Stomach and duodenum dose-volume constraints for locally advanced pancreatic cancer patients treated in 15 fractions in combination with chemotherapy.

Purpose: To assess dosimetry predictors of gastric and duodenal toxicities for locally advanced pancreatic cancer (LAPC) patients treated with chemo-radiotherapy in 15 fractions. Methods: Data from 204 LAPC patients treated with induction+concurrent chemotherapy and radiotherapy (44.25 Gy in 15 fractions) were available. Forty-three patients received a simultaneous integrated boost of 48-58 Gy. Gastric/duodenal Common Terminology Criteria for Adverse Events v. 5 (CTCAEv5) Grade ≥2 toxicities were analyzed. Absolute/% duodenal and stomach dose-volume histograms (DVHs) of patients with/without toxicities were compared: the most predictive DVH points were identified, and their association with toxicity was tested in univariate and multivariate logistic regressions together with near-maximum dose (D0.03) and selected clinical variables. Results: Toxicity occurred in 18 patients: 3 duodenal (ulcer and duodenitis) and 10 gastric (ulcer and stomatitis); 5/18 experienced both. At univariate analysis, V44cc (duodenum: p = 0.02, OR = 1.07; stomach: p = 0.01, OR = 1.12) and D0.03 (p = 0.07, OR = 1.19; p = 0.008, OR = 1.12) were found to be the most predictive parameters. Stomach/duodenum V44Gy and stomach D0.03 were confirmed at multivariate analysis and found to be sufficiently robust at internal, bootstrap-based validation; the results regarding duodenum D0.03 were less robust. No clinical variables or %DVH was significantly associated with toxicity. The best duodenum cutoff values were V44Gy < 9.1 cc (and D0.03 < 47.6 Gy); concerning the stomach, they were V44Gy < 2 cc and D0.03 < 45 Gy. The identified predictors showed a high negative predictive value (>94%). Conclusion: In a large cohort treated with hypofractionated radiotherapy for LAPC, the risk of duodenal/gastric toxicities was associated with duodenum/stomach DVH. Constraining duodenum V44Gy < 9.1 cc, stomach V44Gy < 2 cc, and stomach D0.03 < 45 Gy should keep the toxicity rate at approximately or below 5%. The association with duodenum D0.03 was not sufficiently robust due to the limited number of events, although results suggest that a limit of 45-46 Gy should be safe.

Clinical Implementation of Knowledge-Based Automatic Plan Optimization for Helical Tomotherapy.

PURPOSE: To implement knowledge-based (KB) automatic planning for helical TomoTherapy (HTT). The focus of the first clinical implementation was the case of high-risk prostate cancer, including pelvic node irradiation. METHODS AND MATERIALS: One hundred two HTT clinical plans were selected to train a KB model using the RapidPlan tool incorporated in the Eclipse system (v13.6, Varian Inc). The individually optimized KB-based templates were converted into HTT-like templates and sent automatically to the HTT treatment planning system through scripting. The full dose calculation was set after 300 iterations without any additional planner intervention. Internal (20 patients in the training cohort) and external (28 new patients) validation were performed to assess the performance of the model: Automatic HTT plans (KB-TP) were compared against the original plans (TP) in terms of organs at risk and planning target volume (PTV) dose-volume parameters and by blinded clinical evaluation of 3 expert clinicians. RESULTS: KB-TP plans were generally better than or equivalent to TP plans in both validation cohorts. A significant improvement in PTVs and rectum-PTV overlap dosimetry parameters were observed for both sets. Organ-at-risk sparing for KB-TP was slightly improved, which was more evident in the external validation group and for bladder and bowel. Clinical evaluation reported KB-TP to be better in 60% of cases and worse in 10% compared with TP (P < .05). CONCLUSIONS: The fully KB-based automatic planning workflow was successfully implemented for HTT planning optimization in the case of high-risk patients with prostate cancer.

Impact of sentinel lymph-node biopsy and FDG-PET in staging and radiation treatment of anal cancer patients.

