Measurement of the Sensitivity of Two-Particle Correlations in pp Collisions to the Presence of Hard Scatterings

A key open question in the study of multiparticle production in high-energy pp collisions is the relationship between the "ridge"-i.e., the observed azimuthal correlations between particles in the underlying event that extend over all rapidities-and hard or semihard scattering processes. In particular, it is not known whether jets or their soft fragments are correlated with particles in the underlying event. To address this question, two-particle correlations are measured in pp collisions at sqrt[s]=13  TeV using data collected by the ATLAS experiment at the LHC, with an integrated luminosity of 15.8  pb^{-1}, in two different configurations. In the first case, charged particles associated with jets are excluded from the correlation analysis, while in the second case, correlations are measured between particles within jets and charged particles from the underlying event. Second-order flow coefficients, v_{2}, are presented as a function of event multiplicity and transverse momentum. These measurements show that excluding particles associated with jets does not affect the measured correlations. Moreover, particles associated with jets do not exhibit any significant azimuthal correlations with the underlying event, ruling out hard processes contributing to the ridge.

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Maksimovic P, Roskes J, Sekhar S, Swartz M, Vámi T, Abreu A, Alcerro Alcerro LF, Anguiano J, Baringer P, Bean A, Flowers Z, King J, Krintiras G, Lazarovits M, Le Mahieu C, Lindsey C, Marquez J, Minafra N, Murray M, Nickel M, Rogan C, Royon C, Salvatico R, Sanders S, Smith C, Wang Q, Wilson G, Allmond B, Duric S, Ivanov A, Kaadze K, Kalogeropoulos A, Kim D, Maravin Y, Mitchell T, Modak A, Nam K, Roy D, Rebassoo F, Wright D, Adams E, Baden A, Baron O, Belloni A, Bethani A, Eno SC, Hadley NJ, Jabeen S, Kellogg RG, Koeth T, Lai Y, Lascio S, Mignerey AC, Nabili S, Palmer C, Papageorgakis C, Wang L, Wong K, Busza W, Cali IA, Chen Y, D’Alfonso M, Eysermans J, Freer C, Gomez-Ceballos G, Goncharov M, Harris P, Kovalskyi D, Krupa J, Lee YJ, Long K, Mironov C, Paus C, Rankin D, Roland C, Roland G, Shi Z, Stephans GSF, Wang J, Wang Z, Wyslouch B, Yang TJ, Chatterjee RM, Crossman B, Hiltbrand J, Joshi BM, Kapsiak C, Krohn M, Kubota Y, Mahon D, Mans J, Revering M, Rusack R, Saradhy R, Schroeder N, Strobbe N, Wadud MA, Cremaldi LM, Bloom K, Bryson M, Claes DR, Fangmeier C, Finco L, Golf F, Joo C, Kamalieddin R, Kravchenko I, Reed I, Siado JE, Snow GR, Tabb W, Wightman A, Yan F, Zecchinelli AG, Agarwal G, Bandyopadhyay H, Hay L, Iashvili I, Kharchilava A, McLean C, Morris M, Nguyen D, Pekkanen J, Rappoccio S, Williams A, Alverson G, Barberis E, Haddad Y, Han Y, Krishna A, Li J, Lidrych J, Madigan G, Marzocchi B, Morse DM, Nguyen V, Orimoto T, Parker A, Skinnari L, Tishelman-Charny A, Wamorkar T, Wang B, Wisecarver A, Wood D, Bhattacharya S, Bueghly J, Chen Z, Gilbert A, Hahn KA, Liu Y, Odell N, Schmitt MH, Velasco M, Band R, Bucci R, Cremonesi M, Das A, Goldouzian R, Hildreth M, Hurtado Anampa K, Jessop C, Lannon K, Lawrence J, Loukas N, Lutton L, Mariano J, Marinelli N, Mcalister I, McCauley T, Mcgrady C, Mohrman K, Moore C, Musienko Y, Ruchti R, Townsend A, Wayne M, Yockey H, Zarucki M, Zygala L, Bylsma B, Carrigan M, Durkin LS, Hill C, Joyce M, Lesauvage A, Nunez Ornelas M, Wei K, Winer BL, Yates BR, Addesa FM, Das P, Dezoort G, Elmer P, Frankenthal A, Greenberg B, Haubrich N, Higginbotham S, Kopp G, Kwan S, Lange D, Loeliger A, Marlow D, Ojalvo I, Olsen J, Stickland D, Tully C, Malik S, Bakshi AS, Barnes VE, Chawla R, Das S, Gutay L, Jones M, Jung AW, Kondratyev D, Koshy AM, Liu M, Negro G, Neumeister N, Paspalaki G, Piperov S, Purohit A, Schulte JF, Stojanovic M, Thieman J, Virdi AK, Wang F, Xiao R, Xie W, Dolen J, Parashar N, Acosta D, Baty A, Carnahan T, Dildick S, Ecklund KM, Fernández Manteca PJ, Freed S, Gardner P, Geurts FJM, Kumar A, Li W, Padley BP, Redjimi R, Rotter J, Yang S, Yigitbasi E, Zhang Y, Bodek A, de Barbaro P, Demina R, Dulemba JL, Fallon C, Garcia-Bellido A, Hindrichs O, Khukhunaishvili A, Parygin P, Popova E, Taus R, Van Onsem GP, Goulianos K, Chiarito B, Chou JP, Gershtein Y, Halkiadakis E, Hart A, Heindl M, Jaroslawski D, Karacheban O, Laflotte I, Lath A, Montalvo R, Nash K, Osherson M, Routray H, Salur S, Schnetzer S, Somalwar S, Stone R, Thayil SA, Thomas S, Wang H, Acharya H, Delannoy AG, Fiorendi S, Holmes T, Nibigira E, Spanier S, Bouhali O, Dalchenko M, Delgado A, Eusebi R, Gilmore J, Huang T, Kamon T, Kim H, Luo S, Malhotra S, Mueller R, Overton D, Rathjens D, Safonov A, Akchurin N, Damgov J, Hegde V, Lamichhane K, Lee SW, Mengke T, Muthumuni S, Peltola T, Volobouev I, Whitbeck A, Appelt E, Greene S, Gurrola A, Johns W, Melo A, Romeo F, Sheldon P, Tuo S, Velkovska J, Viinikainen J, Cardwell B, Cox B, Cummings G, Hakala J, Hirosky R, Ledovskoy A, Li A, Neu C, Perez Lara CE, Karchin PE, Aravind A, Banerjee S, Black K, Bose T, Dasu S, De Bruyn I, Everaerts P, Galloni C, He H, Herndon M, Herve A, Koraka CK, Lanaro A, Loveless R, Madhusudanan Sreekala J, Mallampalli A, Mohammadi A, Mondal S, Parida G, Pinna D, Savin A, Shang V, Sharma V, Smith WH, Teague D, Tsoi HF, Vetens W, Warden A, Afanasiev S, Andreev V, Andreev Y, Aushev T, Azarkin M, Babaev A, Belyaev A, Blinov V, Boos E, Borshch V, Budkouski D, Bunichev V, Chadeeva M, Chekhovsky V, Danilov M, Dermenev A, Dimova T, Dremin I, Dubinin M, Dudko L, Epshteyn V, Ershov A, Gavrilov G, Gavrilov V, Gninenko S, Golovtcov V, Golubev N, Golutvin I, Gorbunov I, Ivanov Y, Kachanov V, Kardapoltsev L, Karjavine V, Karneyeu A, Kim V, Kirakosyan M, Kirpichnikov D, Kirsanov M, Klyukhin V, Kodolova O, Konstantinov D, Korenkov V, Kozyrev A, Krasnikov N, Lanev A, Levchenko P, Litomin A, Lychkovskaya N, Makarenko V, Malakhov A, Matveev V, Murzin V, Nikitenko A, Obraztsov S, Oskin A, Ovtin I, Palichik V, Perelygin V, Perfilov M, Petrushanko S, Popov V, Radchenko O, Rusinov V, Savina M, Savrin V, Shalaev V, Shmatov S, Shulha S, Skovpen Y, Slabospitskii S, Smirnov V, Sosnov D, Sulimov V, Tcherniaev E, Terkulov A, Teryaev O, Tlisova I, Toropin A, Uvarov L, Uzunian A, Vorobyev A, Voytishin N, Yuldashev BS, Zarubin A, Zhizhin I, Zhokin A. A search for decays of the Higgs boson to invisible particles in events with a top-antitop quark pair or a vector boson in proton-proton collisions at s=13TeV

A search for decays to invisible particles of Higgs bosons produced in association with a top-antitop quark pair or a vector boson, which both decay to a fully hadronic final state, has been performed using proton-proton collision data collected at s = 13 Te V by the CMS experiment at the LHC, corresponding to an integrated luminosity of 138fb - 1 . The 95% confidence level upper limit set on the branching fraction of the 125Ge V Higgs boson to invisible particles, B ( H → inv ) , is 0.54 (0.39 expected), assuming standard model production cross sections. The results of this analysis are combined with previous B ( H → inv ) searches carried out at s = 7 , 8, and 13Te V in complementary production modes. The combined upper limit at 95% confidence level on B ( H → inv ) is 0.15 (0.08 expected).

Determination of Spin-Parity Quantum Numbers for the Narrow Structure near the pΛ[over ¯] Threshold in e^{+}e^{-}→pK^{-}Λ[over ¯]+c.c

A narrow structure in the pΛ[over ¯] system near the mass threshold, named as X(2085), is observed in the process e^{+}e^{-}→pK^{-}Λ[over ¯] with a statistical significance greater than 20σ. Its spin and parity are determined for the first time to be J^{P}=1^{+} in an amplitude analysis, with a statistical significance greater than 5σ over other quantum numbers (0^{-},1^{-} and 2^{+}). The pole positions of X(2085) are measured to be M_{pole}=(2084_{-2}^{+4}±9)  MeV and Γ_{pole}=(58_{-3}^{+4}±25)  MeV, where the first uncertainties are statistical and the second ones are systematic. The analysis is based on the study of the process e^{+}e^{-}→pK^{-}Λ[over ¯] and uses the data samples collected with the BESIII detector at the center-of-mass energies sqrt[s]=4.008, 4.178, 4.226, 4.258, 4.416, and 4.682 GeV with a total integrated luminosity of 8.35  fb^{-1}.

Observation of τ Lepton Pair Production in Ultraperipheral Pb-Pb Collisions at sqrt[s_{NN}]=5.02 TeV

We present an observation of photon-photon production of τ lepton pairs in ultraperipheral lead-lead collisions. The measurement is based on a data sample with an integrated luminosity of 404  μb^{-1} collected by the CMS experiment at a center-of-mass energy per nucleon pair of sqrt[s_{NN}]=5.02  TeV. The γγ→τ^{+}τ^{-} process is observed for τ^{+}τ^{-} events with a muon and three charged hadrons in the final state. The measured fiducial cross section is σ(γγ→τ^{+}τ^{-})=4.8±0.6(stat)±0.5(syst)  μb, where the second (third) term corresponds to the statistical (systematic) uncertainty in σ(γγ→τ^{+}τ^{-}) in agreement with leading-order QED predictions. Using σ(γγ→τ^{+}τ^{-}), we estimate a model-dependent value of the anomalous magnetic moment of the τ lepton of a_{τ}=0.001_{-0.089}^{+0.055}.

Observation of an Excess of Dicharmonium Events in the Four-Muon Final State with the ATLAS Detector

A search is made for potential ccc[over ¯]c[over ¯] tetraquarks decaying into a pair of charmonium states in the four muon final state using proton-proton collision data at sqrt[s]=13  TeV, corresponding to an integrated luminosity of 140  fb^{-1} recorded by the ATLAS experiment at LHC. Two decay channels, J/ψ+J/ψ→4μ and J/ψ+ψ(2S)→4μ, are studied. Backgrounds are estimated based on a hybrid approach involving Monte Carlo simulations and data-driven methods. Statistically significant excesses with respect to backgrounds dominated by the single parton scattering are seen in the di-J/ψ channel consistent with a narrow resonance at 6.9 GeV and a broader structure at lower mass. A statistically significant excess is also seen in the J/ψ+ψ(2S) channel. The fitted masses and decay widths of the structures are reported.

