Deep Learning Enhanced Label-Free Action Potential Detection Using Plasmonic-Based Electrochemical Impedance Microscopy.

Measuring neuronal electrical activity, such as action potential propagation in cells, requires the sensitive detection of the weak electrical signal with high spatial and temporal resolution. None of the existing tools can fulfill this need. Recently, plasmonic-based electrochemical impedance microscopy (P-EIM) was demonstrated for the label-free mapping of the ignition and propagation of action potentials in neuron cells with subcellular resolution. However, limited by the signal-to-noise ratio in the high-speed P-EIM video, action potential mapping was achieved by averaging 90 cycles of signals. Such extensive averaging is not desired and may not always be feasible due to factors such as neuronal desensitization. In this study, we utilized advanced signal processing techniques to detect action potentials in P-EIM extracted signals with fewer averaged cycles. Matched filtering successfully detected action potential signals with as few as averaging five cycles of signals. Long short-term memory (LSTM) recurrent neural network achieved the best performance and was able to detect single-cycle stimulated action potential successfully [satisfactory area under the receiver operating characteristic curve (AUC) equal to 0.855]. Therefore, we show that deep learning-based signal processing can dramatically improve the usability of P-EIM mapping of neuronal electrical signals.

Study of the cement implantation syndrome: A review.

Bone cement implantation syndrome (BCIS) is a critical and potentially life-threatening condition that manifests during implantation. Characterized by a constellation of symptoms, including hypoxemia, hypotension, cardiac arrhythmias, elevated pulmonary vascular resistance, and occasionally cardiac arrest, BCIS typically ensues shortly after cement introduction, albeit with rare instances of delayed onset. Primarily attributed to the exothermic reaction of bone cement implantation, this syndrome is caused by local tissue damage, histamine and prostaglandin release, and microemboli formation, ultimately triggering a systemic immune response that culminates in respiratory and circulatory failure. The current hypotheses regarding BCIS include embolism, allergic reactions, and cement autotoxicity. BCIS management emphasizes preventative strategies, encompassing meticulous patient risk assessment, comprehensive preoperative and intraoperative evaluations, and precise cement application techniques. Treatment primarily involves symptomatic therapy and life-support measures to address the systemic effects of the syndrome.

Flow field and sediment removal in a stormwater sump utilizing internal structures.

This study investigated the hydraulic characteristics of stormwater sumps and their design optimization for sediment retention using physical experiments. Particle image velocimetry was utilized to measure the flow field, and the use of internal structures was investigated for improving solids retention. Results indicate that these internal structures can significantly improve the sediment removal efficiency of suspended solids with an average size of 125 µm, resulting in an efficiency improvement of 20-30%. Additionally, a modified Péclet number was proposed to more accurately evaluate the sediment removal efficiency of stormwater sumps, and recommendations were provided for further improving and optimizing sump design. This study provides insights into the hydraulic characteristics of stormwater sumps and has important implications for optimizing and designing particle removal systems for various industrial and environmental applications.

Study of linear energy transfer effect on rib fracture in breast patients receiving pencil-beamscanning proton therapy.

Purpose: To study the effect of proton linear energy transfer (LET) on rib fracture in breast cancer patients treated with pencil-beam scanning proton therapy (PBS) using a novel tool of dose-LET volume histogram (DLVH). Methods: From a prospective registry of patients treated with post-mastectomy proton therapy to the chest wall and regional lymph nodes for breast cancer between 2015 and 2020, we retrospectively identified rib fracture cases detected after completing treatment. Contemporaneously treated control patients that did not develop rib fracture were matched to patients 2:1 considering prescription dose, boost location, reconstruction status, laterality, chest wall thickness, and treatment year.The DLVH index, V(d, l), defined as volume(V) of the structure with at least dose(d) and LET(l), was calculated. DLVH plots between the fracture and control group were compared. Conditional logistic regression (CLR) model was used to establish the relation of V(d, l) and the observed fracture at each combination of d and l. The p-value derived from CLR model shows the statistical difference between fracture patients and the matched control group. Using the 2D p-value map derived from CLR model, the DLVH features associated with the patient outcomes were extracted. Results: Seven rib fracture patients were identified, and fourteen matched patients were selected for the control group. The median time from the completion of proton therapy to rib fracture diagnosis was 12 months (range 5 to 14 months). Two patients had grade 2 symptomatic rib fracture while the remaining 5 were grade 1 incidentally detected on imaging. The derived p-value map demonstrated larger V(0-36Gy[RBE], 4.0-5.0 keV/µm) in patients experiencing fracture (p<0.1). For example, the p value for V(30 Gy[RBE], 4.0 keV/um) was 0.069. Conclusions: In breast cancer patients receiving PBS, a larger volume of chest wall receiving moderate dose and high LET may result in increased risk of rib fracture.