To assess the role of sentinel lymph-node biopsy (SLNB) and FDG-PET in staging and radiation treatment (RT) of anal cancer patients. This retrospective study was performed on 80 patients (male: 32, female: 48) with a median age of 60 years (39-89 years) with anal squamous cell carcinoma who were treated from March 2008 to March 2018 at the IRCCS San Raffaele Hospital. Patients without clinical evidence of inguinal LNs metastases and/or with discordance between clinical evidence and imaging features were considered for SLNB. FDG-PET was performed in 69/80 patients. Patients with negative imaging in inguinal region and negative SLNB could avoid RT on groin to spare inguinal toxicity. CTV included GTV (primary tumour and positive LNs) and pelvic ± inguinal LNs. PTV1 and PTV2 corresponded to GTV and CTV, respectively, adding 0.5 cm. RT dose was 50.4 Gy/28 fractions to PTV2 and 64.8 Gy/36 fractions to PTV1, delivered with 3DCRT (n = 24) or IMRT (n = 56), concomitant to Mitomycin-C and 5-FU chemotherapy. FDG-PET showed inguinal uptake in 21/69 patients (30%) and was negative in 48/69 patients (70%). Lymphoscintigraphy was performed in 11/21 positive patients (4 patients SLNB confirmed inguinal metastases, 6 patients false positive and 1 patient SLN not found), and in 29/48 negative patients (5/29 showed metastases, 23/29 true negative and 1 SLN not found). Sensitivity, specificity, positive and negative predictive value of FDG-PET were 62%, 79%, 40% and 82%, respectively. Median follow-up time from diagnosis was 40.3 months (range: 4.6-136.4 months): 69 patients (86%) showed a complete response, 10 patients (13%) a partial response, 1 patient (1%) a stable disease. Patients treated on groin (n = 54) versus not treated (n = 26) showed more inguinal dermatitis (G1-G2: 50% vs. 12%; G3-G4: 17% vs. 0%, p < 0.05). For patients treated on groin, G3-G4 inguinal dermatitis, stomatitis and neutropenia were significantly reduced with IMRT against 3DCRT techniques (13% vs. 36%, p = 0.10; 3% vs. 36%, p = 0.003; 8% vs. 29%, p = 0.02, respectively). SLNB improves the FDG-PET inguinal LNs staging in guiding the decision to treat inguinal nodes. IMRT technique significantly reduced G3-G4 toxicities when patients are treated on groin.

Robustness of CT radiomic features against image discretization and interpolation in characterizing pancreatic neuroendocrine neoplasms.

PURPOSE: To explore the variation of the discriminative power of CT radiomic features (RF) against image discretization/interpolation in characterizing pancreatic neuro-endocrine (PanNEN) neoplasms. MATERIALS AND METHODS: Thirty-nine PanNEN patients with pre-surgical high contrast CT available were considered. Image interpolation and discretization parameters were intentionally changed, including pixel size (0.73-2.19 mm2), slice thickness (2-5 mm) and binning (32-128 grey levels) and their combination generated 27 parameter's set. The ability of 69 RF in discriminating post-surgically assessed tumor grade (>G1), positive nodes, metastases and vascular invasion was tested: AUC changes when changing the parameters were quantified for selected RF, significantly associated to each end-point. The analysis was repeated for the corresponding images with contrast medium and in a sub-group of 29/39 patients scanned on a single scanner. RESULTS: The median tumor volume was 1.57 cm3 (16%-84% percentiles: 0.62-34.58 cm3). RF variability against discretization/interpolation parameters was large: only 21/69 RF showed %COV < 20%. Despite this variability, AUC changes were limited for all end-points: with typical AUC values around 0.75-0.85, AUC ranges for the 27 parameter's set were on average 0.062 (1SD:0.037) for all end-points with maximum %COV equal to 5.5% (mean:2.3%). Performances significantly improved when excluding the 5 mm thickness case and fixing the binning to 64 (mean AUC range: 0.036, 1SD:0.019). Using contrast images or limiting the population to single-scanner patients had limited impact on AUC variability. CONCLUSIONS: The discriminative power of CT RF for panNEN is relatively invariant against image interpolation/discretization within a large range of voxel sizes and binning.

Monitoring skin dose changes during image-guided helical tomotherapy for head and neck cancer patients.

