Motion analysis comparing surface imaging and diaphragm tracking on kV projections for deep inspiration breath hold (DIBH).

BACKGROUND: Surface-guided imaging (SGI) is increasingly utilized to monitor patient motion during deep inspiration breath hold (DIBH) in radiotherapy. Understanding the association between surface and internal motion is crucial for effective monitoring. PURPOSE: To investigate the relation between motion detected by SGI using surface-guided radiotherapy (SGRT) and internal motion measured through diaphragm tracking on kV projections acquired with DIBH for online CBCT. METHODS: Both SGI and kV were simultaneously acquired for ten patients over a total of 200 breath holds (BH). Diaphragm tracking was performed using second-degree polynomial curve fitting on the derivative images for each kV projection and high-pass filtering at 1/30 Hz to remove rotational effects. The superior-inferior (SI) and anterior-posterior (AP) motions of SGI were then compared to kV tracking using various statistical measures. RESULTS: The correlation (individuals' median: -0.07 to 0.73) was a suboptimal metric for the BH data. The median and 95th percentile absolute differences between SGI-SI and kV were 0.73 mm and 3.46 mm, respectively, during DIBH. For SGI-AP, the corresponding values were 0.55 mm and 2.80 mm. For inter-BH measurements, the contingency table based on a 3 mm threshold indicated surface/diaphragm motion agreement for SGI-SI/kV and SGI-AP/kV was 61 % and 56 %, respectively. CONCLUSION: Both intra- and inter-BH measurements indicated a limited association between surface and diaphragm motion, with certain constraints noted due to kV tracking and DIBH data. These findings warrant further investigation into the association between surface and internal motion.

Auto-delineation of treatment target volume for radiation therapy using large language model-aided multimodal learning.

PURPOSE: Artificial intelligence (AI)-aided methods have made significant progress in the auto-delineation of normal tissues. However, these approaches struggle with the auto-contouring of radiotherapy target volume. Our goal is to model the delineation of target volume as a clinical decision-making problem, resolved by leveraging large language model-aided multimodal learning approaches. METHODS AND MATERIALS: A vision-language model, termed Medformer, has been developed, employing the hierarchical vision transformer as its backbone, and incorporating large language models to extract text-rich features. The contextually embedded linguistic features are seamlessly integrated into visual features for language-aware visual encoding through the visual language attention module. Metrics, including Dice similarity coefficient (DSC), intersection over union (IOU), and 95th percentile Hausdorff distance (HD95), were used to quantitatively evaluate the performance of our model. The evaluation was conducted on an in-house prostate cancer dataset and a public oropharyngeal carcinoma (OPC) dataset, totaling 668 subjects. RESULTS: Our Medformer achieved a DSC of 0.81 ± 0.10 versus 0.72 ± 0.10, IOU of 0.73 ± 0.12 versus 0.65 ± 0.09, and HD95 of 9.86 ± 9.77 mm versus 19.13 ± 12.96 mm for delineation of gross tumor volume (GTV) on the prostate cancer dataset. Similarly, on the OPC dataset, it achieved a DSC of 0.77 ± 0.11 versus 0.72 ± 0.09, IOU of 0.70 ± 0.09 versus 0.65 ± 0.07, and HD95 of 7.52 ± 4.8 mm versus 13.63 ± 7.13 mm, representing significant improvements (p < 0.05). For delineating the clinical target volume (CTV), Medformer achieved a DSC of 0.91 ± 0.04, IOU of 0.85 ± 0.05, and HD95 of 2.98 ± 1.60 mm, comparable to other state-of-the-art algorithms. CONCLUSIONS: Auto-delineation of the treatment target based on multimodal learning outperforms conventional approaches that rely purely on visual features. Our method could be adopted into routine practice to rapidly contour CTV/GTV.

Stereotactic Radiosurgery for Residual, Recurrent, and Metastatic Hemangiopericytomas: A Single-Institution Retrospective Experience.

