Generating 3D images of VMAT plans for predictive models and activation maps associated with plan deliverability.

BACKGROUND: Intensity modulation with dynamic multi-leaf collimator (MLC) and monitor unit (MU) changes across control points (CPs) characterizes volumetric modulated arc therapy (VMAT). The increased uncertainty in plan deliverability required patient-specific quality assurance (PSQA), which remained inefficient upon Quality Assurance (QA) failure. To prevent waste before QA, plan complexity metrics (PCMs) and machine learning models with the metrics were generated, which were lack of providing CP-specific information upon QA failures. PURPOSE: By generating 3D images from digital imaging and comminications in medicine in radiation therapy (DICOM RT) plan, we proposed a predictive model that can estimate the deliverability of VMAT plans and visualize CP-specific regions associated with plan deliverability. METHODS: The patient cohort consisted of 259 and 190 cases for left- and right-breast VMAT treatments, which were split into 235 and 166 cases for training and 24 cases from each treatment for testing the networks. Three-channel 3D images generated from DICOM RT plans were fed into a DenseNet-based deep learning network. To reflect VMAT plan complexity as an image, the first two channels described MLC and MU variations between two consecutive CPs, while the last channel assigned the beam field size. The network output was defined as binary classified PSQA results, indicating deliverability. The predictive performance was assessed by accuracy, sensitivity, specificity, F1-score, and area under the curve (AUC). The gradient-weighted class activation map (Grad-CAM) highlighted the regions of CPs in VMAT plans associated with deliverability, compared against PCMs by Spearman correlation. RESULTS: The DenseNet-based predictive model yielded AUCs of 92.2% and 93.8%, F1-scores of 97.0% and 93.8% and accuracies of 95.8% and 91.7% for the left- and right-breast VMAT cases. Additionally, the specificity of 87.5% for both cases indicated that the predictive model accurately detected QA failing cases. The activation maps significantly differentiated QA failing-labeled from passing-labeled classes for the non-deliverable cases. The PCM with the highest correlation to the Grad-CAM varied from patient cases, implying that plan deliverability would be considered patient-specific. CONCLUSION: This work demonstrated that the deep learning-based network based on visualization of dynamic VMAT plan information successfully predicted plan deliverability, which also provided control-point specific planning parameter information associated with plan deliverability in a patient-specific manner.

Defining tumor growth in vestibular schwannomas: a volumetric inter-observer variability study in contrast-enhanced T1-weighted MRI.

PURPOSE: For patients with vestibular schwannomas (VS), a conservative observational approach is increasingly used. Therefore, the need for accurate and reliable volumetric tumor monitoring is important. Currently, a volumetric cutoff of 20% increase in tumor volume is widely used to define tumor growth in VS. The study investigates the tumor volume dependency on the limits of agreement (LoA) for volumetric measurements of VS by means of an inter-observer study. METHODS: This retrospective study included 100 VS patients who underwent contrast-enhanced T1-weighted MRI. Five observers volumetrically annotated the images. Observer agreement and reliability was measured using the LoA, estimated using the limits of agreement with the mean (LOAM) method, and the intraclass correlation coefficient (ICC). RESULTS: The 100 patients had a median average tumor volume of 903 mm3 (IQR: 193-3101). Patients were divided into four volumetric size categories based on tumor volume quartile. The smallest tumor volume quartile showed a LOAM relative to the mean of 26.8% (95% CI: 23.7-33.6), whereas for the largest tumor volume quartile this figure was found to be 7.3% (95% CI: 6.5-9.7) and when excluding peritumoral cysts: 4.8% (95% CI: 4.2-6.2). CONCLUSION: Agreement limits within volumetric annotation of VS are affected by tumor volume, since the LoA improves with increasing tumor volume. As a result, for tumors larger than 200 mm3, growth can reliably be detected at an earlier stage, compared to the currently widely used cutoff of 20%. However, for very small tumors, growth should be assessed with higher agreement limits than previously thought.

Volumetric Additive Manufacturing of Dicyclopentadiene by Solid-State Photopolymerization.

Polymerization in the solid state is generally infeasible due to restrictions on mobility. However, in this work, the solid-state photopolymerization of crystalline dicyclopentadiene is demonstrated via photoinitiated ring-opening metathesis polymerization. The source of mobility in the solid state is attributed to the plastic crystal nature of dicyclopentadiene, which yields local short-range mobility due to orientational degrees of freedom. Polymerization in the solid state enables photopatterning, volumetric additive manufacturing of free-standing structures, and fabrication with embedded components. Solid-state photopolymerization of dicyclopentadiene offers a new paradigm for advanced and freeform fabrication of high-performance thermosets.