PURPOSE: An increase of skin dose during head and neck cancer (HNC) radiotherapy is potentially dangerous. Aim of this study was to quantify skin dose variation and to assess the need of planning adaptation (ART) to counteract it. METHODS: Planning CTs of 32 patients treated with helical tomotherapy (HT) according to a Simultaneous Integrated Boost (SIB) technique delivering 54/66 Gy in 30 fractions were deformably co-registered to MVCTs taken at fractions 15 and 30; in addition, the first fraction was also considered. The delivered dose-of-the-day was calculated on the corresponding deformed images. Superficial body layers (SL) were considered as a surrogate for skin, considering a layer thickness of 2 mm. Variations of SL DVH (∆SL) during therapy were quantified, focusing on ∆SL95% (i.e., 62.7 Gy). RESULTS: Small changes (within ± 1 cc for ∆SL95%) were seen in 15/32 patients. Only 2 patients experienced ∆SL95% > 1 cc in at least one of the two monitored fractions. Negative ∆SL95% > 1 cc (up to 17 cc) were much more common (15/32 patients). The trend of skin dose changes was mostly detected at the first fraction. Negative changes were correlated with the presence of any overlap between PTV and SL at planning and were explained in terms of how the planning system optimizes the PTV dose coverage near the skin. Acute toxicity was associated with planning DVH and this association was not improved if considering DVHs referring to fractions 15/30. CONCLUSION: About half of the patients treated with SIB with HT for HNC experienced a skin-sparing effect during therapy; only 6% experienced an increase. Our findings do not support skin-sparing ART, while suggesting the introduction of improved skin-sparing planning techniques.

Quantifying the robustness of [18F]FDG-PET/CT radiomic features with respect to tumor delineation in head and neck and pancreatic cancer patients.

PURPOSE: To investigate the robustness of PET radiomic features (RF) against tumour delineation uncertainty in two clinically relevant situations. METHODS: Twenty-five head-and-neck (HN) and 25 pancreatic cancer patients previously treated with 18F-Fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT)-based planning optimization were considered. Seven FDG-based contours were delineated for tumour (T) and positive lymph nodes (N, for HN patients only) following manual (2 observers), semi-automatic (based on SUV maximum gradient: PET_Edge) and automatic (40%, 50%, 60%, 70% SUV_max thresholds) methods. Seventy-three RF (14 of first order and 59 of higher order) were extracted using the CGITA software (v.1.4). The impact of delineation on volume agreement and RF was assessed by DICE and Intra-class Correlation Coefficients (ICC). RESULTS: A large disagreement between manual and SUV_max method was found for thresholds  ≥50%. Inter-observer variability showed median DICE values between 0.81 (HN-T) and 0.73 (pancreas). Volumes defined by PET_Edge were better consistent with the manual ones compared to SUV40%. Regarding RF, 19%/19%/47% of the features showed ICC < 0.80 between observers for HN-N/HN-T/pancreas, mostly in the Voxel-alignment matrix and in the intensity-size zone matrix families. RFs with ICC < 0.80 against manual delineation (taking the worst value) increased to 44%/36%/61% for PET_Edge and to 69%/53%/75% for SUV40%. CONCLUSIONS: About 80%/50% of 72 RF were consistent between observers for HN/pancreas patients. PET_edge was sufficiently robust against manual delineation while SUV40% showed a worse performance. This result suggests the possibility to replace manual with semi-automatic delineation of HN and pancreas tumours in studies including PET radiomic analyses.

Skin dose calculation during radiotherapy of head and neck cancer using deformable image registration of planning and mega-voltage computed tomography scans.

BACKGROUND AND PURPOSE: Head-Neck (HN) patients may experience severe acute skin complications that can cause treatment interruption and increase the risk of late fibrosis. This study assessed a method for accurately monitoring skin dose changes during helical tomotherapy for HN cancer based on deformable image registration of planning computed tomography (CT) and mega-voltage CT (MVCT). MATERIALS AND METHODS: Planning CTs of nine patients were deformably registered to mid-treatment MVCT (MV15) images resulting in CTdef images. The original plans were recalculated on both CTdef and mid-treatment kilo-voltage CT (CT15) taken as ground truth. Superficial layers (SL) of the body with thicknesses of 2, 3 and 5 mm (SL2, SL3, SL5) were considered as derma surrogates. SL V95%, V97%, V98%, V100%, V102%, V105% and V107% of the prescribed PTV dose were extracted for CT15/CTdef and compared (considering patients with skin dose > 95%). For comparison, doses were calculated directly on the calibrated MVCT and analyzed in the same way. RESULTS: Differences between SL2/SL3/SL5 V95%-V107% in CT15/CTdef were very small: for eight of nine patients the difference between the considered SL2 Vd% computed on CTdef and CT15 was less than 1.4 cm3 for all d%. A larger value was found when using MVCT for skin dose calculation (4.8 cm3 for SL2), although CTdef body contour matched CT15 body with accuracy similar to that of MV15. CONCLUSIONS: Deforming the planning CT-to-MVCT was shown to be accurate considering external body contours and skin DVHs. The method was able to accurately identify superficial overdosing.

