Evaluation of respiratory motion-corrected cone-beam CT at end expiration in abdominal radiotherapy sites: a prospective study.

BACKGROUND: Cone beam computed tomography (CBCT) for radiotherapy image guidance suffers from respiratory motion artifacts. This limits soft tissue visualization and localization accuracy, particularly in abdominal sites. We report on a prospective study of respiratory motion-corrected (RMC)-CBCT to evaluate its efficacy in localizing abdominal organs and improving soft tissue visibility at end expiration. MATERIAL AND METHODS: In an IRB approved study, 11 patients with gastroesophageal junction (GEJ) cancer and five with pancreatic cancer underwent a respiration-correlated CT (4DCT), a respiration-gated CBCT (G-CBCT) near end expiration and a one-minute free-breathing CBCT scan on a single treatment day. Respiration was recorded with an external monitor. An RMC-CBCT and an uncorrected CBCT (NC-CBCT) were computed from the free-breathing scan, based on a respiratory model of deformations derived from the 4DCT. Localization discrepancy was computed as the 3D displacement of the GEJ region (GEJ patients), or gross tumor volume (GTV) and kidneys (pancreas patients) in the NC-CBCT and RMC-CBCT relative to their positions in the G-CBCT. Similarity of soft-tissue features was measured using a normalized cross correlation (NCC) function. RESULTS: Localization discrepancy from the end-expiration G-CBCT was reduced for RMC-CBCT compared to NC-CBCT in eight of eleven GEJ cases (mean ± standard deviation, respectively, 0.21 ± 0.11 and 0.43 ± 0.28 cm), in all five pancreatic GTVs (0.26 ± 0.21 and 0.42 ± 0.29 cm) and all ten kidneys (0.19 ± 0.13 and 0.51 ± 0.25 cm). Soft-tissue feature similarity around GEJ was higher with RMC-CBCT in nine of eleven cases (NCC =0.48 ± 0.20 and 0.43 ± 0.21), and eight of ten kidneys (0.44 ± 0.16 and 0.40 ± 0.17). CONCLUSIONS: In a prospective study of motion-corrected CBCT in GEJ and pancreas, RMC-CBCT yielded improved organ visibility and localization accuracy for gated treatment at end expiration in the majority of cases.

The mechanism of a ligand-promoted C(sp3)-H activation and arylation reaction via palladium catalysis: theoretical demonstration of a Pd(II)/Pd(IV) redox manifold.

Density functional theory (DFT) computations (BP86 and M06-L) have been utilized to elucidate the detailed mechanism of a palladium-catalyzed reaction involving pyridine-type nitrogen-donor ligands that significantly expands the scope of C(sp(3))-H activation and arylation. The reaction begins with precatalyst initiation, followed by substrate binding to the Pd(II) center through an amidate auxiliary, which directs the ensuing bicarbonate-assisted C(sp(3))-H bond activation producing five-membered-ring cyclopalladate(II) intermediates. These Pd(II) complexes further undergo oxidative addition with iodobenzene to form Pd(IV) complexes, which proceed by reductive C-C elimination/coupling to give final products of arylation. The base-assisted C(sp(3))-H bond cleavage is found to be the rate-determining step, which involves hydrogen bond interactions. The mechanism unravels the intimate involvement of the added 2-picoline ligand in every phase of the reaction, explains the isolation of the cyclopalladate intermediates, agrees with the observed kinetic hydrogen isotope effect, and demonstrates the Pd(II)/Pd(IV) redox manifold.

Automated and Clinically Optimal Treatment Planning for Cancer Radiotherapy.

Each year, approximately 18 million new cancer cases are diagnosed worldwide, and about half must be treated with radiotherapy. A successful treatment requires treatment planning with the customization of penetrating radiation beams to sterilize cancerous cells without harming nearby normal organs and tissues. This process currently involves extensive manual tuning of parameters by an expert planner, making it a time-consuming and labor-intensive process, with quality and immediacy of critical care dependent on the planner's expertise. To improve the speed, quality, and availability of this highly specialized care, Memorial Sloan Kettering Cancer Center developed and applied advanced optimization tools to this problem (e.g., using hierarchical constrained optimization, convex approximations, and Lagrangian methods). This resulted in both a greatly improved radiotherapy treatment planning process and the generation of reliable and consistent high-quality plans that reflect clinical priorities. These improved techniques have been the foundation of high-quality treatments and have positively impacted over 4,000 patients to date, including numerous patients in severe pain and in urgent need of treatment who might have otherwise required longer hospital stays or undergone unnecessary surgery to control the progression of their disease. We expect that the wide distribution of the system we developed will ultimately impact patient care more broadly, including in resource-constrained countries.