Observation of the γγ→ττ Process in Pb+Pb Collisions and Constraints on the τ-Lepton Anomalous Magnetic Moment with the ATLAS Detector

This Letter reports the observation of τ-lepton-pair production in ultraperipheral lead-lead collisions Pb+Pb→Pb(γγ→ττ)Pb and constraints on the τ-lepton anomalous magnetic moment a_{τ}. The dataset corresponds to an integrated luminosity of 1.44  nb^{-1} of LHC Pb+Pb collisions at sqrt[s_{NN}]=5.02  TeV recorded by the ATLAS experiment in 2018. Selected events contain one muon from a τ-lepton decay, an electron or charged-particle track(s) from the other τ-lepton decay, little additional central-detector activity, and no forward neutrons. The γγ→ττ process is observed in Pb+Pb collisions with a significance exceeding 5 standard deviations and a signal strength of μ_{ττ}=1.03_{-0.05}^{+0.06} assuming the standard model value for a_{τ}. To measure a_{τ}, a template fit to the muon transverse-momentum distribution from τ-lepton candidates is performed, using a dimuon (γγ→μμ) control sample to constrain systematic uncertainties. The observed 95% confidence-level interval for a_{τ} is -0.057 Collapse

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Measurement of Ultra-High-Energy Diffuse Gamma-Ray Emission of the Galactic Plane from 10 TeV to 1 PeV with LHAASO-KM2A

The diffuse Galactic γ-ray emission, mainly produced via interactions between cosmic rays and the interstellar medium and/or radiation field, is a very important probe of the distribution, propagation, and interaction of cosmic rays in the Milky Way. In this Letter, we report the measurements of diffuse γ rays from the Galactic plane between 10 TeV and 1 PeV energies, with the square kilometer array of the Large High Altitude Air Shower Observatory (LHAASO). Diffuse emissions from the inner (15°10  TeV). The energy spectrum in the inner Galaxy regions can be described by a power-law function with an index of -2.99±0.04, which is different from the curved spectrum as expected from hadronic interactions between locally measured cosmic rays and the line-of-sight integrated gas content. Furthermore, the measured flux is higher by a factor of ∼3 than the prediction. A similar spectrum with an index of -2.99±0.07 is found in the outer Galaxy region, and the absolute flux for 10≲E≲60  TeV is again higher than the prediction for hadronic cosmic ray interactions. The latitude distributions of the diffuse emission are consistent with the gas distribution, while the longitude distributions show clear deviation from the gas distribution. The LHAASO measurements imply that either additional emission sources exist or cosmic ray intensities have spatial variations.

Precise Measurement of the e^{+}e^{-}→D_{s}^{*+}D_{s}^{*-} Cross Sections at Center-of-Mass Energies from Threshold to 4.95 GeV

The process e^{+}e^{-}→D_{s}^{*+}D_{s}^{*-} is studied with a semi-inclusive method using data samples at center-of-mass energies from threshold to 4.95 GeV collected with the BESIII detector operating at the Beijing Electron Positron Collider. The Born cross sections of the process are measured for the first time with high precision in this energy region. Two resonance structures are observed in the energy-dependent cross sections around 4.2 and 4.4 GeV. By fitting the cross sections with a coherent sum of three Breit-Wigner amplitudes and one phase-space amplitude, the two significant structures are assigned masses of (4186.8±8.7±30) and (4414.6±3.4±6.1)  MeV/c^{2}, widths of (55±15±53) and (122.5±7.5±8.1)  MeV, where the first errors are statistical and the second ones are systematic. The inclusion of a third Breit-Wigner amplitude is necessary to describe a structure around 4.79 GeV.

Hardware Implementation of Quantum Stabilizers in Superconducting Circuits

Stabilizer operations are at the heart of quantum error correction and are typically implemented in software-controlled entangling gates and measurements of groups of qubits. Alternatively, qubits can be designed so that the Hamiltonian corresponds directly to a stabilizer for protecting quantum information. We demonstrate such a hardware implementation of stabilizers in a superconducting circuit composed of chains of π-periodic Josephson elements. With local on-chip flux and charge biasing, we observe a progressive softening of the energy band dispersion with respect to flux as the number of frustrated plaquette elements is increased, in close agreement with our numerical modeling.

[Impact of COVID-19 pandemic on the management of imported malaria in China]

OBJECTIVE

To examine the impact of COVID-19 pandemic on the epidemic status of imported malaria and national malaria control program in China, so as to provide insights into post-elimination malaria surveillance.

METHODS

All data pertaining to imported malaria cases were collected from Anhui Province, Hubei Province, Henan Province, Zhejiang Province and Guangxi Zhuang Autonomous Region during the period from January 1, 2018 through December 31, 2021. The number of malaria cases, species of malaria parasites, country where malaria parasite were infected, diagnosis and treatment after returning to China, and response were compared before (from January 1, 2018 to January 22, 2020) and after the COVID-19 pandemic (from January 23, 2020 to December 31, 2021).

RESULTS

A total of 2 054 imported malaria cases were reported in Anhui Province, Hubei Province, Henan Province, Zhejiang Province and Guangxi Zhuang Autonomous Region during the period from January 1, 2018 to December 31, 2021, and there were 1 722 cases and 332 cases reported before and after the COVID-19 pandemic, respectively. All cases were reported within one day after definitive diagnosis. The annual mean number of reported malaria cases reduced by 79.30% in Anhui Province, Hubei Province, Henan Province, Zhejiang Province and Guangxi Zhuang Autonomous Region after the COVID-19 pandemic (171 cases) than before the pandemic (826 cases), and the number of monthly reported malaria cases significantly reduced in Anhui Province, Hubei Province, Henan Province, Zhejiang Province and Guangxi Zhuang Autonomous Region since February 2020. There was a significant difference in the constituent ratio of species of malaria parasites among the imported malaria cases in Anhui Province, Hubei Province, Henan Province, Zhejiang Province and Guangxi Zhuang Autonomous Region before and after the COVID-19 pandemic (χ2 = 146.70, P < 0.05), and P. falciparum malaria was predominant before the COVID-19 pandemic (72.30%), while P. ovale malaria (44.28%) was predominant after the COVID-19 pandemic, followed by P. falciparum malaria (37.65%). There was a significant difference in the constituent ratio of country where malaria parasites were infected among imported malaria cases in Anhui Province, Hubei Province, Henan Province, Zhejiang Province and Guangxi Zhuang Autonomous Region before and after the COVID-19 pandemic (χ2 = 13.83, P < 0.05), and the proportion of malaria cases that acquired Plasmodium infections in western Africa reduced after the COVID-19 pandemic that before the pandemic (44.13% vs. 37.95%; χ2 = 4.34, P < 0.05), while the proportion of malaria cases that acquired Plasmodium infections in eastern Africa increased after the COVID-19 pandemic that before the pandemic (9.58% vs. 15.36%; χ2 = 9.88, P = 0.02). The proportion of completing case investigation within 3 days was significantly lower after the COVID-19 pandemic than before the pandemic (96.69% vs. 98.32%; χ2= 3.87, P < 0.05), while the proportion of finishing foci investigation and response within 7 days was significantly higher after the COVID-19 pandemic than before the pandemic (100.00% vs. 98.43%; χ2 = 3.95, P < 0.05).

CONCLUSIONS

The number of imported malaria cases remarkably reduced in Anhui Province, Hubei Province, Henan Province, Zhejiang Province and Guangxi Zhuang Autonomous Region of China during the COVID-19 pandemic, with a decreased proportion of completing case investigations within 3 days. The sensitivity of the malaria surveillance-response system requires to be improved to prevent the risk of secondary transmission of malaria due to the sharp increase in the number of imported malaria cases following the change of the COVID-19 containment policy.

First Experimental Study of the Purely Leptonic Decay D_{s}^{*+}→e^{+}ν_{e}

Using 7.33  fb^{-1} of e^{+}e^{-} collision data taken with the BESIII detector at the BEPCII collider, we report the first experimental study of the purely leptonic decay D_{s}^{*+}→e^{+}ν_{e}. Our data contain a signal of this decay with a statistical significance of 2.9σ. The branching fraction of D_{s}^{*+}→e^{+}ν_{e} is measured to be (2.1_{-0.9_{stat}}^{+1.2}±0.2_{syst})×10^{-5}, corresponding to an upper limit of 4.0×10^{-5} at the 90% confidence level. Taking the total width of the D_{s}^{*+} [(0.070±0.028)  keV] predicted with the radiative D_{s}^{*+} decay from the lattice QCD calculation as input, the decay constant of the D_{s}^{*+} is determined to be f_{D_{s}^{*+}}=(214_{-46_{stat}}^{+61}±44_{syst})  MeV, corresponding to an upper limit of 354 MeV at the 90% confidence level.

Impacts of pregnancy and menopause on COVID-19 severity: a systematic review and meta-analysis of 4.6 million women

BACKGROUND

Corona Virus Disease 2019 (COVID-19) pandemic is still a public health emergency of international concern. However, whether pregnancy and menopause impact the severity of COVID-19 remain unclear.

AIM

This study is performed to investigate the truth.

DESIGN

Study appraisal and synthesis follows PRISMA guideline. Meta-analysis is performed in random-effects model.

METHODS

PubMed, Embase, Cochrane database, Central, CINAHL, ClinicalTrials.gov, WHO COVID-19 database and WHO-ICTRP are searched until 28 March 2023.

RESULTS

In total, 57 studies (4 640 275 COVID-19 women) were analyzed. Pregnant women were at a lower risk of severe COVID-19, intensive care unit (ICU) admission and disease mortality compared to those nonpregnant women with comparable comorbidities. In contrast, pregnant women with more prepregnancy comorbidities were at a higher risk of severe COVID-19, ICU admission and invasive mechanical ventilation (IMV). In addition, pregnant women with pregnancy complications had a significantly increased risk of severe COVID-19 and ICU admission. Menopause increased COVID-19 severity, IMV requirement and disease mortality. Hormone replacement therapy inhibited COVID-19 severity in postmenopausal women. Premenopausal and postmenopausal women had a lower chance of severe illness than age-matched men. The impact of pregnancy on COVID-19 severity was significant in Americans and Caucasians, whereas the effect of menopause on COVID-19 severity was only significant in Chinese.

CONCLUSIONS

Pregnancy and menopause are protective and risk factors for severe COVID-19, respectively. The protective role of pregnancy on COVID-19 is minimal and could be counteracted or masked by prepregnancy or pregnancy comorbidities. The administration of estrogen and progesterone may prevent severe COVID-19.

Efficacy of Postoperative Radiotherapy for Patients with New N2 Descriptors of Subclassification in Completely Resected Non-Small Cell Lung Cancer: A Real-World Study

PURPOSE/OBJECTIVE(S)

Patients with N2 non-small cell lung cancer (NSCLC) were heterogeneous groups and required further stratification. The International Society for the Study of Lung Cancer (IASLC) added new descriptors of three sub-stages for stage N2 NSCLC: N2 at a single station without N1 involvement (N2a1), N2 at a single station with N1 involvement (N2a2), and N2 at multiple stations (N2b). This study aimed to investigate the efficacy of postoperative radiotherapy (PORT) for patients with these N2 descriptors.

MATERIALS/METHODS

Patients with histologically confirmed NSCLC after complete resection and divided into PORT group and non-PORT group. The primary endpoint was DFS. The second endpoints were overall survival (OS) and locoregional recurrence-free survival (LRFS). Propensity-score matching (PSM) of baseline characteristics between the PORT and non-PORT groups was used for validation.

RESULTS

Totally 1832 patients were enrolled, including 308 N2a1 patients, 682 N2a2 patients, and 842 N2b patients. The median follow-up time was 50.1 months. The survival outcomes of the PORT and non-PORT groups before PSM were shown in Table 1. For patients with N2a1, PORT could not improve the DFS (median DFS of the PORT group and the non-PORT group: not reached vs. 46.8 months, P = 0.41), OS (P = 0.85), or LRFS (P = 0.32), which were consistent with the multivariate analysis and data after the PSM. For patients with N2a2, PORT significantly improved the DFS (median DFS 29.7 vs. 22.2 months, P = 0.02), OS (P = 0.03), and LRFS (P = 0.01). The multivariate analysis and data after the PSM confirmed the benefits in DFS and LRFS, but no benefit was observed in OS (multivariate analysis: HR 0.79, P = 0.18; median OS after PSM: 103.7 vs. 63.1 months, P = 0.34). For patients with N2b, PORT could not improve the DFS (median DFS 20.6 vs. 21.2 months, P = 0.39) but significantly improved the OS (P<0.001) and LRFS (P<0.001). However, the multivariate analysis showed that PORT significantly improved DFS (HR 0.81, P = 0.03), consistent with the data after the PSM (median DFS 20.6 and 17.6 months, P = 0.04).

CONCLUSION

PORT significantly improved the DFS and LRFS in patients with N2a2 and significantly improved the DFS, LRFS, and OS in patients with N2b. Patients with N2a1 could not benefit from PORT.

An inverse Jiles-Atherton model of nanocrystalline magnetic core for nanoseconds square pulsed magnetization

The magnetic core is a key component of a linear transformer driver (LTD), and the accuracy of the core model affects the calculation of the LTD power flow and the prediction of the output waveform. In this paper, a magnetization model based on the inverse Jiles-Atherton (inverse J-A) model is developed and a particle swarm algorithm is used to identify the parameters and to obtain the variation of the parameters with the excitation characteristic. A nanoseconds square wave LTD magnetic core test platform was built to obtain the magnetization characteristics of nanocrystalline magnetic cores under different excitation characteristic parameters. Under square wave pulses, due to the presence of harmonic components, core loss is more complex. In view of the fitting deviation caused by the traditional J-A model not considering harmonic factors and anisotropy, a dynamic loss correction factor is proposed. Through a comparison of experimental and simulation results, this model can well reflect the magnetization process and has high accuracy in fitting dynamic hysteresis loops and predicting losses, which is important for guiding the design of a square pulse LTD.

Cost Analysis of MR-Guided vs. CT-Guided Radiation Therapy for Locally Advanced Pancreatic Cancer

PURPOSE/OBJECTIVE(S)

Stereotactic magnetic resonance guided on-table adaptive radiotherapy (SMART) is an increasingly utilized radiotherapy (RT) treatment for locally advanced pancreatic cancer (LAPC), providing improved local control and overall survival with reduced toxicity. Computed tomography (CT) guided RT options include stereotactic body radiotherapy (SBRT) and hypofractionated RT with volumetric modulated arc therapy (VMAT). Currently there are no financial comparisons for MR vs CT-guided RT for LAPC. We completed a cost analysis comparing the physician and hospital charges associated with RT options for LAPC.

