L’augmentation de la dose tumorale, nécessaire pour améliorer le taux de contrôle biochimique et clinique des cancers de la prostate (en l’absence d’hormonothérapie), impose le respect de contraintes ...définies a priori (doses et volumes) pour la planification dosimétrique et limiter le risque de lésion des organes à risque. Les histogrammes dose–volume (HDV) pour chaque structure d’intérêt constituent le principal critère de jugement objectif permettant de valider un plan de traitement. Cet article présente une revue de la littérature portant sur les relations entre paramètres dosimétriques (doses et volumes) et toxicité tardive, ainsi que sur les modèles mathématiques utilisant ces paramètres pour prédire le risque de survenue d’effets secondaires rectaux, urinaires, sexuels et osseux. Les recommandations dosimétriques et les modèles prédictifs (Normal Tissue Complication Probability) sont plutôt robustes pour la toxicité rectale tardive (rectorragies). Les contraintes portent sur le volume rectal recevant des doses élevées (≥ 70 Gy), mais aussi sur les volumes recevant des doses intermédiaires (40 à 60 Gy). Les relations sont de moins bonne qualité pour le bulbe et les têtes fémorales et quasi-inexistantes pour la vessie. Des études complémentaires sont nécessaires qui, dans l’idéal, devront intégrer les facteurs de risque propres au patient (« comorbidités »), des tests évaluant la sensibilité aux rayonnements ionisants et des modèles mathématiques appliqués à une imagerie tridimensionnelle réalisée sous l’appareil de traitement (comme la tomographie conique).
Dose escalation in prostate cancer is made possible due to technological advances and to precise dose–volume constraints to limit normal tissue damage. This article is a literature review focusing on the correlations between exposure (doses and volumes) of organs at risk (OAR) and rectal, urinary, sexual and bone toxicity, as well as on mathematical models aiming at toxicity prediction. Dose–volume constraint recommendations are presented that have been shown to be associated with reduced rectal damage. Indeed, the clinical data is relatively strong for late rectal toxicity (bleeding), with constraints put on both the volume of the rectum receiving high doses (≥70 Gy) and the volume receiving intermediate doses (40 to 60 Gy). Predictive models of rectal toxicity (Normal Tissue Complication Probability) appear to accurately estimate toxicity risks. The correlations are much weaker for the bulb and the femoral heads, and nearly do not exist for the bladder. Further prospective studies are required, ideally taking into account patient-related risk factors (co-morbidities and their specific treatments), assays of normal tissue hypersensitivity to ionizing radiation and mathematical models applied on 3D images acquired under the treatment machine (e.g. Cone Beam CT).
To investigate the role of diffusion-weighted imaging (DWI), T2-weighted (W) imaging, and apparent diffusion coefficient (ADC) histogram analysis before, during, and after neoadjuvant ...chemoradiotherapy (CRT) in the prediction of pathological response in patients with locally advanced rectal cancer (LARC).
Magnetic resonance imaging (MRI) at 1.5 T was performed in 43 patients with LARC before, during, and after CRT. Tumour volume was measured on both T2-weighted (VT2W) and on DWI at b=1,000 images (Vb,1,000) at each time point, hence the tumour volume reduction rate (ΔVT2W and ΔVb,1,000) was calculated. Whole-lesion (three-dimensional 3D) first-order texture analysis of the ADC map was performed. Imaging parameters were compared to the pathological tumour regression grade (TRG). The diagnostic performance of each parameter in the identification of complete responders (CR; TRG4), partial responders (PR; TRG3) and non-responders (NR; TRG0–2) was evaluated by multinomial regression analysis and receiver operating characteristics curves.
After surgery, 11 patients were CR, 22 PR, and 10 NR. Before CRT, predictions of CR resulted in an ADC value of the 75th percentile and median, with good accuracy (74% and 86%, respectively) and sensitivity (73% and 82%, respectively). During CRT, the best predictor of CR was ΔVT2W (–58.3%) with good accuracy (81%) and excellent sensitivity (91%). After CRT, the best predictors of CR were ΔVT2W (–82.8%) and ΔVb, 1,000 (–86.8%), with 84% accuracy in both cases and 82% and 91% sensitivity, respectively.
The median ADC value at pre-treatment MRI and ΔVT2W (from pre-to-during CRT MRI) may have a role in early and accurate prediction of response to treatment. Both ΔVT2W and ΔVb,1,000 (from pre-to-post CRT) can help in the identification of CR after CRT.
