ORCID Profile
0000-0002-3547-5247
Current Organisations
National University of Colombia
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Círculo de Crédito
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Publisher: Springer Berlin Heidelberg
Date: 2011
Publisher: IEEE
Date: 05-2012
Publisher: Springer Berlin Heidelberg
Date: 2013
Publisher: Elsevier BV
Date: 11-2013
Publisher: Elsevier BV
Date: 06-2019
DOI: 10.1016/J.IJROBP.2019.01.088
Abstract: To apply a voxel-based analysis to identify urethrovesical symptom-related subregions (SRSs) associated with acute and late urinary toxicity in prostate cancer radiation therapy. Two hundred seventy-two patients with prostate cancer treated with intensity-modulated radiation therapy/image-guided radiation therapy were analyzed prospectively. Each patient's computed tomography imaging was spatially normalized to a common coordinate system via nonrigid registration. The obtained deformation fields were used to map the dose of each patient to the common coordinate system. A voxel-based statistical analysis was applied to generate 3-dimensional dose-volume maps for different urinary symptoms, allowing the identification of corresponding SRSs with statistically significant dose differences between patients with or without toxicity. Each SRS was propagated back to each in idual's native space, and dose-volume histograms (DVHs) for the SRSs and the whole bladder were computed. Logistic and Cox regression were used to estimate the SRS's prediction capability compared with the whole bladder. A local dose-effect relationship was found in the bladder and the urethra. SRSs were identified for 5 symptoms: acute incontinence in the urethra, acute retention in the bladder trigone, late retention and dysuria in the posterior part of the bladder, and late hematuria in the superior part of the bladder, with significant dose differences between patients with and without toxicity, ranging from 1.2 to 9.3 Gy. The doses to the SRSs were significantly predictive of toxicity, with maximum areas under the receiver operating characteristic curve of 0.73 for acute incontinence, 0.62 for acute retention, 0.70 for late retention, 0.81 for late dysuria, and 0.67 for late hematuria. The bladder DVH was predictive only for late retention, dysuria, and hematuria (area under the curve, 0.65-0.72). The dose delivered to the urethra and the posterior and superior parts of the bladder was predictive of acute incontinence and retention and of late retention, dysuria, and hematuria. The dose to the whole bladder was moderately predictive.
Publisher: IOP Publishing
Date: 26-03-2013
Publisher: Elsevier BV
Date: 02-2018
DOI: 10.1016/J.RADONC.2017.11.011
Abstract: To evaluate the benefit of independent component analysis (ICA)-based models for predicting rectal bleeding (RB) following prostate cancer radiotherapy. A total of 593 irradiated prostate cancer patients were prospectively analyzed for Grade ≥2 RB. ICA was used to extract two informative subspaces (presenting RB or not) from the rectal DVHs, enabling a set of new pICA parameters to be estimated. These DVH-based parameters, along with others from the principal component analysis (PCA) and functional PCA, were compared to "standard" features (patient/treatment characteristics and DVH bins) using the Cox proportional hazards model for RB prediction. The whole cohort was ided into: (i) training (N = 339) for ICA-based subspace identification and Cox regression model identification and (ii) validation (N = 254) for RB prediction capability evaluation using the C-index and the area under the receiving operating curve (AUC), by comparing predicted and observed toxicity probabilities. In the training cohort, multivariate Cox analysis retained pICA and PC as significant parameters of RB with 0.65 C-index. For the validation cohort, the C-index increased from 0.64 when pICA was not included in the Cox model to 0.78 when including pICA parameters. When pICA was not included, the AUC for 3-, 5-, and 8-year RB prediction were 0.68, 0.66, and 0.64, respectively. When included, the AUC increased to 0.83, 0.80, and 0.78, respectively. Among the many various extracted or calculated features, ICA parameters improved RB prediction following prostate cancer radiotherapy.
