Baseline shift corrections towards the heart: External validation of the impact on survival in early-stage NSCLC patients.

PURPOSE: To externally validate Johnson-Hart et al. findings: the association of tumor baseline shifts towards the heart with overall survival (OS) in SBRT for NSCLC. Further analysis included investigating the presence of interfractional heart baseline shifts and the association of OS with heart dose change during treatment. METHODS: Data from 416 SBRT early-stage NSCLC patients was collected. Pearson's correlations (PCCs) between clinical variables and treatment-averaged tumor shifts towards/away from the heart were explored. Validation of published multivariable Cox model was performed. PCCs between heart and tumor baseline shifts were analyzed. Dose accumulation was performed following daily CBCT-to-pCT deformable registration. Maximum heart dose (D0) was computed for planned and accumulated doses. Differences in OS according to shifts towards/away from the heart or D0 increase/decrease were analyzed. Significant D0 differences between patients with D0 increase/decrease and different tumor locations were explored. RESULTS: Tumor shifts towards/away from the heart showed no significant association with OS (p = 0.91). Distance between PTV and heart correlated significantly (PCC = 0.18) with shifts to the heart. Cox model did not validate in our cohort. Heart presented baseline shifts positively correlated with tumor baseline shifts in all three directions (PCC ≥ 0.38; p < 0.001). Counterintuitively, patients experiencing increased D0 during treatment showed significantly better OS (p = 0.0077). Upper-lobe tumor patients with increased D0 had lower D0 than those with decreased D0 (right-upper-lobe p ≤ 0.018). CONCLUSIONS: In our SBRT cohort, the shifts towards the heart were not associated with worse OS. Moderate correlations were found between tumor and heart baseline shifts in each direction. Moreover, the distance between the PTV and the heart showed a significant correlation with shifts to the heart.

Severe radiation-induced lymphopenia during concurrent chemoradiotherapy for stage III non-small cell lung cancer: external validation of two prediction models.

Background: Severe radiation-induced lymphopenia (RIL) in patients undergoing chemoradiotherapy (CRT) for non-small cell lung cancer (NSCLC) is associated with decreased immunotherapy efficacy and survival. At The Christie and MD Anderson Cancer Center (MDACC), prediction models for lymphopenia were developed in lung and esophageal cancer patients, respectively. The aim of this study was to externally validate both models in patients with stage III NSCLC. Methods: Patients who underwent concurrent CRT for stage III NSCLC in 2019-2021 were studied. Outcomes were grade ≥3 and grade 4 lymphopenia during CRT. The Christie model predictors for grade ≥3 lymphopenia included age, baseline lymphocyte count, radiotherapy duration, chemotherapy, mean heart and lung doses, and thoracic vertebrae V20Gy. MDACC predictors for grade 4 lymphopenia were age, baseline lymphocyte count, planning target volume (PTV), and BMI. The external performance of both models was assessed. Results: Among 100 patients, 78 patients (78%) developed grade ≥3 lymphopenia, with grade 4 lymphopenia in 17 (17%). For predicting grade ≥3 lymphopenia, the Christie and MDACC models yielded c-statistics of 0.77 and 0.79, respectively. For predicting grade 4 lymphopenia, c-statistics were 0.69 and 0.80, respectively. Calibration for the Christie and MDACC models demonstrated moderate and good agreement, respectively. Conclusion: The PTV-based MDACC prediction model for severe RIL demonstrated superior external performance in NSCLC patients compared to the dosimetry-based Christie model. As such, the MDACC model can aid in identifying patients at high risk for severe lymphopenia. However, to optimize radiotherapy planning, further improvement and external validation of dosimetry-based models is desired.

Detailed dosimetric evaluation of inter-fraction and respiratory motion in lung stereotactic body radiation therapy based on daily 4D cone beam CT images.