•ADC histogram analysis may provide a new insight in pre-treatment rectal cancer evaluation.•Tumour volume reduction rate from pre-to-during treatment is an early and accurate predictor of response to CRT.•DWI are more sensitive than T2w images in the identification of residual tumour after treatment.
•AUC of dose–response models is sensitive to the observational dose-range of the fitted data•AUC value of NTCP models is driven by intrinsic characteristics of the model and by the clinical setting ...of the data used to develop them.•AUC is problematic when used to compare the discriminative performance of NTCP models.
Normal tissue complication probability (NTCP) models are probabilistic models that describe the risk of radio-induced toxicity in tissues or organs. In the field of radiotherapy, the area under the ROC curve (AUC) is widely used to estimate the performance in risk prediction of NTCP models.
In this work, we derived an analytical expression of the AUC for the logistic NTCP model in the case of both symmetrical and asymmetrical dose (to the normal tissue) windows around D50. Using numerical simulations, we studied the behavior of the AUC in general clinical settings, enforcing non-logistic NTCP models (Lyman-Kutcher-Burman and LogEUD) and including risk factors beyond the dose. We validated our findings using real-world radiotherapy data sets of prostate cancer patients.
Our analytical expression of the AUC made explicit the dependence on both the steepness of the logistic curve (β) and the dose window width (w), showing that an increase of w pushes AUC towards higher values. Increasing values of the AUC with increasing values of w were consistently observed across simulated data sets with diverse clinical settings from published studies and real clinical data sets.
Our results reveal that the AUC of NTCP models inherits intrinsic characteristics from the clinical setting of the data set on which the models are developed, and warn against the use of the AUC to compare the performance of models constructed upon data from trials in which substantially different dose ranges were administered or accounting for different risk factors beyond the dose.
Background
Limited information is available on the relevant prognostic variables after surgery for patients with pancreatic ductal adenocarcinoma (PDAC) subjected to neoadjuvant chemotherapy (NACT). ...NACT is known to induce a spectrum of histological changes in PDAC. Different grading regression systems are currently available; unfortunately, they lack precision and accuracy. We aimed to identify a new quantitative prognostic index based on tumor morphology.
Patients and Methods
The study population was composed of 69 patients with resectable or borderline resectable PDAC treated with preoperative NACT (neoadjuvant group) and 36 patients submitted to upfront surgery (upfront-surgery group). A comprehensive histological assessment on hematoxylin and eosin (H&E) stained sections evaluated 20 morphological parameters. The association between patient survival and morphological variables was evaluated to generate a prognostic index.
Results
The distribution of morphological parameters evaluated was significantly different between upfront-surgery and neoadjuvant groups, demonstrating the effect of NACT on tumor morphology. On multivariate analysis for patients that received NACT, the predictors of shorter overall survival (OS) and disease-free survival (DFS) were perineural invasion and lymph node ratio. Conversely, high stroma to neoplasia ratio predicted longer OS and DFS. These variables were combined to generate a semiquantitative prognostic index based on both OS and DFS, which significantly distinguished patients with poor outcomes from those with a good outcome. Bootstrap analysis confirmed the reproducibility of the model.
Conclusions
The pathologic prognostic index proposed is mostly quantitative in nature, easy to use, and may represent a reliable tumor regression grading system to predict patient outcomes after NACT followed by surgery for PDAC.
To evaluate, in prostate cancer (PCa) patients the potential of (11)C-choline PET/CT as a guide to helical tomotherapy (HTT) of lymph-node (LN) relapses with simultaneous integrated boost (SIB). The ...efficacy and feasibility of HTT in terms of acute toxicity were assessed.
We enrolled 83 PCa patients (mean age 68 years, range 51 - 82 years) with biochemical recurrence after radical primary treatment (mean serum PSA 7.61 ng/ml, range 0.37 - 187.00 ng/ml; PSA0) who showed pathological findings on (11)C-choline PET/CT only at the LN site. (11)C-Choline PET/CT was performed for restaging and then for radiation treatment planning (PET/CT0). Of the 83 patients, 8 experienced further LN relapse, of whom 5 were retreated once and 3 were retreated twice (total 94 radiotherapy treatments). All pelvic and/or abdominal LNs positive on PET/CT0 were treated with high doses using SIB. Doses were in the range 36 - 74 Gy administered in 28 fractions. After the end of HTT (mean 83 days, range 16 - 365 days), serum PSA was measured in all patients (PSA1) and compared with PSA0 to evaluate early biochemical response. In 47 patients PET/CT was repeated (PET/CT1) to assess metabolic responses at the treated areas. Toxicity criteria of the Radiation Therapy Oncology Group (RTOG) were used to assess acute toxicity.
