parameters. METHODS: We retrospectively collected 464 patients (60% for training and 40% for testing) from University Hospital of Liège and 63 patients from University Hospital of Brest (external testing set) with ES-NSCLC treated with SBRT between 2010 and 2020 and who had undergone pretreatment [18F]FDG PET/CT and planning CT. Radiomic features were extracted using the PyRadiomics toolbox®. The ComBat harmonization method was applied to reduce the batch effect between centers. Clinical, radiomic, and combined models were trained and tested using a neural network approach to predict regional and/or distant recurrence. RESULTS: In the training (n = 273) and testing sets (n = 191 and n = 63), the clinical model achieved moderate performances to predict regional and/or distant recurrence with C-statistics from 0.53 to 0.59 (95% CI, 0.41, 0.67). The radiomic (original_firstorder_Entropy, original_gldm_LowGrayLevelEmphasis and original_glcm_DifferenceAverage) model achieved higher predictive ability in the training set and kept the same performance in the testing sets, with C-statistics from 0.70 to 0.78 (95% CI, 0.63, 0.88) while the combined model performs moderately well with C-statistics from 0.50 to 0.62 (95% CI, 0.37, 0.69). CONCLUSION: Radiomic features extracted from pre-SBRT analog and digital [18F]FDG PET/CT outperform clinical parameters in the prediction of regional and/or distant recurrence and to discuss an adjuvant systemic treatment in ES-NSCLC. Prospective validation of our models should now be carried out.

Radiomics and Delta-Radiomics Signatures to Predict Response and Survival in Patients with Non-Small-Cell Lung Cancer Treated with Immune Checkpoint Inhibitors.

The aim of our study was to determine the potential role of CT-based radiomics in predicting treatment response and survival in patients with advanced NSCLC treated with immune checkpoint inhibitors. We retrospectively included 188 patients with NSCLC treated with PD-1/PD-L1 inhibitors from two independent centers. Radiomics analysis was performed on pre-treatment contrast-enhanced CT. A delta-radiomics analysis was also conducted on a subset of 160 patients who underwent a follow-up contrast-enhanced CT after 2 to 4 treatment cycles. Linear and random forest (RF) models were tested to predict response at 6 months and overall survival. Models based on clinical parameters only and combined clinical and radiomics models were also tested and compared to the radiomics and delta-radiomics models. The RF delta-radiomics model showed the best performance for response prediction with an AUC of 0.8 (95% CI: 0.65-0.95) on the external test dataset. The Cox regression delta-radiomics model was the most accurate at predicting survival with a concordance index of 0.68 (95% CI: 0.56-0.80) (p = 0.02). The baseline CT radiomics signatures did not show any significant results for treatment response prediction or survival. In conclusion, our results demonstrated the ability of a CT-based delta-radiomics signature to identify early on patients with NSCLC who were more likely to benefit from immunotherapy.

Waldenstrom's macroglobulinemia highlighted by turbidity interference: a case report / Découverte d'une maladie de Waldenström via une interférence de turbidité : à propos d'un cas

A 65-year-old female was admitted to the Emergency Department for a fall. Upon admission, a blood sample was drawn for routine laboratory tests. Blood glucose measurement using the hexokinase method was made impossible due to a high lipemia index measured by the instrument despite a clear plasma specimen. It is well known that hemolysis, icterus, and lipemia interferences disrupt spectrophotometric quantifications. However, in this case, the absence of lipemia was confirmed by plasma triglycerides measurement in the normal reference range. Protein electrophoresis along with an immunofixation were carried out to characterize a monoclonal gammopathy since the presence of a monoclonal gammopathy in very high concentrations generates turbidity and interferes with spectrophotometric assays. A gamma peak evoking a monoclonal gammopathy was found on the serum electrophoresis and the immunofixation was positive for a monoclonal IgM kappa. Myelogram showed plasmocytes, lymphoplasmacytic cells and mast cells infiltration which led to the diagnosis of Waldenstrom macroglobulinemia. Based on this case, we propose a course of action to be taken in the case of a high lipemia index and clear plasma.