Publisher: Elsevier BV
Date: 05-2017
DOI: 10.1016/J.MEDIA.2017.03.001
Abstract: In radiotherapy for prostate cancer irradiation of neighboring organs at risk may lead to undesirable side-effects. Given this setting, the bladder presents the largest inter-fraction shape variations h ering the computation of the actual delivered dose vs. planned dose. This paper proposes a population model, based on longitudinal data, able to estimate the probability of bladder presence during treatment, using only the planning computed tomography (CT) scan as input information. As in previously-proposed principal component analysis (PCA) population-based models, we have used the data to obtain the dominant eigenmodes that describe bladder geometric variations between fractions. However, we have used a longitudinal analysis along each mode in order to properly characterize patient's variance from the total population variance. We have proposed is a mixed-effects (ME) model in order to separate intra- and inter-patient variability, in an effort to control confounding cohort effects. Other than using PCA, bladder shapes are represented by using spherical harmonics (SPHARM) that additionally enables data compression without information lost. Based on training data from repeated CT scans, the ME model was thus implemented following dimensionality reduction by means of SPHARM and PCA. We have evaluated the model in a leave-one-out cross validation framework on the training data but also using independent data. Probability maps (PMs) were thus generated with several draws from the learnt model as predicted regions where the bladder will likely move and deform. These PMs were compared with the actual regions using metrics based on mutual information distance and misestimated voxels. The prediction was also compared with two previous population PCA-based models. The proposed model was able to reduce the uncertainties in the estimation of the probable region of bladder motion and deformation. This model can thus be used for tailoring radiotherapy treatments.
Publisher: SPIE
Date: 19-11-2013
DOI: 10.1117/12.2035238
Publisher: Elsevier BV
Date: 09-2016
DOI: 10.1016/J.RADONC.2016.08.008
Abstract: To describe the evolution and to assess the predictive value of metabolic parameters with different SUV threshold segmentations calculated from two 18F-FDG-PET/CT, one prior to and the other one during concomitant chemoradiation therapy (CCRT), for locally-advanced cervical cancer (LACC). 53 patients treated for LACC by CCRT underwent FDG-PET/CT before treatment (PET1) and another one at 40Gy (PET2). The PET analyzed parameters were: maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG). MTVs were automatically segmented using various percentage SUVmax thresholds (30-70%) and fixed SUV thresholds (all voxels with SUV >1-20). The parameters' predictive capabilities for disease-free (DFS) and overall survival (OS) were assessed using the Harrell's C-index (c) and Cox regression model. Depending on the SUVmax threshold, the relative decreases in MTV and TLG from PET1 to PET2 were, on average, 65% (range: 63-70%) and 85% (range: 83-86%), respectively. The strongest predictive threshold segmentations were 55% SUVmax in PET1 and 32% in PET2. Significant predictors of DFS in multivariate analysis (c=0.82) were MTV1 (55% SUVmax) in PET1 and TLG2 (32% SUVmax) in PET2. MTV1 (55%) was the most significant OS predictor. MTV and TLG calculated with a threshold of 55% SUVmax and 32% SUVmax from pre- and per-treatment PET scans respectively, can be used to predict patient outcome after CCRT for LACC.
Publisher: Springer Science and Business Media LLC
Date: 29-08-2013
DOI: 10.1007/S00345-013-1146-8
Abstract: To analyze late urinary toxicity after prostate cancer radiotherapy (RT): symptom description and identification of patient characteristics or treatment parameters allowing for the generation of nomograms. Nine hundred and sixty-five patients underwent RT in seventeen French centers for localized prostate cancer. Median total dose was 70 Gy (range, 65-80 Gy), using different fractionations (2 or 2.5 Gy/day) and techniques. Late urinary toxicity and the corresponding symptoms (urinary frequency, incontinence, dysuria/decreased stream, and hematuria) were prospectively assessed in half of the patients using the LENT-SOMA classification. Univariate and multivariate Cox regression models addressed patient or treatment-related predictors of late urinary toxicity (≥grade 2). Nomograms were built up, and their performance was assessed. The median follow-up was 61 months. The 5-year (≥grade 2) global urinary toxicity, urinary frequency, hematuria, dysuria, and urinary incontinence rates were 15, 10, 5, 3 and 1 %, respectively. The 5-year (≥grade 3) urinary toxicity rate was 3 %. The following parameters significantly increased the 5-year risk of global urinary toxicity (≥grade 2): anticoagulant treatment (RR = 2.35), total dose (RR = 1.09), and age (RR = 1.06). Urinary frequency was increased by the total dose (RR = 1.07) and diabetes (RR = 4). Hematuria was increased by anticoagulant treatment (RR = 2.9). Dysuria was increased by the total dose (RR = 1.1). Corresponding nomograms and their calibration plots were generated. Nomogram performance should be validated with external data. The first nomograms to predict late urinary toxicity but also specific urinary symptoms after prostate RT were generated, contributing to prostate cancer treatment decision.
