Optimizing b-values schemes for diffusion MRI of the brain with segmented Intravoxel Incoherent Motion (IVIM) model.

PURPOSE: To define an optimal set of b-values for accurate derivation of diffusion MRI parameters in the brain with segmented Intravoxel Incoherent Motion (IVIM) model. METHODS: Simulations of diffusion signals were performed to define an optimal set of b-values targeting different perfusion regimes, by relying on an optimization procedure which minimizes the total relative error on estimated IVIM parameters computed with a segmented fitting procedure. Then, the optimal b-values set was acquired in vivo on healthy subjects and skull base chordoma patients to compare the optimized protocol with a clinical one. RESULTS: The total relative error on simulations decreased of about 40% when adopting the optimal set of 13 b-values (0 10 20 40 50 60 200 300 400 1200 1300 1400 1500 s/mm2 ), showing significant differences and increased precision on D and f estimates with respect to simulations with a non-optimized b-values set. Similarly, in vivo acquisitions demonstrated a dependency of IVIM parameters on the b-values array, with differences between the optimal set of b-values and a clinical non-optimized acquisition. IVIM parameters were compatible to literature values, with D (0.679/0.701 [0.022/0.008] ·10-3 mm2 /s), f (5.49/5.80 [0.70/1.14] %), and D* (8.25/7.67 [0.92/0.83] ·10-3 mm2 /s) median [interquartile range] estimates for white matter/gray matter in volunteers and D (0.709/0.715/1.06 [0.035/0.023/0.271] ·10-3 mm2 /s), f (7.08/7.84/21.54 [1.20/1.06/6.05] %), and D* (10.85/11.84/2.32 [1.38/2.32/4.94] ·10-3 mm2 /s) for white matter/gray matter/Gross Tumor Volume in patients with skull-base chordoma tumor. CONCLUSIONS: The definition of an optimal b-values set can improve the estimation of quantitative IVIM parameters. This allows setting up an optimized approach that can be adopted for IVIM studies in the brain.

Role of diffusion-weighted MRI in recurrent rectal cancer treated with carbon ion radiotherapy.

Aim: To evaluate the association between pretreatment diffusion-weighted MRI (DW-MRI) and 12-month radiological response in locally recurrent rectal cancer treated with carbon ion radiotherapy. Methods: Histogram analysis was performed on pretreatment DW-MRI for patients re-irradiated with carbon ion radiotherapy for local recurrence of rectal cancer. Results: A total of 17 patients were enrolled in the study. Pretreatment DW-MRI b-value of 1000 s/mm2 (b1000) and apparent diffusion coefficient (ADC) lesion median values for 1-year nonresponders (six patients) and responders (11 patients) demonstrated a median (interquartile of median values) of 62.5 (23.9) and 34.0 (13.0) and 953.0 (277.0) and 942.5 (339.0) µm2/s, respectively. All b1000 histogram features (h-features) and ADC h-kurtosis showed statistically significant differences, whereas only b1000 h-median, b1000 h-interquartile range and ADC h-kurtosis demonstrated remarkable diagnostic accuracy. Conclusion: DW-MRI showed promising results in predicting carbon ion radiotherapy outcome in local recurrence of rectal cancer, particularly with regard to b1000 h-median, b1000 h-interquartile range and ADC h-kurtosis.

Carbon ion radiotherapy is a form of advanced radiotherapy that is especially suitable for radioresistant and/or difficult-to-irradiate tumors. In case of recurrence of rectal cancer after pelvic photon beam radiotherapy, carbon ion radiotherapy may be an option. In this study, the authors looked at the potential role of specific MRI sequences performed before treatment to predict response to carbon ion radiotherapy. If confirmed in a larger prospective cohort, the findings of this study may drive clinical decisions toward a more tumor- and patient-tailored therapeutic approach.

Integrating Biological and Radiological Data in a Structured Repository: a Data Model Applied to the COSMOS Case Study.