MATERIALS/METHODS

To compare RT costs, we identified Current Procedural Terminology (CPT) codes utilized for 5-fraction SMART with adaptation (50 Gy, biological effective dose (BED) 100 Gy), 5-fraction CT-guided SBRT (33 Gy, BED 55 Gy), and 15-fraction CT-guided hypofractionated VMAT (67.5 Gy, BED 98 Gy) in a hospital-based practice setting. Physician and hospital Medicare prices associated with these codes together summarize the overall cost. We determined physician fees using the Centers for Medicare and Medicaid Services (CMS) Physician Fee Schedule Search to search the Healthcare Common Procedure Coding System (HCPCS) for "professional" costs included within "facility" costs. We determined hospital fees using the Outpatient Prospective Payment System addendum. To standardize costs, we searched for national payment amounts for the 2022 calendar year.

RESULTS

Total cost of SMART with adaptation was 136% higher than the cost of CT-SBRT and 149% higher than the cost of hypofractionated RT. Physician fees for SMART were 173% higher and 157% higher than the fees for CT-SBRT and hypofractionated RT, respectively. Hospital fees for SMART were 129% higher and 147% higher than the fees for CT-SBRT and hypofractionated RT, respectively. The total cost of CT-SBRT was only 5% higher than cost of hypofractionated RT. The physician fees for hypofractionated RT were 6% higher than those for CT-SBRT, while the outpatient fees for CT SBRT were 7% higher than those for hypofractionated RT.

CONCLUSION

With recent data demonstrating favorable efficacy and toxicity rates for SMART, practices may increasingly consider investing in this treatment modality. This is the first cost analysis comparing SMART to CT-guided SBRT and hypofractionated RT in LAPC. We demonstrate higher costs of SMART compared to CT-guided RT, attributable primarily to higher number of dosimetry calculations for this modality and for adapted fractions. We also demonstrate comparable costs of lower BED CT-guided SBRT and higher BED hypofractionated RT. Further investigation is needed to assess whether the survival benefit of SMART translates to favorable cost per quality adjusted life year.

Prediction of Anatomical Presentation during Radiotherapy of Nasopharyngeal Carcinoma Using GAN-LSTM for Plan Adaption Decision

PURPOSE/OBJECTIVE(S)

During treatment, patients frequently undergo anatomical changes that might result in dose degradation. Adaptive radiation therapy (ART) is now available to overcome this problem. However, this method is time-consuming, and the lack of criteria to trigger replanning prevents its widespread use. To overcome these obstacles, anatomical presentation models are necessary. In this study, we developed a novel deep-learning method to make a series of predictions for the remaining treatment course.

MATERIALS/METHODS

Total 230 nasopharyngeal carcinoma patients who received radiotherapy in 33 fractions were enrolled. The data included cone-beam computed tomography (CBCT) and planning CT images. CBCT image quality was improved to CT level using an in-house software. A generative adversarial network-long short-term memory network model was proposed, with the generation abilities of the former network and forecasting abilities of the latter. To predict the anatomical presentation for 3-6 weeks, we trained four models. The planning CT and CBCT acquired earlier were used as the input. Physicians segmented the gross target volume (GTVnx) and parotid glands on prediction and real CBCT (ground truth). Contours, dosimetry parameters, and plan adaptation decision were used to evaluate the models.

RESULTS

The table shows the overall performance of the test set (18 cases). The anatomical changes were predicted over the treatment course with a dice similarity coefficient (DSC) of 0.96, 0.90 and 0.92 and mean distance to agreement (MDA, in mm) of 0.37, 0.70, and 0.60 for GTVnx, left parotid, and right parotid, respectively. Bland-Altman analysis revealed that dosimetry parameters did not show significant difference between prediction and ground truth. The prescription coverage (%) of GTVnx, V30 of the left parotid, and V30 of the right parotid had mean absolute biases of 0.09, 1.09, and 0.27, respectively. At week 6, there were two cases that required plan adaptation, and the model effectively triggered replanning one week in advance.

CONCLUSION

We developed a framework that predicts the anatomical changes occurring in future fractions. Establishing such a framework provides a proactive approach to ART and saves clinical time by anticipating and preparing for treatment strategies in advance.

Deep Learning for Automated Contouring of Primary Gross Tumor Volumes by MRI for Radiation Therapy of Brain Metastasis

PURPOSE/OBJECTIVE(S)

Radiotherapy is one of the most effective methods for the treatment of brain metastases (BMs). Traditional manual delineation of primary gross tumor volumes (GTV) of multiple BMs (especially small metastases) in radiotherapy practice is extremely labor intensive and highly dependent on oncologists' experience, achieving the precise and efficient automatic delineation of BMs is of great significance for efficient and homogeneous one-stop adaptive radiotherapy.

MATERIALS/METHODS

We retrospectively collected 62 MRI (non-enhanced T1-weighted sequences) sequences of 50 patients with BMs from January 2020 to July 2021. An automatic model (BUC-Net) for automatic delineation BMs was proposed in this work, which was based on deep learning by combining 3D bottler layer module and the cascade architecture to improve the accuracy and efficient of BMs' automatic delineation, especially for small metastases with tiny size and relatively low contrast. The prosed method was compared with the existing 3D U-Net (U-Net) and 3D U-Net Cascade (U-Net Cascade). The performance of our proposed method was evaluated by Dice similarity coefficient (DSC), 95% Hausdorff distance (HD95) and average surface distance (ASD) with human experts.

RESULTS

The automatic segmentation results of BUC-Net evaluated with 310 BMs in 13 test patients was summarized in Table 1. These BMs in each test patient were automatically delineated by two types of contours: as a whole tumor contour (Whole-delineation) and the multiple tumor contours (Multiple-delineation). BUC-Net performed the best mean DSC and HD95, which is significantly outperformed U-Net (Whole-delineation: 0.911 & 0.894 of DSC, Multiple-delineation: 0.794 & 0.754 of DSC, P < 0.05 for both) and U-Net cascade (Whole-delineation: 0.947 & 7.141 of HD95, Multiple-delineation: 0.902 & 1.171 of HD95, P < 0.05 for both); Additionally, BUC-Net achieved the best mean ASD for Whole-delineation and comparable ASD (0.290 & 0.277, P > 0) for Multiple-delineation with U-Net Cascade.

CONCLUSION

Our results showed that the proposed approach is promising for the automatic delineation of BMs in MRI, which can be integrated into a radiotherapy workflow to significantly shorten segmentation time.

Combined effects of soil 3D spatial heterogeneity and biotic spatial heterogeneity (plant clumping) on ecosystem processes in grasslands

Soil heterogeneity has been shown to enhance plant diversity, but its effect on grassland productivity is less clear. Even less is known about the effect of plant clumping (intraspecific aggregation) and its potential interaction with soil heterogeneity. The combined effects of soil 3D spatial heterogeneity and species clumping were experimentally studied in grassland mesocosms consisting of four grassland species. These species were planted in three patterns (i.e. completely mixed, clumped by 9 or 36 individuals of the same species) on soils with heterogeneous cells of alternating nutrient-poor and rich soil differing in size from 0 (mixed soil) to 12, 24, and 48 cm (complete poor or rich mesocosm). Moderate soil cell sizes (12-24 cm) consistently increased whole-mesocosm aboveground productivity by more than 20%, which mainly originated from the increased growth of the plants growing on the poor soil cells. In contrast, total mesocosm productivity was not affected by species clumping although there were some species-specific effects, both of clumping and of the interaction of clumping with soil heterogeneity. Our results show that intermediate soil heterogeneity promotes productivity. Clumping can improve the growth of inferior species, thus promoting coexistence, without affecting overall productivity. We found no interaction effect of clumping and soil heterogeneity on productivity at the community level and some minor species-specific effects.

Exploring the TRP channel superfamily: research hotspots and development trends from function to disease

OBJECTIVE

Transient receptor potential (TRP) channels are a superfamily of permeable cation channels activated by various mechanisms and play a role in nearly all types of sensory signal transduction. In academia, few have comprehensively discussed the research status of TRP channels. This study aims to summarize the knowledge structure and research hotspots of TRP channels using bibliometrics.

MATERIALS AND METHODS

TRP channel-related publications from 2003 to 2022 were searched in the Web of Science Core Collection (WoSCC) database. VOSviewer was used for the bibliometric analysis of the literature.

RESULTS

We included 12,242 articles from 102 countries, primarily from the United States, China, and Japan. Our research indicates that the number of publications related to TRP channels has increased annually from 2003 to 2022. The leading research institutions are KU Leuven, Harvard University, and the Chinese University of Hong Kong. The Journal of Biological Chemistry is the foremost in this field. The main research topics include the structure and function of TRP channels, their role in pathogenesis, and potential therapeutic strategies for diseases such as pain and respiratory diseases. Among these, "transient receptor potential vanilloid 1 (TRPV1)", "transient receptor potential ankyrin 1 (TRPA1)", "TRPV4", "pain", and "therapy" are emerging research hotspots.

CONCLUSIONS

This study offers a comprehensive summary of the current research status and development trends of TRP channels and pinpoints the research hotspots in this field. It not only aids individuals interested in TRP channel-related research in quickly gauging the trends but may also guide the future research directions of researchers.

Racial Difference in Outcomes in Breast Cancer Patients with Residual Nodal Disease after Neoadjuvant Chemotherapy

PURPOSE/OBJECTIVE(S)

African Americans (AA) requiring neoadjuvant chemotherapy (NAC) have been associated with worse outcomes. Residual nodal disease (ypN+) after NAC represents a highly unfavorable risk factor. We hypothesized that even within this unfavorable subgroup, that racial differences in outcome would persist.

MATERIALS/METHODS

An IRB-approved retrospective review of breast cancer (BC) patients in a multi-institutional study was performed between 2005-2018 to identify ypN+ patients (excluding metastatic or inflammatory BC). Clinico-pathologic parameters stratified by race were collected and analyzed. For molecular subtype analyses, patients were stratified into triple negative (TN), hormone receptor (HR)+/HER2-, and HR+/HER2+, and HR-/HER2+ subtypes. Overall survival (OS), disease free survival (DFS) and recurrence outcomes were obtained, and univariate and multivariate (MVA) logistic regression models were constructed and analyzed.

RESULTS

Among 404 ypN+ patients, 107 (26%) were AA, and 297 (74%) were non-AA. Median follow-up for the non-AA group was 3.8 years (y) (IQR 2.4-6.3) and 3.5y (IQR 2.0-6.2) for the AA group. Clinical and pathologic patient characteristics (age, molecular subtypes, BRCA status, histology, grade, smoking status, primary surgery type, axillary/reconstruction surgery rates, margin status, stage) were without significant statistical differences between the non-AA and AA group, except the non-AA group had proportionally more cN3 disease (10.5% vs. 5.1%; p = .01). Despite this, AA demonstrated worse OS and DFS outcomes (Table). AA also had significantly worse local (15% vs. 6.7%, p = .02), regional (11.2% vs. 5.1%, p = .05) and distant recurrences (32.7% vs. 22.6%, p = .05) compared to non-AA. On MVA for OS and DFS, HR+ status, clinical stage, and AA race (HR 2.1 (CI 1.3-3.4), p = .004 and HR 1.7 (CI 1.1-2.6), p = .01 respectively) remained significant. Molecular subtype analysis demonstrated that AA with HR+/HER2- but not the TN subtypes demonstrated significantly worse outcomes (Table). Utilization of endocrine therapy was not different between AA and non-AA patients (94% vs. 97%, p = 0.3) to explain this discrepancy. Worse outcomes in HER2 subtype for AA group was suggested but could not be statistically verified due to insufficient sample size. There was no discernible difference in chemotherapy and radiation therapy regimen or compliance between the AA and non-AA groups.

CONCLUSION

AA patients who fail to achieve nodal clearance with NAC had higher local, regional and distant recurrence, and worse survival compared to non-AA, particularly those with non-TN status. These differences could not be readily explained by therapeutic disparity, or compliance. These hypothesis generating findings suggest need to explore biological implications, and alternative therapeutic strategies for this unfavorable subgroup.

A Generalized Deep Learning Method for Synthetic CT Generation

PURPOSE/OBJECTIVE(S)

The application of deep learning to generate synthetic CT (sCT) has been widely studied in radiotherapy. Existing methods generally involve data from two different image modalities, such as CBCT-CT or MRI-CT, the quality of sCT is adversely affected by source image quality. We propose a unique method of synthesizing MRI and CBCT into sCT based on single-modal CT for training, and call it SmGAN.