BACKGROUND AND OBJECTIVES: Hemangiopericytomas are infrequent vascular tumors originating from Zimmermann pericytes. The conventional treatment involves gross total resection, followed by adjuvant radiotherapy. Nevertheless, their tendency to infiltrate dural sinuses, high vascularity, and anatomic complexity pose challenges for radical resection, leading to a significant risk of recurrence. Stereotactic radiosurgery (SRS) has emerged as a promising adjuvant therapy to address these challenges. Our study provides the largest single-institutional retrospective, aiming to evaluate the effectiveness and safety of SRS as a treatment modality for residual, recurrent, and metastatic hemangiopericytomas. METHODS: From 1998 to 2023, 27 patients with 101 tumors underwent CyberKnife SRS at Stanford University Medical Center. The median age was 51 years at the time of treatment. The median follow-up period from SRS was 103 months (range: 6-250). All patients underwent upfront surgical resection. The median tumor volume was 1.5 cc. The median single-fraction equivalent dose was 19 Gy. The SRS was administered at the 76% of the median isodose line (range: 64-89). RESULTS: Of the 101 treated tumors, 24 (23.8%) progressed with a median time to recurrence of 30 months. At 10 years, the rates of local tumor control (LTC), overall survival (OS), and progression-free survival (PFS) were 74.3%, 80.8%, and 67%, respectively. In patients with metastatic lesions, the LTC rates were significantly greater when compared with those with residual or recurrent tumors. There was no significant difference between patients with residual, recurrent, and metastatic hemangiopericytomas in OS and PFS. Notably, no cases of radiation-induced adverse events were detected. CONCLUSION: SRS leads to excellent LTC, PFS, and OS at 10 years with negligible risk for adverse events. Therefore, it is an effective and safe management modality for patients with residual, recurrent, and metastatic hemangiopericytomas.

The Role of CyberKnife Stereotactic Radiosurgery in Recurrent Cranial Medulloblastomas across Pediatric and Adult Populations.

Background/Objectives: Medulloblastoma is the most common malignant brain tumor in children. In recent decades, the therapeutic landscape has undergone significant changes, with stereotactic radiosurgery (SRS) emerging as a promising treatment for recurrent cases. Our study provides a comprehensive analysis of the long-term efficacy and safety of SRS in recurrent medulloblastomas across both pediatric and adult patients at a single institution. Methods: We retrospectively reviewed the clinical and radiological records of patients who underwent CyberKnife SRS for recurrent cranial medulloblastomas at our institution between 1998 and 2023. Follow-up data were available for 15 medulloblastomas in 10 patients. The cohort comprised eight pediatric patients (ages 3-18) and two adult patients (ages 19-75). The median age at the time of SRS was 13 years, the median tumor volume accounted for 1.9 cc, the median biologically equivalent dose (BED) was 126 Gy, and the single-fraction equivalent dose (SFED) was 18 Gy. The SRS was administered at 75% of the median isodose line. Results: Following a median follow-up of 39 months (range: 6-78), 53.3% of the medulloblastomas progressed, 13.3% regressed, and 33.3% remained stable. The 3-year local tumor control (LTC) rate for all medulloblastomas was 65%, with lower rates observed in the adult cohort (50%) and higher rates in pediatric patients (67%). The 3-year overall survival (OS) rate was 70%, with significantly higher rates in pediatric patients (75%) compared to adult patients (50%). The 3-year progression-free survival (PFS) rate was 58.3%, with higher rates in pediatric patients (60%) compared to adult patients (50%). Two pediatric patients developed radiation-induced edema, while two adult patients experienced radiation necrosis at the latest follow-up, with both adult patients passing away. Conclusions: Our study provides a complex perspective on the efficacy and safety of CyberKnife SRS in treating recurrent cranial medulloblastomas across pediatric and adult populations. The rarity of adverse radiation events (AREs) underscores the safety profile of SRS, reinforcing its role in enhancing treatment outcomes. The intricacies of symptomatic outcomes, intertwined with factors such as age, tumor location, and prior surgeries, emphasize the need for personalized treatment approaches. Our findings underscore the imperative for ongoing research and the development of more refined treatment strategies for recurrent medulloblastomas. Given the observed disparities in treatment outcomes, a more meticulous tailoring of treatment approaches becomes crucial.

Where Does Auto-Segmentation for Brain Metastases Radiosurgery Stand Today?

