Preoperative MRI radiomic analysis for predicting local tumor progression in colorectal liver metastases before microwave ablation.

PURPOSE: Radiomics may aid in predicting prognosis in patients with colorectal liver metastases (CLM). Consistent data is available on CT, yet limited data is available on MRI. This study assesses the capability of MRI-derived radiomic features (RFs) to predict local tumor progression-free survival (LTPFS) in patients with CLMs treated with microwave ablation (MWA). METHODS: All CLM patients with pre-operative Gadoxetic acid-MRI treated with MWA in a single institution between September 2015 and February 2022 were evaluated. Pre-procedural information was retrieved retrospectively. Two observers manually segmented CLMs on T2 and T1-Hepatobiliary phase (T1-HBP) scans. After inter-observer variability testing, 148/182 RFs showed robustness on T1-HBP, and 141/182 on T2 (ICC > 0.7).Cox multivariate analysis was run to establish clinical (CLIN-mod), radiomic (RAD-T1, RAD-T2), and combined (COMB-T1, COMB-T2) models for LTPFS prediction. RESULTS: Seventy-six CLMs (43 patients) were assessed. Median follow-up was 14 months. LTP occurred in 19 lesions (25%).CLIN-mod was composed of minimal ablation margins (MAMs), intra-segment progression and primary tumor grade and exhibited moderately high discriminatory power in predicting LTPFS (AUC = 0.89, p = 0.0001). Both RAD-T1 and RAD-T2 were able to predict LTPFS: (RAD-T1: AUC = 0.83, p = 0.0003; RAD-T2: AUC = 0.79, p = 0.001). Combined models yielded the strongest performance (COMB-T1: AUC = 0.98, p = 0.0001; COMB-T2: AUC = 0.95, p = 0.0003). Both combined models included MAMs and tumor regression grade; COMB-T1 also featured 10th percentile of signal intensity, while tumor flatness was present in COMB-T2. CONCLUSION: MRI-based radiomic evaluation of CLMs is feasible and potentially useful for LTP prediction. Combined models outperformed clinical or radiomic models alone for LTPFS prediction.

Radiomics-enhanced early regression index for predicting treatment response in rectal cancer: a multi-institutional 0.35 T MRI-guided radiotherapy study.

PURPOSE: The accurate prediction of treatment response in locally advanced rectal cancer (LARC) patients undergoing MRI-guided radiotherapy (MRIgRT) is essential for optimising treatment strategies. This multi-institutional study aimed to investigate the potential of radiomics in enhancing the predictive power of a known radiobiological parameter (Early Regression Index, ERITCP) to evaluate treatment response in LARC patients treated with MRIgRT. METHODS: Patients from three international sites were included and divided into training and validation sets. 0.35 T T2*/T1-weighted MR images were acquired during simulation and at each treatment fraction. The biologically effective dose (BED) conversion was used to account for different radiotherapy schemes: gross tumour volume was delineated on the MR images corresponding to specific BED levels and radiomic features were then extracted. Multiple logistic regression models were calculated, combining ERITCP with other radiomic features. The predictive performance of the different models was evaluated on both training and validation sets by calculating the receiver operating characteristic (ROC) curves. RESULTS: A total of 91 patients was enrolled: 58 were used as training, 33 as validation. Overall, pCR was observed in 25 cases. The model showing the highest performance was obtained combining ERITCP at BED = 26 Gy with a radiomic feature (10th percentile of grey level histogram, 10GLH) calculated at BED = 40 Gy. The area under ROC curve (AUC) of this combined model was 0.98 for training set and 0.92 for validation set, significantly higher (p = 0.04) than the AUC value obtained using ERITCP alone (0.94 in training and 0.89 in validation set). CONCLUSION: The integration of the radiomic analysis with ERITCP improves the pCR prediction in LARC patients, offering more precise predictive models to further personalise 0.35 T MRIgRT treatments of LARC patients.

CT radiomic predictors of local relapse after SBRT for lung oligometastases from colorectal cancer: a single institute pilot study.