Une femme de 65 ans est admise aux urgences pour une chute. À l'admission, un échantillon de sang a été prélevé pour réaliser un bilan biologique de routine. Sur ce bilan, la mesure spectrophotométrique de la glycémie par la méthode de l'hexokinase était impossible en raison d'un indice de lactescence trop élevé et ce malgré un plasma d'aspect clair. Il est bien connu que l'hémolyse, l'ictère et la lactescence interfèrent dans le dosage spectrophotométrique. Cependant, dans ce cas, il n'y a pas de perturbation du bilan lipidique chez la patiente. Une prestation de conseil a donc été réalisée par le service de biochimie afin de recommander la réalisation d'une électrophorèse des protéines sériques car la présence d'une gammapathie monoclonale à des concentrations très élevées génère de la turbidité et interfère avec les dosages spectrophotométriques. Un pic dans la fraction des gammaglobulines évoquant une gammapathie monoclonale a été retrouvé sur l'électrophorèse sérique, l'immunofixation confirme la présence d'une IgM kappa monoclonale. Le myélogramme montre une infiltration de plasmocytes, de lymphoplasmocytes et de mastocytes ce qui a conduit au diagnostic de maladie de Waldenström. Sur la base de ce cas, nous proposons une conduite à tenir en cas d'indice de lactescence élevé avec un plasma d'aspect clair.

Periostin in lymph node pre-metastatic niches governs lymphatic endothelial cell functions and metastatic colonization.

Although lymph node (LN) metastasis is an important prognostic parameter in cervical cancer, the tissue remodeling at a pre-metastatic state is poorly documented in LNs. We here identified periostin (POSTN) as a component of non-metastatic LNs by applying proteomic analyses and computerized image quantifications on LNs of patients with cervical cancer. We provide evidence for remarkable modifications of POSTN and lymphatic vessel distributions and densities in non-metastatic sentinel and metastatic human LNs, when compared to distant non-metastatic LNs. POSTN deposition at a pre-metastatic stage was demonstrated in a pre-clinical murine model (the ear sponge assay). Its expression by fibroblastic LN cells was assessed by in situ hybridization and in vitro cultures. In vitro, POSTN promoted lymphatic endothelial cell functions and tumor cell proliferation. Accordingly, the in vivo injection of recombinant POSTN together with VEGF-C boosted the lymphangiogenic response, while the metastatic potential of tumor cells was drastically reduced using a POSTN blocking antibody. This translational study also supports the existence of an unprecedented dialog "in cascade", between the primary tumor and the first pelvic nodal relay in early cervical cancer, and subsequently from pelvic LN to para-aortic LNs in locally advanced cervical cancers. Collectively, this work highlights the association of POSTN deposition with lymphangiogenesis in LNs, and provides evidence for a key contribution of POSTN in promoting VEGF-C driven lymphangiogenesis and the seeding of metastatic cells.

Remodelling of the fibre-aggregate structure of collagen gels by cancer-associated fibroblasts: A time-resolved grey-tone image analysis based on stochastic modelling.