Detection and segmentation of brain metastases (BMs) play a pivotal role in diagnosis, treatment planning, and follow-up evaluations for effective BM management. Given the rising prevalence of BM cases and its predominantly multiple onsets, automated segmentation is becoming necessary in stereotactic radiosurgery. It not only alleviates the clinician's manual workload and improves clinical workflow efficiency but also ensures treatment safety, ultimately improving patient care. Recent strides in machine learning, particularly in deep learning (DL), have revolutionized medical image segmentation, achieving state-of-the-art results. This review aims to analyze auto-segmentation strategies, characterize the utilized data, and assess the performance of cutting-edge BM segmentation methodologies. Additionally, we delve into the challenges confronting BM segmentation and share insights gleaned from our algorithmic and clinical implementation experiences.

Stereotactic Radiosurgery for Ependymoma in Pediatric and Adult Patients: A Single-Institution Experience.

BACKGROUND AND OBJECTIVES: Ependymoma is commonly classified as World Health Organization grade 2 with the anaplastic variant categorized as grade 3. Incomplete resection or anaplastic features can result in unfavorable outcomes. Stereotactic radiosurgery (SRS) provides a minimally invasive approach for recurrent ependymomas. Our study investigates the efficacy and safety of SRS for grade 2 and 3 ependymomas in pediatric and adult populations. METHODS: We conducted a retrospective analysis on 34 patients with 75 ependymomas after CyberKnife SRS between 1998 and 2023. Fourteen were pediatric (3-18 years), and 20 were adult (19-75 years) patients. The median age was 21 years, and the median tumor volume was 0.64 cc. The median single-fraction equivalent dose was 16.6 Gy, with SRS administered at 77% of the median isodose line. RESULTS: After a median follow-up of 42.7 months (range: 3.8-438.3), 22.7% of ependymomas progressed. The 5-year local tumor control rate was 78.1%, varying between 59.6% and 90.2% for children and adults, with grade 2 at 85.9% compared with 58.5% for grade 3 tumors. The 5-year overall survival rate was 73.6%, notably higher in adults (94.7%) than in children (41%), and 100% for grade 2 but decreased to 35.9% for grade 3 patients. The 5-year progression-free survival rate was 68.5%, with 78.3% and 49.2% for adults and children, respectively, and a favorable 88.8% for grade 2, contrasting with 32.6% for grade 3 patients. Symptom improvement was observed in 85.3% of patients. Adverse radiation effects occurred in 21.4% of pediatric patients. CONCLUSION: Our study supports SRS as a viable modality for pediatric and adult patients with grade 2 and 3 ependymomas. Despite lower local tumor control in pediatric and grade 3 cases, integrating SRS holds promise for improved outcomes. Emphasizing careful patient selection, personalized treatment planning, and long-term follow-up is crucial for optimal neurosurgical outcomes.

Online quantification of nicotine in e-cigarette aerosols by vacuum ultraviolet photoionization mass spectrometry.

The growing popularity of e-cigarettes and the associated risks of nicotine addiction present a new challenge to global public health security. Measuring the nicotine levels in e-cigarette aerosols is essential to assess the safety of e-cigarettes. In this study, a rapid in situ method was developed for online quantification of nicotine in e-cigarette aerosols by using a homemade vacuum ultraviolet photoionization aerosol mass spectrometer (VUV-AMS). E-cigarette liquids with different nicotine concentrations were prepared to generate aerosols containing different levels of nicotine, which were employed as the calibration sources for nicotine quantification by VUV-AMS. The results showed that the mass concentration of nicotine in e-cigarette aerosols has a good linear relationship with its signal intensity in the mass spectrum, and the limits of detection and quantitation of nicotine by VUV-AMS were found to be 2.0 and 6.2 µg per puff respectively. Then the online method was utilized to measure five commercial e-cigarettes, and their nicotine yields were determined to be between 31 and 188 µg per puff with the nicotine fluxes from 7.7 to 70 µg s-1, agreeing with the results of the gas chromatography with a flame ionization detector (GC-FID). This study demonstrated the feasibility and advantages of VUV-AMS for quick quantification of nicotine in e-cigarette aerosols within seconds.

