Place de la tomographie par émission de positons au (18)-fluorodésoxyglucose dans la prise en charge initiale des cancers du col utérin

RENNES1-BU Santé (352382103) / SudocSudocFranceF

Treatment plan library based on population shape analysis for cervical adaptive radiotherapy

International audienceExternal radiotherapy is extensively used to treat cervix carcinoma. It is based on the acquisition of a planning CT scan on which the treatment is optimized before being delivered over 25 fractions. However, large pertreatment anatomical variations, hamper the dose delivery accuracy, with a risk of tumor under-dose and healthy organs over-dose resulting to recurrence and toxicity. We propose to generate a patient-specific treatment library based on a population analysis. First, the cervix meshes of the population were registered towards a template anatomy using a deformable mesh registration (DMR). The DMR follows an iterative point matching approach based on the local shape context (histogram of cylindrical neighbor coordinates and normalized geodesic distance to the cervix base), a topology constraint filter, a thin-plate-spline interpolation and a Gaussian regularization. Second, a standard principal component analysis (PCA) model was generated to estimate the dominant deformation modes of the population. Posterior PCA was computed to generate different potential anatomies of the target. For a new patient, her cervix was registered towards the template and her pre-treatment library was modeled. This method was applied on the data of 19 patients (282 images), using a leave-one-patient-out. The DMR was evaluated using point-to-point distance (mean 1.3 mm), Hausdorff distance (5.7 mm), dice coefficient (0.96) and mean triangle area difference (0.49 mm(2)). The performances of two modeled libraries (2 and 6 modeled anatomies) were compared to a classic pre-treatment library based on 3 planning CTs, showing better results according to both target and healthy organs coverage

Blocking Wnt signaling by SFRP-like molecules inhibits in vivo cell proliferation and tumor growth in cells carrying active β-catenin.: An SFRP-like frizzled motif blocks tumor growth

International audienceConstitutive activation of Wnt/β-catenin signaling in cancer results from mutations in pathway components, which frequently coexist with autocrine Wnt signaling or epigenetic silencing of extracellular Wnt antagonists. Among the extracellular Wnt inhibitors, the secreted frizzled-related proteins (SFRPs) are decoy receptors that contain soluble Wnt-binding frizzled domains. In addition to SFRPs, other endogenous molecules harboring frizzled motifs bind to and inhibit Wnt signaling. One of such molecules is V3Nter, a soluble SFRP-like frizzled polypeptide that binds to Wnt3a and inhibits Wnt signaling and expression of the β-catenin target genes cyclin D1 and c-myc. V3Nter is derived from the cell surface extracellular matrix component collagen XVIII. Here, we used HCT116 human colon cancer cells carrying the ΔS45 activating mutation in one of the alleles of β-catenin to show that V3Nter and SFRP-1 decrease baseline and Wnt3a-induced β-catenin stabilization. Consequently, V3Nter reduces the growth of human colorectal cancer xenografts by specifically controlling cell proliferation and cell cycle progression, without affecting angiogenesis or apoptosis, as shown by decreased [(3)H]-thymidine (in vitro) or BrdU (in vivo) incorporation, clonogenesis assays, cell cycle analysis and magnetic resonance imaging in living mice. Additionally, V3Nter switches off the β-catenin target gene expression signature in vivo. Moreover, experiments with β-catenin allele-targeted cells showed that the ΔS45 β-catenin allele hampers, but does not abrogate, inhibition of Wnt signaling by SFRP-1 or by the SFRP-like frizzled domain. Finally, neither SFRP-1 nor V3Nter affect β-catenin signaling in SW480 cells carrying nonfunctional Adenomatous polyposis coli. Thus, SFRP-1 and the SFRP-like molecule V3Nter can inhibit tumor growth of β-catenin-activated tumor cells in vivo

Detection of bladder metabolic artifacts in (18)F-FDG PET imaging.

International audiencePositron emission tomography using (18)F-fluorodeoxyglucose ((18)F-FDG-PET) is a widely used imaging modality in oncology. It enables significant functional information to be included in analyses of anatomical data provided by other image modalities. Although PET offers high sensitivity in detecting suspected malignant metabolism, (18)F-FDG uptake is not tumor-specific and can also be fixed in surrounding healthy tissue, which may consequently be mistaken as cancerous. PET analyses may be particularly hampered in pelvic-located cancers by the bladder׳s physiological uptake potentially obliterating the tumor uptake. In this paper, we propose a novel method for detecting (18)F-FDG bladder artifacts based on a multi-feature double-step classification approach. Using two manually defined seeds (tumor and bladder), the method consists of a semi-automated double-step clustering strategy that simultaneously takes into consideration standard uptake values (SUV) on PET, Hounsfield values on computed tomography (CT), and the distance to the seeds. This method was performed on 52 PET/CT images from patients treated for locally advanced cervical cancer. Manual delineations of the bladder on CT images were used in order to evaluate bladder uptake detection capability. Tumor preservation was evaluated using a manual segmentation of the tumor, with a threshold of 42% of the maximal uptake within the tumor. Robustness was assessed by randomly selecting different initial seeds. The classification averages were 0.94±0.09 for sensitivity, 0.98±0.01 specificity, and 0.98±0.01 accuracy. These results suggest that this method is able to detect most (18)F-FDG bladder metabolism artifacts while preserving tumor uptake, and could thus be used as a pre-processing step for further non-parasitized PET analyses

Segmentation and characterization of tumors in 18F-FDG PET-CT for outcome prediction in cervical cancer radio-chemotherapy.