PET/CT0 revealed pathological LNs in the pelvis in 49 patients, pathological LNs in the abdomen in 15 patients pathological LNs in both the pelvis and abdomen in 18 patients, and pathological LNs in the pelvis or abdomen and other sites in 12 patients. All these sites were treated with HTT. With respect to PSA0, PSA1 (mean 6.28 ng/ml, range 0.00 - 220.46 ng/ml) showed a complete biochemical response after 66 of the 94 HTT treatments, a partial response after 12 treatments, stable disease after 1 treatment and progression of disease after 15 treatments. Of the 47 patients receiving PET/CT1, 20 showed a complete metabolic response at the treated area, 22 a partial metabolic response, 3 progression of disease and 2 stable disease. HTT with SIB was well tolerated in all patients. Grade 3 acute toxicity in the genitourinary tract was observed in two patients.
(11)C-Choline PET/CT is a valuable tool for planning and monitoring HTT in LN relapse after primary treatment. High-dose hypofractionated (11)C-choline PET/CT-guided HTT with SIB is well tolerated and is associated with a high early biochemical response rate.
•The impact of quantization strategies for PET radiomics was assessed.•The images processing chain impact on PET radiomics metrics was measured.•Fixed bin number quantization was found to outperform ...fixed bin size.
The analysis of PET images by textural features, also known as radiomics, shows promising results in tumor characterization. However, radiomic metrics (RMs) analysis is currently not standardized and the impact of the whole processing chain still needs deep investigation. We characterized the impact on RM values of: i) two discretization methods, ii) acquisition statistics, and iii) reconstruction algorithm. The influence of tumor volume and standardized-uptake-value (SUV) on RM was also investigated.
The Chang-Gung-Image-Texture-Analysis (CGITA) software was used to calculate 39 RMs using phantom data. Thirty noise realizations were acquired to measure statistical effect size indicators for each RM. The parameter η2 (fraction of variance explained by the nuisance factor) was used to assess the effect of categorical variables, considering η2 < 20% and 20% < η2 < 40% as representative of a “negligible” and a “small” dependence respectively. The Cohen’s d was used as discriminatory power to quantify the separation of two distributions.
We found the discretization method based on fixed-bin-number (FBN) to outperform the one based on fixed-bin-size in units of SUV (FBS), as the latter shows a higher SUV dependence, with 30 RMs showing η2 > 20%. FBN was also less influenced by the acquisition and reconstruction setup:with FBN 37 RMs had η2 < 40%, only 20 with FBS. Most RMs showed a good discriminatory power among heterogeneous PET signals (for FBN: 29 out of 39 RMs with d > 3).
For RMs analysis, FBN should be preferred. A group of 21 RMs was suggested for PET radiomics analysis.
To report long-term outcomes of relapsed prostate cancer (PC) patients treated in a prospective single-arm study with extended-nodal radiotherapy (ENRT) and 11C-choline positron emission tomography ...(PET)/computed tomography (CT)-guided simultaneous integrated boost (SIB) to positive lymph nodes (LNs).
From 12/2009 to 04/2015, 60 PC patients with biochemical relapse and positive LNs only were treated in this study. ENRT at a median total dose (TD) = 51.8 Gy/28 fr and PET/CT-guided SIB to positive LNs at a median TD = 65.5 Gy was prescribed. Median PSA at relapse was 2.3 (interquartile range, IQR:1.3-4.0) ng/ml. Median number of positive LNs: 2 (range: 1-18). Androgen deprivation therapy (ADT) was prescribed for 48 patients for a median of 30.7 (IQR: 18.5-43.1) months.
Median follow-up from the end of salvage treatment was 121.8 (IQR: 116.1, 130.9) months; 3-, 5-, and 10-year BRFS were 45.0%, 36.0%, and 24.0%, respectively; DMFS: 67.9%, 57.2%, and 45.2%; CRFS: 62.9%, 53.9%, and 42.0%; and OS: 88.2%, 76.3%, and 47.9%, respectively. Castration resistance (p < 0.0001) and ≥ 6 positive LN (p = 0.0024) significantly influenced OS at multivariate analysis. Castration resistance (p < 0.0001 for both) influenced DMFS and CRFS in multivariate analysis.
In PC relapsed patients treated with ENRT and 11C-choline-PET/CT-guided SIB for positive LNs, with 10-year follow-up, a median Kaplan-Meier estimate CRFS of 67 months and OS of 110 months were obtained. These highly favorable results should be confirmed in a prospective, randomized trial.
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