Exploring Deep Learning for Estimating the Isoeffective Dose of FLASH Irradiation From Mouse Intestinal Histological Images.

PURPOSE: Ultrahigh-dose-rate (FLASH) irradiation has been reported to reduce normal tissue damage compared with conventional dose rate (CONV) irradiation without compromising tumor control. This proof-of-concept study aims to develop a deep learning (DL) approach to quantify the FLASH isoeffective dose (dose of CONV that would be required to produce the same effect as the given physical FLASH dose) with postirradiation mouse intestinal histology images. METHODS AND MATERIALS: Eighty-four healthy C57BL/6J female mice underwent 16 MeV electron CONV (0.12 Gy/s; n = 41) or FLASH (200 Gy/s; n = 43) single fraction whole abdominal irradiation. Physical dose ranged from 12 to 16 Gy for FLASH and 11 to 15 Gy for CONV in 1 Gy increments. Four days after irradiation, 9 jejunum cross-sections from each mouse were hematoxylin and eosin stained and digitized for histological analysis. CONV data set was randomly split into training (n = 33) and testing (n = 8) data sets. ResNet101-based DL models were retrained using the CONV training data set to estimate the dose based on histological features. The classical manual crypt counting (CC) approach was implemented for model comparison. Cross-section-wise mean squared error was computed to evaluate the dose estimation accuracy of both approaches. The validated DL model was applied to the FLASH data set to map the physical FLASH dose into the isoeffective dose. RESULTS: The DL model achieved a cross-section-wise mean squared error of 0.20 Gy2 on the CONV testing data set compared with 0.40 Gy2 of the CC approach. Isoeffective doses estimated by the DL model for FLASH doses of 12, 13, 14, 15, and 16 Gy were 12.19 ± 0.46, 12.54 ± 0.37, 12.69 ± 0.26, 12.84 ± 0.26, and 13.03 ± 0.28 Gy, respectively. CONCLUSIONS: Our proposed DL model achieved accurate CONV dose estimation. The DL model results indicate that in the physical dose range of 13 to 16 Gy, the biologic dose response of small intestinal tissue to FLASH irradiation is represented by a lower isoeffective dose compared with the physical dose. Our DL approach can be a tool for studying isoeffective doses of other radiation dose modifying interventions.

Stereotactic Radiosurgery for Cranial and Spinal Hemangioblastomas: A Single-Institution Retrospective Series.

BACKGROUND AND OBJECTIVES: Stereotactic radiosurgery (SRS) has been an attractive treatment modality for both cranial and spinal hemangioblastomas, especially for multiple lesions commonly associated with von Hippel-Lindau (VHL) disease. This study aims to provide the largest long-term analysis of treatment efficacy and adverse effects of SRS for cranial and spinal hemangioblastomas at a single institution. METHODS: We evaluated the clinical and radiological outcomes of patients with hemangioblastomas treated with CyberKnife SRS at our institute from 1998 to 2022. The follow-up data were available for 135 hemangioblastomas in 35 patients. Twenty-eight patients had 123 hemangioblastomas associated with VHL, and 7 had 12 sporadic hemangioblastomas. The median age was 36 years, and the median tumor volume accounted for 0.4 cc. The SRS was administered with the median single-fraction equivalent dose of 18 Gy to the 77% median isodose line. RESULTS: At a median follow-up of 57 months (range: 3-260), only 20 (16.2%) of the VHL-associated and 1 (8.3%) sporadic hemangioblastomas progressed. The 5-year local tumor control rate was 91.3% for all hemangioblastomas, 91.7% among the sporadic lesions, and 92.9% in patients with VHL. SRS improved tumor-associated symptoms of 98 (74.8%) of 131 symptomatic hemangioblastomas, including headache, neck pain, dizziness, visual disturbances, dysesthesia, ataxia, motor impairment, seizures, and dysphagia. Two patients developed radiation necrosis (5.7%), and 1 of them required surgical resection. CONCLUSION: SRS is a safe and effective treatment option for patients with hemangioblastomas in critical locations, such as the brainstem, cervicomedullary junction, and spinal cord, and in patients with multiple hemangioblastomas associated with VHL disease.

Considerations for intensity modulated total body or total marrow and lymphoid irradiation.