Publisher: Elsevier BV
Date: 11-2016
Publisher: Springer Berlin Heidelberg
Date: 2011
Publisher: Springer Berlin Heidelberg
Date: 2011
Publisher: Elsevier BV
Date: 2015
DOI: 10.1016/J.MEDENGPHY.2014.08.009
Abstract: External beam radiotherapy is commonly prescribed for prostate cancer. Although new radiation techniques allow high doses to be delivered to the target, the surrounding healthy organs (rectum and bladder) may suffer from irradiation, which might produce undesirable side-effects. Hence, the understanding of the complex toxicity dose-volume effect relationships is crucial to adapt the treatment, thereby decreasing the risk of toxicity. In this paper, we introduce a novel method to classify patients at risk of presenting rectal bleeding based on a Deterministic Multi-way Analysis (DMA) of three-dimensional planned dose distributions across a population. After a non-rigid spatial alignment of the anatomies applied to the dose distributions, the proposed method seeks for two bases of vectors representing bleeding and non bleeding patients by using the Canonical Polyadic (CP) decomposition of two fourth order arrays of the planned doses. A patient is then classified according to its distance to the subspaces spanned by both bases. A total of 99 patients treated for prostate cancer were used to analyze and test the performance of the proposed approach, named CP-DMA, in a leave-one-out cross validation scheme. Results were compared with supervised (linear discriminant analysis, support vector machine, K-means, K-nearest neighbor) and unsupervised (recent principal component analysis-based algorithm, and multidimensional classification method) approaches based on the registered dose distribution. Moreover, CP-DMA was also compared with the Normal Tissue Complication Probability (NTCP) model. The CP-DMA method allowed rectal bleeding patients to be classified with good specificity and sensitivity values, outperforming the classical approaches.
Publisher: Wiley
Date: 27-06-2016
DOI: 10.1002/JMRI.25335
Abstract: To explore the association between magnetic resonance imaging (MRI), including Haralick textural features, and biochemical recurrence following prostate cancer radiotherapy. In all, 74 patients with peripheral zone localized prostate adenocarcinoma underwent pretreatment 3.0T MRI before external beam radiotherapy. Median follow-up of 47 months revealed 11 patients with biochemical recurrence. Prostate tumors were segmented on T Three T T 3 J. Magn. Reson. Imaging 2017 :103-117.
Publisher: Elsevier BV
Date: 08-2014
DOI: 10.1016/J.IJROBP.2014.04.027
Abstract: To propose a random forest normal tissue complication probability (RF-NTCP) model to predict late rectal toxicity following prostate cancer radiation therapy, and to compare its performance to that of classic NTCP models. Clinical data and dose-volume histograms (DVH) were collected from 261 patients who received 3-dimensional conformal radiation therapy for prostate cancer with at least 5 years of follow-up. The series was split 1000 times into training and validation cohorts. A RF was trained to predict the risk of 5-year overall rectal toxicity and bleeding. Parameters of the Lyman-Kutcher-Burman (LKB) model were identified and a logistic regression model was fit. The performance of all the models was assessed by computing the area under the receiving operating characteristic curve (AUC). The 5-year grade ≥2 overall rectal toxicity and grade ≥1 and grade ≥2 rectal bleeding rates were 16%, 25%, and 10%, respectively. Predictive capabilities were obtained using the RF-NTCP model for all 3 toxicity endpoints, including both the training and validation cohorts. The age and use of anticoagulants were found to be predictors of rectal bleeding. The AUC for RF-NTCP ranged from 0.66 to 0.76, depending on the toxicity endpoint. The AUC values for the LKB-NTCP were statistically significantly inferior, ranging from 0.62 to 0.69. The RF-NTCP model may be a useful new tool in predicting late rectal toxicity, including variables other than DVH, and thus appears as a strong competitor to classic NTCP models.
Publisher: Elsevier BV
Date: 09-2011
Publisher: IEEE
Date: 08-2015
No related grants have been discovered for Juan David Ospina Arango.