Deep-learning based fast and accurate 3D CT deformable image registration in lung cancer.

BACKGROUND: Deformable Image Registration (DIR) is an essential technique required in many applications of radiation oncology. However, conventional DIR approaches typically take several minutes to register one pair of 3D CT images and the resulting deformable vector fields (DVFs) are only specific to the pair of images used, making it less appealing for clinical application. PURPOSE: A deep-learning-based DIR method using CT images is proposed for lung cancer patients to address the common drawbacks of the conventional DIR approaches and in turn can accelerate the speed of related applications, such as contour propagation, dose deformation, adaptive radiotherapy (ART), etc. METHODS: A deep neural network based on VoxelMorph was developed to generate DVFs using CT images collected from 114 lung cancer patients. Two models were trained with the weighted mean absolute error (wMAE) loss and structural similarity index matrix (SSIM) loss (optional) (i.e., the MAE model and the M+S model). In total, 192 pairs of initial CT (iCT) and verification CT (vCT) were included as a training dataset and the other independent 10 pairs of CTs were included as a testing dataset. The vCTs usually were taken 2 weeks after the iCTs. The synthetic CTs (sCTs) were generated by warping the vCTs according to the DVFs generated by the pre-trained model. The image quality of the synthetic CTs was evaluated by measuring the similarity between the iCTs and the sCTs generated by the proposed methods and the conventional DIR approaches, respectively. Per-voxel absolute CT-number-difference volume histogram (CDVH) and MAE were used as the evaluation metrics. The time to generate the sCTs was also recorded and compared quantitatively. Contours were propagated using the derived DVFs and evaluated with SSIM. Forward dose calculations were done on the sCTs and the corresponding iCTs. Dose volume histograms (DVHs) were generated based on dose distributions on both iCTs and sCTs generated by two models, respectively. The clinically relevant DVH indices were derived for comparison. The resulted dose distributions were also compared using 3D Gamma analysis with thresholds of 3 mm/3%/10% and 2 mm/2%/10%, respectively. RESULTS: The two models (wMAE and M+S) achieved a speed of 263.7±163 / 265.8±190 ms and a MAE of 13.15±3.8 / 17.52±5.8 HU for the testing dataset, respectively. The average SSIM scores of 0.987±0.006 and 0.988±0.004 were achieved by the two proposed models, respectively. For both models, CDVH of a typical patient showed that less than 5% of the voxels had a per-voxel absolute CT-number-difference larger than 55 HU. The dose distribution calculated based on a typical sCT showed differences of ≤2cGy[RBE] for clinical target volume (CTV) D95 and D5 , within ±0.06% for total lung V5 , ≤1.5cGy[RBE] for heart and esophagus Dmean , and ≤6cGy[RBE] for cord Dmax compared to the dose distribution calculated based on the iCT. The good average 3D Gamma passing rates (> 96% for 3 mm/3%/10% and > 94% for 2 mm/2%/10%, respectively) were also observed. CONCLUSION: A deep neural network-based DIR approach was proposed and has been shown to be reasonably accurate and efficient to register the initial CTs and verification CTs in lung cancer.

Deep-Learning-based Fast and Accurate 3D CT Deformable Image Registration in Lung Cancer.