Early prediction of radiotherapy-induced parotid shrinkage and toxicity based on CT radiomics and fuzzy classification.

MOTIVATION: Patients under radiotherapy for head-and-neck cancer often suffer of long-term xerostomia, and/or consistent shrinkage of parotid glands. In order to avoid these drawbacks, adaptive therapy can be planned for patients at risk, if the prediction is obtained timely, before or during the early phase of treatment. Artificial intelligence can address the problem, by learning from examples and building classification models. In particular, fuzzy logic has shown its suitability for medical applications, in order to manage uncertain data, and to build transparent rule-based classifiers. In previous works, clinical, dosimetric and image-based features were considered separately, to find different possible predictors of parotid shrinkage. On the other hand, a few works reported possible image-based predictors of xerostomia, while the combination of different types of features has been little addressed. OBJECTIVE: This paper proposes the application of a novel machine learning approach, based on both statistics and fuzzy logic, aimed at the classification of patients at risk of i) parotid gland shrinkage and ii) 12-months xerostomia. Both problems are addressed with the aim of individuating predictors and models to classify respective outcomes. METHODS: Knowledge is extracted from a real dataset of radiotherapy patients, by means of a recently developed method named Likelihood-Fuzzy Analysis, based on the representation of statistical information by fuzzy rule-based models. This method enables to manage heterogeneous variables and missing data, and to obtain interpretable fuzzy models presenting good generalization power (thus high performance), and to measure classification confidence. Numerous features are extracted to characterize patients, coming from different sources, i.e. clinical features, dosimetric parameters, and radiomics-based measures obtained by texture analysis of Computed Tomography images. A learning approach based on the composition of simple models in a more complicated one allows to consider the features separately, in order to identify predictors and models to use when only some data source is available, and obtaining more accurate results when more information can be combined. RESULTS: Regarding parotid shrinkage, a number of good predictors is detected, some already known and confirmed here, and some others found here, in particular among radiomics-based features. A number of models are also designed, some using single features and others involving models composition to improve classification accuracy. In particular, the best model to be used at the initial treatment stage, and another one applicable at the half treatment stage are identified. Regarding 12-months toxicity, some possible predictors are detected, in particular among radiomics-based features. Moreover, the relation between final parotid shrinkage rate and 12-months xerostomia is evaluated. The method is compared to the naïve Bayes classifier, which reveals similar results in terms of classification accuracy and best predictors. The interpretable fuzzy rule-based models are explicitly presented, and the dependence between predictors and outcome is explained, thus furnishing in some cases helpful insights about the considered problems. CONCLUSION: Thanks to the performance and interpretability of the fuzzy classification method employed, predictors of both parotid shrinkage and xerostomia are detected, and their influence on each outcome is revealed. Moreover, models for predicting parotid shrinkage at initial and half radiotherapy stages are found.

Geometrical and dosimetrical uncertainties in hypofractionated radiotherapy of the lung: A review.

The application of high precision hypofractionated regimes (a.k.a. stereotactic body radiotherapy (SBRT)) to the treatment of lung cancer is a 'success story' of radiotherapy. From the technical perspective, lung SBRT is a challenging technique as all aspects of the treatment workflow, from imaging to dose calculation to treatment delivery, should be carefully handled in order to ensure consistency between planned and delivered dose. In this review such technical aspects are presented and discussed, looking at what has been developed over the years. The use of imaging techniques such as slow-CT, breath-hold CT, four-dimensional CT and mid-ventilation is reviewed, presenting the main characteristics of each approach but not necessarily to single out 'the best' solution. Concerning dose calculation, a number of studies clearly separate dose algorithms that should be considered inadequate for lung SBRT (e.g. simple pencil beam algorithms) from approaches such as convolution algorithms, Monte Carlo, and solution of the transport equation, that are much better at handling the combination of small fields and heterogenenous geometries that make dose calculation not trivial. Patient positioning and management of intrafraction motion have been two areas of significant developments, to the point where it is difficult to identify which solution represents the best compromise between technical complexity and clinical effectiveness. The review analyses several of these methods, outlining the residual uncertainties associated with each of them. Last but not least, two subjects are discussed, adaptive therapy and particle therapy, that may represent in the near future additional tools for the technical improvement of lung SBRT.

Early volume variation of positive lymph nodes assessed by in-room mega voltage CT images predicts risk of loco-regional relapses in head and neck cancer patients treated with intensity-modulated radiotherapy.

