Frequency-comb spectroscopy on pure quantum states of a single molecular ion

Spectroscopy is a powerful tool for studying molecules and is commonly performed on large thermal molecular ensembles that are perturbed by motional shifts and interactions with the environment and one another, resulting in convoluted spectra and limited resolution. Here, we use quantum-logic techniques to prepare a trapped molecular ion in a single quantum state, drive terahertz rotational transitions with an optical frequency comb, and read out the final state nondestructively, leaving the molecule ready for further manipulation. We can resolve rotational transitions to 11 significant digits and derive the rotational constant of 40CaH+ to be B R = 142 501 777.9(1.7) kilohertz. Our approach is suited for a wide range of molecular ions, including polyatomics and species relevant for tests of fundamental physics, chemistry, and astrophysics.

The dosimetric impact of replacing the TG-43 algorithm by model based dose calculation for liver brachytherapy

PURPOSE

To compare treatment plans for interstitial high dose rate (HDR) liver brachytherapy with ¹⁹²Ir calculated according to current-standard TG-43U1 protocol with model-based dose calculation following TG-186 protocol.

METHODS

We retrospectively evaluated dose volume histogram (DVH) parameters for liver, organs at risk (OARs) and clinical target volumes (CTVs) of 20 patient cases diagnosed with hepatocellular carcinoma (HCC) or metastatic colorectal cancer (mCRC). Dose calculations on a homogeneous water geometry (TG-43U1 surrogate) and on a computed tomography (CT) based geometry (TG-186) were performed using Monte Carlo (MC) simulations. The CTs were segmented based on a combination of assigning TG-186 recommended tissues to fixed Hounsfield Unit (HU) ranges and using organ contours delineated by physicians. For the liver, V_5Gy and V_10Gy were analysed, and for OARs the dose to 1 cubic centimeter (D_1cc). Target coverage was assessed by calculating V₁₅₀, V₁₀₀, V₉₅ and V₉₀ as well as D₉₅ and D₉₀. For every DVH parameter, median, minimum and maximum values of the deviations of TG-186 from TG-43U1 were analysed.

RESULTS

TG-186-calculated dose was found to be on average lower than dose calculated with TG-43U1. The deviation of highest magnitude for liver parameters was -6.2% of the total liver volume. For OARs, the deviations were all smaller than or equal to -0.5 Gy. Target coverage deviations were as high as -1.5% of the total CTV volume and -3.5% of the prescribed dose.

CONCLUSIONS

In this study we found that TG-43U1 overestimates dose to liver tissue compared to TG-186. This finding may be of clinical importance for cases where dose to the whole liver is the limiting factor.

CBCT correction using a cycle-consistent generative adversarial network and unpaired training to enable photon and proton dose calculation

In presence of inter-fractional anatomical changes, clinical benefits are anticipated from image-guided adaptive radiotherapy. Nowadays, cone-beam CT (CBCT) imaging is mostly utilized during pre-treatment imaging for position verification. Due to various artifacts, image quality is typically not sufficient for photon or proton dose calculation, thus demanding accurate CBCT correction, as potentially provided by deep learning techniques. This work aimed at investigating the feasibility of utilizing a cycle-consistent generative adversarial network (cycleGAN) for prostate CBCT correction using unpaired training. Thirty-three patients were included. The network was trained to translate uncorrected, original CBCT images (CBCT_org) into planning CT equivalent images (CBCT_cycleGAN). HU accuracy was determined by comparison to a previously validated CBCT correction technique (CBCT_cor). Dosimetric accuracy was inferred for volumetric-modulated arc photon therapy (VMAT) and opposing single-field uniform dose (OSFUD) proton plans, optimized on CBCT_cor and recalculated on CBCT_cycleGAN. Single-sided SFUD proton plans were utilized to assess proton range accuracy. The mean HU error of CBCT_cycleGAN with respect to CBCT_cor decreased from 24 HU for CBCT_org to  -6 HU. Dose calculation accuracy was high for VMAT, with average pass-rates of 100%/89% for a 2%/1% dose difference criterion. For proton OSFUD plans, the average pass-rate for a 2% dose difference criterion was 80%. Using a (2%, 2 mm) gamma criterion, the pass-rate was 96%. 93% of all analyzed SFUD profiles had a range agreement better than 3 mm. CBCT correction time was reduced from 6-10 min for CBCT_cor to 10 s for CBCT_cycleGAN. Our study demonstrated the feasibility of utilizing a cycleGAN for CBCT correction, achieving high dose calculation accuracy for VMAT. For proton therapy, further improvements may be required. Due to unpaired training, the approach does not rely on anatomically consistent training data or potentially inaccurate deformable image registration. The substantial speed-up for CBCT correction renders the method particularly interesting for adaptive radiotherapy.