A Comprehensive Analysis of Volumetric 68Ga-PSMA PET/CT Parameters, Clinical and Histopathologic Features: Evaluation of the Predictive Role.

Objectives: To evaluate the relationships between volumetric 68Ga-prostate-specific membrane antigen (PSMA) positron emission tomography/computed tomography (PET/CT) parameters, Gleason score (GS), prostate-specific antigen (PSA) levels, histopathological data, and metastatic status in newly diagnosed prostate cancer (PCa) patients and to assess the predictive factors for progression despite treatment. Methods: A total of 78 newly diagnosed patients with PCa who had 68Ga-PSMA PET/CT scans were included. Clinical parameters, histopathological data, and metastatic status were documented, and volumetric parameters of primary prostate lesions were measured. All obtained data were compared statistically. Results: Primary prostate tumor maximum standardized uptake value (SUVmax) and GS were significantly related to serum PSA levels (p<0.05). PSA levels and SUVmax values were significantly higher in patients with lymph node metastases than in those without. GS was found to be significantly increased in metastatic patients. PSMA-derived tumor volume (PSMA-TV) and total lesion PSMA of the primary lesion had a significant relationship with PSA value, GS, and regional lymph node metastases. Receiver operating characteristic analysis, conducted in patients with metastatic and localized disease, identified the cutoff value for SUVmax as 10.85. According to the results of the logistic regression analysis, PSMA-TV was found to be a predictive factor for progression despite treatment. Conclusion: 68Ga-PSMA PET/CT remains an invaluable imaging modality that should be considered first in PCa staging because of its superior compatibility with clinical and histopathologic data. The importance of this method goes beyond diagnostic accuracy; it also extends into the predictive domain, where the PSMA-TV value of primary prostate lesions is a potential predictor of treatment efficacy. This information is valuable for personalizing patient treatment, improving prognostic accuracy, and predicting clinical outcomes.

Relationships between plasma biomarkers, tau PET, FDG PET, and volumetric MRI in mild to moderate Alzheimer's disease patients.

INTRODUCTION: The "A/T/N" (amyloid/tau/neurodegeneration) framework provides a biological basis for Alzheimer's disease (AD) diagnosis and can encompass additional changes such as inflammation ("I"). A spectrum of T/N/I imaging and plasma biomarkers was acquired in a phase 2 clinical trial of rasagiline in mild to moderate AD patients. We evaluated these to understand biomarker distributions and relationships within this population. METHODS: Plasma biomarkers of pTau-181, neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP), other inflammation-related proteins, imaging measures including fluorodeoxyglucose (FDG) positron emission tomography (PET), flortaucipir PET, and volumetric magnetic resonance imaging (MRI), and cognitive endpoints were analyzed to assess characteristics and relationships for the overall population (N = 47 at baseline and N = 21 for longitudinal cognitive comparisons) and within age-decade subgroups (57-69, 70-79, 80-90 years). RESULTS: Data demonstrate wide clinical and biomarker heterogeneity in this population influenced by age and sex. Plasma pTau-181 and GFAP correlate with tau PET, most strongly in left inferior temporal cortex (p = 0.0002, p = 0.0006, respectively). In regions beyond temporal cortex, tau PET uptake decreased with age for the same pTau-181 or GFAP concentrations. FDG PET and brain volumes correlate with tau PET in numerous regions (such as inferior temporal: p = 0.0007, p = 0.00001, respectively). NfL, GFAP, and all imaging modalities correlate with baseline MMSE; subsequent MMSE decline is predicted by baseline parahippocampal and lateral temporal tau PET (p = 0.0007) and volume (p = 0.0006). Lateral temporal FDG PET (p = 0.006) and volume (p = 0.0001) are most strongly associated with subsequent ADAS-cog decline. NfL correlates with FDG PET and baseline MMSE but not tau PET. Inflammation biomarkers are intercorrelated but correlated with other biomarkers in only the youngest group. DISCUSSION: Associations between plasma biomarkers, imaging biomarkers, and cognitive status observed in this study provide insight into relationships among biological processes in mild to moderate AD. Findings show the potential to characterize AD patients regarding likely tau pathology, neurodegeneration, prospective clinical decline, and the importance of covariates such as age. Highlights: Plasma pTau-181 and GFAP correlated with regional and global tau PET in mild to moderate AD.NfL correlated with FDG PET and cognitive endpoints but not plasma pTau-181 or tau PET.Volume and FDG PET showed strong relationships to tau PET, one another, and cognitive status.Temporal volumes most strongly predicted decline in both MMSE and ADAS-cog.Volume and plasma biomarkers can enrich for elevated tau PET with age a significant covariate.

