J.D. Ospina

Impact of head and neck cancer adaptive radiotherapy to spare the parotid glands and decrease the risk of xerostomia

BackgroundLarge anatomical variations occur during the course of intensity-modulated radiation therapy (IMRT) for locally advanced head and neck cancer (LAHNC). The risks are therefore a parotid glands (PG) overdose and a xerostomia increase.The purposes of the study were to estimate:- the PG overdose and the xerostomia risk increase during a “standard” IMRT (IMRTstd);- the benefits of an adaptive IMRT (ART) with weekly replanning to spare the PGs and limit the risk of xerostomia.Material and methodsFifteen patients received radical IMRT (70 Gy) for LAHNC. Weekly CTs were used to estimate the dose distributions delivered during the treatment, corresponding either to the initial planning (IMRTstd) or to weekly replanning (ART). PGs dose were recalculated at the fraction, from the weekly CTs. PG cumulated doses were then estimated using deformable image registration. The following PG doses were compared: pre-treatment planned dose, per-treatment IMRTstd and ART. The corresponding estimated risks of xerostomia were also compared. Correlations between anatomical markers and dose differences were searched.ResultsCompared to the initial planning, a PG overdose was observed during IMRTstd for 59% of the PGs, with an average increase of 3.7 Gy (10.0 Gy maximum) for the mean dose, and of 8.2% (23.9% maximum) for the risk of xerostomia. Compared to the initial planning, weekly replanning reduced the PG mean dose for all the patients (p < 0.05). In the overirradiated PG group, weekly replanning reduced the mean dose by 5.1 Gy (12.2 Gy maximum) and the absolute risk of xerostomia by 11% (p < 0.01) (30% maximum). The PG overdose and the dosimetric benefit of replanning increased with the tumor shrinkage and the neck thickness reduction (p < 0.001).ConclusionDuring the course of LAHNC IMRT, around 60% of the PGs are overdosed of 4 Gy. Weekly replanning decreased the PG mean dose by 5 Gy, and therefore by 11% the xerostomia risk.

Voxel-based population analysis for correlating local dose and rectal toxicity in prostate cancer radiotherapy

The majority of current models utilized for predicting toxicity in prostate cancer radiotherapy are based on dose-volume histograms. One of their main drawbacks is the lack of spatial accuracy, since they consider the organs as a whole volume and thus ignore the heterogeneous intra-organ radio-sensitivity. In this paper, we propose a dose-image-based framework to reveal the relationships between local dose and toxicity. In this approach, the three-dimensional (3D) planned dose distributions across a population are non-rigidly registered into a common coordinate system and compared at a voxel level, therefore enabling the identification of 3D anatomical patterns, which may be responsible for toxicity, at least to some extent. Additionally, different metrics were employed in order to assess the quality of the dose mapping. The value of this approach was demonstrated by prospectively analyzing rectal bleeding (≥Grade 1 at 2 years) according to the CTCAE v3.0 classification in a series of 105 patients receiving 80 Gy to the prostate by intensity modulated radiation therapy (IMRT). Within the patients presenting bleeding, a significant dose excess (6 Gy on average, p < 0.01) was found in a region of the anterior rectal wall. This region, close to the prostate (1 cm), represented less than 10% of the rectum. This promising voxel-wise approach allowed subregions to be defined within the organ that may be involved in toxicity and, as such, must be considered during the inverse IMRT planning step.

Random Forests to Predict Rectal Toxicity Following Prostate Cancer Radiation Therapy

PURPOSE 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. METHODS AND MATERIALS 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). RESULTS 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. CONCLUSIONS 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.

Haralick textural features on T2 -weighted MRI are associated with biochemical recurrence following radiotherapy for peripheral zone prostate cancer.

To explore the association between magnetic resonance imaging (MRI), including Haralick textural features, and biochemical recurrence following prostate cancer radiotherapy.

Spatial characterization and classification of rectal bleeding in prostate cancer radiotherapy with a voxel-based principal components analysis model for 3D dose distribution

Although external beam radiotherapy is one of the most commonly prescribed treatments for prostate cancer, severe complications may arise as a result of high delivered doses to the neighboring organs at risk, namely the bladder and the rectum. The prediction of this toxicity events are commonly based on the planned dose distribution using the dose-volume histograms within predictive models. However, as different spatial dose distributions may produce similar dose-volume histograms, these models may not be accurate in revealing the subtleties of the dose-effect relationships. Using the prescribed dose, we propose a voxel-based principal component analysis method for characterizing and classifying those individuals at risk of rectal bleeding. Sixty-five cases of patients treated for prostate cancer were reviewed; fifteen of them presented rectal bleeding within two years after the treatment. The method was able to classify rectal bleeding with 0.8 specificity and 0.73 sensitivity. In addition, eigenimages with the most discriminant features suggest that some specific dose patterns are related to rectal bleeding.

A Nomogram to predict parotid gland overdose in head and neck IMRT

PurposesTo generate a nomogram to predict parotid gland (PG) overdose and to quantify the dosimetric benefit of weekly replanning based on its findings, in the context of intensity-modulated radiotherapy (IMRT) for locally-advanced head and neck carcinoma (LAHNC).Material and methodsTwenty LAHNC patients treated with radical IMRT underwent weekly computed tomography (CT) scans during IMRT. The cumulated PG dose was estimated by elastic registration. Early predictors of PG overdose (cumulated minus planned doses) were identified, enabling a nomogram to be generated from a linear regression model. Its performance was evaluated using a leave-one-out method. The benefit of weekly replanning was then estimated for the nomogram-identified PG overdose patients.ResultsClinical target volume 70 (CTV70) and the mean PG dose calculated from the planning and first weekly CTs were early predictors of PG overdose, enabling a nomogram to be generated. A mean PG overdose of 2.5Gy was calculated for 16 patients, 14 identified by the nomogram. All patients with PG overdoses >1.5Gy were identified. Compared to the cumulated delivered dose, weekly replanning of these 14 targeted patients enabled a 3.3Gy decrease in the mean PG dose.ConclusionBased on the planning and first week CTs, our nomogram allowed the identification of all patients with PG overdoses >2.5Gy to be identified, who then benefitted from a final 4Gy decrease in mean PG overdose by means of weekly replanning.