Evaluation of proton and photon dose distributions recalculated on 2D and 3D Unet-generated pseudoCTs from T1-weighted MR head scans

Introduction: The recent developments of magnetic resonance (MR) based adaptive strategies for photon and, potentially for proton therapy, require a fast and reliable conversion of MR images to X-ray computed tomography (CT) values. CT values are needed for photon and proton dose calculation. The improvement of conversion results employing a 3D deep learning approach is evaluated. Material and methods: A database of 89 T1-weighted MR head scans with about 100 slices each, including rigidly registered CTs, was created. Twenty-eight validation patients were randomly sampled, and four patients were selected for application. The remaining patients were used to train a 2D and a 3D U-shaped convolutional neural network (Unet). A stack size of 32 slices was used for 3D training. For all application cases, volumetric modulated arc therapy photon and single-field uniform dose pencil-beam scanning proton plans at four different gantry angles were optimized for a generic target on the CT and recalculated on 2D and 3D Unet-based pseudoCTs. Mean (absolute) error (MAE/ME) and a gradient sharpness estimate were used to quantify the image quality. Three-dimensional gamma and dose difference analyses were performed for photon (gamma criteria: 1%, 1 mm) and proton dose distributions (gamma criteria: 2%, 2 mm). Range (80% fall off) differences for beam's eye view profiles were evaluated for protons. Results: Training 36 h for 1000 epochs in 3D (6 h for 200 epochs in 2D) yielded a maximum MAE of 147 HU (135 HU) for the application patients. Except for one patient gamma pass rates for photon and proton dose distributions were above 96% for both Unets. Slice discontinuities were reduced for 3D training at the cost of sharpness. Conclusions: Image analysis revealed a slight advantage of 2D Unets compared to 3D Unets. Similar dose calculation performance was reached for the 2D and 3D network.

Comparing Unet training with three different datasets to correct CBCT images for prostate radiotherapy dose calculations

Image intensity correction is crucial to enable cone beam computed tomography (CBCT) based radiotherapy dose calculations. This study evaluated three different deep learning based correction methods using a U-shaped convolutional neural network architecture (Unet) in terms of their photon and proton dose calculation accuracy. CT and CBCT imaging data of 42 prostate cancer patients were included. For target ground truth data generation, a CBCT correction method based on CT to CBCT deformable image registration (DIR) was used. The method yields a deformed CT called (i) virtual CT (vCT) which is used to generate (ii) corrected CBCT projections allowing the reconstruction of (iii) a final corrected CBCT image. The single Unet architecture was trained using these three different datasets: (Unet1) raw and corrected CBCT projections, (Unet2) raw CBCT and vCT image slices and (Unet3) raw and reference corrected CBCT image slices. Volumetric arc therapy (VMAT) and proton pencil beam scanning (PBS) single field uniform dose (SFUD) plans were optimized on the reference corrected image and recalculated on the obtained Unet-corrected CBCT images. The mean error (ME) and mean absolute error (MAE) for Unet1/2/3 were [Formula: see text] Hounsfield units (HU) and [Formula: see text] HU. The 1% dose difference pass rates were better than 98.4% for VMAT for 8 test patients not seen during training, with little difference between Unets. Gamma evaluation results were even better. For protons a gamma evaluation was employed to account for small range shifts, and [Formula: see text] mm pass rates for Unet1/2/3 were better than [Formula: see text] and 91%. A 3 mm range difference threshold was established. Only for Unet3 the 5th and 95th percentiles of the range difference distributions over all fields, test patients and dose profiles were within this threshold. A single Unet architecture was successfully trained using both CBCT projections and CBCT image slices. Since the results of the other Unets were poorer than Unet3, we conclude that training using corrected CBCT image slices as target data is optimal for PBS SFUD proton dose calculations, while for VMAT all Unets provided sufficient accuracy.