Greater benefits of deep learning-based computer-aided detection systems for finding small signals in 3D volumetric medical images.

Purpose: Radiologists are tasked with visually scrutinizing large amounts of data produced by 3D volumetric imaging modalities. Small signals can go unnoticed during the 3D search because they are hard to detect in the visual periphery. Recent advances in machine learning and computer vision have led to effective computer-aided detection (CADe) support systems with the potential to mitigate perceptual errors. Approach: Sixteen nonexpert observers searched through digital breast tomosynthesis (DBT) phantoms and single cross-sectional slices of the DBT phantoms. The 3D/2D searches occurred with and without a convolutional neural network (CNN)-based CADe support system. The model provided observers with bounding boxes superimposed on the image stimuli while they looked for a small microcalcification signal and a large mass signal. Eye gaze positions were recorded and correlated with changes in the area under the ROC curve (AUC). Results: The CNN-CADe improved the 3D search for the small microcalcification signal ( Δ AUC = 0.098 , p = 0.0002 ) and the 2D search for the large mass signal ( Δ AUC = 0.076 , p = 0.002 ). The CNN-CADe benefit in 3D for the small signal was markedly greater than in 2D ( Δ Δ AUC = 0.066 , p = 0.035 ). Analysis of individual differences suggests that those who explored the least with eye movements benefited the most from the CNN-CADe ( r = - 0.528 , p = 0.036 ). However, for the large signal, the 2D benefit was not significantly greater than the 3D benefit ( Δ Δ AUC = 0.033 , p = 0.133 ). Conclusion: The CNN-CADe brings unique performance benefits to the 3D (versus 2D) search of small signals by reducing errors caused by the underexploration of the volumetric data.

Development and validation of an automated Tomotherapy planning method for cervical cancer.

PURPOSE: This study aimed to develop an automated Tomotherapy (TOMO) planning method for cervical cancer treatment, and to validate its feasibility and effectiveness. MATERIALS AND METHODS: The study enrolled 30 cervical cancer patients treated with TOMO at our center. Utilizing scripting and Python environment within the RayStation (RaySearch Labs, Sweden) treatment planning system (TPS), we developed automated planning methods for TOMO and volumetric modulated arc therapy (VMAT) techniques. The clinical manual TOMO (M-TOMO) plans for the 30 patients were re-optimized using automated planning scripts for both TOMO and VMAT, creating automated TOMO (A-TOMO) and automated VMAT (A-VMAT) plans. We compared A-TOMO with M-TOMO and A-VMAT plans. The primary evaluated relevant dosimetric parameters and treatment plan efficiency were assessed using the two-sided Wilcoxon signed-rank test for statistical analysis, with a P-value < 0.05 indicating statistical significance. RESULTS: A-TOMO plans maintained similar target dose uniformity compared to M-TOMO plans, with improvements in target conformity and faster dose drop-off outside the target, and demonstrated significant statistical differences (P+ < 0.01). A-TOMO plans also significantly outperformed M-TOMO plans in reducing V50Gy, V40Gy and Dmean for the bladder and rectum, as well as Dmean for the bowel bag, femoral heads, and kidneys (all P+ < 0.05). Additionally, A-TOMO plans demonstrated better consistency in plan quality. Furthermore, the quality of A-TOMO plans was comparable to or superior than A-VMAT plans. In terms of efficiency, A-TOMO significantly reduced the time required for treatment planning to approximately 20 min. CONCLUSION: We have successfully developed an A-TOMO planning method for cervical cancer. Compared to M-TOMO plans, A-TOMO plans improved target conformity and reduced radiation dose to OARs. Additionally, the quality of A-TOMO plans was on par with or surpasses that of A-VMAT plans. The A-TOMO planning method significantly improved the efficiency of treatment planning.

AI driven analysis of MRI to measure health and disease progression in FSHD.

