The Impact of Flow-Mediated Vasodilatation on Mechanism and Prognosis in Patients with Acute Coronary Syndrome: A FMD and OCT Study.

Background: Endothelial dysfunction, characterized by impaired flow-mediated vasodilation (FMD), is associated with atherosclerosis. However, the relationship between FMD, plaque morphology, and clinical outcomes in patients with acute coronary syndrome (ACS) remains underexplored. This study aims to investigate the influence of FMD on the morphology of culprit plaques and subsequent clinical outcomes in patients with ACS. Methods: This study enrolled 426 of 2482 patients who presented with ACS and subsequently underwent both preintervention FMD and optical coherence tomography (OCT) between May 2020 and July 2022. Impaired FMD was defined as an FMD% less than 7.0%. Major adverse cardiac events (MACEs) included cardiac death, nonfatal myocardial infarction, revascularization, or rehospitalization for angina. Results: Within a one-year follow-up, 34 (8.0%) patients experienced MACEs. The median FMD% was 4.0 (interquartile range 2.6-7.0). Among the patients, 225 (52.8%) were diagnosed with plaque rupture (PR), 161 (37.8%) with plaque erosion (PE), and 25 (5.9%) with calcified nodules (CN). Impaired FMD was found to be associated with plaque rupture (odds ratio [OR] = 4.22, 95% confidence interval [CI]: 2.07-6.72, p = 0.012) after adjusting for potential confounding factors. Furthermore, impaired FMD was linked to an increased incidence of MACEs (hazard ratio [HR] = 3.12, 95% CI: 1.27-6.58, p = 0.039). Conclusions: Impaired FMD was observed in three quarters of ACS patients and can serve as a noninvasive predictor of plaque rupture and risk for future adverse cardiac outcomes.

A novel AP/PA total body irradiation technique using abutting IMRT fields at extended SSD.

PURPOSE: To develop a Total Body Irradiation (TBI) technique using IMRT at extended SSD that can be performed in any size Linac room. METHODS: Patients studied were placed on a platform close to the floor, directly under the gantry with cranial-caudal axis parallel to the gantry rotation plane and at SSD ∼200 cm. Two abutting fields with the same external isocenter at gantry angles of ±21˚, collimator angle of 90˚, and field size of 25 × 40 cm2 are employed for both supine and prone positions. An iterative optimization algorithm was developed to generate a uniform dose at the patient mid-plane with adequate shielding to critical organs such as lungs and kidneys. The technique was validated in both phantom and patient CT images for treatment planning, and dose measurement and QA were performed in phantom. RESULTS: A uniform dose distribution in the mid-plane within ±5% of the prescription dose was reached after a few iterations. This was confirmed with ion-chamber measurements in phantom. The mean dose to lungs and kidneys can be adjusted according to clinical requirements and can be as low as ∼25% of the prescription dose. For a typical prescription dose of 200 cGy/fraction, the total MU was ∼2400/1200 for the superior/inferior field. The overall treatment time for both supine/prone positions was ∼54 min to meet the maximum absorbed dose rate criteria of 15 cGy/min. IMRT QA with portal dosimetry shows excellent agreement. CONCLUSIONS: We have developed a promising TBI technique using abutting IMRT fields at extended SSD. The patient is in a comfortable recumbent position with good reproducibility and less motion during treatment. An additional benefit of this technique is that full 3D dose distribution is available from the TPS with a DVH summary for organs of interest. The technique allows precise sparing of lungs and kidneys and can be executed in any linac room.

An end-to-end deep convolutional neural network-based dose engine for parotid gland cancer seed implant brachytherapy.

BACKGROUND: Seed implant brachytherapy (SIBT) is a promising treatment modality for parotid gland cancers (PGCs). However, the current clinical standard dose calculation method based on the American Association of Physicists in Medicine (AAPM) Task Group 43 (TG-43) Report oversimplifies patient anatomy as a homogeneous water phantom medium, leading to significant dose calculation errors due to heterogeneity surrounding the parotid gland. Monte Carlo Simulation (MCS) can yield accurate dose distributions but the long computation time hinders its wide application in clinical practice. PURPOSE: This paper aims to develop an end-to-end deep convolutional neural network-based dose engine (DCNN-DE) to achieve fast and accurate dose calculation for PGC SIBT. METHODS: A DCNN model was trained using the patient's CT images and TG-43-based dose maps as inputs, with the corresponding MCS-based dose maps as the ground truth. The DCNN model was enhanced based on our previously proposed model by incorporating attention gates (AGs) and large kernel convolutions. Training and evaluation of the model were performed using a dataset comprising 188 PGC I-125 SIBT patient cases, and its transferability was tested on an additional 16 non-PGC head and neck cancers (HNCs) I-125 SIBT patient cases. Comparison studies were conducted to validate the superiority of the enhanced model over the original one and compare their overall performance. RESULTS: On the PGC testing dataset, the DCNN-DE demonstrated the ability to generate accurate dose maps, with percentage absolute errors (PAEs) of 0.67% ± 0.47% for clinical target volume (CTV) D90 and 1.04% ± 1.33% for skin D0.1cc. The comparison studies revealed that incorporating AGs and large kernel convolutions resulted in 8.2% (p < 0.001) and 3.1% (p < 0.001) accuracy improvement, respectively, as measured by dose mean absolute error. On the non-PGC HNC dataset, the DCNN-DE exhibited good transferability, achieving a CTV D90 PAE of 1.88% ± 1.73%. The DCNN-DE can generate a dose map in less than 10 ms. CONCLUSIONS: We have developed and validated an end-to-end DCNN-DE for PGC SIBT. The proposed DCNN-DE enables fast and accurate dose calculation, making it suitable for application in the plan optimization and evaluation process of PGC SIBT.