Introduction: Solid tumors consist of tumor cells associated with stromal and immune cells, secreted factors and extracellular matrix (ECM), which together constitute the tumor microenvironment. Among stromal cells, activated fibroblasts, known as cancer-associated fibroblasts (CAFs) are of particular interest. CAFs secrete a plethora of ECM components including collagen and modulate the architecture of the ECM, thereby influencing cancer cell migration. The characterization of the collagen fibre network and its space and time-dependent microstructural modifications is key to investigating the interactions between cells and the ECM. Developing image analysis tools for that purpose is still a challenge because the structural complexity of the collagen network calls for specific statistical descriptors. Moreover, the low signal-to-noise ratio of imaging techniques available for time-resolved studies rules out standard methods based on image segmentation. Methods: In this work, we develop a novel approach based on the stochastic modelling of the gel structure and on grey-tone image analysis. The method is then used to study the remodelling of a collagen matrix by migrating breast cancer-derived CAFs in a three-dimensional spheroid model of cellular invasion imaged by time-lapse confocal microscopy. Results: The structure of the collagen at the scale of a few microns consists in regions with high fibre density separated by depleted regions, which can be thought of as aggregates and pores. The approach developped captures this two-scale structure with a clipped Gaussian field model to describe the aggregates-and-pores large-scale structure, and a homogeneous Boolean model to describe the small-scale fibre network within the aggregates. The model parameters are identified by fitting the grey-tone histograms and correlation functions of the images. The method applies to unprocessed grey-tone images, and it can therefore be used with low magnification, noisy time-lapse reflectance images. When applied to the CAF spheroid time-resolved images, the method reveals different matrix densification mechanisms for the matrix in direct contact or far from the cells. Conclusion: We developed a novel and multidisciplinary image analysis approach to investigate the remodelling of fibrillar collagen in a 3D spheroid model of cellular invasion. The specificity of the method is that it applies to the unprocessed grey-tone images, and it can therefore be used with noisy time-lapse reflectance images of non-fluorescent collagen. When applied to the CAF spheroid time-resolved images, the method reveals different matrix densification mechanisms for the matrix in direct contact or far from the cells.

Efficiency of nilotinib to target chronic phase-chronic myeloid leukaemia primary mature CD34- and immature CD34+ cells.

Accumulation in target cells is an essential pharmacokinetic step of targeted therapies. Tyrosine Kinase Inhibitors (TKI) against the BCR-ABL fusion protein in Chronic Phase-Chronic Myeloid Leukaemia (CP-CML) cells constitute a unique model in terms of efficacy, specificity, and in vivo demonstration of response heterogeneity by target cells. The overall therapeutic response to nilotinib is heterogeneous with no satisfactory explanation. To better understand the patients' response heterogeneity, we quantified nilotinib uptake by primary CP-CML cells in standardized conditions using flow cytometry, which allowed also distinguishing mature (polymorphonuclear cells) from immature (CD34+) cells. Nilotinib was undetectable in 13.3% of PMN and 40% of CD34+ cells. Moreover, in CD34+ cells, intracellular nilotinib did not completely abolish BCR-ABL activity (monitored by CrkL phosphorylation inhibition), although nilotinib accumulated well in most CD34+ cell samples. Intracellular nilotinib concentration was inversely correlated with disease burden parameters, Sokal score, and early haematologic response at day 6 ± 1 only in PMN, suggesting an intrinsic ability to limit nilotinib entry in the forms with higher tumor cell burdenat diagnosis. These findings suggest that nilotinib accumulation in CP-CML cells is influenced by individual characteristics and intra-clonal heterogeneity, and might be used for pharmacokinetic studies and to assess the therapeutic response.

Reciprocal Interplay Between Fibrillar Collagens and Collagen-Binding Integrins: Implications in Cancer Progression and Metastasis.

Cancers are complex ecosystems composed of malignant cells embedded in an intricate microenvironment made of different non-transformed cell types and extracellular matrix (ECM) components. The tumor microenvironment is governed by constantly evolving cell-cell and cell-ECM interactions, which are now recognized as key actors in the genesis, progression and treatment of cancer lesions. The ECM is composed of a multitude of fibrous proteins, matricellular-associated proteins, and proteoglycans. This complex structure plays critical roles in cancer progression: it functions as the scaffold for tissues organization and provides biochemical and biomechanical signals that regulate key cancer hallmarks including cell growth, survival, migration, differentiation, angiogenesis, and immune response. Cells sense the biochemical and mechanical properties of the ECM through specialized transmembrane receptors that include integrins, discoidin domain receptors, and syndecans. Advanced stages of several carcinomas are characterized by a desmoplastic reaction characterized by an extensive deposition of fibrillar collagens in the microenvironment. This compact network of fibrillar collagens promotes cancer progression and metastasis, and is associated with low survival rates for cancer patients. In this review, we highlight how fibrillar collagens and their corresponding integrin receptors are modulated during cancer progression. We describe how the deposition and alignment of collagen fibers influence the tumor microenvironment and how fibrillar collagen-binding integrins expressed by cancer and stromal cells critically contribute in cancer hallmarks.