MATERIALS/METHODS

We used planning CT of a group of 35 head and neck cases to as training data. We then applied two different spatial transformations to the planning CT image to produce the transformed CT1 and CT2. And We used a random style enhancement technique (Shuffle Remap) to modify the image distribution of CT1 which we termed CT1+E. CT1+E was used to simulate the patient's "image of the day" while CT2 to simulate the "planning image". After feeding both CT1+E and CT2 into the generator, we obtained the sCT predicted by the generator. The generator was trained using the Mean Absolute Error (MAE) loss between sCT and CT1. In the actual clinical process, we use the patient's CBCT or MRI instead of CT1+E and the patient's planning CT instead of CT2 as the input of the generator. After processing, we get an sCT that can maintain the spatial position of the image taken on the day, while presenting features similar to the planning CT. The evaluation data we have includes 10 pairs of MRI-Def_CT and 10 pairs of CBCT-Def_CT Head and Neck patients. Def_CT is obtained from the planning CT based on the spatial position deformation of MRI and CBCT. To evaluate the accuracy of sCT based on MRI and CBCT with Def CT, we use a range of metrics, including Hounsfield Unit (HU) difference, peak signal-to-noise ratio (PSNR), structural similarity (SSIM) and gamma pass rate. All results will be benchmarks against the advanced method RegGAN for comparison.

RESULTS

Compared to RegGAN, the results of SmGAN were significantly better. The mean absolute errors within the body were (44.7±216.2 HU vs. 36.7±131.4 HU) and (64.9±123.7 HU vs. 58.2±152.8 HU) for the CBCT-SCT and MRI-SCT, respectively (Table 1). In addition, experimental results show that SmGAN also outperforms RegGAN in dose calculation accuracy. For example, under the 10% threshold, SmGAN's gamma pass rate of 1mm and 1% is 0.926±0.02, compared with gamma rate of 0.896±0.02 for RegGAN.

CONCLUSION

We proposed a generalized deep learning model for synthetic CT generation, based on CBCT or MRI images. The proposed algorithm achieved high accuracy of dosimetric metrics, as well as excellent IMRT QA verification results. Compared to other existing synthetic CT generation methods, the proposed SmGAN required a single-modal image for training, which is considered as a major breakthrough in the industry, and is expected to have wide spread of clinical applications.

Deep Learning and GAN-Synthesis for Auto-Segmentation of Pancreatic Cancer by Non-Enhanced CT for Adaptive Radiotherapy

PURPOSE/OBJECTIVE(S)

In conventional adaptive radiotherapy (ART) for pancreatic cancer, contrast-enhanced CT (CECT) helps to more precisely delineate primary gross tumor volume (GTV) than non-enhanced CT (NECT). However, frequent use of contrast medium can damage kidneys and prolong treatment time. Moreover, traditional manual delineation is labor-intensive and highly dependent on the experience of oncologists. Currently, automatic delineation based on deep learning with Generative Adversarial Networks (GAN)-based CT synthesis is one of the most feasible solutions to these problems.

MATERIALS/METHODS

A dataset of 35 pancreatic cancer patients was retrospectively collected from May 2021 to December 2022. All patients consist of a pair of NECT and CECT. We designed and developed an automatic delineation framework (Proposed) for GTV of pancreatic cancer based on Trans-cycleGAN and a modified 3D U-Net. TranscycleGAN can not only synthesize CECT from NECT, but can also augment the amount of CT images; then all real and synthesized CT images were used to train the modified 3D U-Net for automatic delineation of GTV; finally, our framework was able to automatically delineate GTV by NECT, but not only by CECT. Our framework was evaluated by dice similarity coefficient (DSC), 95% Harsdorff distance (95HD) and average surface distance (ASD) with oncologists' manual delineation ("gold standard").

RESULTS

The evaluation results were summarized in Table 1. The proposed framework achieved the best automatic delineation results by NECT, which was superior to that of CECT: 0.917 & 0.903 of DSC, 2.498mm & 3.029mm of HD95, 0.481mm & 0.534mm of ASD, p < 0.05 for DSC and HD95. Specifically, it is significantly superior to the automatic delineation results using U-Net by CECT 0.917 & 0.818 of DSC, 2.498mm & 13.228mm of HD95, 0.481mm & 3.633mm of ASD, p < 0.05 for DSC.

CONCLUSION

We proposed an automatic delineation framework for contouring GTV in ART of pancreatic cancer based on deep learning and Trans-cycleGAN network. This framework could automatically delineate GTV and achieve better performance with NECT compared to CECT. Our method could not only reduce the use of contrast medium, but also increase the precision and effectiveness of tumor delineation, which could have a positive impact on precision radiotherapy.

Sarcopenia and its clinical correlation in elderly chronic obstructive pulmonary disease: a prospective cohort study

OBJECTIVE

The aim of this study was to examine the effects of sarcopenia on clinical characteristics and short-term outcomes in elderly chronic obstructive pulmonary disease (COPD) patients.

PATIENTS AND METHODS

One hundred twenty elderly COPD patients (age>60) recruited from Beijing Shijingshan Hospital were divided into sarcopenia and non-sarcopenia groups according to the severity of sarcopenia at the first admission. Baseline data, geriatric syndrome, laboratory indicators and body composition analysis were analyzed. One year followed-up by outpatient visits was focused on clinical characteristics and telephone follow-ups for collecting all-cause deaths and acute exacerbations of chronic obstructive pulmonary disease as end-point events. The risk factors for sarcopenia were analyzed by univariate analysis and multivariate logical regression. The proportional hazards model (COX) regression was performed to determine the effect of sarcopenia on COPD patients' prognoses.

RESULTS

One hundred twenty patients (76 men and 44 women) with an average age of 76.7±8.78 years were included, of which 63 patients (52.5%) were diagnosed with sarcopenia. Compared to the non-sarcopenia group, the sarcopenia group exhibited worse lung function and more severe geriatric syndromes with significantly higher incidence ratios of somnipathy and frailty. The sarcopenia group also showed worse muscle indicators and declined body composition. Multivariate analysis showed that the occurrence of sarcopenia in elderly COPD patients was correlated with forced expiratory volume in the first second (FEV1) (OR=0.97, 95% CI: 0.94-1.0, p=0.035), body mass index (BMI) (OR=0.80, 95% CI: 0.71-0.89, p=0.035) and hemoglobin (OR=0.98, 95% CI: 0.96-1.0, p=0.023). Furthermore, the COX regression indicated the association of sarcopenia with acute exacerbations of COPD within the follow-up period (HR=2.4, 95% CI: 1.01-5.72, p=0.048).

CONCLUSIONS

Sarcopenia increases the risk of acute exacerbations of chronic obstructive pulmonary disease in the elderly. Sarcopenia incidence in elderly COPD is associated with FEV1, BMI, and hemoglobin and closely monitoring indicators is useful for early diagnosis of sarcopenia.

A Machine Learning Method to Predict Pathological Complete Response of Esophageal Cancer after Neoadjuvant Chemoradiotherapy with Clinicohematological Markers and MR Radiomics: A Multi-Center Study

PURPOSE/OBJECTIVE(S)

Nearly 30% of patients with local advanced esophageal cancer achieved pathological complete response (pCR) after neoadjuvant chemoradiotherapy (nCRT), who may benefit from organ-preservation strategy under accurate prediction of pCR. We aimed to develop and validate machine learning models based on clinicohematological markers and MR radiomics to accurately predict pCR of esophageal cancer after nCRT.

MATERIALS/METHODS

In this multi-center study, eligible patients with esophageal cancer who received baseline MR scan (T2-weighted image) and nCRT plus surgery were enrolled between September 2014 and September 2022 at institution 1 (training set) and between December 2017 and August 2021 at institution 2 (testing set). Pre-nCRT and post-nCRT blood test results were collected to calculate hematological markers. Models were constructed by machine learning based on clinicohematological markers and MR radiomics to predict pCR. Area under the curve (AUC) and cut-off analysis were used to evaluate model performances.

RESULTS

Totally 154 patients (81 in the training set and 73 in the testing set) were enrolled. The combined model integrating pre-nCRT monocyte-to-lymphocyte ratio and 6 radiomics features achieved AUC of 0.800 (95% CI 0.671-0.918) in the testing set, with sensitivity of 79.2% (95% CI 62.5%-95.8%), specificity of 83.7% (95% CI 73.5%-93.9%), positive predictive value of 76.0% (95% CI 62.5%-90.0%), and negative predictive value of 89.6% (95% CI 82.0%-95.8%).

CONCLUSION

A machine learning model based on clinicohematological markers and MR radiomics to predict pCR after nCRT for patients with esophageal cancer was developed and validated, providing a novel tool for personalized treatment. It is necessary to further validate in more large datasets.

Clinical Verification of a Nomogram Model for Prediction of Brain Metastases in Patients with pⅢA-N2 Non-Small Cell Lung Cancer

PURPOSE/OBJECTIVE(S)

Brain metastasis is one of the most common failure patterns of pⅢA-N2 non-small cell lung cancer (NSCLC) after complete resection. Prophylactic Cranial Irradiation (PCI) can improve intracranial control but not overall survival. Thus, it is particularly important to identify risk factors that are associated with brain metastasis and subsequently provide instructions for selecting patients who will optimally benefit from PCI. We have reported a nomogram model which was established based on the condition of histology, bronchial invasion, perineural invasion, and adjuvant chemotherapy, through which we can predict high risk brain metastases in patients with pⅢA-N2 NSCLC. The purpose of this study is to verify the accuracy of the nomogram model by using new cases information.

MATERIALS/METHODS

Between January 1, 2015 and December 31, 2019, patients of pⅢA-N2 NSCLC were retrospectively analyzed, to verify the consistency between actual and predictive brain metastases. The verification group was divided into two groups according to the years when genetic testing has been widely used in clinic (group1:2015-2016, group2:2017-2019). ROC curves and calibration curves were chosen for validation.

RESULTS

A total of 770 patients were enrolled in our retrospective study (group1:294 patients, group2: 476patients). The 1-, 3- and 5-year survival rates were 97.2%, 76.5%, 63.2% in group1, and 95.8%, 84.5%, 76.9% in group2, respectively. The 1-, 3- and 5-year brain metastasis rates were 7.9%, 19.7%, 25.8%, and 5.4%, 14.5%, 26.3% in group2, respectively. The AUC were 0.74 (95% CI:0.72 - 0.76) in group1, and 0.71(95% CI:0.70 - 0.73) in group 2.The 1.3.5-year calibration curves of the two groups show that the prediction is in good agreement with the actual observation.

CONCLUSION

The nomogram model can predict brain metastases high risk patients with pⅢA-N2 NSCLC. Whether gene test or not, it can be used as a basis to screening out patients of high-risk brain metastases in future clinical trials for PCI.

Adaptive Ultra-Hypofractionated Whole-Pelvic Radiotherapy in High-Risk and Very High-Risk Prostate Cancer on 1.5-1.5 MR Linac: The Estimated Delivered Dose and Early Toxicity Results

PURPOSE/OBJECTIVE(S)

To study the feasibility and safety for patients with high-risk (HR) and very high-risk (VHR) prostate cancer treated with adaptive ultra-hypofractionated whole-pelvic radiotherapy (UHF-WPRT) on 1.5 magnetic resonance (MR)-Linac.

MATERIALS/METHODS

Sevenpatients with clinical stage T3a-4N0-1M0-1c consecutively treated with UHF-WPRT on a 1.5-T MR-Linac were recruited prospectively in a phase II trial (NCT05183074, ChiCTR2000033382). A 36.25 Gy dose in five fractions was delivered every other day with a boost of 40 Gy to the whole prostate, as well as 25 Gy to whole pelvic nodal area with a concomitant boost of 35 Gy to metastatic regional nodes. To estimate the delivered dose, we collected data by 3D-MR for the following stages: pre-MR, position verification-MR (PV-MR) in the Adapt-To-Shape (ATS) workflow, and 3D-MR during the beam-on phase (Bn-MR) and at the end of RT (post-MR). The target and organ-at-risk contours in the PV-MR, Bn-MR, and post-MR stages were projected from the pre-MR data by deformable image registration and manually adapted by the physician, followed by dose recalculation for the ATS plan. The cumulative acute genitourinary (GU) and gastrointestinal (GI) toxicities were evaluated as per NCI-CTCAE 5.0 criteria. The primary endpoints were acute ≥grade 3 genitourinary (GU) and gastrointestinal (GI) toxicities during the first 3 months.

RESULTS

Overall, 133 MR scans were collected (35 pre-MR, 35 PV-MR, 31 Bn-MR and 32 post-MR scans). With a median on-couch time of 61 minutes, the mean prostate and pelvic planning target volume (PTV)-V95% of all scans was 96.98 ± 3.06% and 96.44 ± 2.85%, respectively. The corresponding mean prostate clinical target volume (CTV)-V100% was 99.89 ± 0.32%, 98.71 ± 1.90%, 97.77 ± 2.89%, and 98.56 ± 1.72%, and the mean pelvic CTV-V100% was 97.57% ± 3.70%, 96.54 ± 3.80%, 95.43 ± 4.31%, and 94.39 ± 4.47% on pre-MR, PV-MR, Bn-MR and post-MR scans, respectively. For the 4 patients with positive nodes, the mean V100% of metastatic regional nodes was 99.89 ± 0.81%. The median V29 Gy change in the rectal wall was -1% (-18%-20%). The V29 Gy of the rectal wall increased by >15% was observed in one scan. A slight increase in the high dose of bladder wall was noted due to gradual bladder growth during the workflow. With median follow-up time of 7.3 (4.6-12.2) months, all patients were followed-up for more than 3 months. No patient was observed with acute CTCAE grade 2 or more severe GU or GI toxicities (0%).

CONCLUSION

UHF-RT to prostate and pelvic with ATS workflow is well tolerated by patients with HR and VHR prostate cancer, with only mild GU and GI toxicities. The 3D-MR-based dosimetry analysis demonstrated clinically acceptable estimated dose coverage of target volumes during the beam-on period.