Integrating the information coming from biological samples with digital data, such as medical images, has gained prominence with the advent of precision medicine. Research in this field faces an ever-increasing amount of data to manage and, as a consequence, the need to structure these data in a functional and standardized fashion to promote and facilitate cooperation among institutions. Inspired by the Minimum Information About BIobank data Sharing (MIABIS), we propose an extended data model which aims to standardize data collections where both biological and digital samples are involved. In the proposed model, strong emphasis is given to the cause-effect relationships among factors as these are frequently encountered in clinical workflows. To test the data model in a realistic context, we consider the Continuous Observation of SMOking Subjects (COSMOS) dataset as case study, consisting of 10 consecutive years of lung cancer screening and follow-up on more than 5000 subjects. The structure of the COSMOS database, implemented to facilitate the process of data retrieval, is therefore presented along with a description of data that we hope to share in a public repository for lung cancer screening research.

Intravoxel incoherent motion as a tool to detect early microstructural changes in meningiomas treated with proton therapy.

PURPOSE: To assess early microstructural changes of meningiomas treated with proton therapy through quantitative analysis of intravoxel incoherent motion (IVIM) and diffusion-weighted imaging (DWI) parameters. METHODS: Seventeen subjects with meningiomas that were eligible for proton therapy treatment were retrospectively enrolled. Each subject underwent a magnetic resonance imaging (MRI) including DWI sequences and IVIM assessments at baseline, immediately before the 1st (t0), 10th (t10), 20th (t20), and 30th (t30) treatment fraction and at follow-up. Manual tumor contours were drawn on T2-weighted images by two expert neuroradiologists and then rigidly registered to DWI images. Median values of the apparent diffusion coefficient (ADC), true diffusion (D), pseudo-diffusion (D*), and perfusion fraction (f) were extracted at all timepoints. Statistical analysis was performed using the pairwise Wilcoxon test. RESULTS: Statistically significant differences from baseline to follow-up were found for ADC, D, and D* values, with a progressive increase in ADC and D in conjunction with a progressive decrease in D*. MRI during treatment showed statistically significant differences in D values between t0 and t20 (p = 0.03) and t0 and t30 (p = 0.02), and for ADC values between t0 and t20 (p = 0.04), t10 and t20 (p = 0.02), and t10 and t30 (p = 0.035). Subjects that showed a volume reduction greater than 15% of the baseline tumor size at follow-up showed early D changes, whereas ADC changes were not statistically significant. CONCLUSION: IVIM appears to be a useful tool for detecting early microstructural changes within meningiomas treated with proton therapy and may potentially be able to predict tumor response.

Convolutional Neural Networks Cascade for Automatic Pupil and Iris Detection in Ocular Proton Therapy.

Eye tracking techniques based on deep learning are rapidly spreading in a wide variety of application fields. With this study, we want to exploit the potentiality of eye tracking techniques in ocular proton therapy (OPT) applications. We implemented a fully automatic approach based on two-stage convolutional neural networks (CNNs): the first stage roughly identifies the eye position and the second one performs a fine iris and pupil detection. We selected 707 video frames recorded during clinical operations during OPT treatments performed at our institute. 650 frames were used for training and 57 for a blind test. The estimations of iris and pupil were evaluated against the manual labelled contours delineated by a clinical operator. For iris and pupil predictions, Dice coefficient (median = 0.94 and 0.97), Szymkiewicz-Simpson coefficient (median = 0.97 and 0.98), Intersection over Union coefficient (median = 0.88 and 0.94) and Hausdorff distance (median = 11.6 and 5.0 (pixels)) were quantified. Iris and pupil regions were found to be comparable to the manually labelled ground truths. Our proposed framework could provide an automatic approach to quantitatively evaluating pupil and iris misalignments, and it could be used as an additional support tool for clinical activity, without impacting in any way with the consolidated routine.

Multi-parametric qualitative and quantitative MRI assessment as predictor of histological grading in previously treated meningiomas.

