Dronabinol en manejo de apetito y pérdida de peso en pacientes con cáncer terminal, VIH, cuidados paliativos y vejez. Revisión de la literatura / Dronabinol in appetite management and weight loss in patients with terminal cancer, HIV, palliative care and old age. Literature review

Resumen: Introducción: La caquexia es un síndrome asociado al cáncer avanzado, VIH, pacientes en quimioterapia y quienes tienen seguimiento en cuidados paliativos. La prevalencia es de 25% de los pacientes con diagnóstico de cáncer, 26% en quienes reciben quimioterapia y de 14 a 38% de pacientes con VIH. Un pilar para el manejo es el cannabis debido al efecto del delta-9-tetrahidrocanabinol (THC), del cual se derivó el dronabinol, un fármaco desarrollado para estimular apetito y ganancia de peso. El objetivo de esta revisión bibliográfica es obtener la información sobre los cannabinoides y la evidencia más sólida existente con respecto al uso del dronabinol en pacientes que han presentado pérdida de peso y apetito. Material y métodos: Revisión de la bibliografía con buscador PubMed con las palabras clave Palliative care (cuidados paliativos), Cannabinoids (cannabinoides), cachexia (caquexia), Dronabinol (dronabinol), Appetite (apetito), de 1990 a 2018, limitado a humanos, obteniendo 259 artículos, eliminando 222 por repetirse o tener poca relevancia, dejando 37 artículos para análisis. Resultados: De 37 artículos revisados, nueve fueron estudios experimentales, 10 revisiones sistematizadas, un metaanálisis y 16 artículos de recomendaciones y sugerencias de manejo. Conclusión: El manejo del apetito y pérdida de peso en pacientes en cuidados paliativos, VIH, ancianos o en quimioterapia debe ser multidisciplinario, involucrando nutriólogos, psicólogos y médicos, ajustando el manejo a las características individuales que manifiesten. El dronabinol es un fármaco de primera elección para el manejo de dichos síntomas cuando la historia natural de la enfermedad se acompaña de náusea, vómito o dolor.

Abstract: Introduction: Cachexia is a syndrome associated with advanced cancer, HIV, patients on chemotherapy and those who are followed in palliative care. The prevalence is 25% of patients diagnosed with cancer, 26% in those receiving chemotherapy and 14 to 38% of patients with HIV. A mainstay for management is cannabis, due to the effect of delta-9-tetrahydrocannabinol (THC) from which dronabinol, a drug developed to stimulate appetite and weight gain, was derived. The aim of this literature review is to obtain information on cannabinoids and the strongest existing evidence regarding the use of dronabinol in patients who have presented weight and appetite loss. Material and methods: Literature review with PubMed search engine with the keywords Palliative care, Cannabinoids, cachexia, Dronabinol, Appetite, from 1990 to 2018, limited to humans, obtaining 259 articles, eliminating 222 for repetition or low relevance, leaving 37 articles for analysis. Results: Out of 37 articles reviewed 9 were experimental studies, 10 systematized reviews, 1 meta-analysis and 16 articles of recommendations and management suggestions. Conclusion: The management of appetite and weight loss in palliative care, HIV, elderly or chemotherapy patients should be multidisciplinary, involving nutritionists, psychologists and physicians, adjusting the management to the individual characteristics manifested. Dronabinol is a drug of first choice for the management of these symptoms when the natural history of the disease is accompanied by nausea, vomiting or pain.

Predicting Glioblastoma Recurrence from Preoperative MR Scans Using Fractional-Anisotropy Maps with Free-Water Suppression.

Diffusion tensor imaging (DTI), and fractional-anisotropy (FA) maps in particular, have shown promise in predicting areas of tumor recurrence in glioblastoma. However, analysis of peritumoral edema, where most recurrences occur, is impeded by free-water contamination. In this study, we evaluated the benefits of a novel, deep-learning-based approach for the free-water correction (FWC) of DTI data for prediction of later recurrence. We investigated 35 glioblastoma cases from our prospective glioma cohort. A preoperative MR image and the first MR scan showing tumor recurrence were semiautomatically segmented into areas of contrast-enhancing tumor, edema, or recurrence of the tumor. The 10th, 50th and 90th percentiles and mean of FA and mean-diffusivity (MD) values (both for the original and FWC-DTI data) were collected for areas with and without recurrence in the peritumoral edema. We found significant differences in the FWC-FA maps between areas of recurrence-free edema and areas with later tumor recurrence, where differences in noncorrected FA maps were less pronounced. Consequently, a generalized mixed-effect model had a significantly higher area under the curve when using FWC-FA maps (AUC = 0.9) compared to noncorrected maps (AUC = 0.77, p < 0.001). This may reflect tumor infiltration that is not visible in conventional imaging, and may therefore reveal important information for personalized treatment decisions.