More Efficient Auto-Segmentation Framework Using Patient-Specific Information for CBCT-Guided Adaptive Radiotherapy

PURPOSE/OBJECTIVE(S)

Accurate and fast delineation of regions of interest (ROIs) is critical for online adaptive radiotherapy (ART). Due to the noise, artifacts and low contrast of soft tissue on cone-beam computed tomography (CBCT), the CBCT-guided ART (CBCTgART) needs an effective tool to assist the segmentation of ROIs. This study aims to develop an efficient auto-segmentation workflow with personalized modeling for CBCTgART based on deep learning (DL) model.

MATERIALS/METHODS

Five hundred fifty-two patients with nasopharyngeal carcinoma were enrolled in this study. At the beginning, a cycle consistent adversarial network (CycleGAN) model was trained on 172 patients' CBCT/CT paired images to improve the image quality of CBCT to CT level. A generalized segmentation model was trained using the planning CT (pCT) and contour data from 530 patients. For personalized modeling, the generalized segmentation model was fine-tuned on the specific patient's pCT and contour to get the personalized model. When CBCT images were available, the trained CycleGAN model transformed the CBCT to synthetic pCT. Then the personalized auto-segmentation model generated the contour of ROIs on the synthetic pCT. We randomly selected 22 patients for model test. The proposed method (DL-personalized) was compared with other DL methods based on the same architecture of network: regular deep learning method (DL-regular), which was trained on the CBCT and corresponding contours, and generalized model in our framework (DL-generalized). So, 22 personalized, 1 generalized and 1 regular DL models were tested. The paired t-test was performed to test the significance for mean dice similarity coefficient (DSC), mean distance to agreement (MDA), and Hausdorff distance (HD) between the alternative and proposed methods.

RESULTS

Two ROIs were included: the clinical target volume (CTV) and nasopharynx gross tumor volume (GTVnx). The proposed DL-personalized model achieved better results compared with others as shown in the table. The accuracy and robustness of our proposed framework was reliable. All of p values were under 0.01, which indicated the statistically significant difference.

CONCLUSION

The proposed framework utilizing patient-specific information can improve the segmentation accuracy of ART. This method has potential to be integrated into the ART workflow to improve efficiency.

A Feasibility Study of Dose Band Prediction in Radiotherapy: Predicting a Dose Spectrum

PURPOSE/OBJECTIVE(S)

Current deep learning-based dose prediction methods can only predict a specific dose distribution. If the predicted dose is inaccurate, no more options can be selected. We proposed a novel dose prediction method named dose band prediction, which outcomes a spectrum of predicted dose distribution for planning and quality assurance (QA).

MATERIALS/METHODS

Upper-Band and Lower-Band losses were involved in 3D convolution neural networks to establish the Upper-Band Network (UBN) and Lower-Band Network (LBN). Each voxel's ideal dose spectrum (dose band) was defined by the maximum/minimum rational dose predicted by UBN/LBN. 130 NPC cases with Tomotherapy (dataset 1), 49 cervix cases with IMRT (dataset 2) and 43 cervix cases with VMAT (dataset 3) were enrolled to establish and evaluate our dose band prediction method.

RESULTS

The dose band prediction method can successfully predict a spectrum of doses. Upper-Band/Lower-Band presents maximum/minimum rational dose; Middle-Line presents the average of Upper-Band and Lower-Band. The clinical implement dose was used as the reference dose. We evaluated the maximum interval between the reference and Upper-Band/Middle-Line/Lower-Band doses, and the percentage dose difference was used as the evaluation method. The differences in PTV for Upper-Band, Middle-Line and Lower-Band in dataset 1 were within 2.47%, 0.54%, and 2.8%; in dataset 2, they were within 0.37%, 1.15%, and 2.69%; in dataset 3, they were within 0.96%, 0.35%, and 1.66%. The mean difference of OARs for the Upper-Band, Middle-Line and Lower-Band in dataset 1 were within 8.13%, 4.97%, and 8.19%; in dataset 2, they were within 8.8%, 4.48%, and 5.52%; in dataset 3, they were within 4.01%, 3.13%, and 5.79% (shown in Table 1).

CONCLUSION

Dose Band prediction achieved high-accuracy dose prediction by the Middle-Line. More importantly, the Upper-Band/Lower-Band provided a spectrum of possible rational doses. Our Dose Band prediction method is based on a specific loss function, so it can easily be applied in various network and patient cases. Dose Band prediction towards a more robust plan QA and planning assistance. Table 1. The maximum interval of doses (percentage dose difference, %).

Transcriptomic Heterogeneity of Metastatic Disease Timing within Metastatic Castration-Sensitive Prostate Cancer

PURPOSE/OBJECTIVE(S)

Metastatic castration-sensitive prostate cancer (mCSPC) is commonly partitioned into high- and low-volume subgroups which have demonstrated differential biology, prognosis, and response to therapy. Timing of metastasis has similarly demonstrated differences in clinical outcomes, however less is known about any potential underlying biologic differences between these disease states. Herein we aim to compare transcriptomic differences between synchronous and metachronous mCSPC and identify any differential responses to therapy.

MATERIALS/METHODS

We performed an international multi-institutional retrospective review of men with mCSPC who completed RNA expression profiling evaluation of their primary tumor. Patients were stratified according to disease timing (synchronous vs metachronous). The primary endpoint was to identify differences in transcriptomic profiles between disease time. Median genomic scores between groups were compared with Mann-Whitney U test. Secondary analyses included determining clinical and transcriptomic variables associated with overall survival (OS) from time of metastasis. Survival analysis was performed with the Kaplan-Meier Method and Multivariable Cox regression.

RESULTS

A total of 252 patients were included with a median follow-up of 39.6 months. Patients with synchronous disease experienced worse 5-yr OS (39% vs 79%, p<0.01) and demonstrated lower median Androgen Receptor Activity (AR-A) (11.78 vs 12.64, p<0.01) and Hallmark Androgen Response (HAR) (3.15 vs 3.32; p<0.01). Multivariable cox-regression identified only high-volume disease (HR = 4.97, 95% CI 2.71-9.10; p<0.01) and HAR score (HR = 0.51, 95% CI 0.28-0.88; p = 0.02 significantly associated with OS. Finally, patients with synchronous (HR = 0.47, 95% CI 0.30-0.72; <0.01) but not metachronous (HR = 1.37, 95% CI 0.50-3.92; p = 0.56) disease were found to have better OS with Androgen Receptor (AR) + non-AR combination therapy as compared to monotherapy (p value for interaction = 0.05).

CONCLUSION

We have demonstrated a potential biologic difference between metastatic timing of mCSPC. Specifically, for patients with low volume disease, those with metachronous low volume disease have a more hormone dependent transcriptional profile and exhibit a better prognosis than synchronous low volume disease.

Evaluation of Antitumor Immunity by a Combination Treatment of Radiation, Anti-PD1, and Anti-Angiogenic Therapy in Esophageal Squamous Cell Carcinoma

PURPOSE/OBJECTIVE(S)

Radiotherapy is one of the main therapeutic methods for esophageal cancer. Immunotherapy can improve the anti-tumor immunity of radiotherapy, but the special immune microenvironment of esophageal cancer limits the effect. Therefore, we explored a combination therapy approach based on tumor microenvironment.

MATERIALS/METHODS

As a proof of concept, we constructed a 4NQO-induced esophageal carcinoma mouse model and a human PBMC- tumor cell co-culture system. Tumor suppressive activity and immunophenotyping of radiotherapy alone or in combination with Program Death-1 (PD-1), anti-angiogenesis therapy were evaluated in vivo and in vitro.

RESULTS

Radiotherapy combined with immunotherapy and antiangiogenic therapy increased the expression of CD4+ T, B lymphocytes, and NKT cells in the peripheral blood and spleen of mice while decreasing the expression of Treg cells. Antiangiogenic therapy significantly reduced RT-induced Treg cell expression, suggesting a weak reversal of the immunosuppressive environment. RT combined with anti-PD-1 or anti-angiogenesis therapy can inhibit tumor growth. A similar but more significant effect was observed when anti-VEGF was added to RT combined with anti-PD-1 therapy, which was observed to improve the survival of mice with esophageal cancer. In the co-culture system, it was observed that combination therapy can reduce the expression of TGF-β1, TGF-β2, IL-6, and other genes in tumor cells. This implies that antitumor immunity is additive rather than synergistic. These results provide evidence for the operation of immunosuppressive tumor environments and provide insights for the design of new combination therapies.

CONCLUSION

Radiotherapy combined with PD-1 monoclonal antibody and anti-angiogenesis therapy can not only significantly improve the efficacy of single radiotherapy or targeted therapy for esophageal cancer cells but also improve the immune microenvironment in the state of tumor suppression in esophageal cancer.

A Multicenter Study on Deep Learning for Glioblastoma Auto-Segmentation with Prior Knowledge in Multimodal Imaging

PURPOSE/OBJECTIVE(S)

A precise radiotherapy plan is required to ensure accurate delineation of gross tumor volumes (GTV) and clinical target volumes (CTV1 and CTV2) of glioblastomas (GBMs). However, traditional manual delineation is labor intensive and highly dependent on oncologists' experience. To construct and evaluate a deep learning-based automatic delineation method using prior knowledge in multimodal medical imaging to automate precise GTV, CTV1 and CTV2 contouring in GBM patients.

MATERIALS/METHODS

We retrospectively collected the CT and MRI scans of 55 eligible patients with histologically proven high-grade glioma (HGG) from an institute, these scans were performed with non-enhanced CT (CT), contrast-enhanced T1-weighted (T1C) and T2-FLAIR (T2F) sequences. We proposed a two-stage automatic segmentation framework (PKMI-Net) for GTV, CTV1 and CTV2 based on deep learning using prior knowledge in multimodal medical imaging, and its segmentation performance was evaluated with dice similarity coefficient (DSC), 95% Harsdorff distance (HD95), average surface distance (ASD) and relative volume difference (RVD). To further investigate the generalizability of our method, we designed and conducted two evaluation strategies (Mix and Cross) on four multicenter datasets (including 55 patients, 37 patients, 21 patients and 35 patients).

RESULTS

The evaluation results with an 11-patient test set from the single institute were summarized in Table 1, the proposed method demonstrated the best accuracy in segmenting, respectively, GTV, CTV1 and CTV, achieving a DSC of 0.94, 0.95 and 0.92; HD95 of 2.07 mm, 1.18 mm and 3.80 mm; ASD of 0.69 mm, 0.39 mm and 1.13 mm and RVE of 5.50%, 3.97% and 9.68%. In the multicenter evaluation, the segmentation performance of our method implemented with the Cross strategy was comparable to that with the Mix strategy, demonstrating that our method had high and stable generalizability across multicenter datasets in automatically segmenting GTV, CTV1 and CTV2.

CONCLUSION

Our proposed method achieved promising results in automatically segmenting gliomas across various datasets, which could improve the quality and efficiency of glioblastoma radiotherapy.

Mitigation of Dosimetric Uncertainty in MRI-Based Proton Planning Using Spot-Scanning Proton Arc (SPArc) Technique

PURPOSE/OBJECTIVE(S)

MRI-based synthetic CT (SCT) images created using generative adversarial network (GAN) have been demonstrated to be feasible for intensity-modulated proton therapy (IMPT) planning. However, dose calculation accuracy can be uncertain in some regions within/near the target of head and neck patients due to the local CT number estimation error or sharp dose fall-off. This study investigated the feasibility of using the SPArc technique to mitigate such dosimetric uncertainty.

MATERIALS/METHODS

A GAN using a 3D U-net as the generator and a 6-layer 3D convolutional neural network as the discriminator was trained with T1-weighted MR-CT image pairs from 162 nasopharyngeal carcinoma patients (14 for validation). The generator was used to generate SCT images from MR images for 7 test patients. For each test patient, the CT image was used to create a SPArc plan and an IMPT plan with the same clinical objectives. The SPArc plans (control point frequency sampling, arc trajectory, etc.) were optimized using a previously developed iterative approach. The dose distributions of both SPArc plans and IMPT plans were re-calculated on the SCT images and compared to the one calculated on the CT images. The dosimetric uncertainty was quantified using the gamma index.

RESULTS

The 2%/2mm and 3%/3mm passing rates for SPArc plans were (96.9¡À2.7) % and (98.6¡À1.5) %, while the passing rates for IMPT plans were (94.0¡À3.9) % and (96.4+2.9) %. A significant reduction in dosimetric uncertainty was identified for SPArc plans (p ¡Ü0.021). Table 1 shows the passing rates for the 7 test individuals.

CONCLUSION

SPArc can mitigate the uncertainty of dose calculation in MRI-based proton planning. Further research needs to validate these findings on a larger patient cohort. The study paves the road map for using MRI for SPArc planning.

Association of Radiation Facility Volume with Overall Survival in Patients with Very High-Risk Prostate Cancer Treated with Radiation and Androgen Deprivation Therapy

PURPOSE/OBJECTIVE(S)

Studies suggest an association of treatment at high volume facilities with improved survival in cancer patients receiving surgery or radiation therapy. This association has not been studied in patients with very high-risk prostate cancer, who are treated using a multimodality approach that often requires specialized care with advanced diagnostic imaging, complex radiotherapeutic planning, and multidrug antiandrogen regimens. We used the National Cancer Database (NCDB) to study the association of radiation treatment facility volume (FV) with overall survival (OS).