We compiled a sampling of the treatment techniques of intensity-modulated total body irradiation, total marrow irradiation and total marrow and lymphoid irradiation utilized by several centers across North America and Europe. This manuscript does not serve as a consensus guideline, but rather is meant to serve as a convenient reference for centers that are considering starting an intensity-modulated program.

Angular correction methodology and characterization of a high-resolution CMOS array for patient specific quality assurance on a robotic arm linac.

PURPOSE: To develop an angular correction methodology and characterize a high-resolution complementary metal-oxide-semiconductor (CMOS) array for patient specific quality assurance on a robotic arm linear accelerator. METHODS: Beam path files from the treatment planning software (TPS) were used to calculate the angle of radiation beam with respect to the detector plane. Beams from multiple discrete angles were delivered to the CMOS detector array and an angular dependency look up table (LUT) was created. The LUT was then used to correct for the angular dependency of the detector. An iso-centric 5 mm fixed cone, non iso-centric multi-target fixed cone, 10 mm Iris and a multi-leaf collimator (MLC) based collimated plan were delivered to the phantom and compared to the TPS with and without angular correction applied. Additionally, the CMOS array was compared to gafchromic film and a diode array. RESULTS: Large errors of up to 30% were observed for oblique angles. When angular correction was applied, the gamma passing rate increased from 99.2% to 100% (average gamma value decreased from 0.29 to 0.14) for the 5-mm iso-centric cone plan. Similarly, the passing rate increased from 84.0% to 100% for the Iris plan and from 49.98% to 98.4% for the MLC plan when angular correction was applied. For the multi-target plan, applying angular correction improved the gamma passing rate from 94% to 99.6%. The 5 mm iso-centric fixed cone plan was also delivered to film, and the gamma passing rate was 91.3% when using gafchromic film as the reference dataset, whereas the diode array provided insufficient sampling for this plan. CONCLUSION: A methodology of calculating the beam angle based on the beam path files was developed and validated. The array was demonstrated to be superior to other quality assurance tools because of its sub-millimeter spatial resolution and immediate read out of the results.

A deep learning approach for automatic delineation of clinical target volume in stereotactic partial breast irradiation (S-PBI).

Accurate and efficient delineation of the clinical target volume (CTV) is of utmost significance in post-operative breast cancer radiotherapy. However, CTV delineation is challenging as the exact extent of microscopic disease encompassed by CTV is not visualizable in radiological images and remains uncertain. We proposed to mimic physicians' contouring practice for CTV segmentation in stereotactic partial breast irradiation (S-PBI) where CTV is derived from tumor bed volume (TBV) via a margin expansion followed by correcting the extensions for anatomical barriers of tumor invasion (e.g. skin, chest wall). We proposed a deep-learning model, where CT images and the corresponding TBV masks formed a multi-channel input for a 3D U-Net based architecture. The design guided the model to encode the location-related image features and directed the network to focus on TBV to initiate CTV segmentation. Gradient weighted class activation map (Grad-CAM) visualizations of the model predictions revealed that the extension rules and geometric/anatomical boundaries were learnt during model training to assist the network to limit the expansion to a certain distance from the chest wall and the skin. We retrospectively collected 175 prone CT images from 35 post-operative breast cancer patients who received 5-fraction partial breast irradiation regimen on GammaPod. The 35 patients were randomly split into training (25), validation (5) and test (5) sets. Our model achieved mean (standard deviation) of 0.94 (±0.02), 2.46 (±0.5) mm, and 0.53 (±0.14) mm for Dice similarity coefficient, 95th percentile Hausdorff distance, and average symmetric surface distance respectively on the test set. The results are promising for improving the efficiency and accuracy of CTV delineation during on-line treatment planning procedure.

Stability and reproducibility comparisons between deep inspiration breath-hold techniques for left-sided breast cancer patients: A prospective study.