International audienceCervical cancer is one of the most common cancer to affect women worldwide. Despite the efficiency of radiotherapy treatment, some patients present recurrency. Early unfavorable outcomes prediction could help oncologist to adapt the treatment. Several studies suggest that tumor characteristics visible with 18FFDG PET imaging before and during the treatment could be used to predict post-treatment recurrency. We present a framework for segmentation and characterization of metabolic tumor activity aimed at exploring the predictive value of pre-treatment and per-treatment 18F-FDG PET images. Thirty-five patients with locally advanced cervix cancer treated by chemoradiotherapy were considered in our study. For each patient, a coregistered PET/CT scan was acquired before and during the treatment and was segmented and characterized with our semi-automated framework. A segmentation process was applied on the baseline acquisition in order to find the metabolic tumor region (MTR). This MTR was propagated to the follow-up acquisition using a rigid registration step. For every patient, 40 features from the two MTRs were extracted to characterize the tumor changes between the two observation points.We identified explanatory characteristics by exploring the threshold which minimizes the p-value computed from the Kaplan-Meier free-disease survival curves. Seven features were identified as potentially correlated with cancer recurrency (p-value<0.05). Results suggest that our method can compute early meaningful features that are related with tumor recurrence

[From image-guided radiotherapy to dose-guided radiotherapy].

International audiencePURPOSE: In case of tumour displacement, image-guided radiotherapy (IGRT) based on the use of cone beam CT (tomographie conique) allows replacing the tumour under the accelerator by rigid registration. Anatomical deformations require however replanning, involving an estimation of the cumulative dose, session after session. This is the objective of this study. PATIENTS AND METHODS: Two examples of arc-intensity modulated radiotherapy are presented: a case of prostate cancer (total dose=80 Gy) with tomographie conique (daily prostate registration) and one head and neck cancer (70 Gy). For the head and neck cancer, the patient had a weekly scanner allowing a dose distribution calculation. The cumulative dose was calculated per voxel on the planning CT after deformation of the dose distribution (with trilinear interpolation) following the transformation given by a non-rigid registration step (Demons registration method) from: either the tomographie conique (prostate), or the weekly CT. The cumulative dose was eventually compared with the planned dose. RESULTS: In cases of prostate irradiation, the "cumulative" dose corresponded to the planned dose to the prostate. At the last week of irradiation, it was above the planned dose for the rectum and bladder. The volume of rectal wall receiving more than 50 Gy (V50) was 20% at the planning and 26% at the end of treatment, increasing the risk of rectal toxicity (NTCP) of 14%. For the bladder wall, V50 were 73% and 82%, respectively. In head and neck, the "cumulative" dose to the parotid exceeded the planned dose (mean dose increasing from 46 Gy to 54 Gy) from the 5th week of irradiation on, suggesting the need for replanning within the first 5 weeks of radiotherapy. CONCLUSION: The deformable registration estimates the cumulative dose delivered in the different anatomical structures. Validation on digital and physical phantoms is however required before clinical evaluation

Weighted quantification of F-18-FDG tumor metabolism activity using fuzzy-thresholding to predict post-treatment tumor recurrence

International audienceCervical cancer is one of the most common cancer to affect women worldwide. Despite the efficiency of radiotherapy treatment, some patients present post-treatment tumor recurrence which increases the risk of death. Early outcome prediction could help oncologists to adapt the treatment. Several studies suggest that quantification of tumor activity using F-18-FDG PET imaging could be used to predict post-treatment tumor recurrence. In this paper we study the predictive value of weighted quantification of tumor metabolism extracted by fuzzy-thresholding for tumor recurrence of locally advanced cervical cancer. Fifty-three patients with locally advanced cervical cancer treated by chemo-radiotherapy were considered in our study. For each patient, a coregistered F-18-FDG PET/CT scan was acquired before the treatment and was segmented using different hard and fuzzy segmentations methods. The tumor activity was extracted through the total lesion glycolysis and through a weighted analog of the total lesion glycolysis using the probability maps provided by the fuzzy segmentations. Outcomes prediction was performed using the area under the receiver operating characteristic curve (AUC) and the Harrell's C-index. Results suggest that weighted quantification of tumor activity seems to be strongly informative and could be used to predict post-treatment tumor recurrence in cervical cance