OBJECTIVES: To assess the potential of radiomic features (RFs) extracted from simulation computed tomography (CT) images in discriminating local progression (LP) after stereotactic body radiotherapy (SBRT) in the management of lung oligometastases (LOM) from colorectal cancer (CRC). MATERIALS AND METHODS: Thirty-eight patients with 70 LOM treated with SBRT were analyzed. The largest LOM was considered as most representative for each patient and was manually delineated by two blinded radiation oncologists. In all, 141 RFs were extracted from both contours according to IBSI (International Biomarker Standardization Initiative) recommendations. Based on the agreement between the two observers, 134/141 RFs were found to be robust against delineation (intraclass correlation coefficient [ICC] > 0.80); independent RFs were then assessed by Spearman correlation coefficients. The association between RFs and LP was assessed with Mann-Whitney test and univariate logistic regression (ULR): the discriminative power of the most informative RF was quantified by receiver-operating characteristics (ROC) analysis through area under curve (AUC). RESULTS: In all, 15/38 patients presented LP. Median time to progression was 14.6 months (range 2.4-66 months); 5/141 RFs were significantly associated to LP at ULR analysis (p < 0.05); among them, 4 RFs were selected as robust and independent: Statistical_Variance (AUC = 0.75, p = 0.002), Statistical_Range (AUC = 0.72, p = 0.013), Grey Level Size Zone Matrix (GLSZM) _zoneSizeNonUniformity (AUC = 0.70, p = 0.022), Grey Level Dependence Zone Matrix (GLDZM) _zoneDistanceEntropy (AUC = 0.70, p = 0.026). Importantly, the RF with the best performance (Statisical_Variance) is simply representative of density heterogeneity within LOM. CONCLUSION: Four RFs extracted from planning CT were significantly associated with LP of LOM from CRC treated with SBRT. Results encourage further research on a larger population aiming to define a usable radiomic score combining the most predictive RFs and, possibly, additional clinical features.

External validation of an 18F-FDG-PET radiomic model predicting survival after radiotherapy for oropharyngeal cancer.

PURPOSE/OBJECTIVE: The purpose of the study is to externally validate published 18F-FDG-PET radiomic models for outcome prediction in patients with oropharyngeal cancer treated with chemoradiotherapy. MATERIAL/METHODS: Outcome data and pre-radiotherapy PET images of 100 oropharyngeal cancer patients (stage IV:78) treated with concomitant chemotherapy to 66-69 Gy/30 fr were available. Tumors were segmented using a previously validated semi-automatic method; 450 radiomic features (RF) were extracted according to IBSI (Image Biomarker Standardization Initiative) guidelines. Only one model for cancer-specific survival (CSS) prediction was suitable to be independently tested, according to our criteria. This model, in addition to HPV status, SUVmean and SUVmax, included two independent meta-factors (Fi), resulting from combining selected RF clusters. In a subgroup of 66 patients with complete HPV information, the global risk score R was computed considering the original coefficients and was tested by Cox regression as predictive of CSS. Independently, only the radiomic risk score RF derived from Fi was tested on the same subgroup to learn about the radiomics contribution to the model. The metabolic tumor volume (MTV) was also tested as a single predictor and its prediction performances were compared to the global and radiomic models. Finally, the validation of MTV and the radiomic score RF were also tested on the entire dataset. RESULTS: Regarding the analysis of the subgroup with HPV information, with a median follow-up of 41.6 months, seven patients died due to cancer. R was confirmed to be associated to CSS (p value = 0.05) with a C-index equal 0.75 (95% CI=0.62-0.85). The best cut-off value (equal to 0.15) showed high ability in patient stratification (p=0.01, HR=7.4, 95% CI=1.6-11.4). The 5-year CSS for R were 97% (95% CI: 93-100%) vs 74% (56-92%) for low- and high-risk groups, respectively. RF and MTV alone were also significantly associated to CSS for the subgroup with an almost identical C-index. According to best cut-off value (RF>0.12 and MTV>15.5cc), the 5-year CSS were 96% (95% CI: 89-100%) vs 65% (36-94%) and 97% (95% CI: 88-100%) vs 77% (58-93%) for RF and MTV, respectively. Results regarding RF and MTV were confirmed in the overall group. CONCLUSION: A previously published PET radiomic model for CSS prediction was independently validated. Performances of the model were similar to the ones of using only the MTV, without improvement of prediction accuracy.

