Appropriate use of CT for patients presenting with suspected renal colic: a quality improvement study

IntroductionCT use for renal colic has increased costs, radiation exposure and frequently does not alter management. Consequently, choosing wisely (CW) recommends avoiding CT imaging of otherwise healthy patients younger than 50 years presenting with symptoms of recurrent, uncomplicated renal colic. We evaluated the utilisation of CT imaging for this subgroup of patients and subsequently implemented a quality improvement initiative with an aim to reduce unnecessary radiation exposure.MethodsA retrospective chart review was performed for all patients younger than 50 years who visited Sunnybrook Health Sciences Centre emergency department (ED) between December 2015 and May 2016 with a discharge diagnosis of renal colic. After the audit period, emergency physicians were engaged to perform a root cause analysis and a driver diagram was developed. In December 2016, a clinical decision tool was introduced to standardise the imaging for patients with presumed renal colic. In May 2017, a separate electronic order was created for low-dose CT for renal colic, including a prompt to remind clinicians of the CW recommendation. The impact of these changes was measured over 15 months.ResultsOver the initial audit period, 17/63 (27%) of our target population received a CT to rule out renal colic. Many patients received multiple CT scans for renal colic during past ED visits, while one received a total of 13 CTs. At the time of our interventions, the baseline rate of CT scans in our target population was 37%, which reduced to 29% after our project began.ConclusionCT is often used as an initial diagnostic modality for suspected recurrent renal colic despite current guidelines. While this initiative caused only a modest change in management, it led to the introduction of a new low-dose CT scan order specifically to reduce radiation exposure in patients at risk for repeat scans.

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Screening for lung cancer with low-dose CT scans

Respiratory Investigation ◽

10.1016/j.resinv.2013.10.001 ◽

2013 ◽

Vol 51 (4) ◽

pp. 205-206 ◽

Cited By ~ 1

Author(s):

James R. Jett

Keyword(s):

Lung Cancer ◽

Low Dose ◽

Ct Scans ◽

Low Dose Ct

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Radiomic Phenotyping of the Lung Parenchyma: Feasibility Study in a Screening Cohort

10.21203/rs.3.rs-1086873/v1 ◽

2021 ◽

Author(s):

Babak Haghighi ◽

Hannah Horng ◽

Peter B Noël ◽

Eric Cohen ◽

Lauren Pantalone ◽

...

Keyword(s):

Lung Cancer ◽

Cancer Screening ◽

Low Dose ◽

Lung Cancer Screening ◽

Lung Parenchyma ◽

Ct Scans ◽

Lung Field ◽

Reconstruction Algorithms ◽

Low Dose Ct ◽

Significant Difference

Abstract Rationale: High-throughput extraction of radiomic features from low-dose CT scans can characterize the heterogeneity of the lung parenchyma and potentially aid in identifying subpopulations that may have higher risk of lung diseases, such as COPD, and lung cancer due to inflammation or obstruction of the airways. We aim to determine the feasibility a lung radiomics phenotyping approach in a lung cancer screening cohort, while quantifying the effect of different CT reconstruction algorithms on phenotype robustness. Methods: We identified low-dose CT scans (n = 308) acquired with Siemens Healthineers scanners from patients who completed low-dose CT within our lung cancer screening program between 2015-2018 and had two different sets of image reconstructions kernel available (i.e., medium (I30f), sharp (I50f)) for the same acquisition. Following segmentation of the lung field, a total of 26 radiomic features were extracted from the entire 3D lung-field using a previously validated fully-automated lattice-based software pipeline, adapted for low-dose CT scans. The features extracted included gray-level histogram, co-occurrence, and run-length descriptors. Each feature was averaged for each scan within a range of lattice window sizes (W) ranging from 4-20mm. The extracted imaging features from both datasets were harmonized to correct for differences in image acquisition parameters. Subsequently, unsupervised hierarchal clustering was applied on the extracted features to identify distinct phenotypic patterns of the lung parenchyma, where consensus clustering was used to identify the optimal number of clusters (K = 2). Differences between? phenotypes for demographic and clinical covariates including sex, age, BMI, pack-years of smoking, Lung-RADS and cancer diagnosis were assessed for each phenotype cluster, and then compared across clusters for the two different CT reconstruction algorithms using the cluster entanglement metric, where a lower entanglement coefficient corresponds to good cluster alignment. Furthermore, an independent set of low-dose CT scans (n = 88) from patients with available pulmonary function data on lung obstruction were analyzed using the identified optimal clusters to assess associations to lung obstruction and validate the lung phenotyping paradigm. Results: Heatmaps generated by radiomic features identified two distinct lung parenchymal phenotype patterns across different feature extraction window sizes, for both reconstruction algorithms (P < 0.05 with K = 2). Associations of radiomic-based clusters with clinical covariates showed significant difference for BMI and pack-years of smoking (P < 0.05) for both reconstruction kernels. Radiomic phenotype patterns where similar across the two reconstructed kernels, specifically when smaller window sizes (W=4 and 8mm) were used for radiomic feature extraction, as deemed by their entanglement coefficient. Validation of clustering approaches using cluster mapping for the independent sample with lung obstruction also showed two statistically significant phenotypes (P < 0.05) with significant difference for BMI and smoking pack-years.ConclusionsRadiomic analysis can be used to characterize lung parenchymal phenotypes from low-dose CT scans, which appear reproducible for different reconstruction kernels. Further work should seek to evaluate the effect of additional CT acquisition parameters and validate these phenotypes in characterizing lung cancer screening populations, to potentially better stratify disease patterns and cancer risk.