BACKGROUND: We investigated the possibility to early identify non-responding patients based on FDG-PET positive lymph nodes (PNs) volume variation assessed with in-room images. MATERIAL AND METHODS: Twenty-seven head and neck cancer patients with at least one pre-treatment PNs were retrospectively analyzed; they received 54 Gy, 66 Gy, 69 Gy in 30 fractions on precautionary lymph nodal (N), primary (T) and PET positive (BTV) planning target volumes (PTVs), respectively with Helical TomoTherapy (SIB approach). PNs volume changes during treatment were assessed based on megavoltage computed tomography (MVCT) used for image guidance as ratio between volumes at fractions 10/20/30 and at first fraction. Data on T, N and M relapses (rT, rN, rM) were collected for all patients. The difference of PNs volume changes, during treatment, between patients with versus without relapses was tested (Mann-Whitney test). The impact of shrinkage on the corresponding survival curves (Cox proportional-hazard regression), dividing between no/moderate versus large shrinkage (based on ROC curve best cut-off value) was also investigated. RESULTS: Median follow-up was 27.4 m (3.7-108.9). The numbers for rT, rN, rM were 5, 4, 6, respectively. Differences in PNs shrinkage were found between patients with and without rT/rN at all considered timing [fr 20, rT: 0.56 vs. 1.07 (median), p = 0.06; rN: 0.57 vs. 1.25, p = 0.07]. Differences were lower for rM. Survival curves provide high hazard ratios (HR) between PNs changes and rT/rN at all considered timing [fr 20, rT: best cut-off = 0.58, HR 5.1 (95% CI 0.5-49.4), p = 0.12; rN: best cut-off = 0.98, HR 14.9 (1.6-142.9), p = 0.01]. CONCLUSION: A limited shrinkage of PNs during treatment is associated with poorer outcome in terms of T/N relapses. The early variation of PNs observed on in-room images may provide useful information about the individual response with potential application in guiding an early adaptation of the treatment.

Characterization of volume and shape modifications of PET-positive nodes during Tomotherapy for head and neck cancer as assessed by MVCTs.

PURPOSE: Characterizing the changes of PET-positive lymphnodes (PNs) of head-neck cancer patients during image-guided Tomotherapy in order to verify if our clinical margin for PTV(boost) are adequate. MATERIAL AND METHODS: Weekly MVCTs of 30 patients were matched with the planning kVCT (kVCT_pl) on bony anatomy: 42 visible PNs were contoured on kVCT_pl/MVCTs. Intra/inter-observer and inter-modality variability in contouring PNs was evaluated by blind re-delineation. Shrinkage of PNs and center-of-mass (CM) shifts were measured and Van Herk margins for the residual error were estimated. In addition, due to the PNs' shrinkage during therapy, probability coverage maps were considered to estimate the fraction of the high probability contours missed by the clinical PTV (5 mm margin); larger margins were tried for PNs showing some missing. RESULTS: MVCTs were adequate for PNs' delineation (DICE=0.85; range=0.79-0.91). Twenty-seven PNs showed a significant volume shrinkage at the end of therapy (median: 71%, range: 27-94%, ρ=-0.93). Time-trend of 3D-CM shift was significant for 38% of PNs (median: 5.1 mm at the end of treatment, range: 1.0-8.9). The clinical PTV included 95% of the 90%/100% probability contours in 40/36 (95%/86%) PNs respectively. Van Herk margins (not considering shrinkage) were approximately 7 mm for all three main axes. The clinical PTV included 95% of the 90%/100% probability contours in 40/36 (95%/86%) PNs respectively. CONCLUSIONS: The residual error relative to PNs after bone match is relatively small; the impact of CM shifts is partially counterbalanced by shrinkage. Our results do not seem to support an extensive use of adaptive re-planning to avoid the missing of PNs in dose-escalated protocols, although more information about the dosimetry impact of the reported changes is warranted.

Accuracy of dose calculation algorithms for static and rotational IMRT of lung cancer: A phantom study.