Prediction of the characteristics of aggressiveness of pancreatic neuroendocrine neoplasms (PanNENs) based on CT radiomic features.

OBJECTIVES: To predict tumor grade (G1 vs. G2/3), presence of distant metastasis (M+), metastatic lymph nodes (N+), and microvascular invasion (VI) of pancreatic neuroendocrine neoplasms (PanNEN) based on preoperative CT radiomic features (RFs), by applying a machine learning approach aimed to limit overfit. METHODS: This retrospective study included 101 patients who underwent surgery for PanNEN; the entire population was split into training (n = 70) and validation cohort (n = 31). Based on a previously validated methodology, after tumor segmentation on contrast-enhanced CT, RFs were extracted from unenhanced CT images. In addition, conventional radiological and clinical features were combined with RFs into multivariate logistic regression models using minimum redundancy and a bootstrap-based machine learning approach. For each endpoint, models were trained and validated including only RFs (RF_model), and both (radiomic and clinicoradiological) features (COMB_model). RESULTS: Twenty-five patients had G2/G3 tumor, 37 N+, and 14 M+ and 38 were shown to have VI. From a total of 182 RFs initially extracted, few independent radiomic and clinicoradiological features were identified. For M+ and G, the resulting models showed moderate to high performances: areas under the curve (AUC) for training/validation cohorts were 0.85/0.77 (RF_model) and 0.81/0.81 (COMB_model) for M+ and 0.67/0.72 and 0.68/0.70 for G. Concerning N+ and VI, only the COMB_model could be built, with poorer performance for N+ (AUC = 0.72/0.61) compared to VI (0.82/0.75). For all endpoints, the negative predictive value was good (≥ 0.75). CONCLUSIONS: Combining few radiomic and clinicoradiological features resulted in presurgical prediction of histological characteristics of PanNENs. Despite the limited risk of overfit, external validations are warranted. KEY POINTS: • Histology is the only tool currently available allowing characterization of PanNEN biological characteristics important for prognostic assessment; significant limitations to this approach exist. • Based upon preoperative contrast-enhanced CT images, a machine learning approach optimized to favor models' generalizability was successfully applied to train predictive models for tumor grading (G1 vs. G2/3), microvascular invasion, metastatic lymph nodes, and distant metastatic spread. • Moderate to high discriminative models (AUC: 0.67-0.85) based on few parameters (≤ 3) showing high negative predictive value (0.75-0.98) were generated and then successfully validated.

Patient-reported persistent symptoms after radiotherapy and association with quality of life for prostate cancer survivors.

PURPOSE: To evaluate the persistence of symptoms after radiotherapy (RT) for localised prostate cancer (PCa) and the association with quality of life (QOL). MATERIALS AND METHODS: Prospective patient-reported outcome (PRO) from a multi-institutional study on PCa treated with radical RT (2010-2014) was analysed. Data was collected at baseline (BL) and follow-ups (FUPs) up to 5 years. Patients with BL and ≥3 late FUPs (≥6 months) were analysed. PRO was scored by means of the IPSS and ICIQ-SF (urinary), LENT-SOMA (gastrointestinal [GI]), and EORTC-C30 (pain, insomnia, fatigue, and QOL) questionnaires. Symptoms were defined 'persistent' if the median score over FUPs was ≥3 (urinary) or ≥2 (GI, pain, insomnia, and fatigue), and worse than BL. Different thresholds were chosen to have enough events for each symptom. QOL was linearly transformed on a continuous scale (0-100). Linear-mixed models were used to identify significant differences between groups with and without persistent symptoms including age, smoking status, previous abdominal surgery, and diabetes as confounders. Mean QOL differences between groups were evaluated longitudinally over FUPs. RESULTS: The analysis included 293 patients. Persistent urinary symptoms ranged from 2% (straining) to 12% (weak stream, and nocturia). Gastrointestinal symptoms ranged from 7% (rectal pain, and incontinence) to 30% (urgency). Proportions of pain, insomnia, and fatigue were 6, 13, and 18%. Significant QOL differences of small-to-medium clinical relevance were found for urinary incontinence, frequency, urgency, and nocturia. Among GI symptoms, rectal pain and incontinence showed small-to-medium differences. Fatigue was associated with the largest differences. CONCLUSIONS: The analysis showed that symptoms after RT for PCa occur with different persistence and their association with QOL varies in magnitude. A number of persistent urinary and GI symptoms showed differences in a comparable range. Urinary incontinence and frequency, rectal pain, and faecal incontinence more often had significant associations. Fatigue was also prevalent and associated with largely deteriorated QOL.