MATERIALS/METHODS

We selected for patients with very high risk, localized prostate cancer by NCCN criteria (cT3b-T4, primary Gleason pattern 5, >4 cores with grade group 4-5, and/or 2-3 high risk features). We included patients who received hormone therapy with either external beam radiation to a dose of ≥60 Gy or external beam radiation to a dose of ≥45 Gy combined with brachytherapy. Association of FV with OS was evaluated through a bias-adjusted log-rank test to identify the optimal cut point of FV for dichotomization. Kaplan-Meier curves were used to study the association of binary FV with overall survival (OS) with and without IPTW (inverse probability treatment weighting) balancing the following confounders: age, race, median income, education, insurance, academic treatment facility, Charlson comorbidity score, T stage, PSA, Gleason score, total radiation dose, year of diagnosis, and patient distance from treatment facility. Cox proportional hazards model was built using backward variable selection strategy (α of 0.05 for removal).

RESULTS

We identified 25,219 very high-risk prostate cancer patients by NCCN criteria (median follow up 57.36 months; 95% CI 56.67 - 58.09) diagnosed between 2004 and 2015. High FV (n = 6,438) was associated with better OS on univariable analysis (hazard ratio [HR] = 0.81; 95% confidence interval [CI] 0.77 - 0.86; p < 0.001) and multivariable analysis (HR = 0.89; 95% CI 0.84 - 0.95; p < 0.001). Other factors associated with improved OS on multivariable analysis included younger age, non-white/black race, higher income, private insurance, academic/research treatment facility, lower comorbidity, lower T-stage, lower PSA, and lower Gleason score. After IPTW adjustment, high FV remained associated with better OS (HR = 0.90; 95% CI 0.85 - 0.95; p < 0.001).

CONCLUSION

Patients with NCCN very high-risk prostate cancer treated at a radiation facility with high case volume had better OS than patients treated at a facility with low volume, after adjustment for confounders. This may suggest that for very high-risk patients, outcomes may be improved by the expertise and optimal multidisciplinary care that typically accompany high facility treatment volume.

Real world experience of therapeutic monitoring of medically treated prosthetic valve infective endocarditis by 18F-FDG-PET/CT

INTRODUCTION

18F-FDG-PET/CT is recommended to improve the diagnosis of prosthetic valve infective endocarditis (PVIE) and is a major criterion in the ESC-2015 classification. However, there is little evidence for its usefulness in the follow-up of medically treated PVIE patients.

METHODS

A monocentric retrospective analysis of patients hospitalized for PVIE between January 2013 and December 2019 who were not treated with surgery and who had at least two 18F-FDG-PET/CT examinations during their medical management.

RESULTS

Among 170 patients with PVIE, 117 were treated with antibiotic therapy but no surgery. Of these, 36 (31%) had at least two 18F-FDG-PET/CT examinations. At initial imaging, 28 patients had heterogeneous FDG uptake on their prosthetic valve and eight on their associated aortic graft. Hypermetabolism of spleen and bone marrow (HSBM) was observed in 18 and 19 patients, respectively. At the first follow-up 18F-FDG-PET/CT, 21 (58%) patients still had heterogeneous uptake, indicating persistent active endocarditis. HSBM was still present at the last follow-up imaging in four of the six patients with recurrent PVIE.

CONCLUSION

18F-FDG-PET/CT monitoring of medically treated patients with PVIE provides valuable additional information and prospective multicentric study should be conducted to assess its usefulness.

Clinical efficacy of modified percutaneous kyphoplasty (PKP) vs. conventional PKP for osteoporotic vertebral compression fractures: a single-center retrospective study

OBJECTIVE

To investigate the clinical efficacy of using a standardized modified percutaneous kyphoplasty (transverse process‑pedicle approach to percutaneous kyphoplasty, TPKP) approach for the treatment of osteoporotic vertebral compression fractures (OVCFs) and to explore the possibility that it may become the preferred option in the future.

PATIENTS AND METHODS

A retrospective analysis was conducted on a total of 81 patients (TPKP group, 43 cases; PKP group, 38 cases) with OVCFs who underwent TPKP and PKP at the Department of Spine Surgery, Wuhan Fourth Hospital, from May 2021 to October 2021. We evaluated the patients' demographic information, intraoperative data (volume of cement injection and, duration of surgery), clinical outcomes at different time points (Visual Analog Scale, Oswestry Dysfunction Index), and radiographic data (Cobb angle, anterior vertebral body height). Statistical analysis was performed to assess the efficacy of the procedure, both within and between the two groups before and after surgery.

RESULTS

The difference in preoperative general information between the two groups of patients was non-statistically significant (p>0.05), and they were comparable. Additionally, no statistically significant difference (p>0.05) was found between the TPKP and PKP groups in terms of operative time, length of hospital stay, recovery of injured spine height, Cobb angle, and cement leakage rate. However, significant statistical differences (p<0.05) were noted between the two groups regarding cement volume, distribution pattern, 1-day postoperative VAS scores, 1-day postoperative ODI scores, and loss of height of the injured spine. TPKP demonstrated superior performance compared to PKP in these specific areas.

CONCLUSIONS

TPKP offers the same surgical safety as the conventional approach, with better cement distribution and better pain relief, as well as the advantage of maintaining the height of the operated vertebral body. The technique is easy to master and use when guided by standard puncture procedures.

Pre-Brachytherapy Diffusion-Weighted Magnetic Resonance Imaging (DW-MRI) Response as Predictor of Local Control in the Definitive Treatment of Cervical Cancer

PURPOSE/OBJECTIVE(S)

Chemoradiation consisting of external beam radiotherapy (EBRT) followed by brachytherapy (BT) is the standard of care for Stage IB2-IVA cervical cancer (CC). Multi-parametric MRI (mpMRI) is a valuable tool for initial staging, treatment planning and response assessment. In this study, we aim to explore the potential of mpMRI, in particular DW-MRI, to predict overall tumor control following chemoradiation in CC.

MATERIALS/METHODS

We identified 78 consecutive patients treated with chemoradiation for FIGO IB2-IVA CC between 2012-2020, who had an MRI at baseline (MRb) and post-EBRT prior to brachytherapy boost (MRpb) that included DW-MRI (b-value = 0 and 800 s/mm2). Median age was 53 years, most patients had squamous cell carcinoma (76.9%) and advanced-stage disease (56.4% stage IIIA-IVA). Median time from completion of EBRT to MRpb was 3 days. Regions of interest (ROI) in primary tumor were delineated on DW image (b = 0 s/mm2) using ITK-SNAP software. DW-MRI data were fitted to a monoexponential model to calculate apparent diffusion coefficient (ADC) values using in-house software platform (MRI-QAMPER). MRpb mean ADC values (n = 78) and relative changes (%) in mean ADC values between MRb and MRpb (n = 64) were correlated with outcomes, including local failure (LF), regional or distant failure (RDF), and failure at any site (FAS), with death without failure as a competing risk. Median follow-up time was 45 months (95% CI 38, 53).

RESULTS

At first post treatment assessment, 72 patients (92.3%) had a complete response (CR) in the cervix and 68 patients (87.2%) had CR in all disease sites. Of patients who had CR in the cervix (n = 72), only 1 patient had local recurrence. Of patients who had CR in all disease sites, 10 later recurred (1 LF only, 1 LF&RDF, 8 RDF only). Overall, 7 patients (9%) had LF, and 19 patients (24.4%) had FAS. A higher mean ADC value in MRpb was associated with LF (HR 4.3, 95% CI 1.32, 14.6; P = 0.016), but not with RDF (P = 0.4) or FAS (P = 0.5). A higher relative change in the mean ADC value between MRb and MRpb was associated with a lower risk of LF (HR 0.94, 95% CI 0.90, 0.98; P = 0.002), but not with RDF (P = 0.8) or FAS (P = 0.4).

CONCLUSION

Treatment response as measured on prebrachytherapy DW-MRI is a significant predictor of local control in patients undergoing chemoradiation for stage IB2-IVA CC. ADC values, a quantitative imaging biomarker on MRpb may be instrumental in dose intensification/de-escalation efforts in CC.

Factors Associated with Grade 3-4 Late Toxicity after Hypofractionated Prostate Salvage Radiation

PURPOSE/OBJECTIVE(S)

We previously reported disease outcomes on patients treated with moderately hypofractionated salvage RT (65-70 Gy in 26-28 fractions using imaging guided IMRT) with >13 years of follow-up. The rate of all late surgical/radiation/disease related grade 3-5 toxicities was 27%, which were documented at a median of 8.7 years after the end of radiation. Here we performed an analysis to attempt to identify factors associated with these toxicities.

MATERIALS/METHODS

A total of 161 patients were analyzed; 44 patients experienced 58 late grade ≥3 toxicities. These were analyzed in several groups which included: all (n = 44), GU (n = 40), GU excluding incontinence (n = 35), stricture/fistula related (n = 28), hematuria related (n = 7), and grade 4 stricture/fistula related (n = 8). We investigated patient factors (age, preRT IPSS), surgical factors (clip volume, approach, margin status), and disease factors (stage, Gleason group, PSA nadir, preRT PSA, surgery to RT time). Surgical clip volume was contoured on CT and recorded in cc. Significance was determined using Mann-Whitney U test for continuous variables and Fisher's Exact test for binary variables.

RESULTS

A higher volume of surgical clips in the prostate fossa was found to be significantly related to eventual grade ≥3 stricture/fistula related event (p = 0.05). The mean surgical clip volume was found to be 2.30 cc in those with a documented grade ≥3 stricture/fistula compared to 1.23 cc in those without. Patients with a positive margin had a 30.0% rate of grade ≥3 GU toxicity compared to 16.2% in those with a negative margin (p = 0.03). Surgical clip volume was not found to be significantly related to pathologic stage, nor to eventual biochemical failure (p = 0.799/0.897). A positive margin was associated with a lower rate of biochemical failure after salvage (p = 0.04). Grade 3 events were documented at a median of 7.7 years and grade 4 events at 12.0 years after the end of radiation.

CONCLUSION

Our previous study found a high rate of grade ≥3 toxicities at time points for which there is a paucity of data both in conventional and hypofractionated regimens, particularly in the era of modern surgical and radiation techniques. We also found late toxicities can occur with increasing severity for many years after salvage radiotherapy. This analysis suggests that margin positivity and volume of surgical clips might identify patients at higher risk for late grade ≥3 toxicities, although the etiologies of these toxicities, whether surgery or radiation-related, are uncertain.

Association of Overall Survival Benefit Profile of Radiotherapy with Progression-Free Survival after Chemotherapy for Diffuse Large B-Cell Lymphoma

PURPOSE/OBJECTIVE(S)

Benefit of radiotherapy (RT) after chemotherapy (CT) of diffuse large B-cell lymphoma (DLBCL) remains controversial. It is unknown whether improved progression-free survival (PFS) by RT translate into an overall survival (OS) benefit. To address this question, our research comprehensively evaluated the risk-benefit assessment of RT in DLBCL through an in-depth examination of previously reported data from randomized controlled trials (RCTs) and retrospective comparative studies.

MATERIALS/METHODS

After screening and quality control, this study included 7 randomized controlled trials and 52 retrospective studies of combined-modality therapy (CMT) versus CT alone. The correlation between PFS and OS was evaluated using the Pearson linear correlation coefficient at trial- and study arm-level. A risk-benefit assessment to describe the OS benefit of RT was performed in meta-analyses of pooled HROS with PFS patterns.

RESULTS

In RCTs, strong correlations were found between HRPFS and HROS at trial-level (r = 0.876), and PFS and OS at treatment arm-level, regardless of treatments (r = 0.945-0.964 for all, CMT or CT). In retrospective studies, similar correlations between HRPFS and HROS (r = 0.639-0.650), and PFS and OS rates (r = 0.882-0.910) were observed, independent of treatments or rituximab. Adding RT into rituximab-based CT increased the average PFS rate from 63.6 ± 18.9% to 81.5 ± 10.6% (P<0.001), with differential OS benefits of RT between studies. Patients can be stratified into four PFS patterns (>80%, >60-80%, >40-60%, and ≤40%); absolute gain in OS from RT ranged from ≤5% at PFS >80% to ∼21% at PFS ≤40%, with pooled-HROS from 0.70 (95% CI, 0.51-0.97) to 0.48 (95% CI, 0.36-0.63) after rituximab-based CT. Linear analysis revealed an OS advantage of CMT over CT alone in a PFS-dependent manner.

CONCLUSION

We demonstrate a varied OS benefit profile of RT upon different PFS patterns, and provide valuable evidence for making treatment decisions and designing clinical trials. Future strategies to select the use of RT will need careful tailoring in clinical practice or within RCT to optimize outcome.

Analysis of the efficacy of azelastine nasal spray combined with mussel mucin in the treatment of allergic rhinitis and the influence of peripheral blood CCL26 and CCR3 levels

OBJECTIVE

A retrospective study was conducted to investigate the efficacy of azelastine nasal spray combined with mussel mucin in the treatment of allergic rhinitis (AR) and the effects of CCL26 and CC chemokine receptor-3 (CCR3).