PURPOSE: Meningiomas are mainly benign tumors, though a considerable proportion shows aggressive behaviors histologically consistent with atypia/anaplasia. Histopathological grading is usually assessed through invasive procedures, which is not always feasible due to the inaccessibility of the lesion or to treatment contraindications. Therefore, we propose a multi-parametric MRI assessment as a predictor of meningioma histopathological grading. METHODS: Seventy-three patients with 74 histologically proven and previously treated meningiomas were retrospectively enrolled (42 WHO I, 24 WHO II, 8 WHO III) and studied with MRI including T2 TSE, FLAIR, Gradient Echo, DWI, and pre- and post-contrast T1 sequences. Lesion masks were segmented on post-contrast T1 sequences and rigidly registered to ADC maps to extract quantitative parameters from conventional DWI and intravoxel incoherent motion model assessing tumor perfusion. Two expert neuroradiologists assessed morphological features of meningiomas with semi-quantitative scores. RESULTS: Univariate analysis showed different distributions (p < 0.05) of quantitative diffusion parameters (Wilcoxon rank-sum test) and morphological features (Pearson's chi-square; Fisher's exact test) among meningiomas grouped in low-grade (WHO I) and higher grade forms (WHO II/III); the only exception consisted of the tumor-brain interface. A multivariate logistic regression, combining all parameters showing statistical significance in the univariate analysis, allowed discrimination between the groups of meningiomas with high sensitivity (0.968) and specificity (0.925). Heterogeneous contrast enhancement and low ADC were the best independent predictors of atypia and anaplasia. CONCLUSION: Our multi-parametric MRI assessment showed high sensitivity and specificity in predicting histological grading of meningiomas. Such an assessment may be clinically useful in characterizing lesions without histological diagnosis. Key points • When surgery and biopsy are not feasible, parameters obtained from both conventional and diffusion-weighted MRI can predict atypia and anaplasia in meningiomas with high sensitivity and specificity. • Low ADC values and heterogeneous contrast enhancement are the best predictors of higher grade meningioma.

Accuracy of low-dose proton CT image registration for pretreatment alignment verification in reference to planning proton CT.

PURPOSE: Proton CT (pCT) has the ability to reduce inherent uncertainties in proton treatment by directly measuring the relative proton stopping power with respect to water, thereby avoiding the uncertain conversion of X-ray CT Hounsfield unit to relative stopping power and the deleterious effect of X- ray CT artifacts. The purpose of this work was to further evaluate the potential of pCT for pretreatment positioning using experimental pCT data of a head phantom. METHODS: The performance of a 3D image registration algorithm was tested with pCT reconstructions of a pediatric head phantom. A planning pCT simulation scan of the phantom was obtained with 200 MeV protons and reconstructed with a 3D filtered back projection (FBP) algorithm followed by iterative reconstruction and a representative pretreatment pCT scan was reconstructed with FBP only to save reconstruction time. The pretreatment pCT scan was rigidly transformed by prescribing random errors with six degrees of freedom or deformed by the deformation field derived from a head and neck cancer patient to the pretreatment pCT reconstruction, respectively. After applying the rigid or deformable image registration algorithm to retrieve the original pCT image before transformation, the accuracy of the registration was assessed. To simulate very low-dose imaging for patient setup, the proton CT images were reconstructed with 100%, 50%, 25%, and 12.5% of the total number of histories of the original planning pCT simulation scan, respectively. RESULTS: The residual errors in image registration were lower than 1 mm and 1° of magnitude regardless of the anatomic directions and imaging dose. The mean residual errors ranges found for rigid image registration were from -0.29 ± 0.09 to 0.51 ± 0.50 mm for translations and from -0.05 ± 0.13 to 0.08 ± 0.08 degrees for rotations. The percentages of sub-millimetric errors found, for deformable image registration, were between 63.5% and 100%. CONCLUSION: This experimental head phantom study demonstrated the potential of low-dose pCT imaging for 3D image registration. Further work is needed to confirm the value pCT for pretreatment image-guided proton therapy.