PURPOSE: In some proton therapy facilities, patient alignment relies on two 2D orthogonal kV images, taken at fixed, oblique angles, as no 3D on-the-bed imaging is available. The visibility of the tumor in kV images is limited since the patient's 3D anatomy is projected onto a 2D plane, especially when the tumor is behind high-density structures such as bones. This can lead to large patient setup errors. A solution is to reconstruct the 3D CT image from the kV images obtained at the treatment isocenter in the treatment position. METHODS: An asymmetric autoencoder-like network built with vision-transformer blocks was developed. The data was collected from 1 head and neck patient: 2 orthogonal kV images (1024x1024 voxels), 1 3D CT with padding (512x512x512) acquired from the in-room CT-on-rails before kVs were taken and 2 digitally-reconstructed-radiograph (DRR) images (512x512) based on the CT. We resampled kV images every 8 voxels and DRR and CT every 4 voxels, thus formed a dataset consisting of 262,144 samples, in which the images have a dimension of 128 for each direction. In training, both kV and DRR images were utilized, and the encoder was encouraged to learn the jointed feature map from both kV and DRR images. In testing, only independent kV images were used. The full-size synthetic CT (sCT) was achieved by concatenating the sCTs generated by the model according to their spatial information. The image quality of the synthetic CT (sCT) was evaluated using mean absolute error (MAE) and per-voxel-absolute-CT-number-difference volume histogram (CDVH). RESULTS: The model achieved a speed of 2.1s and a MAE of <40HU. The CDVH showed that <5% of the voxels had a per-voxel-absolute-CT-number-difference larger than 185 HU. CONCLUSION: A patient-specific vision-transformer-based network was developed and shown to be accurate and efficient to reconstruct 3D CT images from kV images.

Asymmetric Alternative Current Electrochemical Method Coupled with Amidoxime-Functionalized Carbon Felt Electrode for Fast and Efficient Removal of Hexavalent Chromium from Wastewater.

A large amount of Cr (VI)-polluted wastewater produced in electroplating, dyeing and tanning industries seriously threatens water ecological security and human health. Due to the lack of high-performance electrodes and the coulomb repulsion between hexavalent chromium anion and cathode, the traditional DC-mediated electrochemical remediation technology possesses low Cr (VI) removal efficiency. Herein, by modifying commercial carbon felt (O-CF) with amidoxime groups, amidoxime-functionalized carbon felt electrodes (Ami-CF) with high adsorption affinity for Cr (VI) were prepared. Based on Ami-CF, an electrochemical flow-through system powered by asymmetric AC was constructed. The mechanism and influencing factors of efficient removal of Cr (VI) contaminated wastewater by an asymmetric AC electrochemical method coupling Ami-CF were studied. Scanning Electron Microscopy (SEM), Fourier Transform Infrared (FTIR), and X-ray photoelectron spectroscopy (XPS) characterization results showed that Ami-CF was successfully and uniformly loaded with amidoxime functional groups, and the adsorption capacity of Cr (VI) was more than 100 times higher than that of O-CF. In particular, the Coulomb repulsion effect and the side reaction of electrolytic water splitting were inhibited by the high-frequency anode and cathode switching (asymmetric AC), the mass transfer rate of Cr (VI) from electrode solution was increased, the reduction efficiency of Cr (VI) to Cr (III) was significantly promoted and a highly efficient removal of Cr (VI) was achieved. Under optimal operating conditions (positive bias 1 V, negative bias 2.5 V, duty ratio 20%, frequency 400 Hz, solution pH = 2), the asymmetric AC electrochemistry based on Ami-CF can achieve fast (30 s) and efficient removal (>99.11%) for 0.5-100 mg·L-1 Cr (VI) with a high flux of 300 L h-1 m-2. At the same time, the durability test verified the sustainability of the AC electrochemical method. For Cr (VI)-polluted wastewater with an initial concentration of 50 mg·L-1, the effluent concentration could still reach drinking water grade (<0.05 mg·L-1) after 10 cycling experiments. This study provides an innovative approach for the rapid, green and efficient removal of Cr (VI) containing wastewater at low and medium concentrations.

Experimental study of sediment washout from stormwater sumps.