Facioscapulohumeral muscular dystrophy (FSHD) affects roughly 1 in 7500 individuals. While at the population level there is a general pattern of affected muscles, there is substantial heterogeneity in muscle expression across- and within-patients. There can also be substantial variation in the pattern of fat and water signal intensity within a single muscle. While quantifying individual muscles across their full length using magnetic resonance imaging (MRI) represents the optimal approach to follow disease progression and evaluate therapeutic response, the ability to automate this process has been limited. The goal of this work was to develop and optimize an artificial intelligence-based image segmentation approach to comprehensively measure muscle volume, fat fraction, fat fraction distribution, and elevated short-tau inversion recovery signal in the musculature of patients with FSHD. Intra-rater, inter-rater, and scan-rescan analyses demonstrated that the developed methods are robust and precise. Representative cases and derived metrics of volume, cross-sectional area, and 3D pixel-maps demonstrate unique intramuscular patterns of disease. Future work focuses on leveraging these AI methods to include upper body output and aggregating individual muscle data across studies to determine best-fit models for characterizing progression and monitoring therapeutic modulation of MRI biomarkers.

Flow-Independent Thermal Conductivity and Volumetric Heat Capacity Measurement of Pure Gases and Binary Gas Mixtures Using a Single Heated Wire.

Among the different techniques for monitoring the flow rate of various fluids, thermal flow sensors stand out for their straightforward measurement technique. However, the main drawback of these types of sensors is their dependency on the thermal properties of the medium, i.e., thermal conductivity (k), and volumetric heat capacity (ρcp). They require calibration whenever the fluid in the system changes. In this paper, we present a single hot wire suspended above a V-groove cavity that is used to measure k and ρcp through DC and AC excitation for both pure gases and binary gas mixtures, respectively. The unique characteristic of the proposed sensor is its independence of the flow velocity, which makes it possible to detect the medium properties while the fluid flows over the sensor chip. The measured error due to fluctuations in flow velocity is less than ±0.5% for all test gases except for He, where it is ±6% due to the limitations of the measurement setup. The working principle and measurement results are discussed.

Automatic Segmentation and Alignment of Uterine Shapes from 3D Ultrasound Data.

BACKGROUND: The uterus is the most important organ in the female reproductive system. Its shape plays a critical role in fertility and pregnancy outcomes. Advances in medical imaging, such as 3D ultrasound, have significantly improved the exploration of the female genital tract, thereby enhancing gynecological healthcare. Despite well-documented data for organs like the liver and heart, large-scale studies on the uterus are lacking. Existing classifications, such as VCUAM and ESHRE/ESGE, provide different definitions for normal uterine shapes but are not based on real-world measurements. Moreover, the lack of comprehensive datasets significantly hinders research in this area. Our research, part of the larger NURSE study, aims to fill this gap by establishing the shape of a normal uterus using real-world 3D vaginal ultrasound scans. This will facilitate research into uterine shape abnormalities associated with infertility and recurrent miscarriages. METHODS: We developed an automated system for the segmentation and alignment of uterine shapes from 3D ultrasound data, which consists of two steps: automatic segmentation of the uteri in 3D ultrasound scans using deep learning techniques, and alignment of the resulting shapes with standard geometrical approaches, enabling the extraction of the normal shape for future analysis. The system was trained and validated on a comprehensive dataset of 3D ultrasound images from multiple medical centers. Its performance was evaluated by comparing the automated results with manual annotations provided by expert clinicians. RESULTS: The presented approach demonstrated high accuracy in segmenting and aligning uterine shapes from 3D ultrasound data. The segmentation achieved an average Dice similarity coefficient (DSC) of 0.90. Our method for aligning uterine shapes showed minimal translation and rotation errors compared to traditional methods, with the preliminary average shape exhibiting characteristics consistent with expert findings of a normal uterus. CONCLUSION: We have presented an approach to automatically segment and align uterine shapes from 3D ultrasound data. We trained a deep learning nnU-Net model that achieved high accuracy and proposed an alignment method using a combination of standard geometrical techniques. Additionally, we have created a publicly available dataset of 3D transvaginal ultrasound volumes with manual annotations of uterine cavities to support further research and development in this field. The dataset and the trained models are available at https://github.com/UL-FRI-LGM/UterUS.

The safety and efficacy of volumetric modulated Arc therapy combined with computer tomography-guided adaptive brachytherapy for locally advanced cervical cancer: a single institution experience.