Target position reproducibility in left-breast irradiation with deep inspiration breath-hold using multiple optical surface control points.

The aim of this study was to investigate the use of 3D optical localization of multiple surface control points for deep inspiration breath-hold (DIBH) guidance in left-breast radiotherapy treatments. Ten left-breast cancer patients underwent whole-breast DIBH radiotherapy controlled by the Real-time Position Management (RPM) system. The reproducibility of the tumor bed (i.e., target) was assessed by the position of implanted clips, acquired through in-room kV imaging. Six to eight passive fiducials were positioned on the patients' thoraco-abdominal surface and localized intrafractionally by means of an infrared 3D optical tracking system. The point-based registration between treatment and planning fiducials coordinates was applied to estimate the interfraction variations in patients' breathing baseline and to improve target reproducibility. The RPM-based DIBH control resulted in a 3D error in target reproducibility of 5.8 ± 3.4 mm (median value ± interquartile range) across all patients. The reproducibility errors proved correlated with the interfraction baseline variations, which reached 7.7 mm for the single patient. The contribution of surface fiducials registration allowed a statistically significant reduction (p < 0.05) in target localization errors, measuring 3.4 ± 1.7 mm in 3D. The 3D optical monitoring of multiple surface control points may help to optimize the use of the RPM system for improving target reproducibility in left-breast DIBH irradiation, providing insights on breathing baseline variations and increasing the robustness of external surrogates for DIBH guidance.

Role of interim 18F-FDG-PET/CT for the early prediction of clinical outcomes of Non-Small Cell Lung Cancer (NSCLC) during radiotherapy or chemo-radiotherapy. A systematic review.

BACKGROUND: Non-Small Cell Lung Cancer (NSCLC) is characterized by aggressiveness and includes the majority of thorax malignancies. The possibility of early stratification of patients as responsive and non-responsive to radiotherapy with a non-invasive method is extremely appealing. The distribution of the Fluorodeoxyglucose (18F-FDG) in tumours, provided by Positron-Emission-Tomography (PET) images, has been proved to be useful to assess the initial staging of the disease, recurrence, and response to chemotherapy and chemo-radiotherapy (CRT). OBJECTIVES: In the last years, particular efforts have been focused on the possibility of using ad interim 18F-FDG PET (FDGint) to evaluate response already in the course of radiotherapy. However, controversial findings have been reported for various malignancies, although several results would support the use of FDGint for individual therapeutic decisions, at least in some pathologies. The objective of the present review is to assemble comprehensively the literature concerning NSCLC, to evaluate where and whether FDGint may offer predictive potential. METHODS: Several searches were completed on Medline and the Embase database, combining different keywords. Original papers published in the English language from 2005 to 2016 with studies involving FDGint in patients affected by NSCLC and treated with radiation therapy or chemo-radiotherapy only were chosen. RESULTS: Twenty-one studies out of 970 in Pubmed and 1256 in Embase were selected, reporting on 627 patients. CONCLUSION: Certainly, the lack of univocal PET parameters was identified as a major drawback, while standardization would be required for best practice. In any case, all these papers denoted FDGint as promising and a challenging examination for early assessment of outcomes during CRT, sustaining its predictivity in lung cancer.

MRI quantification of pancreas motion as a function of patient setup for particle therapy -a preliminary study.