Objective. Periodic respiratory motion and inter-fraction variations are sources of geometric uncertainty in stereotactic body radiation therapy (SBRT) of pulmonary lesions. This study extensively evaluates and validates the separate and combined dosimetric effect of both factors using 4D-CT and daily 4D-cone beam CT (CBCT) dose accumulation scenarios.Approach. A first cohort of twenty early stage or metastatic disease lung cancer patients were retrospectively selected to evaluate each scenario. The planned-dose (3DRef) was optimized on a 3D mid-position CT. To estimate the dosimetric impact of respiratory motion (4DRef), inter-fractional variations (3DAcc) and the combined effect of both factors (4DAcc), three dose accumulation scenarios based on 4D-CT, daily mid-cone beam CT (CBCT) position and 4D-CBCT were implemented via CT-CT/CT-CBCT deformable image registration (DIR) techniques. Each scenario was compared to 3DRef.A separate cohort of ten lung SBRT patients was selected to validate DIR techniques. The distance discordance metric (DDM) was implemented per voxel and per patient for tumor and organs at risk (OARs), and the dosimetric impact for CT-CBCT DIR geometric errors was calculated.Main results.Median and interquartile range (IQR) of the dose difference per voxel were 0.05/2.69 Gy and -0.12/2.68 Gy for3DAcc-3DRefand4DAcc-3DRef.For4DRef-3DRefthe IQR was considerably smaller -0.15/0.78 Gy. These findings were confirmed by dose volume histogram parameters calculated in tumor and OARs. For CT-CT/CT-CBCT DIR validation, DDM (95th percentile) was highest for heart (6.26 mm)/spinal cord (8.00 mm), and below 3 mm for tumor and the rest of OARs. The dosimetric impact of CT-CBCT DIR errors was below 2 Gy for tumor and OARs.Significance. The dosimetric impact of inter-fraction variations were shown to dominate those of periodic respiration in SBRT for pulmonary lesions. Therefore, treatment evaluation and dose-effect studies would benefit more from dose accumulation focusing on day-to-day changes then those that focus on respiratory motion.

Delivered dose-effect analysis of radiation induced rib fractures after thoracic SBRT.

BACKGROUND AND PURPOSE: Anatomical changes during the stereotactic body radiation therapy (SBRT) of early stage non-small cell lung cancer (NSCLC) may cause the delivered dose to deviate from the planned dose. We investigate if normal tissue complication probability (NTCP) models based on the delivered dose predict radiation-induced rib fractures better than models based on the planned dose. MATERIAL AND METHODS: 437 NSCLC patients treated to a median dose of 3x18 Gy were included. Delivered dose was estimated by accumulating EQD2-corrected fraction doses after being deformed with daily CBCT-to-planning CT deformable image registration. Dosimetric parameters Dx (dose to a relative volume x) were extracted for each rib included in the CBCTs field-of-view. An NTCP model was constructed for both planned and delivered dose, optimizing the parameters TD50 (dose with 50% toxicity risk), m (steepness of the curve) and x, using maximum likelihood estimation. Best NTCP model was determined using Akaike weights (Aw). Differences between the models were tested for significance using the Vuong's test. RESULTS: Median time to fracture of 110 fractured ribs was 22.5 months. The maximum rib dose, D0, best predicted fractures for both planned and delivered dose. The average delivered D0 was significantly lower than planned (p < 0.001). NTCP model based on the delivered D0 was the best, with Aw = 0.95. The models were not significantly different. CONCLUSION: Delivered maximum dose to the ribs was significantly lower than planned. The NTCP model based on delivered dose improved predictions of radiation-induced rib fractures but did not reach statistical significance.

A multivariable study of deformable image registration evaluation metrics in 4DCT of thoracic cancer patients.