Dose-guided patient positioning in proton radiotherapy using multicriteria-optimization

Proton radiotherapy (PT) requires accurate target alignment before each treatment fraction, ideally utilizing 3D in-room X-ray computed tomography (CT) imaging. Typically, the optimal patient position is determined based on anatomical landmarks or implanted markers. In the presence of non-rigid anatomical changes, however, the planning scenario cannot be exactly reproduced and positioning should rather aim at finding the optimal position in terms of the actually applied dose. In this work, dose-guided patient alignment, implemented as multicriterial optimization (MCO) problem, was investigated in the scope of intensity-modulated and double-scattered PT (IMPT and DSPT) for the first time. A method for automatically determining the optimal patient position with respect to pre-defined clinical goals was implemented. Linear dose interpolation was used to access a continuous space of potential patient shifts. Fourteen head and neck (H&N) and eight prostate cancer patients with up to five repeated CTs were included. Dose interpolation accuracy was evaluated and the potential dosimetric advantages of dose-guided over bony-anatomy-based patient alignment investigated by comparison of clinically relevant target and organ-at-risk (OAR) dose-volume histogram (DVH) parameters. Dose interpolation was found sufficiently accurate with average pass-rates of 90% and 99% for an exemplary H&N and prostate patient, respectively, using a 2% dose-difference criterion. Compared to bony-anatomy-based alignment, the main impact of automated MCO-based dose-guided positioning was a reduced dose to the serial OARs (spinal cord and brain stem) for the H&N cohort. For the prostate cohort, under-dosage of the target structures could be efficiently diminished. Limitations of dose-guided positioning were mainly found in reducing target over-dosage due to weight loss for H&N patients, which might require adaptation of the treatment plan. Since labor-intense online quality-assurance is not required for dose-guided patient positioning, it might, nevertheless, be considered an interesting alternative to full online re-planning for initially mitigating the effects of anatomical changes.

Virome Analysis Reveals No Association of Head and Neck Vascular Anomalies with an Active Viral Infection

BACKGROUND/AIM

Vascular anomalies encompass different vascular malformations [arteriovenous (AVM), lymphatic (LM), venous lymphatic (VLM), venous (VM)] and vascular tumors such as hemangiomas (HA). The pathogenesis of vascular anomalies is still poorly understood. Viral infection was speculated as a possible underlying cause.

MATERIALS AND METHODS

A total of 13 human vascular anomalies and three human skin control tissues were used for viral analysis. RNA derived from AVM (n=4) and normal skin control (n=3) tissues was evaluated by RNA sequencing. The Virome Capture Sequencing Platform for Vertebrate Viruses (VirCapSeq-VERT) was deployed on 10 tissues with vascular anomalies (2×AVM, 1×HA, 1×LM, 2×VLM, 4×VM).

RESULTS

RNA sequencing did not show any correlation of AVM with viral infection. By deploying VirCapSeq-VERT, no consistent viral association was seen in the tested tissues.

CONCLUSION

The analysis does not point to the presence of an active viral infection in vascular anomalies. However, transient earlier viral infections, e.g. during pregnancy, cannot be excluded with this approach.

Gel dosimetry for three dimensional proton range measurements in anthropomorphic geometries

Proton beams used for radiotherapy have potential for superior sparing of normal tissue, although range uncertainties are among the main limiting factors in the accuracy of dose delivery. The aim of this study was to benchmark an N-vinylpyrrolidone based polymer gel to perform three-dimensional measurement of geometric proton beam characteristics and especially to test its suitability as a range probe in combination with an anthropomorphic phantom. For single proton pencil beams as well as for 3×3cm² mono-energy layers depth dose profiles, lateral dose distribution at different depths and proton range were evaluated in simple cubic gel phantoms at different energies from 75 to 115MeV and different dose levels. In addition, a 90MeV mono-energetic beam was delivered to an anthropomorphic 3D printed head phantom, which was filled with gel. Subsequently, all phantoms underwent magnetic resonance imaging using an axial pixel size of 0.68-0.98mm and with slice thicknesses of 2 or 3mm to derive a 3-dimensional distribution of the T₂ relaxation time, which correlates with radiation dose. Indices describing lateral dose distribution and proton range were compared against predictions from a treatment planning system (TPS, for cubic and head phantoms) and Monte Carlo simulations (MC, for the head phantom) after manual rigid co-registration with the T₂ relaxation time datasets. For all pencil beams, the FWHM agreement with TPS was better than 1mm or 7%. For the mono-energetic layer, the agreement with TPS in this respect was even better than 0.3mm in each case. With respect to range, results from gel measurements differed no more than 0.9mm (1.6%) from values predicted by TPS. In case of the anthropomorphic phantom, deviations with respect to a nominal range of about 61mm as well as in FWHM were slightly higher, namely within 1.0mm and 1.1mm respectively. Average deviations between gel and TPS/MC were similar (-0.3mm±0.4mm/-0.2±0.5mm). In conclusion, polymer gel dosimetry was found to be a valuable tool to determine geometric proton beam properties three-dimensionally and with high spatial resolution in simple cubic as well as in a more complex anthropomorphic phantom. Post registration range errors of the order of 1mm could be achieved. The additional registration uncertainty (95%) was 1mm.