Particle therapy (PT) has shown positive therapeutic results in local control of locally advanced pancreatic lesions. PT effectiveness is highly influenced by target localization accuracy both in space, since the pancreas is located in proximity to radiosensitive vital organs, and in time as it is subject to substantial breathing-related motion. The purpose of this preliminary study was to quantify pancreas range of motion under typical PT treatment conditions. Three common immobilization devices (vacuum cushion, thermoplastic mask, and compressor belt) were evaluated on five male patients in prone and supine positions. Retrospective four-dimensional magnetic resonance imaging data were reconstructed for each condition and the pancreas was manually segmented on each of six breathing phases. A k-means algorithm was then applied on the manually segmented map in order to obtain clusters representative of the three pancreas segments: head, body, and tail. Centers of mass (COM) for the pancreas and its segments were computed, as well as their displacements with respect to a reference breathing phase (beginning exhalation). The median three-dimensional COM displacements were in the range of 3 mm. Latero-lateral and superior-inferior directions had a higher range of motion than the anterior-posterior direction. Motion analysis of the pancreas segments showed slightly lower COM displacements for the head cluster compared to the tail cluster, especially in prone position. Statistically significant differences were found within patients among the investigated setups. Hence a patient-specific approach, rather than a general strategy, is suggested to define the optimal treatment setup in the frame of a millimeter positioning accuracy.

Optimal marker placement in hadrontherapy: intelligent optimization strategies with augmented Lagrangian pattern search.

PURPOSE: In high precision photon radiotherapy and in hadrontherapy, it is crucial to minimize the occurrence of geometrical deviations with respect to the treatment plan in each treatment session. To this end, point-based infrared (IR) optical tracking for patient set-up quality assessment is performed. Such tracking depends on external fiducial points placement. The main purpose of our work is to propose a new algorithm based on simulated annealing and augmented Lagrangian pattern search (SAPS), which is able to take into account prior knowledge, such as spatial constraints, during the optimization process. MATERIAL AND METHODS: The SAPS algorithm was tested on data related to head and neck and pelvic cancer patients, and that were fitted with external surface markers for IR optical tracking applied for patient set-up preliminary correction. The integrated algorithm was tested considering optimality measures obtained with Computed Tomography (CT) images (i.e. the ratio between the so-called target registration error and fiducial registration error, TRE/FRE) and assessing the marker spatial distribution. Comparison has been performed with randomly selected marker configuration and with the GETS algorithm (Genetic Evolutionary Taboo Search), also taking into account the presence of organs at risk. RESULTS: The results obtained with SAPS highlight improvements with respect to the other approaches: (i) TRE/FRE ratio decreases; (ii) marker distribution satisfies both marker visibility and spatial constraints. We have also investigated how the TRE/FRE ratio is influenced by the number of markers, obtaining significant TRE/FRE reduction with respect to the random configurations, when a high number of markers is used. CONCLUSIONS: The SAPS algorithm is a valuable strategy for fiducial configuration optimization in IR optical tracking applied for patient set-up error detection and correction in radiation therapy, showing that taking into account prior knowledge is valuable in this optimization process. Further work will be focused on the computational optimization of the SAPS algorithm toward fast point-of-care applications.

An image-based method to synchronize cone-beam CT and optical surface tracking.

The integration of in-room X-ray imaging and optical surface tracking has gained increasing importance in the field of image guided radiotherapy (IGRT). An essential step for this integration consists of temporally synchronizing the acquisition of X-ray projections and surface data. We present an image-based method for the synchronization of cone-beam computed tomography (CBCT) and optical surface systems, which does not require the use of additional hardware. The method is based on optically tracking the motion of a component of the CBCT/gantry unit, which rotates during the acquisition of the CBCT scan. A calibration procedure was implemented to relate the position of the rotating component identified by the optical system with the time elapsed since the beginning of the CBCT scan, thus obtaining the temporal correspondence between the acquisition of X-ray projections and surface data. The accuracy of the proposed synchronization method was evaluated on a motorized moving phantom, performing eight simultaneous acquisitions with an Elekta Synergy CBCT machine and the AlignRT optical device. The median time difference between the sinusoidal peaks of phantom motion signals extracted from the synchronized CBCT and AlignRT systems ranged between -3.1 and 12.9 msec, with a maximum interquartile range of 14.4 msec. The method was also applied to clinical data acquired from seven lung cancer patients, demonstrating the potential of the proposed approach in estimating the individual and daily variations in respiratory parameters and motion correlation of internal and external structures. The presented synchronization method can be particularly useful for tumor tracking applications in extracranial radiation treatments, especially in the field of patient-specific breathing models, based on the correlation between internal tumor motion and external surface surrogates.