Sumps are commonly used in urban stormwater systems, which can be considered as a simple pretreatment device for stormwater quality control. However, they may function as pollution sources due to sediment washout under high flow conditions. An experimental study was conducted to investigate the scour process of predeposited sediments from a sump and its influencing parameters. Under conditions with large inflows or high sediment deposit, the sediment particles could be resuspended, entrained and flushed out. The washout mass decreased exponentially with time if the sediment bed surface depth was larger than a threshold value; otherwise, the amount of washout would be much smaller. The same scour pattern was observed for all the testing cases, of which the largest scour depth always occurred below the outlet. The deposit below the inlet might increase under conditions with high flow rates and low levels of sediment bed. Dimension analysis was performed and principal non-dimensional parameters were found, including the Péclet number, the pipe Froude number, and the dimensionless particle diameter, which can be used to determine whether the washout would occur and its intensity in a stormwater sump under given conditions.

Technical note: Investigation of dose and LETd effect to rectum and bladder by using non-straight laterals in prostate cancer receiving proton therapy.

BACKGROUND: Parallel-opposed lateral beams are the conventional beam arrangements in proton therapy for prostate cancer. However, when considering linear energy transfer (LET) and RBE effects, alternative beam arrangements should be investigated. PURPOSE: To investigate the dose and dose averaged LET (LETd ) impact of using new beam arrangements rotating beams 5°-15° posteriorly to the laterals in prostate cancer treated with pencil-beam-scanning (PBS) proton therapy. METHODS: Twenty patients with localized prostate cancer were included in this study. Four proton treatment plans for each patient were generated utilizing 0°, 5°, 10°, and 15° posterior oblique beam pairs relative to parallel-opposed lateral beams. Dose-volume histograms (DVHs) from posterior oblique beams were analyzed. Dose-LETd -volume histogram (DLVH) was employed to study the difference in dose and LETd with each beam arrangement. DLVH indices, V ( d , l ) $V( {d,l} )$ , defined as the cumulative absolute volume that has a dose of at least d (Gy[RBE]) and a LETd of at least l (keV/µm), were calculated for both the rectum and bladder to the whole group of patients and two-sub groups with and without hydrogel spacer. These metrics were tested using Wilcoxon signed-rank test. RESULTS: Rotating beam angles from laterals to slightly posterior by 5°-15° reduced high LETd volumes while it increased the dose volume in the rectum and increased LETd in bladders. Beam angles rotated five degrees posteriorly from laterals (i.e., gantry in 95° and 265°) are proposed since they achieved the optimal balance of better LETd sparing and minimal dose increase in the rectum. A reduction of V(50 Gy[RBE], 2.6 keV/µm) from 7.41 to 3.96 cc (p < 0.01), and a slight increase of V(50 Gy[RBE], 0 keV/µm) from 20.1 to 21.6 cc (p < 0.01) were observed for the group without hydrogel spacer. The LETd sparing was less effective for the group with hydrogel spacer, which achieved the reduction of V(50 Gy[RBE], 2.6 keV/µm) from 4.28 to 2.10 cc (p < 0.01). CONCLUSIONS: Posterior oblique angle plans improved LETd sparing of the rectum while sacrificing LETd sparing in the bladder in the treatment of prostate cancer with PBS. Beam angle modification from laterals to slightly posterior may be a strategy to redistribute LETd and perhaps reduce rectal toxicity risks in prostate cancer patients treated with PBS. However, the effect is reduced for patients with hydrogel spacer.

Rapid Detection of Urinary Tract Infection in 10 min by Tracking Multiple Phenotypic Features in a 30 s Large-Volume Scattering Video of Urine Microscopy.

Rapid point-of-care (POC) diagnosis of bacterial infection diseases provides clinical benefits of prompt initiation of antimicrobial therapy and reduction of the overuse/misuse of unnecessary antibiotics for nonbacterial infections. We present here a POC compatible method for rapid bacterial infection detection in 10 min. We use a large-volume solution scattering imaging (LVSi) system with low magnifications (1-2×) to visualize bacteria in clinical samples, thus eliminating the need for culture-based isolation and enrichment. We tracked multiple intrinsic phenotypic features of individual cells in a short video. By clustering these features with a simple machine learning algorithm, we can differentiate Escherichia coli from similar-sized polystyrene beads, distinguish bacteria with different shapes, and distinguish E. coli from urine particles. We applied the method to detect urinary tract infections in 104 patient urine samples with a 30 s LVSi video, and the results showed 92.3% accuracy compared with the clinical culture results. This technology provides opportunities for rapid bacterial infection diagnosis at POC settings.