Limited impact of discretization/interpolation parameters on the predictive power of CT radiomic features in a surgical cohort of pancreatic cancer patients.

PURPOSE: To explore the variation of the discriminative power of CT (Computed Tomography) radiomic features (RF) against image discretization/interpolation in predicting early distant relapses (EDR) after upfront surgery. MATERIALS AND METHODS: Data of 144 patients with pre-surgical high contrast CT were processed consistently with IBSI (Image Biomarker Standardization Initiative) guidelines. Image interpolation/discretization parameters were intentionally changed, including cubic voxel size (0.21-27 mm3) and binning (32-128 grey levels) in a 15 parameter's sets. After excluding RF with poor inter-observer delineation agreement (ICC < 0.80) and not negligible inter-scanner variability, the variation of 80 RF against discretization/interpolation was first quantified. Then, their ability in classifying patients with early distant relapses (EDR, < 10 months, previously assessed at the first quartile value of time-to-relapse) was investigated in terms of AUC (Area Under Curve) variation for those RF significantly associated to EDR. RESULTS: Despite RF variability against discretization/interpolation parameters was large and only 30/80 RF showed %COV < 20 (%COV = 100*STDEV/MEAN), AUC changes were relatively limited: for 30 RF significantly associated with EDR (AUC values around 0.60-0.70), the mean values of SD of AUC variability and AUC range were 0.02 and 0.05 respectively. AUC ranges were between 0.00 and 0.11, with values ≤ 0.05 in 16/30 RF. These variations were further reduced when excluding the extreme values of 32 and 128 for grey levels (Average AUC range 0.04, with values between 0.00 and 0.08). CONCLUSIONS: The discriminative power of CT RF in the prediction of EDR after upfront surgery for pancreatic cancer is relatively invariant against image interpolation/discretization within a large range of voxel sizes and binning.

CT-derived radiomic features to discriminate histologic characteristics of pancreatic neuroendocrine tumors.

PURPOSE: To assess the ability of radiomic features (RF) extracted from contrast-enhanced CT images (ceCT) and non-contrast-enhanced (non-ceCT) in discriminating histopathologic characteristics of pancreatic neuroendocrine tumors (panNET). METHODS: panNET contours were delineated on pre-surgical ceCT and non-ceCT. First- second- and higher-order RF (adjusted to eliminate redundancy) were extracted and correlated with histological panNET grade (G1 vs G2/G3), metastasis, lymph node invasion, microscopic vascular infiltration. Mann-Whitney with Bonferroni corrected p values assessed differences. Discriminative power of significant RF was calculated for each of the end-points. The performance of conventional-imaged-based-parameters was also compared to RF. RESULTS: Thirty-nine patients were included (mean age 55-years-old; 24 male). Mean diameters of the lesions were 24 × 27 mm. Sixty-nine RF were considered. Sphericity could discriminate high grade tumors (AUC = 0.79, p = 0.002). Tumor volume (AUC = 0.79, p = 0.003) and several non-ceCT and ceCT RF were able to identify microscopic vascular infiltration: voxel-alignment, neighborhood intensity-difference and intensity-size-zone families (AUC ≥ 0.75, p < 0.001); voxel-alignment, intensity-size-zone and co-occurrence families (AUC ≥ 0.78, p ≤ 0.002), respectively). Non-ceCT neighborhood-intensity-difference (AUC = 0.75, p = 0.009) and ceCT intensity-size-zone (AUC = 0.73, p = 0.014) identified lymph nodal invasion; several non-ceCT and ceCT voxel-alignment family features were discriminative for metastasis (p < 0.01, AUC = 0.80-0.85). Conventional CT 'necrosis' could discriminate for microscopic vascular invasion (AUC = 0.76, p = 0.004) and 'arterial vascular invasion' for microscopic metastasis (AUC = 0.86, p = 0.001). No conventional-imaged-based-parameter was significantly associated with grade and lymph node invasion. CONCLUSIONS: Radiomic features can discriminate histopathology of panNET, suggesting a role of radiomics as a non-invasive tool for tumor characterization. TRIAL REGISTRATION NUMBER: NCT03967951, 30/05/2019.