Reproducibility of the external surface position in left-breast DIBH radiotherapy with spirometer-based monitoring.

Deep inspiration breath hold (DIBH) in left-sided breast cancer radiotherapy treatments allows for a reduction in cardiac and pulmonary doses without compromising target coverage. The selection of the most appropriate technology for DIBH monitoring is a crucial issue. We evaluated the stability and reproducibility of DIBHs controlled by a spirometric device, by assessing the variability of the external surface position within a single DIBH (intra-DIBH) and between DIBHs performed in the same treatment session (intrafraction) or in different sessions (interfraction). The study included seven left-breast cancer patients treated with spirometer-based DIBH radiotherapy. Infrared optical tracking was used to record the 3D coordinates of seven to eleven passive markers placed on the patient's thoraco-abdominal surface during 29-43 DIBHs performed in six to eight treatment sessions. The obtained results showed displacements of the external surface between different sessions up to 6.3mm along a single direction, even at constant inspired volumes. The median value of the interfraction variability in the position of breast passive markers was 2.9 mm (range 1.9-4.8 mm) in the latero-lateral direction, 3.6 mm (range 2.2-4.6mm) in the antero-posterior direction, and 4.3mm (range 2.8-6.2 mm) in the cranio-caudal direction. There were no significant dose distribution variations for target and organs at risk with respect to the treatment plan, confirming the adequacy of the applied clinical margins (15 mm) to compensate for the measured setup uncertainties. This study demonstrates that spirometer-based control does not guarantee a stable and reproducible position of the external surface in left-breast DIBH radiotherapy, suggesting the need for more robust DIBH monitoring techniques when reduced margins and setup uncertainties are required for improving normal tissue sparing and decreasing cardiac and pulmonary toxicity.

Proton beam radiotherapy: report of the first ten patients treated at the "Centro Nazionale di Adroterapia Oncologica (CNAO)" for skull base and spine tumours.

PURPOSE: The Italian National Centre for Oncological Hadrontherapy (Centro Nazionale di Adroterapia Oncologica, CNAO), equipped with a proton and ion synchrotron, started clinical activity in September 2011. The clinical and technical characteristics of the first ten proton beam radiotherapy treatments are reported. MATERIALS AND METHODS: Ten patients, six males and four females (age range 27-73 years, median 55.5), were treated with proton beam radiotherapy. After one to two surgical procedures, seven patients received a histological diagnosis of chordoma (of the skull base in three cases, the cervical spine in one case and the sacrum in three cases) and three of low-grade chondrosarcoma (skull base). Prescribed doses were 74 GyE for chordoma and 70 GyE for chondrosarcoma at 2 GyE/fraction delivered 5 days per week. RESULTS: Treatment was well tolerated without toxicity-related interruptions. The maximal acute toxicity was grade 2, with oropharyngeal mucositis, nausea and vomiting for the skull base tumours, and grade 2 dermatitis for the sacral tumours. After 6-12 months of follow-up, no patient developed tumour progression. CONCLUSIONS: The analysis of the first ten patients treated with proton therapy at CNAO showed that this treatment was feasible and safe. Currently, patient accrual into these as well as other approved protocols is continuing, and a longer follow-up period is needed to assess tumour control and late toxicity.

Feasibility of proton dosimetry overriding planning CT with daily CBCT elaborated through generative artificial intelligence tools.