PURPOSE: Deep inspiration breath-hold (DIBH) is crucial in reducing the lung and cardiac dose for treatment of left-sided breast cancer. We compared the stability and reproducibility of two DIBH techniques: Active Breathing Coordinator (ABC) and VisionRT (VRT). MATERIALS AND METHODS: We examined intra- and inter-fraction positional variation of the left lung. Eight left-sided breast cancer patients were monitored with electronic portal imaging during breath-hold (BH) at every fraction. For each patient, half of the fractions were treated using ABC and the other half with VRT, with an equal amount starting with either ABC or VRT. The lung in each portal image was delineated, and the variation of its area was evaluated. Intrafraction stability was evaluated as the mean coefficient of variation (CV) of the lung area for the supraclavicular (SCV) and left lateral (LLat) field over the course of treatment. Reproducibility was the CV for the first image of each fraction. Daily session time and total imaging monitor units (MU) used in patient positioning were recorded. RESULTS: The mean intrafraction stability across all patients for the LLat field was 1.3 ± 0.7% and 1.5 ± 0.9% for VRT and ABC, respectively. Similarly, this was 1.5 ± 0.7% and 1.6 ± 0.8% for VRT and ABC, respectively, for the SCV field. The mean interfraction reproducibility for the LLat field was 11.0 ± 3.4% and 14.9 ± 6.0% for VRT and ABC, respectively. Similarly, this was 13.0 ± 2.5% and 14.8 ± 9% for VRT and ABC, respectively, for the SCV. No difference was observed in the number of verification images required for either technique. CONCLUSIONS: The stability and reproducibility were found to be comparable between ABC and VRT. ABC can have larger interfractional variation with less feedback to the treating therapist compared to VRT as shown in the increase in geometric misses at the matchline.

Feasibility and efficacy of active breathing coordinator assisted deep inspiration breath hold technique for treatment of locally advanced breast cancer.

BACKGROUND: Active breathing coordinator (ABC)-assisted deep inspiration breath hold (DIBH) is an important organ sparing radiation therapy (RT) technique for left-sided breast cancer patients. Patients with advanced breast cancer undergoing chest wall and regional nodal irradiation often require a field matching technique. While field matching has been demonstrated to be safe and effective in free breathing patients, its safety and accuracy in DIBH/ABC use has not been previously reported. PURPOSE: To report the accuracy, feasibility, and safety of field matching with ABC/DIBH for patients receiving breast/chest wall irradiation with nodal irradiation using a three-field technique. METHODS: From December 2012 to May 2018, breast cancer patients undergoing ABC/DIBH-based RT at a single institution were reviewed. For each fraction, the amount of overlap/gap between the supraclavicular and the tangential field were measured and recorded. Patient characteristics, including acute and delayed skin toxicities, were analyzed. RESULTS: A total of 202 patients utilized ABC/DIBH and 4973 fractions had gap/overlap measurements available for analysis. The average gap/overlap measured at junction was 0.28 mm ± 0.99 mm. A total of 72% of fractions had no measurable gap/overlap (0 mm), while 5.6% had an overlap and 22.7% a gap. There was no significant trend for worsening or improvement of gap/overlap measurements with increasing fraction number per patient. OSLD measurements were compared to the planned dose. The median dose 1 cm above the junction was 106% ± 7% of planned dose (range 94%-116%). One centimeter below the junction, the median dose was 114% ± 11% of planned dose (range 95%-131%). At the junction, the median dose was 106% ± 16.3% of planned dose (range 86%-131%). Acute skin toxicity was similar to historically reported values (grade 3, 5.4%, grade 4, 0%). CONCLUSION: ABC-assisted DIBH is a safe and technically feasible method of delivering RT in the setting of complex matching field technique for breast and regional nodal treatments.

Ensemble learning for glioma patients overall survival prediction using pre-operative MRIs.