PATIENTS AND METHODS

A total of 80 patients with AR admitted to our hospital from March 2020 to March 2022 were included as the research objects. All subjects were divided into two groups according to the different therapeutic strategies by reviewing the patient's treatment. The control group (n = 40) was given azelastine nasal spray, while the study group (n = 40) was treated with a combination of mussel mucin and azelastine nasal spray. The clinical efficacy, clinical symptoms, and sleep quality improvement of the two groups were calculated and compared retrospectively. The serological indexes were compared, and the incidence of adverse reactions between the two groups was calculated retrospectively based on the patient's medical records.

RESULTS

In the study and control groups, the effective rate was 95.00% and 72.50%. After treatment, the symptom scores of nasal congestions, nasal itching, sneezing, and runny nose and the total score of Pittsburgh sleep quality index (PSQI) in the study group were remarkably less. After treatment, the serum levels of sVCAM-1, interleukin-4 (IL-4), and immunoglobulin E (IgE) were decreased, and the levels of IL-12 were upregulated. Following treatment, Minimum nasal cross-section (NMCA) and total nasal resistance (TNR) at 75Pa in the study group were reduced more noticeably (p < 0.05). After treatment, the expression levels of CCL26 and CCR3 in peripheral blood were significantly decreased. In the control and study groups, the incidence of adverse reactions was 7.50% and 10.00%.

CONCLUSIONS

Azelastine nasal spray combined with mussel mucin is effective in the treatment of allergic rhinitis, which can effectively improve patients' clinical symptoms, alleviate nasal ventilation disorders, reduce inflammatory reactions, and improve sleep quality. This strategy of combined treatment is safe and, therefore, worth advocating.

Lymphocyte Count Kinetics and the Effect of Different Radiotherapy Techniques on Radiation-Induced Lymphopenia in Patients with Breast Cancer Receiving Hypofractionated Postmastectomy Radiotherapy

PURPOSE/OBJECTIVE(S)

Radiation-induced lymphopenia (RIL) is associated with poor prognosis in solid tumors. This study aimed to describe the lymphocyte kinetics in patients with breast cancer receiving hypofractionated postmastectomy radiotherapy (RT) and to investigate the association of different RT techniques with RIL.

MATERIALS/METHODS

We assessed 607 patients who received hypofractionated postmastectomy RT for breast cancer in our prospective clinical database from 8 hospitals. All patients received irradiation to the chest wall and supraclavicular fossa. RT techniques included integrated RT with the photon-based intensity modulated techniques to irradiate all target volumes (integrated RT) and a hybrid approach combining photon irradiation to supraclavicular nodes and electron irradiation to the chest wall (hybrid RT). Peripheral lymphocyte counts (PLC) were tested prior to RT (baseline), weekly during RT, at 1, 2 weeks, 3, 6 months after RT, and then every 6 months. Grade 3+ RIL was defined as PLC nadir during RT of <0.5 ×103/ml. Mean PLC was compared by the t test. Univariate, multivariate, and propensity score matching (PSM) analyses were used to evaluate the effect of different RT techniques on grade 3+ RIL.

RESULTS

During RT, 121 (19.9%) of patients had grade 3+ RIL. The PLC started to recover at 1 week and reached baseline levels 1 year after RT. A greater proportion of the patients treated with the integrated RT (90/269, 33.5%) developed grade 3+ PLC compared with those receiving hybrid RT (31/338, 9.2%, P < 0.001). After conducting PSM, multivariate analyses showed lower baseline PLC (HR = 0.15, P<0.001) and RT technique (the integrated RT vs. hybrid RT, HR = 4.76, P<0.001) were independent risk factors for grade 3+ RIL. The PLC in patients receiving the integrated RT after RT were higher than that in those receiving hybrid RT (p<0.05).

CONCLUSION

RT technique affect the risk of and recovery from RIL, which may impact survival. Choosing appropriate RT technique to minimize RIL might be considered to benefit their outcomes.

Utilization of Radical Prostatectomy vs. Radiation Therapy for Gleason Grade Group 5 Prostate Cancer before and after USPSTF Grade D Recommendation against Prostate-Specific Antigen Screening in 2012

PURPOSE/OBJECTIVE(S)

The 2012 United States Preventive Services Task Force (USPSTF) Grade D recommendation against prostate-specific antigen (PSA) screening has resulted in a shift to higher-stage prostate cancer (PC) at diagnosis. While incidence of low-risk prostate cancer has declined, more men are diagnosed with high-risk disease, and multimodal treatment is often required. The impact of this epidemiologic shift on practice patterns, specifically radical prostatectomy (RP) versus definitive radiation therapy (RT), for men with localized PC at high risk of recurrence is unknown. Herein, we evaluate the utilization of RP versus RT in the United States for Gleason grade group 5 (GG5) prostate cancer before and after 2012.

MATERIALS/METHODS

We identified 34,011 men with localized GG5 PC treated with (1) RP or (2) RT plus androgen deprivation therapy (ADT) between 2004 and 2017 in the National Cancer Database. We excluded those who were clinically node-positive, had metastatic disease, or received chemotherapy or palliative-intent treatment. Chi-square was used to compare the relative use of RP and RT before versus after January 1, 2012, corresponding to the year of USPSTF recommendation against PSA screening. Annual use of RP versus RT from 2004 to 2017 was compared in academic and non-academic centers using Cochran-Armitage test for trend. Joinpoint regression assessed if 2012 was significant for inflection of crude rates of RP. Finally, we modeled the effect of treatment year (i.e., 2012-2017 versus 2004-2011) on use of RP using multivariable logistic regression. Sensitivity analysis tested an interaction term for facility type (i.e., academic versus community). Tests were two-sided with a 0.05 level of significance.

RESULTS

Of the eligible men, 10,745 (31.6%) had T3-T4 disease. Between 2004 and 2011, 36.5% (n = 5,483) underwent RP; between 2012 and 2017, 42.3% (n = 8,034) underwent RP (p = .02). Across all centers, use of RP increased from 31% to 41% (p for trend <.001). In academic centers, use of RP increased from 32% to 44% (p for trend <.001); in community centers, use of RP increased from 30% to 39% (p for trend <.001). 2012 was associated with significant inflection for increase in RP use in all centers. On multivariable analysis, there was an increased odds of receiving RP after 2012 (adjusted OR 1.34, 95% CI 1.28-1.40, p<.001). No differential effect by facility type was observed (p = .15).

CONCLUSION

Utilization of RP for GG5 PC has significantly increased in the United States over the past decade, particularly after the USPSTF Grade D recommendation against PSA screening in 2012. It remains unknown whether oncologic or functional outcomes may be compromised in this group of high-risk men, many of whom require post-prostatectomy RT and/or ADT. While historically rare, prospective comparison of RP versus RT+ADT for GG5 PC may be helpful given the evolving epidemiology of localized PC.

Combining Dosimetric and Radiomics Features for the Prediction of Radiation Pneumonitis in Locally Advanced Non-Small Cell Lung Cancer by Machine Learning

PURPOSE/OBJECTIVE(S)

This study aimed to analyze the dosimetric factors and radiomics features of tumor and lungs in locally advanced non-small cell lung cancer (LANSCLC) to establish machine learning models and improve the prediction of grade (G) 2 radiation pneumonitis (RP).

MATERIALS/METHODS

This study retrospectively collected data of 284 LANSCLC patients underwent concurrent chemoradiotherapy (CCRT) to a median dose of 64 Gy in 20-33 fractions between 2013 and 2021. Of this cohort, 21.1% of patients had ≥ G2 RP. There were 4 regions of interest (ROIs) had been identified in planning computed tomography images: gross tumor volume (GTV), ipsilesional lung (IL), contralesional lung (CL), and total lung (TL). We calculated the dose-volume histogram (DVH) from the lowest dose to the maximum dose increasing by degrees with 1 Gy, and extracted a total of 172 radiomics features from all the 4 ROIs. We selected the best predictors for classifying 2 groups of patients using a sequential backward elimination support vector machine model.

RESULTS

The best predictors for ≥ G2 RP were the combination of 8 radiomics features and 7 dosimetric factors in training group, and the validation group achieved an area under the curve (AUC) of 0.847 (accuracy, 80.38%; sensitivity, 78.95%; specificity, 81.82%). The eight radiomic features included 2 from GTV while 1, 2 and 3 from IL, CL and TL, respectively. For dosimetric factors, V65 of GTV, V20, V50 and V55 of IL, V10 of CL, V20 and V55 of TL appeared to be significantly related to symptomatic RP. These dosimetric factors should be constrained to less than 99.2%, 50.0%, 17.5%, 13.0%, 39.5%, 32.0%, and 6.6%, respectively.

CONCLUSION

Combining dosimetric factors and radiomics features within GTV, IL, CL and TL can improve the prediction of symptomatic RP in LANSCLC patients treated with CCRT. The results suggested the importance of V65 of GTV, V20, V50 and V55 of IL, V10 of CL, V20 and V55 of TL as predictors of symptomatic RP and provide useful information for optimization of treatment planning in the era of combination of radiotherapy and immunotherapy.

Deep Learning-Based Synthesis of Contrast-Enhanced MRI for Automated Delineation of Primary Gross Tumor Volume in Radiotherapy of Nasopharyngeal Carcinoma

PURPOSE/OBJECTIVE(S)

Contrast-enhanced MRIs are necessary to delineate the primary gross tumor volume (GTVp) in radiotherapy of nasopharyngeal carcinoma (NPC). However, using contrast agents to scan contrast-enhanced MRIs is not applicable to some patients due to metal implants or their allergy, and it increases the treatment cost of patients. To address these problems, this work aims at synthesizing contrast-enhance MRIs from unenhanced MRIs by implementing generative adversarial network (GAN).

MATERIALS/METHODS

In this work, 324 MRI datasets of patients with NPC were retrospectively collected between September 2016 and September 2017 from a single institute. MRI examinations were performed with un-enhanced T1-weighted (T1) and T2-weighted (T2) sequences, and contrast-enhanced T1-weighted (T1C) and fat-suppressed T1-weighted (T1FSC) sequences. We designed and developed a modified pix2pix network to synthesize T1C (sT1C) and T1FSC (sT1FSC) from real T1. The end of the generator in this network was assembled with multiple heads (the classification head and gradient head) to learn more representation information and features from real images, the discriminator in this network distinguished whether the synthesized image is real and fake and supervised that the generator outputs more realistic synthesized image. We verified the performance of the synthesized images for automated delineation of GTVp. In an independent testing set of 11 patients, the synthesized sT1C and sT1FSC were inputted into the segmentation deep learning network along with their corresponding T1 and T2 sequences to generate GTVp contours. Delineation performance of the synthesized images and real images for automated delineation were evaluated by dice similarity coefficient (DSC), and average surface distance (ASD), using human expert contours as the ground truth.

RESULTS

In automated contouring of GTVp for NPC, the segmentation deep learning network using one or two synthesized MRIs showed equivalent performance when compared with the automated contours which generated from four real MRI sequences. Mean DSCs between automated contours by sT1C-replaced or sT1C and sT1FSC-replaced network and ground truth contours were 0.726 ± 0.143 and 0.711 ± 0.157, respectively, slightly inferior to that of contours generated from four real MRI sequences (0.740 ± 0.154, both P >0.05). In terms of mean ASD, there was also no significant difference between automated contours generated from synthesized images and real images (3.056 ± 4.216 mm and 3.537 ± 4.793 mm vs. 3.124 ± 4.637 mm; both P > 0.05).

CONCLUSION

We proposed an MRI-synthesis method based on GAN and the synthesized contrast-enhanced MRIs performed equivalent as the real contrast-enhanced MRIs in the automated delineation of gross tumor volume for radiotherapy of NPC.

Hybrid Immuno-RT for Bulky Tumors: Standard Fractionation with Partial Tumor SBRT

PURPOSE/OBJECTIVE(S)

Bulky tumors remain challenging to be treated. Stereotactic body radiation therapy (SBRT) is effective against radioresistant tumor cells and can induce immunogenic cell death (ICD) that leads to T-cell-mediated antitumor effects. Low-dose radiation (LDRT) can inflame the tumor microenvironment (TME) by recruiting T cells. We designed a novel radiotherapy technique (RT, ERT) whose dose distribution map resembles the "eclipse" by concurrently delivering LDRT to the whole tumor, meanwhile SBRT to only a part of the same tumor. This study examined the safety and efficacy of ERT to bulky lesions with PD-1 inhibitors in mice and patients.

MATERIALS/METHODS

In mice with CT26 colon or LLC1 lung bulky tumors (400 - 500 cm3), the whole tumor was irradiated by LDRT (2 Gy x 3), meanwhile the tumor center was irradiated by SBRT (10 Gy x 3); αPD-1 was given weekly. The dependence of therapeutic effects on CD8+ T cells was determined using depleting antibodies. Frequencies of CD8+ T cells and M1 macrophages (Mφ) were determined by flow cytometry. Multiplex Immunohistochemistry (mIHC) was applied to analyze the number and the location of CD8+ T cells and their subpopulations, as well as the phospho-eIF2α level (the ICD marker) of tumor cells in TME. Patients with advanced lung or liver bulky tumors who failed standard treatment or with oncologic emergencies were treated. Kaplan-Meier method was applied to estimate patients' progression-free survival (PFS) and overall survival (OS).