BACKGROUND: Volumetric modulated arc therapy (VMAT) is a novel form of IMRT, which can deliver more accurate dose distribution and shorten treatment time. Compared to MRI-guided adaptive brachytherapy, which is recommended as gold standard imaging for cervical cancer contours, CT-guided adaptive brachytherapy (CTGAB) is more available, more widespread, and more affordable in many centers. This study aims to retrospectively analyze the efficacy and the safety of VMAT combined with CTGAB for patients with locally advanced cervical cancer. METHODS AND MATERIALS: This study retrospectively analyzed 102 patients with locally advanced cervical cancer who underwent VMAT and CTGAB. Clinical outcomes including local control (LC), overall survival (OS) and progression-free survival (PFS), tumor response to treatment evaluated by the Response Evaluation Criteria in Solid Tumors (RECIST) (version 1.1), and toxicities including gastrointestinal toxicity, urinary toxicity and hematologic toxicity evaluated by the Common Terminology Criteria for Adverse Events (CTCAE) (version 5.0) were analyzed. The Kaplan-Meier method was used to calculate LC, OS, and PFS. RESULTS: Median follow-up time was 19 months. Complete response (CR), partial response (PR), stable disease (SD), and progressive disease (PD) occurred in 68 (66.7%), 24 (23.5%), 4 (3.92%), and 6 (5.88%), respectively. The 2-year and 3-year OS were 89.6% and 83%, respectively. The 2-year and 3-year PFS were 84.2% and 74.3%, respectively. The 2-year and 3-year LC were 90.1% and 79.3%, respectively. The average cumulative D2cm3 in the rectum, the bladder, the colon, and the small intestine were 78.07 (SD: 0.46) Gy, 93.20 (SD: 0.63) Gy, 63.55 (SD: 1.03) Gy and 61.07 (SD: 0.75) Gy, respectively. The average cumulative D90% of the high-risk clinical target volume (HR-CTV) was 92.26 (SD: 0.35) Gy. Grade ≥ 3 gastrointestinal and urinary toxicities occurred in 4.9% and 0.98%, respectively. 1.96% of patients were observed grade ≥ 4 gastrointestinal toxicities and none of the patients observed grade ≥ 4 urinary toxicities. CONCLUSION: VMAT combined with CTGAB for locally advanced cervical cancer was an effective and safe treatment method, which showed satisfactory LC, OS, PFS, and acceptable toxicities.

Volumetric Analysis and Healing Ratio: Refining Prognostic Assessment in Maxillofacial Cysts Using Cone-Beam Computed Tomography.

Introduction: Volumetric analysis with imaging techniques provides clinicians with the capability to visualize the spatial extent of the lesions. CBCT offers images with minimal radiation, facilitating a detailed assessment of cystic dimension's relationships. This crucial information helps in formulating appropriate strategies, including excision, enucleation, or nonsurgical approaches. The "Healing ratio" emerges as a valuable technique for prognostic evaluation. Materials and Methods: This retrospective study focused on outpatient cases with, clinic-radiologically diagnosed cases of odontogenic keratocyst or radicular cysts. Preoperative CBCT was utilized for volumetric analysis through MIMIC Software. Subsequent analyses were performed at 24 and 48 weeks postoperatively. The healing ratio was calculated for further correlation. Results: A total of 21 cases were included in the study, with a mean age of 36.67 years with predominance of males (72.6%, n = 16). Healing ratio estimation revealed minimal or no association with age, gender, and location on point-biserial analysis. Noteworthy implications were observed concerning total cyst volume and the specific diagnosis of the cyst. Results suggested more favorable healing outcomes in smaller cysts and those diagnosed as radicular cysts. Discussion: Proficiency in deciphering three-dimensional CBCT images accurately demands specialized training. The crux of our study lies in the application of volumetric analysis, particularly the "Healing Ratio," as a robust means of evaluating prognoses in management. The Healing Ratio, derived from three-dimensional imaging techniques, offers a comprehensive insight into the spatial dynamics of cystic lesions. Our findings underscore its significance as the optimal technique for prognostic assessment in the context of cyst management. Supplementary Information: The online version contains supplementary material available at 10.1007/s12663-024-02168-7.

A Case Report of Isolated Cervical Ligament Rupture With Hyper-Pronation Injury: Specific MRI Protocol and Surgical Reconstruction.

Background: The aim of this case report is to present a case of chronic cervical ligament tear and instability, which occurred by an unusual work injury with an eversion/hyper-pronation mechanism in contrast to the usual mechanism of inversion. The ligament was reconstructed using an allograft with satisfactory results up to 30 months after surgery. A new magnetic resonance imaging protocol (MRI) was developed to better evaluate the cervical ligament/graft. Conclusion: In diagnosis of foot sprains, a specific ligament injury should always be sought. In this case, physical examination producing tenderness at the location of the cervical ligament and correlating this with an oblique intercolumn stress test that reproduced pain with apprehension and gross instability supported the diagnosis. Retrospectively applying anatomic knowledge to the earlier MRI findings of bone marrow edema at the insertion points of the cervical ligament on the talus and calcaneus was important in confirming the diagnosis. To better evaluate the cervical ligament allograft tendon reconstruction, a novel volumetric MRI sequence was developed which may prove helpful to also diagnose cervical ligament injuries in future cases. Anatomic reconstruction of the cervical ligament provided satisfactory clinical and radiographic results at 30-month follow-up.Level of Evidence: V.