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.

Patterns in ano-rectal dose maps and the risk of late toxicity after prostate IMRT.

Purpose: The aim of this work was to determine how the spatial pattern of dose in the ano-rectal wall is related to late gastro-intestinal toxicity for prostate cancer patients treated with mainly IMRT.Patients and methods: Patients from the DUE-01 multicentre study with patient-reported (prospective) follow-up and available dosimetric data were included. Conventionally fractionated patients received 74-80 Gy and hypofractionated patients received 65-75.2 Gy. A large majority of the patients were treated with intensity-modulated radiotherapy (IMRT). Dose-surface maps (DSMs) for the anal canal and rectum as a single structure, and for the anal canal and the rectum separately, were co-registered rigidly in two dimensions and, for the patients with and without toxicity, respectively, the mean value of the dose in each pixel was calculated. A pixel-wise t-test was used to highlight the anatomical areas where there was a significant difference between the 'mean dose maps' of each group. Univariate models were also fitted to a range of spatial parameters. The endpoints considered were a mean grade ≥1 late fecal incontinence and a maximum grade ≥2 late rectal bleeding.Results: Twenty-six out of 213 patients had fecal incontinence, while 21/225 patients had rectal bleeding. Incontinence was associated with a higher dose in the caudal region of the anal canal; the most relevant spatial parameter was the lateral extent of the low and medium isodoses (5-49 Gy in EQD2). Bleeding was associated with high isodoses reaching the posterior rectal wall. The spatial dose parameters with the highest AUC value (.69) were the lateral extent of the 60-70 Gy isodoses.Conclusions: To avoid fecal incontinence it is important to limit the portion of the anal canal irradiated. Our analysis confirms that rectal bleeding is a function of similar spatial dose parameters for patients treated with IMRT, compared to previous studies on patients treated with three-dimensional conformal radiotherapy.

Toxicity and efficacy of salvage carbon 11-choline positron emission tomography/computed tomography-guided radiation therapy in patients with lymph node recurrence of prostate cancer.

OBJECTIVE: To report the 3-year toxicity and outcomes of carbon 11 (11C)-choline-positron emission tomography (PET)/computed tomography (CT)-guided radiotherapy (RT), delivered via helical tomotherapy (HTT; Tomotherapy® Hi-Art II® Treatment System, Accuray Inc., Sunnyvale, CA, USA) after lymph node (LN) relapses in patients with prostate cancer. PATIENTS AND METHODS: From January 2005 to March 2013, 81 patients with biochemical recurrence after surgery, with or without adjuvant/salvage RT or radical RT, and with evidence of LN 11C-choline-PET/CT pathological uptake, underwent HTT (median [range] prostate-specific antigen level 2.59 [0.61-187] ng/mL). Of the 81 patients, 72 were treated at the pelvic and/or lumbar-aortic LN chain with HTT at 51.8 Gy/28 fr and with simultaneous integrated boost to a median dose of 65.5 Gy on the pathological uptake sites detected by 11C-choline-PET/CT. Nine patients were treated without simultaneous integrated boost (50-65.5 Gy, 25-30 fr). RESULTS: With a median (range) follow-up of 36 (9-116) months, 91.4% of the patients had a PSA reduction 3 months after HTT. The 3-year overall, local relapse-free and clinical relapse-free survival rates were 80.0, 89.8 and 61.8%, respectively. The 3-year actuarial incidences of ≥grade 2 rectal and ≥grade 2 genitourinary toxicity were 6.6% (±2.9%) and 26.3% (±5.5%), respectively. A PSA nadir of ≥0.26 ng/mL (hazard ratio [HR] 3.6, 95% confidence interval [CI] 1.7-7.7; P = 0.001), extrapelvic 11C-choline-PET/CT-positive LN location (HR 2.4, 95% CI 0.9-6.4; P = 0.07), RT previous to HTT (HR 2.7; 95% CI 1.07-6.9, P = 0.04) and number of positive LNs (HR 1.13, 95% CI 1.04-1.22; P = 0.003) were the main predictors of clinical relapse after HTT. CONCLUSIONS: 11C-choline-PET/CT-guided HTT is safe and effective in the treatment of LN relapses of prostate cancer in previously treated patients.