Spatial nonparametric mixed-effects model with spatial-varying coefficients for analysis of population

Voxel-wise comparisons have been largely used in the analysis of populations to identify biomarkers for pathologies, disease progression, or to predict a treatment outcome. On the basis of a good interindividual spatial alignment, 3D maps are produced, allowing to localise regions where significant differences between groups exist. However, these techniques have received some criticism as they rely on conditions wich are not always met. Firstly, the results may be affected by misregistrations; secondly, the statistics behind the models assumes normally distributed data; finally, because of the size of the images, some strategies must be used to control for the rate of false detection. In this paper, we propose a spatial (3D) nonparametric mixed-effects model for population analysis. It overcomes some of the issues of classical voxel-based approaches, namely robustness to false positive rates, misregistrations and large variances between groups. Examples on numerical phantoms and real clinical data illustrate the feasiblity of the approach. An example of application within the development of voxel-wise predictive models of rectal toxicity in prostate cancer radiotherapy is presented. Results demonstrate an improved sensitivity and reliability for group analysis compared with standard voxel-wise methods and open the way for potential applications in computational anatomy.

Dose monitoring in prostate cancer radiotherapy using CBCT to CT constrained elastic image registration

The recent concept of Dose Guided Radiotherapy (DGRT) consists in computing a cumulative dose distribution at each treatment fraction to decide if a treatment replanning is necessary. These cumulative dose distributions are obtained by mapping the daily dose distributions with the results of a non-rigid registration between the planning CT scan and daily CBCT images. But, mainly because of large deformations and of the scatter effect of CBCT, the application of this methodology to prostate cancer radiotherapy is very challenging. In this paper, we adapt a nonparametric non-rigid registration algorithm based on Mutual Information to register the daily CBCT scan to the planning CT scan in the context of prostate cancer DGRT. In order to improve registration accuracy, we then propose a modification of the registration framework to introduce landmark constraints. We show that this constrained non-rigid registration algorithm was able to significantly increase the accuracy of the cumulative dose estimation.

Nomogram to predict rectal toxicity following prostate cancer radiotherapy

Background To identify predictors of acute and late rectal toxicity following prostate cancer radiotherapy (RT), while integrating the potential impact of RT technique, dose escalation, and moderate hypofractionation, thus enabling us to generate a nomogram for individual prediction. Methods In total, 972 patients underwent RT for localized prostate cancer, to a total dose of 70 Gy or 80 Gy, using two different fractionations (2 Gy or 2.5 Gy/day), by means of several RT techniques (3D conformal RT [3DCRT], intensity-modulated RT [IMRT], or image-guided RT [IGRT]). Multivariate analyses were performed to identify predictors of acute and late rectal toxicity. A nomogram was generated based on the logistic regression model used to predict the 3-year rectal toxicity risk, with its accuracy assessed by dividing the cohort into training and validation subgroups. Results Mean follow-up for the entire cohort was 62 months, ranging from 6 to 235. The rate of acute Grade ≥2 rectal toxicity was 22.2%, decreasing when combining IMRT and IGRT, compared to 3DCRT (RR = 0.4, 95%CI: 0.3–0.6, p<0.01). The 5-year Grade ≥2 risks for rectal bleeding, urgency/tenesmus, diarrhea, and fecal incontinence were 9.9%, 4.5%, 2.8%, and 0.4%, respectively. The 3-year Grade ≥2 risk for overall rectal toxicity increased with total dose (p<0.01, RR = 1.1, 95%CI: 1.0–1.1) and dose per fraction (2Gy vs. 2.5Gy) (p = 0.03, RR = 3.3, 95%CI: 1.1–10.0), and decreased when combining IMRT and IGRT (RR = 0.50, 95% CI: 0.3–0.8, p<0.01). Based on these three parameters, a nomogram was generated. Conclusions Dose escalation and moderate hypofractionation increase late rectal toxicity. IMRT combined with IGRT markedly decreases acute and late rectal toxicity. Performing combined IMRT and IGRT can thus be envisaged for dose escalation and moderate hypofractionation. Our nomogram predicts the 3-year rectal toxicity risk by integrating total dose, fraction dose, and RT technique.

A tensor-based population value decomposition to explain rectal toxicity after prostate cancer radiotherapy.

In prostate cancer radiotherapy the association between the dose distribution and the occurrence of undesirable side-effects is yet to be revealed. In this work a method to perform population analysis by comparing the dose distributions is proposed. The method is a tensor-based approach that generalises an existing method for 2D images and allows for the highlighting of over irradiated zones correlated with rectal bleeding after prostate cancer radiotherapy. Thus, the aim is to contribute to the elucidation of the dose patterns correlated with rectal toxicity. The method was applied to a cohort of 63 patients and it was able to build up a dose pattern characterizing the difference between patients presenting rectal bleeding after prostate cancer radiotherapy and those who did not.