RESUMEN
PURPOSE: The first aim was to generate and compare synthetic-CT (sCT) images using a conditional generative adversarial network (cGAN) method (Pix2Pix) for MRI-only prostate radiotherapy planning by testing several generators, loss functions, and hyper-parameters. The second aim was to compare the optimized Pix2Pix model with five other architectures (bulk-density, atlas-based, patch-based, U-Net, and GAN). METHODS: For 39 patients treated by VMAT for prostate cancer, T2-weighted MRI images were acquired in addition to CT images for treatment planning. sCT images were generated using the Pix2Pix model. The generator, loss function, and hyper-parameters were tuned to improve sCT image generation (in terms of imaging endpoints). The final evaluation was performed by 3-fold cross-validation. This method was compared to five other methods using the following imaging endpoints: the mean absolute error (MAE) and mean error (ME) between sCT and reference CT images (rCT) of the whole pelvis, bones, prostate, bladder, and rectum. For dose planning analysis, the dose-volume histogram metric differences and 3D gamma analysis (local, 1 %/1 mm) were calculated using the sCT and reference CT images. RESULTS: Compared with the other architectures, Pix2Pix with Perceptual loss function and generator ResNet 9 blocks showed the lowest MAE (29.5, 107.7, 16.0, 13.4, and 49.1 HU for the whole pelvis, bones, prostate, bladder, and rectum, respectively) and the highest gamma passing rates (99.4 %, using the 1 %/1mm and 10 % dose threshold criterion). Concerning the DVH points, the mean errors were -0.2% for the planning target volume V95%, 0.1 % for the rectum V70Gy, and -0.1 % for the bladder V50Gy. CONCLUSION: The sCT images generated from MRI data with the Pix2Pix architecture had the lowest image errors and similar dose uncertainties (in term of gamma pass-rate and dose-volume histogram metric differences) than other deep learning methods.
Asunto(s)
Aprendizaje Profundo , Próstata , Masculino , Humanos , Tomografía Computarizada por Rayos X/métodos , Imagen por Resonancia Magnética/métodos , Pelvis , Planificación de la Radioterapia Asistida por Computador/métodos , Dosificación RadioterapéuticaRESUMEN
Gene transfer with adenoviral vectors is an attractive approach for the treatment of atherosclerosis and restenosis. However, because expression of a therapeutic gene in nontarget tissues may have deleterious effects, artery-specific expression is desirable. Although expression vectors containing transcriptional regulatory elements of genes expressed solely in smooth muscle cells (SMCs) have proved efficient to restrict expression of the transgene, their use in the clinical setting can be limited by their reduced strength. In the present study, we show that low levels of transgene expression are obtained with the smooth muscle (SM)-specific SM22alpha promoter compared with the viral cytomegalovirus (CMV) enhancer/promoter. We have generated chimeric transcriptional cassettes containing either a SM (SM-myosin heavy chain) or a skeletal muscle (creatine kinase) enhancer combined with the SM22alpha promoter. With both constructs we observed significantly stronger expression that remains SM-specific. In vivo, reporter gene expression was restricted to arterial SMCs with no detectable signal at remote sites. Moreover, when interferon-gamma expression was driven by one of these two chimeras, SMC growth was inhibited as efficiently as with the CMV promoter. Finally, we demonstrate that neointima formation in the rat carotid balloon injury model was reduced to the same extent by adenoviral gene transfer of interferon-gamma driven either by the SM-myosin heavy chain enhancer/SM22alpha promoter or the CMV promoter. These results indicate that such vectors can be useful for the treatment of hyperproliferative vascular disorders.
Asunto(s)
Elementos de Facilitación Genéticos/genética , Proteínas Musculares/genética , Músculo Liso Vascular/metabolismo , Regiones Promotoras Genéticas/genética , Adenoviridae/genética , Animales , Enfermedades Cardiovasculares/genética , Enfermedades Cardiovasculares/terapia , Arterias Carótidas/metabolismo , Diferenciación Celular , División Celular , Línea Celular , Células Cultivadas , Citomegalovirus/genética , Expresión Génica , Técnicas de Transferencia de Gen , Terapia Genética , Vectores Genéticos/genética , Proteínas Fluorescentes Verdes , Humanos , Interferón gamma/genética , Interferón gamma/metabolismo , Proteínas Luminiscentes/genética , Proteínas Luminiscentes/metabolismo , Ratones , Ratones Endogámicos C57BL , Proteínas de Microfilamentos/genética , Músculo Liso Vascular/citología , Cadenas Pesadas de Miosina/genética , Ratas , Proteínas Recombinantes de Fusión/genética , Proteínas Recombinantes de Fusión/metabolismo , Sensibilidad y Especificidad , Células Tumorales Cultivadas , Túnica Íntima/metabolismoRESUMEN
We previously demonstrated that a single injection of 10(9) PFU of recombinant adenovirus into patients induces strong vector-specific immune responses (H. Gahéry-Ségard, V. Molinier-Frenkel, C. Le Boulaire, P. Saulnier, P. Opolon, R. Lengagne, E. Gautier, A. Le Cesne, L. Zitvogel, A. Venet, C. Schatz, M. Courtney, T. Le Chevalier, T. Tursz, J.-G. Guillet, and F. Farace, J. Clin. Investig. 100:2218-2226, 1997). In the present study we analyzed the mechanism of vector recognition by cytotoxic T lymphocytes (CTL). CD8(+) CTL lines were derived from two patients and maintained in long-term cultures. Target cell infections with E1-deleted and E1-plus E2-deleted adenoviruses, as well as transcription-blocking experiments with actinomycin D, revealed that host T-cell recognition did not require viral gene transcription. Target cells treated with brefeldin A were not lysed, indicating that viral input protein-derived peptides are associated with HLA class I molecules. Using recombinant capsid component-loaded targets, we observed that the three major proteins could be recognized. These results raise the question of the use of multideleted adenoviruses for gene therapy in the quest to diminish antivector CTL responses.