Baseline status and dose to the penile bulb predict impotence 1 year after radiotherapy for prostate cancer.

AIM: To assess the predictors of the onset of impotence 1 year after radiotherapy for prostate cancer. PATIENTS AND METHODS: In a multi-centric prospective study, the International Index of Erectile Function (IIEF) questionnaire-based potency of 91 hormone-naïve and potent patients (IIEF1-5 > 11 before radiotherapy) was assessed. At the time of this analysis, information on potency 1 year after treatment was available for 62 of 91 patients (42 treated with hypofractionation: 2.35-2.65 Gy/fr, 70-74.2 Gy; 20 with conventional fractionation: 74-78 Gy). Prospectively collected individual information and Dmax/Dmean to the penile bulb were available; the corresponding 2 Gy-equivalent values (EQD2_max/EQD2_mean) were also considered. Predictors of 1­year impotency were assessed through uni- and multi-variable backward logistic regression: The best cut-off values discriminating between potent and impotent patients were assessed by ROC analyses. The discriminative power of the models and goodness-of-fit were measured by AUC analysis and the Hosmer-Lemeshow (H&L) test. RESULTS: At 1­year follow-up, 26 of 62 patients (42 %) became impotent. The only predictive variables were baseline IIEF1-5 values (best cut-off baseline IIEF1-5 ≥ 19), Dmax ≥ 68.5 Gy and EQD2_max ≥ 74.2 Gy. The risk of 1­year impotence may be predicted by a two-variable model including baseline IIEF1-5 (OR: 0.80, p = 0.003) and EQD2_max ≥ 74.2 Gy (OR: 4.1, p = 0.022). The AUC of the model was 0.77 (95% CI: 0.64-0.87, p = 0.0007, H&L: p = 0.62). The 1­year risk of impotency after high-dose radiotherapy in potent men depends on the EQD2_max to the penile bulb and on baseline IIEF1-5 values. CONCLUSION: A significant reduction in the risk may be expected mainly when sparing the bulb in patients with no/mild baseline impotency (IIEF1-5 > 17).

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.

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.

Impact of low skeletal muscle mass in oropharyngeal cancer patients treated with radical chemo-radiotherapy: A mono-institutional experience.

AIMS: Low skeletal muscle mass index (SMI) has recently emerged as an independent prognostic factor in oncological patients and it is linked with poor survival and higher treatment toxicity. The present study aims to determine the possible impact of low SMI on survival and acute toxicity in oropharyngeal patients. METHODS: Seventy-six patients with locally advanced oropharyngeal squamous cell carcinoma (stage III-IVC) were treated in our institution with Helical TomoTherapy® (HT - Accuray, Maddison, WI, USA) between 2005 and 2021. All patients received concomitant platinum-based chemotherapy (CT) (at least 200 mg/m2). The SMI was determined using the calculation of cross-sectional area at C3. Twenty patients (26%) presented pre-treatment low SMI, according to Chargi definitions. RESULTS: All patients concluded the treatment. Thirteen patients with low SMI (65%) and 22 patients with normal SMI (39%) presented acute toxicity greater than or equal to grade 3, but this difference was not statistically significant (p-value = 0.25). Overall survival was analyzed in 65 patients, excluding those who finished CT-RT less than six months before the analysis. Overall survival was significantly lower in low SMI versus normal SMI patients (p-value = 0.035). Same difference was observed in N0-N2a patients, suggesting an important role of SMI also in lower nodal burden and putatively better prognosis. CONCLUSIONS: Although the results are limited to a small population, our case series has the advantage to be very homogeneous in patients and treatment characteristics. In our setting, SMI demonstrated a crucial impact on overall survival. Further investigation with larger samples is necessary to confirm our results to improve patient outcomes.