PURPOSE: To evaluate the dosimetric accuracy of Pencil beam (PB), Anisotropic Analytical Algorithm (AAA) and Collapsed Cone Convolution Superposition (CCCS) in thoracic tumours for various IMRT techniques. METHODS: Step-and-shoot Linac IMRT (IMRT), arc volumetric RapidArc (RA) and Helical Tomotherapy (HT) lung treatments for different clinical situations (mediastinum tumour, single metastasis and multiple metastases) were simulated and calculated with PB/AAA, AAA, CCCS, respectively. Delivery quality assurance plans were first verified in homogeneous media (Cheese phantom and ArcCHECK); then several low-density inhomogeneous phantoms were used: the Multiplug ArcCHECK, the commercial ArcCHECK slightly modified with a low density lung-shape insert and a custom-made slab heterogeneous phantom simulating the thorax region. Absolute doses and planar dose maps were checked to assess the agreement between measured and calculated dose distributions. RESULTS: In total, data referred to 195 point dose measurements and 189 planar measurements were considered. Average point absolute deviations <3% were found for all the delivery techniques/dose algorithms. In small targets completely embedded in very low density media, deviations up to 7-10% and 4-5% were found for PB and AAA/CCCS respectively. Excellent results were found for planar measurements in ArcCHECK configurations, where ≥ 95% of points satisfy the 3%/3 mm acceptance criteria for all the algorithms. CONCLUSIONS: A satisfactory agreement (<2%) between planned and measured doses was generally found for CCCS and AAA, excepting the very critical situation of a small tumour completely embedded in air. A significant dose overestimation (from few to 5-7%) was confirmed for PB in complex inhomogeneous arrangements.

Assessment and clinical validation of margins for adaptive simultaneous integrated boost in neo-adjuvant radiochemotherapy for rectal cancer.

PURPOSE: An adaptive concomitant boost (ACB) for the neo-adjuvant treatment of rectal cancer was clinically implemented. In this study population margins M(90,90) considering rectal deformation were derived for 10 consecutive patients treated at 18 × 2.3Gy with Helical Tomotherapy (HT) and prospectively validated on 20 additional patients treated with HT, delivering ACB in the last 6 fractions. METHODS: Sectorial margins M(90,90) of the whole and second treatment parts were assessed for 90% population through a method combining the 90% coverage probability maps of rectal positions (CPC90%) with 3D local distance measurements between the CPC90% and a reference rectal contour. M(90,90) were compared with the margins M(90,90)(95%/99%), ensuring CPC90% coverage with 95%/99% confidence level. M(90,90) of the treatment second part were chosen as ACB margins which were clinically validated for each patient by means of %volume missing of CPC5/6 excluded by the ACB margins. RESULTS: The whole treatment M(90,90) ranged between 1.9 mm and 9 mm in the lower-posterior and upper-anterior sectors, respectively. Regarding ACB, M(90,90) were 7 mm in the anterior direction and <5 mm elsewhere. M(90,90)(95%/99%) did not significantly differ from M(90,90). The %volume excluded by the ACB margin was<2% for all male and <5% for 9/10 female patients. The dosimetry impact on R_adapt for the patients with the largest residual error was negligible. CONCLUSIONS: Local deformation measurements confirm an anisotropic motion of rectum once set-up error is rigidly corrected. Margins of 7 mm anterior and 5 mm elsewhere are adequate for ACB. Female patients show a slightly larger residual error.

Analysis of serial CT images for studying the RT effects in head-neck cancer patients.

Images taken during and after RT for head and neck cancer have the potential to quantitatively assess xerostomia. Image information may be used as biomarkers of RT effects on parotid glands with significant potential to support adaptive treatment strategies. We investigated the possibility to extract information based on in-room CT images (kVCT, MVCT), acquired for daily image-guided radiotherapy treatment of head-and-neck cancer patients, in order to predict individual response in terms of toxicity. Follow-up MRI images were also used in order to investigate long term parotid gland deformation.

Modelling the impact of fractionation on late urinary toxicity after postprostatectomy radiation therapy.

