The Diagnostic Contribution of SPECT/CT Imaging in the Assessment of Gastrointestinal Bleeding: Especially for Previously Operated Patients

Demir, Selin Soyluoğlu; Korkmaz, Ülkü; Özdemir, Büşra; Altun, Gülay Durmuş

doi:10.4274/mirt.galenos.2020.24392

Cited by 4 publications

(3 citation statements)

References 34 publications

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“…A 99m Tc-labeled RBC scan was performed when the patient still had hemorrhagic symptoms. We also performed a SPECT/CT scan because it is better than planar images are at diagnosing bleeding points and collecting information about the etiology[ 16 , 17 ]. Moreover, SPECT/CT may contribute to confirming aortic aneurysms and determining their clinical significance[ 17 ].…”

Section: Discussionmentioning

confidence: 99%

“…We also performed a SPECT/CT scan because it is better than planar images are at diagnosing bleeding points and collecting information about the etiology[ 16 , 17 ]. Moreover, SPECT/CT may contribute to confirming aortic aneurysms and determining their clinical significance[ 17 ]. In conclusion, if a bleeding site is identified on 99m Tc-labeled RBC planar imaging, a SPECT/CT study is recommended for confirmation.…”

Section: Discussionmentioning

confidence: 99%

“…To treat GI bleeding, the bleeding site must be localized, usually by using endoscopy. Other methods include angiography, computed tomography (CT) angiography (CTA), capsule endoscopy, and 99m Tc-labeled red blood cell (RBC) scanning, each of which has its limitations[ 11 - 17 ].…”

Section: Introductionmentioning

confidence: 99%

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Time series analysis is a valuable tool in epidemiology that complements the classical epidemiological models in two different ways: Prediction and forecast. Prediction is related to explaining past and current data based on various internal and external influences that may or may not have a causative role. Forecasting is an exploration of the possible future values based on the predictive ability of the model and hypothesized future values of the external and/or internal influences. The time series analysis approach has the advantage of being easier to use (in the cases of more straightforward and linear models such as Auto-Regressive Integrated Moving Average). Still, it is limited in forecasting time, unlike the classical models such as Susceptible-Exposed-Infectious-Removed. Its applicability in forecasting comes from its better accuracy for short-term prediction. In its basic form, it does not assume much theoretical knowledge of the mechanisms of spreading and mutating pathogens or the reaction of people and regulatory structures (governments, companies, etc. ). Instead, it estimates from the data directly. Its predictive ability allows testing hypotheses for different factors that positively or negatively contribute to the pandemic spread; be it school closures, emerging variants, etc. It can be used in mortality or hospital risk estimation from new cases, seroprevalence studies, assessing properties of emerging variants, and estimating excess mortality and its relationship with a pandemic.

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Section: Discussionmentioning

confidence: 99%