Exploratory study of seed spots analysis to characterize dose and linear-energy-transfer effect in adverse event initialization of pencil-beam-scanning proton therapy.

BACKGROUND: Both dose and linear energy transfer (LET) could play a substantial role in adverse event (AE) initialization of cancer patients treated with pencil-beam-scanning (PBS) proton therapy. However, not all the voxels within the AE regions are directly induced from the dose and LET effect. It is important to study the synergistic effect of dose and LET in AE initialization by only including a subset of voxels that are dosimetrically important. PURPOSE: To perform exploratory investigation of the dose and LET effects upon AE initialization in PBS using seed spots analysis. METHODS: A total of 113 head-and-neck (H&N) cancer patients receiving curative PBS were included. Among them, 20 patients experienced unanticipated CTCAEv4.0 grade ≥3 AEs (AE group) and 93 patients did not (control group). Within the AE group, 13 AE patients were included in the seed spot analysis to derive the descriptive features of AE initialization and the remaining 7 mandible osteoradionecrosis patients and 93 control patients were used to derive the feature-based volume constraint of mandible osteoradionecrosis. The AE regions were contoured and the corresponding dose-LET volume histograms of AE regions were generated for all patients in the AE group. We selected high LET voxels (the highest 5% of each dose bin) with a range of moderate-to-high dose (≥∼40-Gy relative biological effectiveness) as critical voxels. Critical voxels that were contiguous with each other were grouped into clusters. Each cluster was considered a potential independent seed spot for AE initialization. Seed spots were displayed in a 2D dose-LET plane based on their mean dose and LET to derive the descriptive features of AE initialization. A volume constraint of mandible osteoradionecrosis was then established based on the extracted features using a receiver operating characteristic curve. RESULTS: The product of dose and LET (xBD) was found to be a descriptive feature of seed spots leading to AE initialization in this preliminary study. The derived xBD volume constraint for mandible osteoradionecrosis showed good performance with an area under curve of 0.87 (sensitivity of 0.714 and specificity of 0.807 in the leave-one-out cross-validation) for the very limited patient data included in this study. CONCLUSION: Our exploratory study showed that both dose and LET were observed to be important in AE initializations. The derived xBD volume constraint could predict mandible osteoradionecrosis reasonably well in the very limited H&N cancer patient data treated with PBS included in this study.

Label-Free Quantification of Molecular Interaction in Live Red Blood Cells by Tracking Nanometer Scale Membrane Fluctuations.

Molecular interactions in live cells play an important role in both cellular functions and drug discovery. Current methods for measuring binding kinetics involve extracting the membrane protein and labeling, while the in situ quantification of molecular interaction with surface plasmon resonance (SPR) imaging mainly worked with fixed cells due to the micro-motion related noises of live cells. Here, an optical imaging method is presented to measure the molecular interaction with live red blood cells by tracking the nanometer membrane fluctuations. The membrane fluctuation dynamics are measured by tracking the membrane displacement during glycoprotein interaction. The data are analyzed with a thermodynamic model to determine the elastic properties of the cell observing reduced membrane fluctuations under fixatives, indicating cell fixations affect membrane mechanical properties. The binding kinetics of glycoprotein to several lectins are obtained by tracking the membrane fluctuation amplitude changes on single live cells. The binding kinetics and strength of different lectins are quite different, indicating the glycoproteins expression heterogeneity in single cells. It is anticipated that the method will contribute to the understanding of mechanisms of cell interaction and communication, and have potential applications in the mechanical assessment of cancer or other diseases at the single-cell level, and screening of membrane protein targeting drugs.

Empirical Relative Biological Effectiveness (RBE) for Mandible Osteoradionecrosis (ORN) in Head and Neck Cancer Patients Treated With Pencil-Beam-Scanning Proton Therapy (PBSPT): A Retrospective, Case-Matched Cohort Study.

