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Fatigue is common in breast‐cancer survivors. Our study assessed fatigue longitudinally in breast cancer patients receiving adjuvant radiotherapy (RT) and aimed to identify risk factors associated with long‐term fatigue and underlying fatigue trajectories. Fatigue was measured in a prospective multicenter cohort (REQUITE) using the Multidimensional Fatigue Inventory (MFI‐20) and analyzed using mixed models. Multivariable logistic models identified factors associated with fatigue dimensions at 2 years post‐RT and latent class growth analysis identified individual fatigue trajectories. A total of 1443, 1302, 1203 and 1098 patients completed the MFI‐20 at baseline, end of RT, after 1 and 2 years. Overall, levels of fatigue significantly increased from baseline to end of RT for all fatigue dimensions (P <.05) and returned to baseline levels after 2 years. A quarter of patients were assigned to latent trajectory high (23.7%) and moderate (24.8%) fatigue classes, while 46.3% and 5.2% to the low and decreasing fatigue classes, respectively. Factors associated with multiple fatigue dimensions at 2 years include age, BMI, global health status, insomnia, pain, dyspnea and depression. Fatigue present at baseline was consistently associated with all five MFI‐20 fatigue dimensions (ORGeneralFatigue = 3.81, P <.001). From latent trajectory analysis, patients with a combination of factors such as pain, insomnia, depression, younger age and endocrine therapy had a particularly high risk of developing early and persistent high fatigue years after treatment. Our results confirmed the multidimensional nature of fatigue and will help clinicians identify breast cancer patients at higher risk of having persistent/late fatigue so that tailored interventions can be delivered. [ABSTRACT FROM AUTHOR]

This document is a reply to comments on a previously published paper about the risk factors for fatigue in breast cancer patients who have undergone radiotherapy. The authors explain that they focused on late fatigue because there is a lack of understanding about this aspect of fatigue in breast cancer patients. They also address concerns about missing data and attrition rates in their study, stating that mortality did not substantially influence the attrition rate. The authors express gratitude for the opportunity to discuss their research and express interest in future collaborations to further understand fatigue in breast cancer patients. [Extracted from the article]

Three‐dimensional (3D) imaging techniques (e.g., confocal microscopy) are commonly used to visualize in vitro models, especially microvasculature on‐a‐chip. Conversely, 3D analysis is not the standard method to extract quantitative information from those models. We developed the μVES algorithm to analyze vascularized in vitro models leveraging 3D data. It computes morphological parameters (geometry, diameter, length, tortuosity, eccentricity) and intravascular flow velocity. μVES application to microfluidic vascularized in vitro models shows that they successfully replicate functional features of the microvasculature in vivo in terms of intravascular fluid flow velocity. However, wall shear stress is lower compared to in vivo references. The morphological analysis also highlights the model's physiological similarities (vessel length and tortuosity) and shortcomings (vessel radius and surface‐over‐volume ratio). The addition of the third dimension in our analysis produced significant differences in the metrics assessed compared to 2D estimations. It enabled the computation of new indices, such as vessel eccentricity. These μVES capabilities can find application in analyses of different in vitro vascular models, as well as in vivo and ex vivo microvasculature. [ABSTRACT FROM AUTHOR]

Purpose: Aim of this study is to assess the repeatability of radiomic features on magnetic resonance images (MRI) and their stability to variations in time of repetition (TR), time of echo (TE), slice thickness (ST), and pixel spacing (PS) using vegetable phantoms. Methods: The organic phantom was realized using two cucumbers placed inside a cylindrical container, and the analysis was performed using T1-weighted (T1w), T2-weighted (T2w), and diffusion-weighted images. One dataset was used to test the repeatability of the radiomic features, whereas other four datasets were used to test the sensitivity of the different MRI sequences to image acquisition parameters (TR, TE, ST, and PS). Four regions of interest (ROIs) were segmented: two for the central part of each cucumber and two for the external parts. Radiomic features were extracted from each ROI using Pyradiomics. To assess the effect of preprocessing on the reduction of variability, features were extracted both before and after the preprocessing. The coefficient of variation (CV) and intra-class correlation coefficient (ICC) were used to evaluate variability. Results: The use of intensity standardization increased the stability for the first-order statistics features. Shape and size features were always stable for all the analyses. Textural features were particularly sensitive to changes in ST and PS, although some increase in stability could be obtained by voxel size resampling. When images underwent image preprocessing, the number of stable features (ICC > 0.75 and mean absolute CV < 0.3) was 33 for apparent diffusion coefficient (ADC), 52 for T1w, and 73 for T2w. Conclusions: The most critical source of variability is related to changes in voxel size (either caused by changes in ST or PS). Preprocessing increases features stability to both test-retest and variation of the image acquisition parameters for all the types of analyzed MRI (T1w, T2w, and ADC), except for ST. [ABSTRACT FROM AUTHOR]