PURPOSE: To fit urinary toxicity data of patients treated with postprostatectomy radiation therapy with the linear quadratic (LQ) model with/without introducing a time factor. METHODS AND MATERIALS: Between 1993 and 2010, 1176 patients were treated with conventional fractionation (1.8 Gy per fraction, median 70.2 Gy, n=929) or hypofractionation (2.35-2.90 Gy per fraction, n=247). Data referred to 2004-2010 (when all schemes were in use, n=563; conventional fractionation: 316; hypofractionation: 247) were fitted as a logit function of biological equivalent dose (BED), according to the LQ model with/without including a time factor γ (fixing α/ß = 5 Gy). The 3-year risks of severe urethral stenosis, incontinence, and hematuria were considered as endpoints. Best-fit parameters were derived, and the resulting BEDs were taken in multivariable backward logistic models, including relevant clinical variables, considering the whole population. RESULTS: The 3-year incidences of severe stenosis, incontinence, and hematuria were, respectively, 6.6%, 4.8%, and 3.3% in the group treated in 2004-2010. The best-fitted α/ß values were 0.81 Gy and 0.74 Gy for incontinence and hematuria, respectively, with the classic LQ formula. When fixing α/ß = 5 Gy, best-fit values for γ were, respectively, 0.66 Gy/d and 0.85 Gy/d. Sensitivity analyses showed reasonable values for γ (0.6-1.0 Gy/d), with comparable goodness of fit for α/ß values between 3.5 and 6.5 Gy. Likelihood ratio tests showed that the fits with/without including γ were equivalent. The resulting multivariable backward logistic models in the whole population included BED, pT4, and use of antihypertensives (area under the curve [AUC] = 0.72) for incontinence and BED, pT4, and year of surgery (AUC = 0.80) for hematuria. Stenosis data could not be fitted: a 4-variable model including only clinical factors (acute urinary toxicity, pT4, year of surgery, and use of antihypertensives) was suggested (AUC = 0.73). CONCLUSIONS: The unexpected impact of moderate hypofractionation on severe incontinence and hematuria after postprostatectomy radiation therapy may be explained by a bladder α/ß value <1 Gy or, radiobiologically more plausible, by introducing a time factor likely to represent a previously hypothesized consequential component of late effect.

Likelihood-fuzzy analysis of parotid gland shrinkage in radiotherapy patients.

In head-and-neck radiotherapy, an early detection of patients who will undergo parotid glands shrinkage during the treatment is of primary importance, since this condition has been found to be associated with acute toxicity. In this work, a recently proposed approach, here named Likelihood-Fuzzy Analysis, based on both statistical learning and Fuzzy Logic, is proposed to support the identification of early predictors of parotid shrinkage from Computed Tomography images acquired during radiotherapy. For this purpose, a set of textural image parameters was extracted and considered as candidate of parotid shrinkage prediction; for all these parameters and combinations of maximum three of them, a fuzzy rule base was extracted, gaining very good results in terms of accuracy, sensitivity and specificity. The performance of classification was also compared to a classical Fisher's Linear Discriminant Analysis and found to provide better results. Moreover, the use of Fuzzy Logic allowed obtaining an interpretable description of the relations between textural features and the shrinkage process.

Static and rotational intensity modulated techniques for head-neck cancer radiotherapy: a planning comparison.

PURPOSE: To compare helical Tomotherapy (HT), two volumetric-modulated arc techniques and conventional fixed-field intensity modulated techniques (S-IMRT) for head-neck (HN) cancers. METHODS AND MATERIALS: Eighteen HN patients were considered. Four treatment plans were generated for each patient: HT, S-IMRT optimised with Eclipse treatment planning system and two volumetric techniques using Elekta-Oncentra approach (VMAT) and Varian-RapidArc (RA), using two full arcs. All techniques were optimised to simultaneously deliver 66Gy to PTV1 (GTV and enlarged nodes) and 54Gy to PTV2 (subclinical and electively treated nodes). Comparisons were assessed on several dosimetric parameters and, secondarily, on planned MUs and delivery time. RESULTS: Concerning PTV coverage, significantly better results were found for HT and RA. HT significantly improved the target coverage both compared to S-IMRT and VMAT. No significant differences were found between S-IMRT and volumetric techniques in terms of dose homogeneity. For OARs, all the techniques were able to satisfy all hard constraints; significantly better results were found for HT, especially in the intermediate dose range (15-30 Gy). S-IMRT reached a significantly better OARs sparing with respect to VMAT and RA. No significant differences were found for body mean dose, excepting higher values of V5-V10 for HT. A reduction of planned MUs and delivery treatment time was found with volumetric techniques. CONCLUSIONS: The objectives of satisfying target coverage and sparing of critical structures were reached with all techniques. S-IMRT techniques were found more advantageous compared to RA and VMAT for OARs sparing. HT reached the best overall treatment plan quality.

Early changes of parotid density and volume predict modifications at the end of therapy and intensity of acute xerostomia.