Purpose: To retrospectively investigate empirical relative biological effectiveness (RBE) for mandible osteoradionecrosis (ORN) in head and neck (H&N) cancer patients treated with pencil-beam-scanning proton therapy (PBSPT). Methods: We included 1,266 H&N cancer patients, of which, 931 patients were treated with volumetric-modulated arc therapy (VMAT) and 335 were treated with PBSPT. Among them, 26 VMAT and 9 PBSPT patients experienced mandible ORN (ORN group), while all others were included in the control group. To minimize the impact of the possible imbalance in clinical factors between VMAT and PBSPT patients in the dosimetric comparison between these two modalities and the resulting RBE quantification, we formed a 1:1 case-matched patient cohort (335 VMAT patients and 335 PBSPT patients including both the ORN and control groups) using the greedy nearest neighbor matching of propensity scores. Mandible dosimetric metrics were extracted from the case-matched patient cohort and statistically tested to evaluate the association with mandibular ORN to derive dose volume constraints (DVCs) for VMAT and PBSPT, respectively. We sought the equivalent constraint doses for VMAT so that the critical volumes of VMAT were equal to those of PBSPT at different physical doses. Empirical RBEs of PBSPT for ORN were obtained by calculating the ratio between the derived equivalent constraint doses and physical doses of PBSPT. Bootstrapping was further used to get the confidence intervals. Results: Clinical variables of age, gender, tumor stage, prescription dose, chemotherapy, hypertension or diabetes, dental extraction, smoking history, or current smoker were not statistically related to the incidence of ORN in the overall patient cohort. Smoking history was found to be significantly associated with the ORN incidence in PBSPT patients only. V40Gy[RBE], V50Gy[RBE], and V60Gy[RBE] were statistically different (p<0.05) between the ORN and control group for VMAT and PBSPT. Empirical RBEs of 1.58(95%CI: 1.34-1.64), 1.34(95%CI: 1.23-1.40), and 1.24(95%: 1.15-1.26) were obtained for proton dose at 40 Gy[RBE=1.1], 50 Gy[RBE=1.1] and 60 Gy[RBE=1.1], respectively. Conclusions: Our study suggested that RBEs were larger than 1.1 at moderate doses (between 40 and 60 Gy[RBE=1.1]) with high LET for mandible ORN. RBEs are underestimated in current clinical practice in PBSPT. The derived DVCs can be used for PBSPT plan evaluation and optimization to minimize the incidence rate of mandible ORN.

Three-Dimensional Tracking of Tethered Particles for Probing Nanometer-Scale Single-Molecule Dynamics Using a Plasmonic Microscope.

Three-dimensional (3D) tracking of surface-tethered single particles reveals the dynamics of the molecular tether. However, most 3D tracking techniques lack precision, especially in the axial direction, for measuring the dynamics of biomolecules with a spatial scale of several nanometers. Here, we present a plasmonic imaging technique that can track the motion of ∼100 tethered particles in 3D simultaneously with sub-nanometer axial precision and single-digit nanometer lateral precision at millisecond time resolution. By tracking the 3D coordinates of a tethered particle with high spatial resolution, we are able to determine the dynamics of single short DNA and study its interaction with enzymes. We further show that the particle motion pattern can be used to identify specific and nonspecific interactions in immunoassays. We anticipate that our 3D tracking technique can contribute to the understanding of molecular dynamics and interactions at the single-molecule level.

Offspring production of ovarian organoids derived from spermatogonial stem cells by defined factors with chromatin reorganization.

Introduction: Fate determination of germline stem cells remains poorly understood at the chromatin structure level. Objectives: Our research hopes to develop successful offspring production of ovarian organoids derived from spermatogonial stem cells (SSCs) by defined factors. Methods: The offspring production from oocytes transdifferentiated from mouse SSCs with tracking of transplanted SSCs in vivo, single cell whole exome sequencing, and in 3D cell culture reconstitution of the process of oogenesis derived from SSCs. The defined factors were screened with ovarian organoids. We uncovered extensive chromatin reorganization during SSC conversion into induced germline stem cells (iGSCs) using high throughput chromosome conformation. Results: We demonstrate successful production of offspring from oocytes transdifferentiated from mouse spermatogonial stem cells (SSCs). Furthermore, we demonstrate direct induction of germline stem cells (iGSCs) differentiated into functional oocytes by transduction of H19, Stella, and Zfp57 and inactivation of Plzf in SSCs after screening with ovarian organoids. We uncovered extensive chromatin reorganization during SSC conversion into iGSCs, which was highly similar to female germline stem cells. We observed that although topologically associating domains were stable during SSC conversion, chromatin interactions changed in a striking manner, altering 35% of inactive and active chromosomal compartments throughout the genome. Conclusion: We demonstrate successful offspring production of ovarian organoids derived from SSCs by defined factors with chromatin reorganization. These findings have important implications in various areas including mammalian gametogenesis, genetic and epigenetic reprogramming, biotechnology, and medicine.