Preclinical photon minibeam radiotherapy using a custom collimator: Dosimetry characterization and preliminary in-vivo results on a glioma model.

PURPOSE: The purpose of this study is to investigate the dosimetric characteristics of a collimator for minibeam radiotherapy (MBRT) with film dosimetry and Monte Carlo (MC) simulations. The outcome of MBRT with respect to conventional RT using a glioma preclinical model was also evaluated. METHODS: A multi-slit collimator was designed to be used with commercial small animal irradiator. The collimator was built by aligning 0.6 mm wide and 5 mm thick parallel lead leaves at 0.4 mm intervals. Dosimetry characteristics were evaluated by Gafchromic (CG) films and TOPAS Monte Carlo (MC) code. An in vivo experiment was performed using a glioma preclinical model by injecting two million GL261cells subcutaneously and treating with 25 Gy, single fraction, with MBRT and conventional RT. Survival curves and acute radiation damage were measured to compare both treatments. RESULTS: A satisfactory agreement between experimental results and MC simulations were obtained, the measured FWHM and distance between the peaks were respectively 0.431 and 1.098 mm. In vivo results show that MBRT can provide local tumor control for three weeks after RT treatment and a similar survival fraction of open beam radiotherapy. No severe acute effects were seen for the MBRT group. CONCLUSIONS: We developed a minibeam collimator and presented its dosimetric features. Satisfactory agreement between MC and GC films was found with differences consistent with uncertainties due to fabrication and set-up errors. The survival curves of MBRT and open field RT are similar while atoxicity is dramatically lower with MBRT, preliminarily confirming the expected effect.

Hypofractionated radiotherapy concomitant to capecitabine after induction chemotherapy for advanced pancreatic adenocarcinoma.

Background and purpose: To assess feasibility, toxicity and outcome of moderately hypofractionated radiotherapy concomitant to capecitabine after induction chemotherapy for advanced pancreatic cancer. Materials and methods: Patients with advanced pancreatic cancer without distant progression after induction chemotherapy (CHT) were considered. Radiochemotherapy (RCT) consisted of 44.25 Gy in 15 fractions to the tumor and involved lymph-nodes concomitant to capecitabine 1250 mg/m2/day. Feasibility and toxicity were evaluated in all pts. Overall survival (OS), progression free survival (PFS), distant PFS (DPFS) and local PFS (LPFS) were assessed only in stage III patients. Results: 254 patients, 220 stage III, 34 stage IV, were treated. Median follow up was 19 months. Induction CHT consisted of Gemcitabine (35 patients), or drug combination (219 patients); median duration was 6 months.Four patients (1.6 %) did not complete RT (1 early progression, 3 toxicity), median duration of RT was 20 days, 209 patients (82 %) received ≥ 75 % of capecitabine dose.During RCT G3 gastrointestinal toxicity occurred in 3.2% of patients, G3-G4 hematologic toxicity in 5.4% of patients. Subsequently, G3, G4, G5 gastric or duodenal lesions occurred in 10 (4%), 2 (0.8%) and 1 patients (0.4%), respectively.Median PFS, LPFS, and DPFS were 11.9 months (95 % CI:11.4-13), 16 months (95 % CI:14.2-17.3) and 14.0 months (95 % CI:12.6-146.5), respectively.Median OS was 19.5 months (95 % CL:18.1-21.3). One- and two-year survival were 85.2 % and 36 %, respectively. Conclusions: The present schedule of hypofractionated RT after induction CHT is feasible with acceptable toxicity rate and provides an outcome comparable with that achievable with standard doses and fractionation.

Comparing Performances of Predictive Models of Toxicity after Radiotherapy for Breast Cancer Using Different Machine Learning Approaches.