RESULTS

ERT/αPD-1 is superior to SBRT/αPD-1 or LDRT/αPD-1 in controlling bulky tumors in both mouse models in a CD8+ T-cell dependent manner. In the CT26 model, ERT/αPD-1 resulted in complete tumor regression in 3/11 mice and induced more CD8+ T cells and M1 Mφ in TME compared to other groups. mIHC analysis showed that ERT/αPD-1 induced higher bulk, stem-like (TCF1+ TIM3- PD-1+), and more differentiated (TCF1- TIM3+ PD-1+) CD8+ T cells infiltration into the tumor center and periphery compared to other groups. Compared to untreated or LDRT-treated tumor centers, tumor centers irradiated with ERT or SBRT showed elevated phospho-eIF2α accompanied by higher dendritic cell infiltration. In total, 39 advanced cancer patients were treated with ERT/αPD-1 or plus chemotherapy. Radiation-induced pneumonitis occurred in 1 of 26 patients receiving thoracic ERT. There were two cases of grade III toxicity associated with PD-1 inhibitors. No toxicity above grade III was observed. The objective response rate was 38.5%. The median PFS was 5.6 months and median OS was not reached at a median follow-up of 11.7 months.

CONCLUSION

ERT/αPD-1 showed superior efficacy in controlling bulky tumor in two mouse models. The hybrid immuno-RT (ERT) combing PD-1 inhibitors was safe and effective in patients with bulky tumors. Further clinical trials in combination with bioimaging to identify the optimal SBRT target region for the bulky tumor are warranted.

[Progress in surgical treatment of hepatocellular carcinoma with tumor thrombus in the inferior vena cava]

Hepatocellular carcinoma(HCC) is one of the most common malignancies of the digestive system,which is prone to be associated with microvascular or macrovascular invasion. Among them,HCC with inferior vena cava tumor thrombus(IVCTT) or right atrium tumor thrombus(RATT) is rare and has a poor prognosis. However,surgical treatment of HCC with IVCTT and (or) RATT is rarely reported and summarized. The review described the classification of HCC tumor thrombus with IVCTT and (or) RATT, summarized the progress of surgical approaches and surgical operations,and introduced a case of thrombectomy after pushing from the outer surface of the atrium,rendering the RATT to the inferior vena cava under non-cardiopulmonary bypass. The review also proposed the prospective treatments for HCC with IVCTT or RATT,providing clinical guidance to hepatobiliary surgeons.

Role of Radiation Therapy in Liver-Only Oligometastatic Disease: A SEER Analysis

PURPOSE/OBJECTIVE(S)

Radiation therapy (RT) for oligometastasis has the potential to prolong survival in certain disease sites. There is a paucity of data regarding the benefit of RT for overall survival (OS) or disease-specific survival (DSS) in patients with liver-only oligometastatic disease.

MATERIALS/METHODS

The Surveillance, Epidemiology and End Results Program (SEER) includes comprehensive metastasis data for patients from 2016-2019. The SEER database was queried for patients with liver-only metastatic disease at diagnosis by selecting stage IV cases with liver-only metastasis, without metastatic disease in bone, brain, lung, distant lymph nodes, or other sites. OS and DSS were estimated using Kaplan-Meier with log-rank analysis to compare patients who received RT versus no RT. Cox proportional hazards regression was applied to identify potential confounders. Subgroup analysis was used to explore the benefit of RT in different primary tumor sites including pancreas (N = 8846), followed by colon (N = 6535), lung (N = 3075), rectum (N = 1739), and stomach (N = 1448).

RESULTS

A total of 29,422 patients with liver-only metastatic disease treated from 2016-2019 were included. The median age was 67 years old and 77.0% of the patients were Caucasian. 2448 (8.3%) patients were confirmed to have received RT. Patients who received RT had better OS (median survival, RT vs no RT: 18 vs 6 months, P<0.001) and DSS (18 vs 7 months, P<0.001). On multivariable analyses, RT still significantly improved both OS (HR: 0.705, 95% CI: 0.665-0.747, P<0.001) and DSS (HR: 0.390, 95% CI: 0.378-0.402, P<0.001) after adjusting for potential confounders, including age, tumor size, lymph node status, and chemotherapy. RT was significantly associated with improved OS and DSS (all P<0.001) in all primary tumors sites queried except for stomach primary for which RT did not impact OS (P = 0.122) and DSS (P = 0.229). In patients who received chemotherapy, RT also prolonged OS (P<0.001) and DSS (P<0.001).

CONCLUSION

In the SEER database of patients with liver-only oligometastatic disease, RT improves OS as well as DSS, however the benefit varies for the different primary tumor sites. Prospective studies could help further clarify the survival benefits of RT in liver-only oligometastatic disease.

Prospective Trial of Using Imaging to Predict Pathologic Response and Clinical Outcomes in Locally Advanced Esophageal Cancer

PURPOSE/OBJECTIVE(S)

Trimodality therapy with chemoradiation (CRT) followed by esophagectomy is the standard of care for locally advanced esophageal cancer. An unresolved question is whether pathologic complete response (pCR) can be assessed non-invasively for patients post-CRT. In this study, we assessed whether diffusion-weighted imaging (DWI) with MRI or PET can be used as predictors of pCR and other clinical outcomes after CRT.

MATERIALS/METHODS

Patients were enrolled on a single-arm institutional trial (PA13-0380) assessing the role of imaging in predicting outcomes in potentially resectable esophageal patients undergoing trimodality therapy. All patients received neoadjuvant CRT, and 29 patients had subsequent surgery. DWI MRI and PET scans were obtained at baseline, 2 weeks after the start of CRT (interim) and 4 to 6 weeks after completion of CRT (follow up). Apparent diffusion coefficients (ADCs) were calculated based on DWI images. Circulating tumor DNA was obtained for 27 patients post-radiation using CAPP-Seq. Mann-Whitney tests compared imaging changes associated with pCR. Discrimination of pCR by imaging changes was quantified by received operating characteristics. Youden's index was applied to select optimal thresholds. Kaplan-Meier analysis was performed to assess differences in overall survival (OS) and progression-free survival (PFS) by changes in DWI, PET, and ctDNA parameters.

RESULTS

Our cohort of 60 patients had a median follow up of 42.7 months, age of 65.4 yrs, and ECOG of 1 at completion of CRT. 90% were male, 58% had a history of smoking, and 85% were white. 83% had adenocarcinoma with the rest squamous cell carcinoma. Stages of the patients ranged from IIA to IIIB. All had moderately (47%) or poorly (53%) differentiated disease. All received 41.4-50.4 Gy in 1.8 Gy fractions with the majority receiving 50.4 Gy (95%). 29 patients underwent surgery after CRT of which 8 (27.6%) had pCR. Mean ΔADC from baseline to mid-treatment was most associated with pCR (AUC = 0.98, p<0.001) for patients undergoing surgery. Max ΔADC from baseline to first follow-up was most associated with OS (p = 0.002) and PFS (p<0.001) for the whole cohort. 27 patients had ctDNA analyzed after RT with the presence of ctDNA significantly associated with worse OS (HR = 0.12, p = 0.05) and PFS (HR = 0.10, p = 0.002). Combining ctDNA and max ΔADC generated a model that was more predictive of OS and PFS than either alone. We found that neither the PET parameters of TLG or SUV max at baseline or changes in these parameters from baseline to mid-treatment or first follow-up were as predictive as DWI.

CONCLUSION

We show that changes in DWI is associated with pCR, OS, and PFS in resectable esophageal cancer patients undergoing CRT. DWI was more predictive than PET and a model combining DWI and ctDNA was the most predictive of clinical outcomes. This study shows the significant promise of using DWI in potentially guiding treatment decisions in esophageal cancer patients and will require validation in a larger cohort.

Clinical prior Knowledge-Based One-Shot Learning for Automatic Delineation of Clinical Target Volumes in Adaptation Radiotherapy of Cervical Cancer

PURPOSE/OBJECTIVE(S)

Rapid and accurate delineation of clinical target volumes (CTV) of cervical cancer is the crux to ensure the efficiency and benefits of adaptation radiotherapy (ART). However, contour propagation using deformation image registration (DIR) is difficult to ensure the accuracy of CTV contours due to the significant tumor recession in next fraction, and the tumor progress in each fraction is not considered by conventional automatic delineation methods based on deep learning (DL). Currently, one-shot learning (OSL) is feasible to learn the tumor progress from former fractions to improve the accuracy of automatically delineating CTV.

MATERIALS/METHODS

We retrospectively collected 45 patients with cervical cancer from January 2021 to May 2022 in our department. All patients consist of a pair of planning CT and daily CT in ART. A personalized automatic delineation method based on one-shot learning was developed to delineate CTV in daily CT by learning the clinical prior knowledge from the CTV contours and images of planning CT. The performance of our proposed method was evaluated by dice similarity coefficient (DSC), 95% Harsdorff distance (95HD) and average surface distance (ASD) with human experts, and its automatic delineation performance were compared with DIR and DL in daily CT.

RESULTS

Our automatic delineation method OSL performed the best results in all evaluation metrics (denoted by mean ± standard deviation) as shown in Table 1, it is superior to method DL: 0.92 & 0.90 of DSC, 2.33 mm & 2.68 mm of HD95, 0.68 mm & 0.82 mm of ASD, P < 0.05 for DSC and ASD. Specifically, our method is significantly superior to the automatic delineation results by method DIR: 0.92 & 0.84 of DSC, 2.33 mm & 4.11 mm of HD95, 0.68 mm & 1.52 mm of ASD, P < 0.05 for all. In addition, OSL can significantly overcome the delineation problems in fuzzy boundary and delineation missing and perform better generalization for some unusual images, compared with DIR and DL.

CONCLUSION

We proposed an automatic delineation method based on one-shot learning for CTV of cervical cancer in ART, the results demonstrated that the proposed method could improve the precision and generalization of automatically delineating CTV compared against current popular methods. Therefore, it is potential to improve the quality and efficiency of ART for personalized patients and have a positive impact on tumor control and patient survival.

A Feasible Study for Auto Planning and Auto Re-Planning for Nasopharyngeal Carcinoma (NPC) Adaptive Radiation Therapy (ART)

PURPOSE/OBJECTIVE(S)

To explore the necessity of Image Guided Radiation Therapy (IGRT) for Nasopharyngeal Carcinoma (NPC) adaptive radiation therapy (ART), and evaluate the consistency and robustness of auto re-planning during ART.

MATERIALS/METHODS

Eleven NPC patients were enrolled in this study at one institution. We used a CT-integrated linear accelerator, which integrates a 16-slice helical CT to acquire diagnostic-grade fan-beam CT (FBCT) for IGRT. Electron density accuracy from FBCT provides a solid foundation for accurate radiation dose calculation. PGTVp, PTV1 and PTV2 prescription dose are 69.96 Gy, 60.06 Gy and 54.12 Gy with 33 fractions. All ROIs, including Targets and OARs, were auto delineated via a treatment planning system (TPS), and modified by a senior physician with more than 15-year experience to confirm that they follow the clinical requirement. An initial plan (Plan A) was automatically generated based on the first CT-Sim images on the TPS. Another adjusted re-plan (Plan B) was also automatically generated based on the second CT-Sim images after 20 fractions of treatment for ART implementation. During the whole course of the 33 fractions delivery, there are 20 fractions Plan A (with 4 weekly IGRTi, i = 1∼4) and 13 fractions Plan B (with 3 weekly IGRTj, j = 5∼7). After carefully rigid registration between the CT-Sim images and their following weekly FBCT images, we copied Plan A and Plan B to IGRTi and IGRTj, respectively. Plan_IGRT would be re-calculated for dose evaluation. In addition, the Plan A was copied to the second CT-Sim (Plan A_2nd CT-Sim) after first CT-Sim and second CT-Sim rigid images registration.

RESULTS

There is a significant target volume change of -5%±4%, -3%±3%, and -5%±3% from Plan A to Plan B, for PGTVp, PTV1 and PTV2 (p<0.05), respectively. All the Plan A and Plan B could be generated within 210.2s±1.4s, which is more time-saving than manual planning greatly, and there is no statistical difference between Plan A and Plan B of the plan quality index (p>0.05). The plans for IGRT7 are inferior to the plans for IGRT5 with higher V110% for PGTVp (4.40%±8.60% for Plan A, 2.37%±8.91% for Plan B). PlanA_2nd CT-Sim for each patient is inferior to Plan B, with higher V110% for PGTVp (19.12%±18.91%), lower V100% for PTV2 (-2.84%±2.89%) and higher Dmax for Brainstem (315.88 cGy ± 190.39 cGy) statistically. Furthermore, all the Plan B_IGRTj are superior to Plan A_IGRTj, with the dose index difference of -17.50% ± 23.15%/-15.47% ± 14.85%, 2.45% ± 3.23%/2.31% ± 3.09% and -194.03 cGy ± 221.91 cGy/-170.07 cGy ± 168.41 cGy for V110% of PGTVp, V100% for PTV2 and Dmax of Brainstem for j = 5/7 (p<0.05), respectively.

CONCLUSION

The world's first integrated CT-Linac platform, equipped with FBCT, can provide a diagnostic-quality FBCT for achieve offline ART. It is necessary for NPC patients to have the IGRT, ART and re-planning after 20 fractions treatment, for the target volumes change sharply. Auto planning and auto re-planning for NPC ART are able to maintain the plan consistency and robustness while shorten the planning time.