Deformable image registration (DIR) accuracy is often validated using manually identified landmarks or known deformations generated using digital or physical phantoms. In daily practice, the application of these approaches is limited since they are time-consuming or require additional equipment. An alternative is the use of metrics automatically derived from the registrations, but their interpretation is not straightforward. In this work we aim to determine the suitability of DIR-derived metrics to validate the accuracy of 4 commonly used DIR algorithms. First, we investigated the DIR accuracy using a landmark-based metric (target registration error (TRE)) and a digital phantom-based metric (known deformation recovery error (KDE)). 4DCT scans of 16 thoracic cancer patients along with corresponding pairwise anatomical landmarks (AL) locations were collected from two public databases. Digital phantoms with known deformations were generated by each DIR algorithm to test all other algorithms and compute KDE. TRE and KDE were evaluated at AL. KDE was additionally quantified in coordinates randomly sampled (RS) inside the lungs. Second, we investigated the associations of 5 DIR-derived metrics (distance discordance metric (DDM), inverse consistency error (ICE), transitivity (TE), spatial (SS) and temporal smoothness (TS)) with DIR accuracy through uni- and multivariable linear regression models. TRE values were found higher compared to KDE values and these varied depending on the phantom used. The algorithm with the best accuracy achieved average values of TRE = 1.1 mm and KDE ranging from 0.3 to 0.8 mm. DDM was the best predictor of DIR accuracy, with moderate correlations (R 2 < 0.61). Poor correlations were obtained at AL for algorithms with better accuracy, which improved when evaluated at RS. Only slight correlation improvement was obtained with a multivariable analysis (R 2 < 0.64). DDM can be a useful metric to identify inaccuracies for different DIR algorithms without employing landmarks or digital phantoms.

Correcting geometric image distortions in slice-based 4D-MRI on the MR-linac.

PURPOSE: The importance of four-dimensional-magnetic resonance imaging (4D-MRI) is increasing in guiding online plan adaptation in thoracic and abdominal radiotherapy. Many 4D-MRI sequences are based on multislice two-dimensional (2D) acquisitions which provide contrast flexibility. Intrinsic to MRI, however, are machine- and subject-related geometric image distortions. Full correction of slice-based 4D-MRIs acquired on the Unity MR-linac (Elekta AB, Stockholm, Sweden) is challenging, since through-plane corrections are currently not available for 2D sequences. In this study, we implement a full three-dimensional 3D correction and quantify the geometric and dosimetric effects of machine-related (residual) geometric image distortions. METHODS: A commercial three-dimensional (3D) geometric QA phantom (Philips, Best, the Netherlands) was used to quantify the effect of gradient nonlinearity (GNL) and static-field inhomogeneity (B0I) on geometric accuracy. Additionally, the effectiveness of 2D (in-plane, machine-generic), 3D (machine-generic), and in-house developed 3D + (machine-specific) corrections was investigated. Corrections were based on deformable vector fields derived from spherical harmonics coefficients. Three patients with oligometastases in the liver were scanned with axial 4D-MRIs on our MR-linac (total: 10 imaging sessions). For each patient, a step-and-shoot IMRT plan (3 × 20 Gy) was created based on the simulation mid-position (midP)-CT. The 4D-MRIs were then warped into a daily midP-MRI and geometrically corrected. Next, the treatment plan was adapted according to the position offset of the tumor between midP-CT and the 3D-corrected midP-MRIs. The midP-CT was also deformably registered to the daily midP-MRIs (different corrections applied) to quantify the dosimetric effects of (residual) geometric image distortions. RESULTS: Using phantom data, median GNL distortions were 0.58 mm (no correction), 0.42-0.48 mm (2D), 0.34 mm (3D), and 0.34 mm (3D + ), measured over a diameter of spherical volume (DSV) of 200 mm. Median B0I distortions were 0.09 mm for the same DSV. For DSVs up to 500 mm, through-plane corrections are necessary to keep the median residual GNL distortion below 1 mm. 3D and 3D + corrections agreed within 0.15 mm. 2D-corrected images featured uncorrected through-plane distortions of up to 21.11 mm at a distance of 20-25 cm from the machine's isocenter. Based on the 4D-MRI patient scans, the average external body contour distortions were 3.1 mm (uncorrected) and 1.2 mm (2D-corrected), with maximum local distortions of 9.5 mm in the uncorrected images. No (residual) distortions were visible for the metastases, which were all located within 10 cm of the machine's isocenter. The interquartile range (IQR) of dose differences between planned and daily dose caused by variable patient setup, patient anatomy, and online plan adaptation was 1.37 Gy/Fx for the PTV D95%. When comparing dose on 3D-corrected with uncorrected (2D-corrected) images, the IQR was 0.61 (0.31) Gy/Fx. CONCLUSIONS: GNL is the main machine-related source of image distortions on the Unity MR-linac. For slice-based 4D-MRI, a full 3D correction can be applied after respiratory sorting to maximize spatial fidelity. The machine-specific 3D + correction did not substantially reduce residual geometric distortions compared to the machine-generic 3D correction for our MR-linac. In our patients, dosimetric variations in the target not related to geometric distortions were larger than those caused by geometric distortions.