Radiotherapy commonly utilizes cone beam computed tomography (CBCT) for patient positioning and treatment monitoring. CBCT is deemed to be secure for patients, making it suitable for the delivery of fractional doses. However, limitations such as a narrow field of view, beam hardening, scattered radiation artifacts, and variability in pixel intensity hinder the direct use of raw CBCT for dose recalculation during treatment. To address this issue, reliable correction techniques are necessary to remove artifacts and remap pixel intensity into Hounsfield Units (HU) values. This study proposes a deep-learning framework for calibrating CBCT images acquired with narrow field of view (FOV) systems and demonstrates its potential use in proton treatment planning updates. Cycle-consistent generative adversarial networks (cGAN) processes raw CBCT to reduce scatter and remap HU. Monte Carlo simulation is used to generate CBCT scans, enabling the possibility to focus solely on the algorithm's ability to reduce artifacts and cupping effects without considering intra-patient longitudinal variability and producing a fair comparison between planning CT (pCT) and calibrated CBCT dosimetry. To showcase the viability of the approach using real-world data, experiments were also conducted using real CBCT. Tests were performed on a publicly available dataset of 40 patients who received ablative radiation therapy for pancreatic cancer. The simulated CBCT calibration led to a difference in proton dosimetry of less than 2%, compared to the planning CT. The potential toxicity effect on the organs at risk decreased from about 50% (uncalibrated) up the 2% (calibrated). The gamma pass rate at 3%/2 mm produced an improvement of about 37% in replicating the prescribed dose before and after calibration (53.78% vs 90.26%). Real data also confirmed this with slightly inferior performances for the same criteria (65.36% vs 87.20%). These results may confirm that generative artificial intelligence brings the use of narrow FOV CBCT scans incrementally closer to clinical translation in proton therapy planning updates.

Retrospective reconstruction of four-dimensional magnetic resonance from interleaved cine imaging - A comparative study with four-dimensional computed tomography in the lung.

Background and purpose: Imaging of respiration-induced anatomical changes is essential to ensure high accuracy in radiotherapy of lung cancer. We expanded here on methods for retrospective reconstruction of time-resolved volumetric magnetic resonance (4DMR) of the thoracic region and benchmarked the results against 4D computed tomography (4DCT). Materials and method: MR data of six lung cancer patients were collected by interleaving cine-navigator images with 2D data frame images, acquired across the thorax. The data frame images have been stacked in volumes based on a similarity metric that considers the anatomical deformation of lungs, while addressing ambiguities in respiratory phase detection and interpolation of missing data. The resulting images were validated against cine-navigator images and compared to paired 4DCTs in terms of amplitude and period of motion, assessing differences in internal target volume (ITV) margin definition. Results: 4DMR-based motion amplitude was on average within 1.8 mm of that measured in the corresponding 2D cine-navigator images. In our dataset, the 4DCT motion and the 4DMR median amplitude were always within 3.8 mm. The median period was generally close to CT references, although deviations up to 24 % have been observed. These changes were reflected in the ITV, which was generally larger for MRI than for 4DCT (up to 39.7 %). Conclusions: The proposed algorithm for retrospective reconstruction of time-resolved volumetric MR provided quality anatomical images with high temporal resolution for motion modelling and treatment planning. The potential for imaging organ motion variability makes 4DMR a valuable complement to standard 4DCT imaging.

Dosimetric assessment of a novel metal artifact reduction method in CT images.

The aim of this study was to assess the ability of metal artifact reduction (MAR) algorithm in restoring the CT image quality while correcting the tissue density information for the accurate estimation of the absorbed dose. A phantom filled with titanium (low-Z metal) and Cerrobend (high-Z metal) inserts was used for this purpose. The MAR algorithm was applied to phantom's CT dataset. Static intensity-modulated radiation therapy (IMRT) plans, including five beam angles, were designed and optimized on the uncorrected images to deliver 10 Gy on the simulated target. Monte Carlo dose calculation was computed on uncorrected, corrected, and ground truth image datasets. It was firstly verified that MAR methodology was able to correct HU errors due to the metal presence. In the worst situation (high-Z phantom), the image difference, uncorrected ground truth and corrected ground truth, went from -4.4 ± 118.8 HU to 0.4 ± 10.8 HU, respectively. Secondly, it was observed that the impact of dose errors estimation depends on the atomic number of the metal: low-Z inserts do not produce significant dose inaccuracies, while high-Z implants substantially influence the computation of the absorbed dose. In this latter case, dose errors in the PTV region were up to 23.56% (9.72% mean value) when comparing the uncorrected vs. the ground truth dataset. After MAR correction, errors dropped to 0.11% (0.10% mean value). In conclusion, it was assessed that the new MAR algorithm is able to restore image quality without distorting mass density information, thus producing a more accurate dose estimation.