Deep learning derived tumor infiltration maps for personalized target definition in Glioblastoma radiotherapy.

PURPOSE: Glioblastoma is routinely treated by concomitant radiochemotherapy. Current target definition guidelines use anatomic MRI (magnetic resonance imaging) scans, taking into account contrast enhancement and the rather unspecific hyperintensity on the fluid-attenuated inversion recovery (FLAIR) sequence. METHODS AND MATERIALS: We applied deep learning based free water correction of diffusion tensor imaging (DTI) scans to estimate the infiltrative gross tumor volume (iGTV) inside of the FLAIR hyperintense region. We analyzed the resulting iGTVs and their impact on target volume definition in a retrospective cohort of 33 GBM patients. RESULTS: iGTVs were significantly smaller compared to standard pre- and post-operative gross tumor volume (GTV) definitions. Two novel infiltrative tumor GTVs (nGTVPRE-OP and nGTVPOST-OP) defined as the conjunction volume of the standard GTV and the iGTV showed only a moderate increase in size compared to standard GTV definitions. On postoperative scans, the iGTV was predominantly covered by the two clinical target volume (CTV) concepts CTVEORTC and CTVROTG1. A novel infiltrative tumor CTV (nCTV) [nGTVPOST-OP + 2 cm margin] was significantly smaller compared to CTVROTG1 but larger than CTVEORTC. The overlap volume and conformity index demonstrated a distinct spatial configuration of the nCTV. Tumor recurrences overlapped with the iGTV in all but one patients and were completely covered by the nCTV in all patients. After reducing the margin to 1 cm recurrences coverage was at least in-field in all patients. CONCLUSION: To conclude, free water corrected DTI scans may help to define infiltrative tumor areas of GBM that could ultimately be used to individualize RT treatment planning in terms of dose sparing or dose escalation.

Designing contrasts for rapid, simultaneous parameter quantification and flow visualization with quantitative transient-state imaging.

Magnetic resonance imaging (MRI) has evolved into an outstandingly versatile diagnostic modality, as it has the ability to non-invasively produce detailed information on a tissue's structure and function. Complementary data is normally obtained in separate measurements, either as contrast-weighted images, which are fast and simple to acquire, or as quantitative parametric maps, which offer an absolute quantification of underlying biophysical effects, such as relaxation times or flow. Here, we demonstrate how to acquire and reconstruct data in a transient-state with a dual purpose: 1 - to generate contrast-weighted images that can be adjusted to emphasise clinically relevant image biomarkers; exemplified with signal modulation according to flow to obtain angiography information, and 2 - to simultaneously infer multiple quantitative parameters with a single, highly accelerated acquisition. This is achieved by introducing three novel elements: a model that accounts for flowing blood, a method for sequence design using smooth flip angle excitation patterns that incorporates both parameter encoding and signal contrast, and the reconstruction of temporally resolved contrast-weighted images. From these images we simultaneously obtain angiography projections and multiple quantitative maps. By doing so, we increase the amount of clinically relevant data without adding measurement time, creating new dimensions for biomarker exploration and adding value to MR examinations for patients and clinicians alike.

A diffusion model-free framework with echo time dependence for free-water elimination and brain tissue microstructure characterization.

PURPOSE: The compartmental nature of brain tissue microstructure is typically studied by diffusion MRI, MR relaxometry or their correlation. Diffusion MRI relies on signal representations or biophysical models, while MR relaxometry and correlation studies are based on regularized inverse Laplace transforms (ILTs). Here we introduce a general framework for characterizing microstructure that does not depend on diffusion modeling and replaces ill-posed ILTs with blind source separation (BSS). This framework yields proton density, relaxation times, volume fractions, and signal disentanglement, allowing for separation of the free-water component. THEORY AND METHODS: Diffusion experiments repeated for several different echo times, contain entangled diffusion and relaxation compartmental information. These can be disentangled by BSS using a physically constrained nonnegative matrix factorization. RESULTS: Computer simulations, phantom studies, together with repeatability and reproducibility experiments demonstrated that BSS is capable of estimating proton density, compartmental volume fractions and transversal relaxations. In vivo results proved its potential to correct for free-water contamination and to estimate tissue parameters. CONCLUSION: Formulation of the diffusion-relaxation dependence as a BSS problem introduces a new framework for studying microstructure compartmentalization, and a novel tool for free-water elimination.