ReviewInsights into imaging2023
Stepwise diagnostic algorithm for high-attenuation pulmonary abnormalities on CT.
Review in Insights into imaging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- Potential of quantitative X-ray imaging from photon-counting CT: A novel analysis based on effective atomic number and physical density.Journal of applied clinical medical physics · 2026Article
- A puzzling case of pulmonary infiltrates in a young man with chronic kidney disease.Breathe (Sheffield, England) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
High-attenuation pulmonary abnormalities are commonly seen on CT. These findings are increasingly encountered with the growing number of CT examinations and the wide availability of thin-slice images. The abnormalities include benign lesions, such as infectious granulomatous diseases and metabolic diseases, and malignant tumors, such as lung cancers and metastatic tumors. Due to the wide spectrum of diseases, the proper diagnosis of high-attenuation abnormalities can be challenging. The assessment of these abnormal findings requires scrutiny, and the treatment is imperative. Our proposed stepwise diagnostic algorithm consists of five steps. Step 1: Establish the presence or absence of metallic artifacts. Step 2: Identify associated nodular or mass-like soft tissue components. Step 3: Establish the presence of solitary or multiple lesions if identified in Step 2. Step 4: Ascertain the predominant distribution in the upper or lower lungs if not identified in Step 2. Step 5: Identify the morphological pattern, such as linear, consolidation, nodular, or micronodular if not identified in Step 4. These five steps to diagnosing high-attenuation abnormalities subdivide the lesions into nine categories. This stepwise radiologic diagnostic approach could help to narrow the differential diagnosis for various pulmonary high-attenuation abnormalities and to achieve a precise diagnosis.Critical relevance statement Our proposed stepwise diagnostic algorithm for high-attenuation pulmonary abnormalities may help to recognize a variety of those high-attenuation findings, to determine whether the associated diseases require further investigation, and to guide appropriate patient management. Key points • To provide a stepwise diagnostic approach to high-attenuation pulmonary abnormalities.• To familiarize radiologists with the varying cause of high-attenuation pulmonary abnormalities.• To recognize which high-attenuation abnormalities require scrutiny and prompt treatment.
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.