Optimized Biomanufacturing for Treatment of Volumetric Muscle Loss Enables Physiomimetic Recovery.

Volumetric muscle loss (VML) injuries are defined by loss of sufficient skeletal muscle to produce persistent deficits in muscle form and function, with devastating lifelong consequences to both soldiers and civilians. There are currently no satisfactory treatments for VML injuries. The work described herein details the implementation of a fully enclosed bioreactor environment (FEBE) system that efficiently interfaces with our existing automated bioprinting and advanced biomanufacturing methods for cell deposition on sheet-based scaffolds for our previously described tissue-engineered muscle repair (TEMR) technology platform. Briefly, the TEMR technology consists of a porcine bladder acellular matrix seeded with skeletal muscle progenitor cells and preconditioned via 10% uniaxial cyclic stretch in a bioreactor. Overall, TEMR implantation in an established rat tibialis anterior (TA) VML injury model can result in 60 to ∼90% functional recovery. However, our original study documented >50% failure rate. That is, more than half of the implanted TEMR constructs produced no functional improvement beyond no treatment/repair. The high failure rate was attributed to the untoward mechanical disruption of TEMR during surgical implantation. In a follow-up study, adjustments were made to the geometry of both the VML injury and the TEMR construct, and the "nonresponder" group was reduced from over half the TEMR-treated animals to just 33%. Nonetheless, additional improvement is needed for clinical applicability. The main objectives of the current study were twofold: (1) explore the use of advanced biomanufacturing methods (i.e., FEBE bioreactor) to further improve TEMR reliability (i.e., increase functional response rate), (2) determine if previously established bioprinting methods, when coupled to the customized FEBE system would further improve the rate, magnitude or amplitude of functional outcomes following TEMR implantation in the same rat TA VML injury model. The current study demonstrates the unequivocal benefits of a customized bioreactor system that reduces manipulation of TEMR during cell seeding and maturation via bioprinting while simultaneously maximizing TEMR stability throughout the biofabrication process. This new biomanufacturing strategy not only accelerated the rate of functional recovery, but also eliminated all TEMR failures. In addition, implementation of bioprinting resulted in more physiomimetic skeletal muscle characteristics of repaired muscle tissue.

A Novel Approach for the Detection and Severity Grading of Chronic Obstructive Pulmonary Disease Based on Transformed Volumetric Capnography.

Chronic Obstructive Pulmonary Disease (COPD), as the third leading cause of death worldwide, is a major global health issue. The early detection and grading of COPD are pivotal for effective treatment. Traditional spirometry tests, requiring considerable physical effort and strict adherence to quality standards, pose challenges in COPD diagnosis. Volumetric capnography (VCap), which can be performed during natural breathing without requiring additional compliance, presents a promising alternative tool. In this study, the dataset comprised 279 subjects with normal pulmonary function and 148 patients diagnosed with COPD. We introduced a novel quantitative analysis method for VCap. Volumetric capnograms were converted into two-dimensional grayscale images through the application of Gramian Angular Field (GAF) transformation. Subsequently, a multi-scale convolutional neural network, CapnoNet, was conducted to extract features and facilitate classification. To improve CapnoNet's performance, two data augmentation techniques were implemented. The proposed model exhibited a detection accuracy for COPD of 95.83%, with precision, recall, and F1 measures of 95.21%, 95.70%, and 95.45%, respectively. In the task of grading the severity of COPD, the model attained an accuracy of 96.36%, complemented by precision, recall, and F1 scores of 88.49%, 89.99%, and 89.15%, respectively. This work provides a new perspective for the quantitative analysis of volumetric capnography and demonstrates the strong performance of the proposed CapnoNet in the diagnosis and grading of COPD. It offers direction and an effective solution for the clinical application of capnography.

Should new organ involvement be included in Response Evaluation Criteria in PSMA Imaging?