Objective: Gliomas are the most common primary brain tumors. Approximately 70% of the glioma patients diagnosed with glioblastoma have an averaged overall survival (OS) of only ∼16 months. Early survival prediction is essential for treatment decision-making in glioma patients. Here we proposed an ensemble learning approach to predict the post-operative OS of glioma patients using only pre-operative MRIs.Approach: Our dataset was from the Medical Image Computing and Computer Assisted Intervention Brain Tumor Segmentation challenge 2020, which consists of multimodal pre-operative MRI scans of 235 glioma patients with survival days recorded. The backbone of our approach was a Siamese network consisting of twinned ResNet-based feature extractors followed by a 3-layer classifier. During training, the feature extractors explored traits of intra and inter-class by minimizing contrastive loss of randomly paired 2D pre-operative MRIs, and the classifier utilized the extracted features to generate labels with cost defined by cross-entropy loss. During testing, the extracted features were also utilized to define distance between the test sample and the reference composed of training data, to generate an additional predictor via K-NN classification. The final label was the ensemble classification from both the Siamese model and the K-NN model.Main results: Our approach classifies the glioma patients into 3 OS classes: long-survivors (>15 months), mid-survivors (between 10 and 15 months) and short-survivors (<10 months). The performance is assessed by the accuracy (ACC) and the area under the curve (AUC) of 3-class classification. The final result achieved an ACC of 65.22% and AUC of 0.81.Significance: Our Siamese network based ensemble learning approach demonstrated promising ability in mining discriminative features with minimal manual processing and generalization requirement. This prediction strategy can be potentially applied to assist timely clinical decision-making.

Online analysis of chemical composition and size distribution of fresh cigarette smoke emitted from a heated tobacco product.

Online analysis of chemical composition of cigarette smoke of a heated tobacco product (HTP) was performed by using a home-made vacuum ultraviolet (VUV) lamp-based photoionization time-of-flight (TOF) mass spectrometer. A capillary inlet and an aerodynamic lens were utilized to sample the gas- and particulate-phase of the HTP smoke, without dilution and pretreatment, which can be switched from each other within minutes. A thermal desorption unit was installed to vaporize the particulate-phase into gas and its vaporization temperature was determined, based on an equilibrium between the evaporation efficiency and the thermal decomposition of organic compounds. Then these species were softly ionized by VUV photons and their ions were measured by a reflectron TOF mass analyzer. Meanwhile, the puff-by-puff resolved size distributions of the HTP smoke were probed with a commercial scanning mobility particle sizers (SMPS). The mean diameters of particles firstly increase with the puff number, mainly located in the range of 200 - 300 nm, and then approached a steady state. This method was validated to measure the physical-chemical characteristics of the HTP cigarette smoke.•A capillary inlet and an aerodynamic lens were utilized to sample the gas- and particulate-phase of the HTP smoke.•Chemical composition of the HTP smoke was measured by using a compact VUV photoionization mass spectrometer.•The particle size distribution of the HTP smoke without dilution was measured online.

Global optimization for spot-based treatment planning.

PURPOSE: Many radiotherapy modalities can deliver concentrated radiation in the form of spots, such as Gamma Knife (GK), GammaPod (GP), intensity-modulated proton therapy, and brachytherapy, and can be generalized as spot-based treatments. These treatments have a great therapeutic advantage of creating potent target dose while sparing the surrounding normal tissues. However, global optimization to determine the spot positions, shapes, and intensities is an intractable combinatorial problem for any real 3D problem. The conventional approach adopts heuristic spot selection and intensity optimization in a sequential manner to mitigate the problem complexity. In this work, we propose a novel framework that enables global optimization of spot-based treatment planning. METHODS: The framework is based on kernel decomposition (KD) dose calculation, which models each spot dose as a scaled shift-invariant kernel, with the reference kernels and scales pre-calculated. During optimization, the framework incorporates Fast Fourier Transform (FFT) for objective and derivative evaluations and accommodates all spot candidates in optimization search with a temporal complexity of O(N3 log N) as opposed to O(N6 ) complexity in the conventional beamlet framework for volume dimensions of N × N × N. We demonstrated the FFT framework using simulations with different objectives. The framework's planning performance was illustrated using clinical GK and GP cases. RESULTS: Pre-processing involves only a small number of reference kernels and a scale map for the KD model with marginal spatial and temporal overheads. For simulations with 512 × 512 image dimensions, plan optimization finished in ∼2 seconds with FFT, whereas it took 100× longer with the beamlet approach. For clinical cases, the FFT attained solutions within a minute with improved plan quality compared to clinical plans: better conformity and less integral dose because of using a global fine search space for optimal spots. CONCLUSIONS: The scaled shift-invariance and FFT framework opens a new paradigm for spot-based treatment planning, as it can substantially reduce both the spatial and temporal complexities. The framework makes global optimization for spot-based treatment planning clinically feasible.