An adaptive fuzzy prediction model for real time tumor tracking in radiotherapy via external surrogates.

In the radiation treatment of moving targets with external surrogates, information on tumor position in real time can be extracted by using accurate correlation models. A fuzzy environment is proposed here to correlate input surrogate data with tumor motion estimates in real time. In this study, two different data clustering approaches were analyzed due to their substantial effects on the fuzzy modeler performance. Moreover, a comparative investigation was performed on two fuzzy-based and one neuro-fuzzy-based inference systems with respect to state-of-the-art models. Finally, due to the intrinsic interpatient variability in fuzzy models' performance, a model selectivity algorithm was proposed to select an adaptive fuzzy modeler on a case-by-case basis. The performance of multiple and adaptive fuzzy logic models were retrospectively tested in 20 patients treated with CyberKnife real-time tumor tracking. Final results show that activating adequate model selection of our fuzzy-based modeler can significantly reduce tumor tracking errors.

Deep inspiration breath-hold technique guided by an opto- electronic system for extracranial stereotactic treatments.

The purpose of this work was to evaluate the intrapatient tumor position reproducibility in a deep inspiration breath-hold (DIBH) technique based on two infrared optical tracking systems, ExacTrac and ELITETM, in stereotactic treatment of lung and liver lesions. After a feasibility study, the technique was applied to 15 patients. Each patient, provided with a real-time visual feedback of external optical marker displacements, underwent a full DIBH, a free-breathing (FB), and three consecutive DIBH CT-scans centered on the lesion to evaluate the tumor position reproducibility. The mean reproducibility of tumor position during repeated DIBH was 0.5 ± 0.3 mm in laterolateral (LL), 1.0 ± 0.9 mm in anteroposterior (AP), and 1.4 ± 0.9 mm in craniocaudal (CC) direction for lung lesions, and 1.0 ± 0.6 mm in LL, 1.1 ± 0.5 mm in AP, and 1.2 ± 0.4 mm in CC direction for liver lesions. Intra- and interbreath-hold reproducibility during treatment, as determined by optical markers displacements, was below 1 mm and 3 mm, respectively, in all directions for all patients. Optically-guided DIBH technique provides a simple noninvasive method to minimize breathing motion for collaborative patients. For each patient, it is important to ensure that the tumor position is reproducible with respect to the external markers configuration.

Comparative assessment of 3D surface scanning systems in breast plastic and reconstructive surgery.

In this work, we compared accuracy, repeatability, and usability in breast surface imaging of 2 commercial surface scanning systems and a hand-held laser surface scanner prototype coupled with a patient's motion acquisition and compensation methodology. The accuracy of the scanners was assessed on an anthropomorphic phantom, and to evaluate the usability of the scanners on humans, thorax surface images of 3 volunteers were acquired. Both the intrascanner repeatability and the interscanner comparative accuracy were assessed. The results showed surface-to-surface distance errors inferior to 1 mm and to 2 mm, respectively, for the 2 commercial scanners and for the prototypical one. Moreover, comparable performances of the 3 scanners were found when used for acquiring the breast surface. On the whole, this study demonstrated that handheld laser surface scanners coupled with subject motion compensation methods lend themselves as competitive technologies for human body surface modeling.