PURPOSE: The current study is intended to investigate the effect of new organ involvement on overall survival (OS) and modify the Response Evaluation Criteria in PSMA Imaging (RECIP) by including new organ involvement to RECIP 1.0. MATERIALS AND METHODS: This retrospective study includes 114 patients diagnosed with metastatic castration-resistant prostate cancer (mCRPC) between September 2017 and June 2022 who had received docetaxel treatment and had baseline and post-treatment prostate-specific membrane antigen (PSMA) positron emission tomography/computed tomography (PET/CT) images. The inclusion criteria were patients with pre- and post-treatment [18F]FDG PET/CT images and whose [18F]FDG PET images were negative. Those whose data were unavailable, who had additional malignancy, or who received abiraterone, enzalutamide, or Lutetium (Lu)-177 treatment were excluded. Age, Gleason score (GS), TPSA (total prostate-specific antigen) levels, surgical history, and OS information were recorded for each patient. RESULTS: The 114 patients herein had a median age of 72.5 (51-91) years and a median GS of 8 (7-10). New lesions were observed in 59 patients (51.7%) and new organ PSMA uptake was observed in 14 patients (12.2%). In the multivariate Cox regression analysis, volume-based treatment response (vTR)-total lesion PSMA (TLP), RECIP PSMA-VOL, modified RECIP (mRECIP) PSMA-VOL, and mRECIP TLP were independent prognostic factors for mortality (p < 0.001, p = 0.006, p = 0.003, and p = 0.003, respectively). The median OS of patients with new organ involvement and new lesion with PSMA uptake was 9.3 months (95% CI 2.1-16.5 months) and 11.8 months (95% CI 7.4-16.2 months), respectively. CONCLUSION: The study concluded that new organ involvement had a shorter OS than new lesion involvement. In the mRECIP that we developed, unlike RECIP, we demonstrated that both PSMA-VOL and TLP value were independent prognostic factors for mortality.

Fetal dose assessment in a pregnant patient with brain tumor: A comparative study of proton PBS and 3DCRT/VMAT radiation therapy techniques.

PURPOSE: The treatment of brain tumors in pregnant patients poses challenges, as the out-of-field dose exposure to the fetus can potentially be harmful. A pregnant patient with prior radiation treatment was presented with a brain tumor at our clinic. This work reports on our pre-treatment study that compared fetal dose exposure between intensity-modulated proton therapy (IMPT) using pencil beam scanning (PBS) and conventional photon 3D conformal radiation therapy (3DCRT) and volumetric-modulated arc therapy (VMAT), and the subsequent pregnant patient's radiation treatment. MATERIALS AND METHODS: Pre-treatment measurements of clinical plans, 3DCRT, VMAT, and IMPT, were conducted on a phantom. Measurements were performed using a device capable of neutron detections, closely following AAPM guidelines, TG158. For photon measurements, fetus shielding was utilized. On patient treatment days, which was determined to be proton treatment, shielding was used only during daily imaging for patient setup. Additionally, an in vivo measurement was conducted on the patient. RESULTS: Measurements showed that IMPT delivered the lowest fetal dose, considering both photon and neutron out-of-field doses to the fetus, even when shielding was implemented for photon measurements. Additionally, the proton plans demonstrated superior treatment for the mother, a reirradiation case. CONCLUSION: The patient was treated with proton therapy, and the baby was subsequently delivered at full term with no complications. This case study supports previous clinical findings and advocates for the expanded use of proton therapy in this patient population.

Root Zone Water Management Effects on Soil Hydrothermal Properties and Sweet Potato Yield.

Sufficient soil moisture is required to ensure the successful transplantation of sweet potato seedlings. Thus, reasonable water management is essential for achieving high quality and yield in sweet potato production. We conducted field experiments in northern China, planted on 18 May and harvested on 18 October 2021, at the Nancun Experimental Base of Qingdao Agricultural University. Three water management treatments were tested for sweet potato seedlings after transplanting: hole irrigation (W1), optimized drip irrigation (W2), and traditional drip irrigation (W3). The variation characteristics of soil volumetric water content, soil temperature, and soil CO2 concentration in the root zone were monitored in situ for 0-50 days. The agronomy, root morphology, photosynthetic parameters, 13C accumulation, yield, and yield components of sweet potato were determined. The results showed that soil VWC was maintained at 22-25% and 27-32% in the hole irrigation and combined drip irrigation treatments, respectively, from 0 to 30 days after transplanting. However, there was no significant difference between the traditional (W3) and optimized (W2) drip irrigation systems. From 30 to 50 days after transplanting, the VWC decreased significantly in all treatments, with significant differences among all treatments. Soil CO2 concentrations were positively correlated with VWC from 0 to 30 days after transplanting but gradually increased from 30 to 50 days, with significant differences among treatments. Soil temperature varied with fluctuations in air temperature, with no significant differences among treatments. Sweet potato survival rates were significantly lower in the hole irrigation treatments than in the drip irrigation treatments, with no significant difference between W2 and W3. The aboveground biomass, photosynthetic parameters, and leaf area index were significantly higher under drip irrigation than under hole irrigation, and values were higher in W3 than in W2. However, the total root length, root volume, and 13C partitioning rate were higher in W2 than in W3. These findings suggest that excessive drip irrigation can lead to an imbalance in sweet potato reservoir sources. Compared with W1, the W2 and W3 treatments exhibited significant yield increases of 42.98% and 36.49%, respectively. The W2 treatment had the lowest sweet potato deformity rate.