A Critical Review of LET-Based Intensity-Modulated Proton Therapy Plan Evaluation and Optimization for Head and Neck Cancer Management.

In this review article, we review the 3 important aspects of linear-energy-transfer (LET) in intensity-modulated proton therapy (IMPT) for head and neck (H&N) cancer management. Accurate LET calculation methods are essential for LET-guided plan evaluation and optimization, which can be calculated either by analytical methods or by Monte Carlo (MC) simulations. Recently, some new 3D analytical approaches to calculate LET accurately and efficiently have been proposed. On the other hand, several fast MC codes have also been developed to speed up the MC simulation by simplifying nonessential physics models and/or using the graphics processor unit (GPU)-acceleration approach. Some concepts related to LET are also briefly summarized including (1) dose-weighted versus fluence-weighted LET; (2) restricted versus unrestricted LET; and (3) microdosimetry versus macrodosimetry. LET-guided plan evaluation has been clinically done in some proton centers. Recently, more and more studies using patient outcomes as the biological endpoint have shown a positive correlation between high LET and adverse events sites, indicating the importance of LET-guided plan evaluation in proton clinics. Various LET-guided plan optimization methods have been proposed to generate proton plans to achieve biologically optimized IMPT plans. Different optimization frameworks were used, including 2-step optimization, 1-step optimization, and worst-case robust optimization. They either indirectly or directly optimize the LET distribution in patients while trying to maintain the same dose distribution and plan robustness. It is important to consider the impact of uncertainties in LET-guided optimization (ie, LET-guided robust optimization) in IMPT, since IMPT is sensitive to uncertainties including both the dose and LET distributions. We believe that the advancement of the LET-guided plan evaluation and optimization will help us exploit the unique biological characteristics of proton beams to improve the therapeutic ratio of IMPT to treat H&N and other cancers.

Rapid Antimicrobial Susceptibility Testing on Clinical Urine Samples by Video-Based Object Scattering Intensity Detection.

To combat the ongoing public health threat of antibiotic-resistant infections, a technology that can quickly identify infecting bacterial pathogens and concurrently perform antimicrobial susceptibility testing (AST) in point-of-care settings is needed. Here, we develop a technology for point-of-care AST with a low-magnification solution scattering imaging system and a real-time video-based object scattering intensity detection method. The low magnification (1-2×) optics provides sufficient volume for direct imaging of bacteria in urine samples, avoiding the time-consuming process of culture-based bacterial isolation and enrichment. Scattering intensity from moving bacteria and particles in the sample is obtained by subtracting both spatial and temporal background from a short video. The time profile of scattering intensity is correlated with the bacterial growth rate and bacterial response to antibiotic exposure. Compared to the image-based bacterial tracking and counting method we previously developed, this simple image processing algorithm accommodates a wider range of bacterial concentrations, simplifies sample preparation, and greatly reduces the computational cost of signal processing. Furthermore, development of this simplified processing algorithm eases implementation of multiplexed detection and allows real-time signal readout, which are essential for point-of-care AST applications. To establish the method, 130 clinical urine samples were tested, and the results demonstrated an accuracy of ∼92% within 60-90 min for UTI diagnosis. Rapid AST of 55 positive clinical samples revealed 98% categorical agreement with both the clinical culture results and the on-site parallel AST validation results. This technology provides opportunities for prompt infection diagnosis and accurate antibiotic prescriptions in point-of-care settings.

Exploratory Investigation of Dose-Linear Energy Transfer (LET) Volume Histogram (DLVH) for Adverse Events Study in Intensity Modulated Proton Therapy (IMPT).