Registration-guided deep learning image segmentation for cone beam CT-based online adaptive radiotherapy.

PURPOSE: Adaptive radiotherapy (ART), especially online ART, effectively accounts for positioning errors and anatomical changes. One key component of online ART process is accurately and efficiently delineating organs at risk (OARs) and targets on online images, such as cone beam computed tomography (CBCT). Direct application of deep learning (DL)-based segmentation to CBCT images suffered from issues such as low image quality and limited available contour labels for training. To overcome these obstacles to online CBCT segmentation, we propose a registration-guided DL (RgDL) segmentation framework that integrates image registration algorithms and DL segmentation models. METHODS: The RgDL framework is composed of two components: image registration and RgDL segmentation. The image registration algorithm transforms/deforms planning contours that were subsequently used as guidance by the DL model to obtain accurate final segmentations. We had two implementations of the proposed framework-Rig-RgDL (Rig for rigid body) and Def-RgDL (Def for deformable)-with rigid body (RB) registration or deformable image registration (DIR) as the registration algorithm, respectively, and U-Net as the DL model architecture. The two implementations of RgDL framework were trained and evaluated on seven OARs in an institutional clinical head-and-neck dataset. RESULTS: Compared to the baseline approaches using the registration or the DL alone, RgDLs achieved more accurate segmentation, as measured by higher mean Dice similarity coefficients (DSCs) and other distance-based metrics. Rig-RgDL achieved a DSC of 84.5% on seven OARs on average, higher than RB or DL alone by 4.5% and 4.7%. The average DSC of Def-RgDL was 86.5%, higher than DIR or DL alone by 2.4% and 6.7%. The inference time required by the DL model component to generate final segmentations of seven OARs was less than 1 s in RgDL. By examining the contours from RgDLs and DL case by case, we found that RgDL was less susceptible to image artifacts. We also studied how the performances of RgDL and DL vary with the size of the training dataset. The DSC of DL dropped by 12.1% as the number of training data decreased from 22 to 5, whereas RgDL only dropped by 3.4%. CONCLUSION: By incorporating the patient-specific registration guidance to a population-based DL segmentation model, RgDL framework overcame the obstacles associated with online CBCT segmentation, including low image quality and insufficient training data, and achieved better segmentation accuracy than baseline methods. The resulting segmentation accuracy and efficiency show promise for applying this RgDL framework for online ART.

Achieved and Functional Optical Zone in Myopic Eyes With High Astigmatism After Small Incision Lenticule Extraction.

PURPOSE: To investigate the achieved optical zone and functional optical zone in myopic eyes with high astigmatism after small incision lenticule extraction (SMILE). METHODS: Seventy-five eyes of 75 consecutive patients with myopia before SMILE were included and divided into two groups (no astigmatism group: without astigmatism vs high astigmatism group: with astigmatism > 2.00 diopters). The achieved optical zone, functional optical zone, and corneal aberrations were compared using Scheimpflug imaging at 6 months postoperatively. Correlations between corneal aberrations and functional optical zone were analyzed. RESULTS: The mean achieved optical zone diameter was smaller in the no astigmatism group than in the high astigmatism group. There were no significant differences in achieved optical zone among the different meridians in each group. The mean functional optical zone diameter was significantly smaller in the no astigmatism group than in the high astigmatism group. Compared with the programmed optical zone, significant reduction of the functional optical zone was found in the two groups. The reduction of the functional optical zone was significantly smaller in the high astigmatism group than in the no astigmatism group, except for the 60°, 90°, and 120° meridians. There were significant correlations between the functional optical zone area and the induced corneal aberrations in the high astigmatism group, except for horizontal coma, whereas significant correlations of functional optical zone with total higher order aberrations and spherical aberration were detected in the no astigmatism group. CONCLUSIONS: Myopic eyes with high astigmatism following SMILE had a circular achieved optical zone, but the functional optical zone was oval and larger than in eyes without astigmatism. Moreover, a lower spherical aberration was observed in the patients with high astigmatism. [J Refract Surg. 2022;38(4):243-249.].