Usability of American Sign Language Videos for Presenting Mathematics Assessment Content

There is considerable interest in determining whether high-quality American Sign Language videos can be used as an accommodation in tests of mathematics at both K-12 and postsecondary levels; and in learning more about the usability (e.g., comprehensibility) of ASL videos with two different types of signers - avatar (animated figure) and human. The researchers describe the results of administering each of nine pre-college mathematics items in both avatar and human versions to each of 31 Deaf participants with high school and post-high school backgrounds. This study differed from earlier studies by obliging the participants to rely on the ASL videos to answer the items. While participants preferred the human version over the avatar version (apparently due largely to the better expressiveness and fluency of the human), there was no discernible relationship between mathematics performance and signed version.

Feasibility of MR-only proton dose calculations for prostate cancer radiotherapy using a commercial pseudo-CT generation method

A magnetic resonance (MR)-only radiotherapy workflow can reduce cost, radiation exposure and uncertainties introduced by CT-MRI registration. A crucial prerequisite is generating the so called pseudo-CT (pCT) images for accurate dose calculation and planning. Many pCT generation methods have been proposed in the scope of photon radiotherapy. This work aims at verifying for the first time whether a commercially available photon-oriented pCT generation method can be employed for accurate intensity-modulated proton therapy (IMPT) dose calculation. A retrospective study was conducted on ten prostate cancer patients. For pCT generation from MR images, a commercial solution for creating bulk-assigned pCTs, called MR for Attenuation Correction (MRCAT), was employed. The assigned pseudo-Hounsfield Unit (HU) values were adapted to yield an increased agreement to the reference CT in terms of proton range. Internal air cavities were copied from the CT to minimise inter-scan differences. CT- and MRCAT-based dose calculations for opposing beam IMPT plans were compared by gamma analysis and evaluation of clinically relevant target and organ at risk dose volume histogram (DVH) parameters. The proton range in beam's eye view (BEV) was compared using single field uniform dose (SFUD) plans. On average, a [Formula: see text] mm) gamma pass rate of 98.4% was obtained using a [Formula: see text] dose threshold after adaptation of the pseudo-HU values. Mean differences between CT- and MRCAT-based dose in the DVH parameters were below 1 Gy ([Formula: see text]). The median proton range difference was [Formula: see text] mm, with on average 96% of all BEV dose profiles showing a range agreement better than 3 mm. Results suggest that accurate MR-based proton dose calculation using an automatic commercial bulk-assignment pCT generation method, originally designed for photon radiotherapy, is feasible following adaptation of the assigned pseudo-HU values.

The association between BMI and health-related quality of life in the US population: sex, age and ethnicity matters

BACKGROUND

Obesity is a major public health problem. Detailed knowledge about the relationship between body mass index (BMI) and health-related quality of life (HRQL) is important for deriving effective and cost-effective prevention and weight management strategies. This study aims to describe the sex-, age- and ethnicity-specific association between BMI and HRQL in the US adult population.

METHODS

Analyses are based on pooled cross-sectional data from 41 459 participants of the Medical Expenditure Panel Survey (MEPS) Household Component (HC) for the years 2000-2003. BMI was calculated using self-reported height and weight, and HRQL was assessed with the EuroQol five-dimensional questionnaire. Generalized additive models were fitted with a smooth function for BMI and a smooth-factor interaction for BMI with sex adjusted for age, ethnicity, poverty, smoking and physical activity. Models were further stratified by age and ethnicity.

RESULTS

The association between BMI and HRQL is inverse U-shaped with a HRQL high point at a BMI of 22 kg m^-2 in women and a HRQL high plateau at BMI values of 22-30 kg m^-2 in men. Men aged 50 years and older with a BMI of 29 kg m^-2 reported on average five-point higher visual analog scale (VAS) scores than peers with a BMI of 20 kg m^-2. The inverse U-shaped association is more pronounced in older people, and the BMI-HRQL relationship differs between ethnicities. In Hispanics, the BMI associated with the highest HRQL is higher than in white people and, in black women, the BMI-HRQL association has an almost linear negative slope.

CONCLUSIONS

The results show that a more differentiated use of BMI cutoffs in scientific discussions and daily practice is indicated. The findings should be considered in the design of future weight loss and weight management programs.