Stromal integrin α11 regulates PDGFR-ß signaling and promotes breast cancer progression.

Cancer-associated fibroblasts (CAFs) are key actors in modulating the progression of many solid tumors such as breast cancer (BC). Herein, we identify an integrin α11/PDGFRß+ CAF subset displaying tumor-promoting features in BC. In the preclinical MMTV-PyMT mouse model, integrin α11-deficiency led to a drastic reduction of tumor progression and metastasis. A clear association between integrin α11 and PDGFRß was found at both transcriptional and histological levels in BC specimens. High stromal integrin α11/PDGFRß expression was associated with high grades and poorer clinical outcome in human BC patients. Functional assays using five CAF subpopulations (one murine, four human) revealed that integrin α11 promotes CAF invasion and CAF-induced tumor cell invasion upon PDGF-BB stimulation. Mechanistically, integrin α11 pro-invasive activity relies on its ability to interact with PDGFRß in a ligand-dependent manner and to promote its downstream JNK activation, leading to the production of tenascin C, a pro-invasive matricellular protein. Pharmacological inhibition of PDGFRß and JNK impaired tumor cell invasion induced by integrin α11-positive CAFs. Collectively, our study uncovers an integrin α11-positive subset of pro-tumoral CAFs that exploits PDGFRß/JNK signalling axis to promote tumor invasiveness in BC.

uPARAP/Endo180 receptor is a gatekeeper of VEGFR-2/VEGFR-3 heterodimerisation during pathological lymphangiogenesis.

The development of new lymphatic vessels occurs in many cancerous and inflammatory diseases through the binding of VEGF-C to its receptors, VEGFR-2 and VEGFR-3. The regulation of VEGFR-2/VEGFR-3 heterodimerisation and its downstream signaling in lymphatic endothelial cells (LECs) remain poorly understood. Here, we identify the endocytic receptor, uPARAP, as a partner of VEGFR-2 and VEGFR-3 that regulates their heterodimerisation. Genetic ablation of uPARAP leads to hyperbranched lymphatic vasculatures in pathological conditions without affecting concomitant angiogenesis. In vitro, uPARAP controls LEC migration in response to VEGF-C but not VEGF-A or VEGF-CCys156Ser. uPARAP restricts VEGFR-2/VEGFR-3 heterodimerisation and subsequent VEGFR-2-mediated phosphorylation and inactivation of Crk-II adaptor. uPARAP promotes VEGFR-3 signaling through the Crk-II/JNK/paxillin/Rac1 pathway. Pharmacological Rac1 inhibition in uPARAP knockout mice restores the wild-type phenotype. In summary, our study identifies a molecular regulator of lymphangiogenesis, and uncovers novel molecular features of VEGFR-2/VEGFR-3 crosstalk and downstream signaling during VEGF-C-driven LEC sprouting in pathological conditions.

A Bayesian joint model of menstrual cycle length and fecundity.

Menstrual cycle length (MCL) has been shown to play an important role in couple fecundity, which is the biologic capacity for reproduction irrespective of pregnancy intentions. However, a comprehensive assessment of its role requires a fecundity model that accounts for male and female attributes and the couple's intercourse pattern relative to the ovulation day. To this end, we employ a Bayesian joint model for MCL and pregnancy. MCLs follow a scale multiplied (accelerated) mixture model with Gaussian and Gumbel components; the pregnancy model includes MCL as a covariate and computes the cycle-specific probability of pregnancy in a menstrual cycle conditional on the pattern of intercourse and no previous fertilization. Day-specific fertilization probability is modeled using natural, cubic splines. We analyze data from the Longitudinal Investigation of Fertility and the Environment Study (the LIFE Study), a couple based prospective pregnancy study, and find a statistically significant quadratic relation between fecundity and menstrual cycle length, after adjustment for intercourse pattern and other attributes, including male semen quality, both partner's age, and active smoking status (determined by baseline cotinine level 100 ng/mL). We compare results to those produced by a more basic model and show the advantages of a more comprehensive approach.