Purpose: Despite its increasing application, radiomics has not yet demonstrated a solid reliability, due to the difficulty in replicating analyses. The extraction of radiomic features from clinical MRI (T1w/T2w) presents even more challenges because of the absence of well‐defined units (e.g. HU). Some preprocessing steps are required before the estimation of radiomic features and one of this is the intensity normalization, that can be performed using different methods. The aim of this work was to evaluate the effect of three different normalization techniques, applied on T2w‐MRI images of the pelvic region, on radiomic features reproducibility. Methods: T2w‐MRI acquired before (MRI1) and 12 months after radiotherapy (MRI2) from 14 patients treated for prostate cancer were considered. Four different conditions were analyzed: (a) the original MRI (No_Norm); (b) MRI normalized by the mean image value (Norm_Mean); (c) MRI normalized by the mean value of the urine in the bladder (Norm_ROI); (d) MRI normalized by the histogram‐matching method (Norm_HM). Ninety‐one radiomic features were extracted from three organs of interest (prostate, internal obturator muscles and bulb) at both time‐points and on each image discretized using a fixed bin‐width approach and the difference between the two time‐points was calculated (Δfeature). To estimate the effect of normalization methods on the reproducibility of radiomic features, ICC was calculated in three analyses: (a) considering the features extracted on MRI2 in the four conditions together and considering the influence of each method separately, with respect to No_Norm; (b) considering the features extracted on MRI2 in the four conditions with respect to the inter‐observer variability in region of interest (ROI) contouring, considering also the effect of the discretization approach; (c) considering Δfeature to evaluate if some indices can recover some consistency when differences are calculated. Results: Nearly 60% of the features have shown poor reproducibility (ICC < 0.5) on MRI2 and the method that most affected features reliability was Norm_ROI (average ICC of 0.45). The other two methods were similar, except for first‐order features, where Norm_HM outperformed Norm_Mean (average ICC = 0.33 and 0.76 for Norm_Mean and Norm_HM, respectively). In the inter‐observer setting, the number of reproducible features varied in the three structures, being higher in the prostate than in the penile bulb and in the obturators. The analysis on Δfeature highlighted that more than 60% of the features were not consistent with respect to the normalization method and confirmed the high reproducibility of the features between Norm_Mean and Norm_HM, whereas Norm_ROI was the less reproducible method. Conclusions: The normalization process impacts the reproducibility of radiomic features, both in terms of changes in the image information content and in the inter‐observer setting. Among the considered methods, Norm_Mean and Norm_HM seem to provide the most reproducible features with respect to the original image and also between themselves, whereas Norm_ROI generates less reproducible features. Only a very small subset of feature remained reproducible and independent in any tested condition, regardless the ROI and the adopted algorithm: skewness or kurtosis, correlation and one among Imc2, Idmn and Idn from GLCM group. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the potential of texture analysis applied on T2‐w and postcontrast T1‐w images acquired before radiotherapy for prostate cancer (PCa) and 12 months after its completion in quantitatively characterizing local radiation effect on the muscular component of internal obturators, as organs potentially involved in urinary toxicity. Methods: T2‐w and postcontrast T1‐w MR images were acquired at 1.5 T before treatment (MRI1) and at 12 months of follow‐up (MRI2) in 13 patients treated with radiotherapy for PCa. Right and left internal obturator muscle contours were manually delineated upon MRI1 and then automatically propagated on MRI2 by an elastic registration method. Planning CT images were coregistered to both MRIs and dose maps were deformed accordingly. A high‐dose region receiving >55 Gy and a low‐dose region receiving <55 Gy were identified in each muscle volume. Eighteen textural features were extracted from each region of interest and differences between MRI1 and MRI2 were evaluated. Results: A signal increase was highlighted in both T2‐w and T1‐w images in the portion of the obturators near the prostate, i.e., in the region receiving medium‐high doses. A change in the spatial organization was identified, as an increase in homogeneity and a decrease in contrast and complexity, compatible with an inflammatory status. In particular, the region receiving medium‐high doses presented more significant or, at least, stronger differences. Conclusions: Texture analysis applied on T1‐w and T2‐w MR images has demonstrated its ability in quantitative evaluating radiation‐induced changes in obturator muscles after PCa radiotherapy. [ABSTRACT FROM AUTHOR]