PURPOSE: We proposed a novel tool-a dose linear energy transfer (LET)-volume histogram (DLVH)-and performed an exploratory study to investigate rectal bleeding in prostate cancer treated with intensity modulated proton therapy. METHODS AND MATERIALS: The DLVH was constructed with dose and LET as 2 axes, and the normalized volume of the structure was contoured in the dose-LET plane as isovolume lines. We defined the DLVH index, DLv%(d,l) (ie, v% of the structure) to have a dose of ≥d Gy and an LET of ≥l keV/µm, similar to the dose-volume histogram index Dv%. Nine patients with prostate cancer with rectal bleeding (Common Terminology Criteria for Adverse Events grade ≥2) were included as the adverse event group, and 48 patients with no complications were considered the control group. A P value map was constructed by comparison of the DLVH indices of all patients between the 2 groups using the Mann-Whitney U test. Dose-LET volume constraints (DLVCs) were derived based on the P value map with a manual selection procedure facilitated by Spearman's correlation tests. The obtained DLVCs were further cross-validated using a multivariate support vector machine (SVM)-based normal tissue complication probability (NTCP) model with an independent testing data set composed of 8 adverse event and 13 control patients. RESULTS: We extracted 2 DLVC constraints. One DLVC was obtained, Vdose/LETboundary:2.5keVµmat 75 Gy to 3.2keVµmat8.65Gy <1.27% (DLVC1), revealing a high LET volume effect. The second DLVC, V(72.2Gy,0keVµm) < 2.23% (DVLC2), revealed a high dose volume effect. The SVM-based NTCP model with 2 DLVCs provided slightly superior performance than using dose only, with an area under the curve of 0.798 versus 0.779 for the testing data set. CONCLUSIONS: Our results demonstrated the importance of rectal "hot spots" in both high LET (DLVC1) and high dose (DLVC2) in inducing rectal bleeding. The SVM-based NTCP model confirmed the derived DLVCs as good predictors for rectal bleeding when intensity modulated proton therapy is used to treat prostate cancer.

Charge-Sensitive Optical Detection of Small Molecule Binding Kinetics in Normal Ionic Strength Buffer.

Most label-free detection technologies detect the masses of molecules, and their sensitivities thus decrease with molecular weight, making it challenging to detect small molecules. To address this need, we have developed a charge-sensitive optical detection (CSOD) technique, which detects the charge rather than the mass of a molecule with an optical fiber. However, the effective charge of a molecule decreases with the buffer ionic strength. For this reason, the previous CSOD works with diluted buffers, which could affect the measured molecular binding kinetics. Here, we show a technique capable of detecting molecular binding kinetics in normal ionic strength buffers. An H-shaped sample well was developed to increase the current density at the sensing area to compensate the signal loss due to ionic screening at normal ionic strength buffer, while keeping the current density low at the electrodes to minimize the electrode reaction. In addition, agarose gels were used to cover the electrodes to prevent electrode reaction generated bubbles from entering the sensing area. With this new design, we have measured the binding kinetics between G-protein-coupled receptors (GPCRs) and their small molecule ligands in normal buffer. We found that the affinities measured in normal buffer are stronger than those measured in diluted buffer, likely due to the stronger electrostatic repulsion force between the same charged ligands and receptors in the diluted buffer.

Gradient-Based Rapid Digital Immunoassay for High-Sensitivity Cardiac Troponin T (hs-cTnT) Detection in 1 µL Plasma.

Rapid and sensitive detection of biomarkers is the key to the diagnosis of acute diseases. One example is the detection of troponin in myocardial infarction. Here, we report a gradient-based digital immunoassay method, which can achieve high-sensitivity cardiac troponin T (hs-cTnT) detection with only 1 µL of plasma sample. We designed a multizone microfluidic channel functionalized with capture antibody specific to troponin. Taking advantage of limited sample volume, a troponin concentration gradient is created along the channel because of binding induced depletion. We quantified the concentration gradient by counting the detection antibody conjugated gold nanoparticles bound to different test zones with optical imaging. Differential counting between the zones removes most common noises and nonspecific bindings. The total analytical time is about 30 min, and the limit of quantification is 6.2 ng/L. We examined 41 clinical plasma samples from 15 patients and the change in hs-cTnT concentration in serial samples showed good linear correlation with clinical results (R2 = 0.98). Therefore, this simple and sensitive gradient-based digital immunoassay method is a promising technology for clinical hs-cTnT detection and could be adapted for detection of other biomarkers.