Alterations of Effective Connectivity Patterns in Mild Cognitive Impairment: An MEG Study.

Neuroimaging techniques have demonstrated over the years their ability to characterize the brain abnormalities associated with different neurodegenerative diseases. Among all these techniques, magnetoencephalography (MEG) stands out by its high temporal resolution and noninvasiveness. The aim of the present study is to explore the coupling patterns of resting-state MEG activity in subjects with mild cognitive impairment (MCI). To achieve this goal, five minutes of spontaneous MEG activity were acquired with a 148-channel whole-head magnetometer from 18 MCI patients and 26 healthy controls. Inter-channel relationships were investigated by means of two complementary coupling measures: coherence and Granger causality. Coherence is a classical method of functional connectivity, while Granger causality quantifies effective (or causal) connectivity. Both measures were calculated in the five conventional frequency bands: delta (δ, 1-4 Hz), theta (θ, 4-8 Hz), alpha (α, 8-13 Hz), beta (ß, 13-30 Hz), and gamma (γ, 30-45 Hz). Our results showed that connectivity values were lower for MCI patients than for controls in all frequency bands. However, only Granger causality revealed statistically significant differences between groups (p-values < 0.05, FDR corrected Mann-Whitney U-test), mainly in the beta band. Our results support the role of MCI as a disconnection syndrome, which elicits early alterations in effective connectivity patterns. These findings can be helpful to identify the neural substrates involved in prodromal stages of dementia.

Analysis of spontaneous EEG activity in Alzheimer's disease using cross-sample entropy and graph theory.

The aim of this pilot study was to analyze spontaneous electroencephalography (EEG) activity in Alzheimer's disease (AD) by means of Cross-Sample Entropy (Cross-SampEn) and two local measures derived from graph theory: clustering coefficient (CC) and characteristic path length (PL). Five minutes of EEG activity were recorded from 37 patients with dementia due to AD and 29 elderly controls. Our results showed that Cross-SampEn values were lower in the AD group than in the control one for all the interactions among EEG channels. This finding indicates that EEG activity in AD is characterized by a lower statistical dissimilarity among channels. Significant differences were found mainly for fronto-central interactions (p <; 0.01, permutation test). Additionally, the application of graph theory measures revealed diverse neural network changes, i.e. lower CC and higher PL values in AD group, leading to a less efficient brain organization. This study suggests the usefulness of our approach to provide further insights into the underlying brain dynamics associated with AD.

Analysis of magnetoencephalography signals from Alzheimer's disease patients using granger causality.

The aim of this study was to analyze resting-state magnetoencephalography (MEG) activity in Alzheimer's disease (AD) by means of Granger Causality (GC), an effective connectivity measure that provides an estimation of the information flow between brain regions. For this task, five minutes of MEG recordings were acquired with a 148-channel whole-head magnetometer from 36 AD patients and 26 healthy controls. Abnormalities in AD connectivity were found in the five typical frequency bands: delta (δ, 1-4 Hz), theta (θ, 4-8 Hz), alpha (α, 8-13 Hz), beta (ß, 13-30 Hz), and gamma (γ, 30-65 Hz). Noteworthy increments in delta band and decrements in beta and gamma bands revealed disrupted connections in AD brain activity. Our analyses suggest that GC may be useful to characterize the brain impairment in AD.