Cataract Surgery Outcomes in Uveitis: The Multicenter Uveitis Steroid Treatment Trial.

PURPOSE: To assess the visual outcomes of cataract surgery in eyes that received fluocinolone acetonide implant or systemic therapy with oral corticosteroids and immunosuppression during the Multicenter Uveitis Steroid Treatment (MUST) Trial. DESIGN: Nested prospective cohort study of patients enrolled in a randomized clinical trial. PARTICIPANTS: Patients that underwent cataract surgery during the first 2 years of follow-up in the MUST Trial. METHODS: Visual outcomes of cataract surgery were evaluated 3, 6, and 9 months after surgery using logarithmic visual acuity charts. Change in visual acuity over time was assessed using a mixed-effects model. MAIN OUTCOME MEASURES: Best-corrected visual acuity. RESULTS: After excluding eyes that underwent cataract surgery simultaneously with implant surgery, among the 479 eyes in the MUST Trial, 117 eyes (28 eyes in the systemic, 89 in the implant group) in 82 patients underwent cataract surgery during the first 2 years of follow-up. Overall, visual acuity increased by 23 letters from the preoperative visit to the 3-month visit (95% confidence interval [CI], 17-29 letters; P < 0.001) and was stable through 9 months of follow-up. Eyes presumed to have a more severe cataract, as measured by inability to grade vitreous haze, gained an additional 42 letters (95% CI, 34-56 letters; P < 0.001) beyond the 13-letter gain in eyes that had gradable vitreous haze before surgery (95% CI, 9-18 letters; P < 0.001) 3 months after surgery, making up for an initial difference of -45 letters at the preoperative visit (95% CI, -56 to -34 letters; P < 0.001). Black race, longer time from uveitis onset, and hypotony were associated with worse preoperative visual acuity (P < 0.05), but did not affect postsurgical recovery (P > 0.05, test of interaction). After adjusting for other risk factors, there was no significant difference in the improvement in visual acuity between the 2 treatment groups (implant vs. systemic therapy, 2 letters; 95% CI, -10 to 15 letters; P = 0.70). CONCLUSIONS: Cataract surgery resulted in substantial, sustained, and similar visual acuity improvement in the eyes of patients with uveitis treated with the fluocinolone acetonide implant or standard systemic therapy.

Radiographic findings in the nail-patella syndrome.

Nail-patella syndrome is a rare disorder characterized classically by the tetrad of nail hypoplasia or aplasia, aplastic or hypoplastic patellae, elbow dysplasia, and the presence of iliac horns. Iliac horns are considered pathognomonic, and the presence of hypoplastic or aplastic patellae in conjunction with nail abnormalities is a cardinal feature of diagnosis. Elbow dysplasia is present in most cases and can exhibit features typical of the syndrome. Herein we present the radiographic findings of the elbows, knees, and pelvis of a woman with nail-patella syndrome.

An Exponential Tilt Mixture Model for Time-to-Event Data to Evaluate Treatment Effect Heterogeneity in Randomized Clinical Trials.

Evaluating the effect of a treatment on a time-to-event outcome is the focus of many randomized clinical trials. It is often observed that the treatment effect is heterogeneous, where only a subgroup of the patients may respond to the treatment due to some unknown mechanism such as genetic polymorphism. In this paper, we propose a semiparametric exponential tilt mixture model to estimate the proportion of patients who respond to the treatment and to assess the treatment effect. Our model is a natural extension of parametric mixture models to a semiparametric setting with a time-to-event outcome. We propose a nonparametric maximum likelihood estimation approach for inference and establish related asymptotic properties. Our method is illustrated by a randomized clinical trial on biodegradable polymer-delivered chemotherapy for malignant gliomas patients.