ArticleJournal of medical physics
Does Single Computed Tomography Attenuation Correction able to Surrogate Serial Computed Tomography Attenuation Correction in Single-Photon Emission Computed Therapy Imaging for Peptide Receptor Radionuclide Therapy Dosimetry Result?
Article in Journal of medical physics. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed, 0 citations in OpenAlex.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Peptide Receptor Radionuclide Therapy (PRRT) is the administration of a radionuclide, such as the Lu-177 label, along with a pharmaceutical agent to destroy the lesion cell. The first cycle of Lu-177 DOTA-TATE is an excellent way to estimate radionuclide uptake for organs at risk. To estimate the absorbed dose for a kidney, serial SPECT-CT imaging with up to five sets is required. In general, serial CT on patients would result in additional external exposure and extra time consuming, especially for low dose CT such as cone beam CT technology. However, by introducing a new method, such as optimized single CT (24 h) to perform with serial SPECT attenuation correction, additional external exposure from serial CT exposure could be reduced. Aims: The purpose of this study is to assess the agreement between single CT scanning as CT attenuation Correction with serial CT scanning for serial SPECT imaging as well as estimated absorbed dose to the organ at risk. Settings and Design: During the first cycle of Lu177-DOTA-TATE, all patients should undergo internal dosimetry technique using SPECT-CT imaging with a PHILIP Brightview XCT gamma camera. The quantifications of SPECT images are being used to measure the uptake activity to the organ. In this investigation, Partik's categorical grading criteria are being used to convert the numeric value of Lin's concordance coefficient into an ordinal scale. Method: Total of 9 patients at our institution was administered with Lu177-DOTA-TATE enroll in this study. SPECT-CT data were acquired using automatic body contouring with a total of 48 angular views at steps of 6° (15 s/projections). The pixel size is 4.66 x 4.66 x 4.66 mm, the images size set to one, and SPECT data has been acquired for three-bed positions extending from the abdomen to the thorax region. Low-dose CT imaging performed at an X-ray tube voltage of 120 kVp. Results: Our current result demonstrated by single CT scanning for SPECT attenuation shown the excellent agreement with standard serial CT imaging for organs at risk such as kidney 0.999, spleen 0.9951, liver 0.9951 and bladder 0.9972. Conclusions: When compared to the previous method, patients benefit significantly more from this study, such as lower CT exposure.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.