A novel insight of degradation ibuprofen in aqueous by catalytic ozonation with supported catalyst: Supports effect on ozone mass transfer.

Catalytic ozonation is an effective wastewater purification process. However, the low ozone mass transfer in packed bubble columns leads to low ozone utilization efficiency (OUE), poor organic degradation performance, and high energy consumption. Therefore, there is an urgent need to develop efficient supported catalysts that can enhance mass transfer and performance. However, the reaction mechanism of the support on ozone mass transfer remains unclear, which hinders the development of catalytic ozonation applications. In this study, lava rocks (LR)-supported catalysts, specifically CuMn2O4@LR and MnO2Co3O4@LR, were proposed for catalytic ozonation of IBP degradation due to their superior catalytic activity, stability, and high OUE. Addition of CuMn2O4@LR or MnO2Co3O4@LR increased IBP removal efficiency from 85% to 91% or 88%, and reduced energy consumption from 2.86 to 2.14 kWh/m3 or 2.60 kWh/m3, respectively. This improvement was attributed to LR-supported catalysts enhancing mass transfer and promoting O3 decomposition to generate •OH and •O2-, leading to IBP degradation. Furthermore, this study investigated the effects of ozone dose, supporter sizes, and catalyst components on ozone-liquid mass transfer. The results revealed that the size of the supporter influenced stacked porosity and consequently affected ozone mass transfer. Larger-sized LR (kLa= 0.172 min-1) exhibited better mass transfer compared to smaller-sized supports. Based on these findings, it was concluded that both CuMn2O4@LR and MnO2Co3O4@LR are potential catalysts for catalytic ozonation in residual IBP degradation of pharmaceutical wastewater, and LR showed good credibility as a catalyst supporter. Understanding the effects of supporters and active components on ozone mass transfer provides a fundamental principle for designing supported catalysts in catalytic ozonation applications.

Comparative study of dynamic conformal arc therapy and volumetric modulated arc therapy for treating single brain metastases: A retrospective analysis of dosimetric and clinical outcomes.

Background and purpose: Stereotactic radiation therapy (SRT) is commonly used to treat brain metastases (BMs). This retrospective study compared two SRT techniques, dynamic conformal arc therapy (DCAT) and volumetric modulated arc therapy (VMAT), for single BM treatments. Material and methods: Data of patients treated between January 2010 and June 2020 were considered. Patients with multiple BMs, resected BMs, reirradiation, whole-brain radiation therapy and brainstem metastases were excluded. We focused our analysis on 97 patients who received 23.1 Gy in three fractions. Acute toxicities and follow-up outcomes were recorded. Dosimetric data were analyzed in two subgroups (PTV ≤ 10 cc and PTV > 10 cc). Results: DCAT and VMAT were used in 70 (72.2 %) and 27 (27.8 %) patients, respectively. Acute toxicities were not significantly different between groups (p = 0.259), and no difference was detected in the incidence rate of radionecrosis, local recurrence and cerebral recurrence (p > 0.999, p > 0.999 and p = 0.682, respectively). PTV coverage was better with DCAT for small volumes (PTV ≤ 10 cc). Mean conformity index (CI) was significantly higher with VMAT and mean gradient index (GI) was significantly lower with DCAT whatever volume subgroups (p < 0.001). DCAT had more heterogeneous plans and VMAT required more monitor units. DCAT resulted in reduced low and intermediate doses, whereas VMAT led to decreased high doses. Conclusion: DCAT and VMAT are two effective and safe SRT techniques for BMs treatment. In the era of re-irradiation, it is important to reduce the doses delivered to healthy tissues. Further prospective studies are needed to validate these findings.