PURPOSE: To quantitatively assess the predictive power of early variations of parotid gland volume and density on final changes at the end of therapy and, possibly, on acute xerostomia during IMRT for head-neck cancer. MATERIALS AND METHODS: Data of 92 parotids (46 patients) were available. Kinetics of the changes during treatment were described by the daily rate of density (rΔρ) and volume (rΔvol) variation based on weekly diagnostic kVCT images. Correlation between early and final changes was investigated as well as the correlation with prospective toxicity data (CTCAEv3.0) collected weekly during treatment for 24/46 patients. RESULTS: A higher rΔρ was observed during the first compared to last week of treatment (-0,50 vs -0,05HU, p-value = 0.0001). Based on early variations, a good estimation of the final changes may be obtained (Δρ: AUC = 0.82, p = 0.0001; Δvol: AUC = 0.77, p = 0.0001). Both early rΔρ and rΔvol predict a higher "mean" acute xerostomia score (≥ median value, 1.57; p-value = 0.01). Median early density rate changes for patients with mean xerostomia score ≥ / < 1.57 were -0.98 vs -0.22 HU/day respectively (p = 0.05). CONCLUSIONS: Early density and volume variations accurately predict final changes of parotid glands. A higher longitudinally assessed score of acute xerostomia is well predicted by higher rΔρ and rΔvol in the first two weeks of treatment: best cut-off values were -0.50 HU/day and -380 mm(3)/day for rΔρ and rΔvol respectively. Further studies are necessary to definitively assess the potential of early density/volume changes in identifying more sensitive patients at higher risk of experiencing xerostomia.

Texture analysis for the assessment of structural changes in parotid glands induced by radiotherapy.

BACKGROUND AND PURPOSE: During radiotherapy (RT) for head-and-neck cancer, parotid glands undergo significant anatomic, functional and structural changes which could characterize pre-clinical signs of an increased risk of xerostomia. Texture analysis is proposed to assess structural changes of parotids induced by RT, and to investigate whether early variations of textural parameters (such as mean intensity and fractal dimension) can predict parotid shrinkage at the end of treatment. MATERIAL AND METHODS: Textural parameters and volumes of 42 parotids from 21 patients treated with intensity-modulated RT for nasopharyngeal cancer were extracted from CT images. To individuate which parameters changed during RT, a Wilcoxon signed-rank test between textural indices (first and second RT week; first and last RT week) was performed. Discriminant analysis was applied to variations of these parameters in the first two weeks of RT to assess their power in predicting parotid shrinkage at the end of RT. RESULTS: A significant decrease in mean intensity (1.7 HU and 3.8 HU after the second and last weeks, respectively) and fractal dimension (0.016 and 0.021) was found. Discriminant analysis, based on volume and fractal dimension, was able to predict the final parotid shrinkage (accuracy of 71.4%). CONCLUSION: Textural features could be used in combination with volume to characterize structural modifications on parotid glands and to predict parotid shrinkage at the end of RT.

Density variation of parotid glands during IMRT for head-neck cancer: correlation with treatment and anatomical parameters.

PURPOSE: Measuring parotid density changes in patients treated with IMRT for head-neck cancer (HNC) and assessing correlation with treatment-related parameters. PATIENTS AND MATERIALS: Data of 84 patients treated with IMRT for different HNC were pooled from three institutions. Parotid deformation and average Hounsfield number changes (ΔHU) were evaluated through MVCT (with Helical Tomotherapy) or diagnostic kVCT images taken at the treatment start/end. Parotids were delineated in the first image and propagated to the last using a previously validated algorithm based on elastic registration. The correlation between ΔHU and several treatment-related parameters was tested; then, logistic uni- and multi-variate analyses taking "large" ΔHU as end-point were carried out. Due to the better image quality, analyses were repeated considering only kVCT data. RESULTS: ΔHU was negative in 116/168 parotids (69%; for kVCT patients: 72/92, 78%). The average ΔHU was significantly different from zero (-7.3, 0.20-0.25 HU/fraction, p<0.001). Individual ΔHU was highly correlated with parotid deformation both in terms of volume change and mean value of the Jacobian of the deformation field (Jac_mean), and with neck thickness variation; these correlations were much stronger for kVCT data. Logistic analyses considering ΔHU<-11 (quartile value) as the end-point showed a two-variable model including large deformation (Jac_mean<0.68) and initial neck thickness to be the most predictive variables (p<0.0005, AUC=0.683; AUC=0.776 for kVCT); the odd ratio of large vs moderate/small parotid deformation was 3.8 and 8.0 for the whole and the kVCT population respectively. CONCLUSIONS: Parotid density reduced in most patients during IMRT and this phenomenon was highly correlated with parotid deformation. The individual assessment of density changes was highly reliable just with diagnostic KvCT. Density changes should be considered as an additional objective measurement of early parotid radiation-induced modifications; further research is warranted.