Study Type - Therapy (decision analysis) Level of Evidence 2b What's known on the subject? and What does the study add? The benefits of the multidisciplinary approach in oncology are widely recognised. In particular, managing patients with prostate cancer within a multidisciplinarity and multiprofessional context is of paramount importance, to address the complexity of a disease where patients may be offered multiple therapeutic and observational options handled by different specialists and having severe therapy-induced side-effects. The present study describes the establishing of a multidisciplinary clinic at the Prostate Cancer Programme of Milan Istituto Nazionale dei Tumori, its effects on the quality of care provided, and strategies implemented to meet upcoming needs and improve quality standards. Having analysed the data of the 2260 multidisciplinary clinics held from March 2005 to March 2011, our dynamic and modifiable organisational model was evaluated for ways to optimise the human resources, offer high-quality standards, meet new needs and ultimately reduce costs. The study is focused on the organisational aspects and adds a perspective from one of the major oncological centres of reference in Italy and in Europe. OBJECTIVES To describe the establishing of a multidisciplinary clinic for men with prostate cancer at the Istituto Nazionale Tumori, Milan., To evaluate the quality of care provided and to describe the management changes implemented to improve standards and meet new needs., MATERIALS AND METHODS In March 2005, we established a multidisciplinary clinic comprising weekly clinics and case-discussion sessions., We have altered the organisational model periodically to meet new needs and improve quality., RESULTS We held 2260 multidisciplinary clinics up to March 2011., For stage distribution, patients with low-risk prostate cancer increased to a peak of 61% in 2009, probably because of the anticipation of diagnosis and the active surveillance expertise of the Prostate Cancer Programme at Istituto Nazionale Tumori, Milan. The slight decrease in 2010 might be due to the availability of robot-assisted prostatectomy in several hospitals in Milan, and the start of a multicentre active surveillance protocol in December 2009., In terms of the efficacy of our multidisciplinary strategy, 11% of drug therapies (mostly hormones) prescribed outside our institute were terminated in the multidisciplinary clinic, and 6% of indications formulated in the multidisciplinary clinics were altered during the case-discussion sessions., CONCLUSIONS The multidisciplinary approach needs to be adaptable to meet new needs and improve quality., Our experience has proved successful for both physicians and patients. The team agrees on strategies; complex cases are managed by a multidisciplinary team; dedicated psychologists contribute their knowledge and perspectives; and patients report the feeling of being cared for. [ABSTRACT FROM AUTHOR]

The article reports on the multivariate correlation between late genitourinary and gastrointestinal toxicities and clinical/dosimetric risk factors. It cites that predicting a high probability of toxicity could avoid unnecessary daily costs to single patient in terms of quality of life modification during and after treatment. It reveals that the integrated evaluation of clinical and dosimetric parameters in single patient can help to offer tailored probability of the specific outcome considered.

The article examines the dose-volume modeling of late and acute toxicity in radiotherapy for prostate cancer. According to the authors, the largest studies on dose-volume modeling of rectal toxicity has produced very consistent results, recommending that the rectum is prevalently serial organ when bleeding is considered as the endpoint. However, it suggests that further investigation on large groups of patients will be important to reliably evaluate quantitative models of dose-volume effects.

The authors discuss the concept of health-related quality of life (HRQoL) which is considered a fundamental health outcome. The authors mention the significance of collecting longitudinal HRQoL data from patients with prostate cancer (PCa) who underwent carbon-ion radiotherapy. Also discussed is the need to provide the basis for the design of targeted counseling interventions in evaluating HRQoL.