PURPOSE: Different ML models were compared to predict toxicity in RT on a large cohort (n = 1314). METHODS: The endpoint was RTOG G2/G3 acute toxicity, resulting in 204/1314 patients with the event. The dataset, including 25 clinical, anatomical, and dosimetric features, was split into 984 for training and 330 for internal tests. The dataset was standardized; features with a high p-value at univariate LR and with Spearman ρ>0.8 were excluded; synthesized data of the minority were generated to compensate for class imbalance. Twelve ML methods were considered. Model optimization and sequential backward selection were run to choose the best models with a parsimonious feature number. Finally, feature importance was derived for every model. RESULTS: The model's performance was compared on a training-test dataset over different metrics: the best performance model was LightGBM. Logistic regression with three variables (LR3) selected via bootstrapping showed performances similar to the best-performing models. The AUC of test data is slightly above 0.65 for the best models (highest value: 0.662 with LightGBM). CONCLUSIONS: No model performed the best for all metrics: more complex ML models had better performances; however, models with just three features showed performances comparable to the best models using many (n = 13-19) features.

Inter-institutional variability of knowledge-based plan prediction of left whole breast irradiation.

PURPOSE: Within a multi-institutional project, we aimed to assess the transferability of knowledge-based (KB) plan prediction models in the case of whole breast irradiation (WBI) for left-side breast irradiation with tangential fields (TF). METHODS: Eight institutions set KB models, following previously shared common criteria. Plan prediction performance was tested on 16 new patients (2 pts per centre) extracting dose-volume-histogram (DVH) prediction bands of heart, ipsilateral lung, contralateral lung and breast. The inter-institutional variability was quantified by the standard deviations (SDint) of predicted DVHs and mean-dose (Dmean). The transferability of models, for the heart and the ipsilateral lung, was evaluated by the range of geometric Principal Component (PC1) applicability of a model to test patients of the other 7 institutions. RESULTS: SDint of the DVH was 1.8 % and 1.6 % for the ipsilateral lung and the heart, respectively (20 %-80 % dose range); concerning Dmean, SDint was 0.9 Gy and 0.6 Gy for the ipsilateral lung and the heart, respectively (<0.2 Gy for contralateral organs). Mean predicted doses ranged between 4.3 and 5.9 Gy for the ipsilateral lung and 1.1-2.3 Gy for the heart. PC1 analysis suggested no relevant differences among models, except for one centre showing a systematic larger sparing of the heart, concomitant to a worse PTV coverage, due to high priority in sparing the left anterior descending coronary artery. CONCLUSIONS: Results showed high transferability among models and low inter-institutional variability of 2% for plan prediction. These findings encourage the building of benchmark models in the case of TF-WBI.

Skin dose-volume predictors of moderate-severe late side effects after whole breast radiotherapy.

BACKGROUND: Toxicity after whole breast Radiotherapy is a relevant issue, impacting the quality-of-life of a not negligible number of patients. We aimed to develop a Normal Tissue Complication Probability (NTCP) model predicting late toxicities by combining dosimetric parameters of the breast dermis and clinical factors. METHODS: The skin structure was defined as the outer CT body contour's 5 mm inner isotropic expansion. It was retrospectively segmented on a large mono-institutional cohort of early-stage breast cancer patients enrolled between 2009 and 2017 (n = 1066). Patients were treated with tangential-field RT, delivering 40 Gy in 15 fractions to the whole breast. Toxicity was reported during Follow-Up (FU) using SOMA/LENT scoring. The study endpoint was moderate-severe late side effects consisting of Fibrosis-Atrophy-Telangiectasia-Pain (FATP G ≥ 2) developed within 42 months after RT completion. A machine learning pipeline was designed with a logistic model combining clinical factors and absolute skin DVH (cc) parameters as output. RESULTS: The FATP G2 + rate was 3.8 %, with 40/1066 patients experiencing side effects. After the preprocessing of variables, a cross-validation was applied to define the best-performing model. We selected a 4-variable model with Post-Surgery Cosmetic alterations (Odds Ratio, OR = 7.3), Aromatase Inhibitors (as a protective factor with OR = 0.45), V20 Gy (50 % of the prescribed dose, OR = 1.02), and V42 Gy (105 %, OR = 1.09). Factors were also converted into an adjusted V20Gy. CONCLUSIONS: The association between late reactions and skin DVH when delivering 40 Gy/15 fr was quantified, suggesting an independent role of V20 and V42. Few clinical factors heavily modulate the risk.