Statistical shape model to generate a planning library for cervical adaptive radiotherapy

International audienceExternal beam radiotherapy is extensively used to treat cervical carcinomas. A single planning CT scan enables the calculation of the dose distribution. The treatment is delivered over 5 weeks. Large per-treatment anatomical variations may hamper the dose delivery, with the potential of an organs at risk (OAR) overdose and a tumor underdose. To anticipate these deformations, a recent approach proposed three planning CTs with variable bladder volumes, which had the limitation of not covering all per-treatment anatomical variations. An original patient-specific population-based library has been proposed. It consisted of generating two representative anatomies, in addition to the standard planning CT anatomy. First, the cervix and bladder meshes of a population of 20 patients (314 images) were registered to an anatomical template, using a deformable mesh registration. An iterative point-matching algorithm was developed based on local shape context (histogram of polar or cylindrical coordinates and geodesic distance to the base) and on a topology constraint filter. Second, a standard principal component analysis (PCA) model of the cervix and bladder was generated to extract the dominant deformation modes. Finally, specific deformations were obtained using posterior PCA models, with a constraint representing the top of the uterus deformation. For a new patient, the cervix-uterus and bladder were registered to the template, and the patient’s modeled planning library was built according to the model deformations. This method was applied following a leave-one-patient-out cross-validation. The performances of the modeled library were compared to those of the three-CT-based library and showing an improvement in both target coverage and OAR sparing

Random forests to predict tumor recurrence following cervical cancer therapy using pre- and per-treatment F-18-FDG PET parameters

International audienceThe ability to predict tumor recurrence after chemoradiotherapy of locally advanced cervical cancer is a crucial clinical issue to intensify the treatment of the most high-risk patients. The objective of this study was to investigate tumor metabolism characteristics extracted from pre- and per-treatment F-18-FDG PET images to predict 3-year overall recurrence (OR). A total of 53 locally advanced cervical cancer patients underwent pre-and per-treatment F-18-FDG PET (respectively PET1 and PET2). Tumor metabolism was characterized through several delineations using different thresholds, based on a percentage of the maximum uptake, and applied by region-growing. The SUV distribution in PET1 and PET2 within each segmented region was characterized through 7 intensity and histogram-based parameters, 9 shape descriptors and 16 textural features for a total of 1026 parameters. Predictive capability of the extracted parameters was assessed using the area under the receiver operating curve (AUC) associated to univariate logistic regression models and random forest (RF) classifier. In univariate analyses, 36 parameters were highly significant predictors of 3-year OR (p < 0.01), AUC ranging from 0.72 to 0.83. With RF, the Out-of-Bag (OOB) error rate using the totality of the extracted parameters was 26.42% (AUC=0.72). By recursively eliminating the less important variables, OOB error rate of the RF classifier using the nine most important parameters was 13.21% (AUC=0.90). Results suggest that both pre-and per-treatment F-18-FDG PET exams provide meaningful information to predict the tumor recurrence. RF classifier is able to handle a very large number of extracted features and allows the combination of the most prognostic parameters to improve the prediction

Tomographie par émission de positons au (18 F)-fluorodésoxyglucose dans les cancers du col utérin: évaluation ganglionnaire et valeur pronostique/prédictive des données de la tumeur primitive [((18)F)-fluorodeoxyglucose PET/CT in cervix cancer: lymph node assessment and prognostic/predictive value of primary tumour analysis].

National audiencePURPOSE: In cervix carcinoma: (a) to evaluate the ability of ((18)F)-fluorodeoxyglucose (FDG) positron emission tomography (PET) in the lymph node detection; (b) to investigate the prognostic and predictive value of the primary cervical PET parameters. PATIENTS AND METHODS: Ninety patients treated for cervix carcinoma and evaluated initially by MRI and FGD PET were included. The performances of FDG-PET for lymph node detection (relatively to the lymph node dissection) have been described (sensitivity, specificity, positive predictive value and negative predictive value). PET tumour parameters analyzed were: maximum standard uptake value (SUVmax), the volume and the maximum diameter. The prognostic and predictive values of these parameters were investigated. The tumour response was evaluated on surgical specimens. RESULTS: PET detected the cervical tumour with a sensitivity of 97% (mean values: SUVmax=15.8, volume=27 mm(3), maximum diameter=47). For the detection of the lymph nodes, the values of sensibility, specificity, positive predictive value and negative predictive value were: 86, 56, 69 and 78% in the pelvic, and 90, 67, 50 and 95% for the para-aortic area, respectively. The SUVmax was correlated with histologic response (P=0.04). The frequency of partial histological response was significantly higher for tumour SUVmax>10.9 (P=0.017). The maximum PET diameter and pathologic response had an impact on disease-free survival and overall survival in multivariate analysis (P<0.05). CONCLUSION: PET has high sensitivity in detecting pelvic and para-aortic lymph nodes. Some primary cervical tumour PET parameters are useful as prognostic and predictive factors