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Detecting airway remodeling in COPD and emphysema using low-dose CT imaging

10.1117/12.910901 ◽

2012 ◽

Author(s):

R. Rudyanto ◽

M. Ceresa ◽

A. Muñoz-Barrutia ◽

C. Ortiz-de-Solorzano

Keyword(s):

Low Dose ◽

Airway Remodeling ◽

Ct Imaging ◽

Low Dose Ct

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Experiments on Sensitivity of Template Matching for Lung Nodule Detection in Low Dose CT Scans

2007 IEEE International Symposium on Signal Processing and Information Technology ◽

10.1109/isspit.2007.4458213 ◽

2007 ◽

Cited By ~ 1

Author(s):

Shireen Y Elhabian ◽

Hossam Abd el Munim ◽

Salwa Elshazly ◽

AlyA. Farag ◽

Mohamed Aboelghar

Keyword(s):

Template Matching ◽

Low Dose ◽

Lung Nodule ◽

Ct Scans ◽

Low Dose Ct ◽

Lung Nodule Detection ◽

Nodule Detection

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Ultra-low-dose CT detects synovitis in patients with suspected rheumatoid arthritis

Annals of the Rheumatic Diseases ◽

10.1136/annrheumdis-2018-213904 ◽

2018 ◽

Vol 78 (1) ◽

pp. 31-35 ◽

Cited By ~ 2

Author(s):

Torsten Diekhoff ◽

Sevtap Tugce Ulas ◽

Denis Poddubnyy ◽

Udo Schneider ◽

Sandra Hermann ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Soft Tissue ◽

Radiation Exposure ◽

Low Dose ◽

Intravenous Contrast ◽

Low Dose Ct ◽

Contrast Enhanced ◽

Pearson's R ◽

Sum Scores ◽

Pearson’S R

PurposeTo prove the feasibility and measure the diagnostic accuracy of contrast-enhanced ultra-low-dose CT (ULD-CT) for the depiction of inflammatory soft-tissue changes (synovitis, tenosynovitis and peritendonitis) in patients with arthritis of the hand.Materials and methodsIn this institutional review board–approved study, 36 consecutive patients over the age of 50 with suspected rheumatoid arthritis underwent ULD-CT (estimated radiation exposure <0.01 mSv) and MRI of the hand with weight-adapted intravenous contrast administration. ULD-CT subtraction and MR images were assessed for synovitis, tenosynovitis and peritendonitis by three readers using a modified Rheumatoid Arthritis MRI Score (RAMRIS). Patients were asked which modality they would prefer for future examinations. Sensitivity and specificity of ULD-CT for detection of inflammatory changes were calculated using MRI as standard of reference. The sum scores were correlated using Pearson’s r.ResultsAll 36 patients showed synovitis in MRI. ULD-CT had 69% sensitivity on the patient level and 65% on the joint level with 87% specificity. Sensitivity was higher in patients with more severe inflammation (80% for MRI RAMRIS >1). There was almost perfect correlation between the modified RAMRIS sum scores of ULD-CT and MRI (Pearson’s r=0.94). Regarding preferences for future examinations, 85% preferred ULD-CT over MRI. ULD-CT detected more differential diagnoses than MRI (8 vs 2/12).Conclusion Contrast-enhanced ULD-CT of the hand allows for depiction of soft-tissue inflammation at the hand and can be achieved using very low radiation exposure (<0.01 mSv). ULD-CT may evolve to a fast and comfortable alternative to MRI, although it is not as sensitive as MRI for detecting mild disease.

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