Evidence map›Paper›PMID 42319638›Full record

ArticleEmergency radiology2026

Emphysematous cystitis: imaging patterns and diagnostic approach on CT.

Hajra Arshad, Satomi Kawamoto, Elliot K Fishman

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Article in Emergency radiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Hajra ArshadThe Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD, 21287, USA. harshad1@jh.edu.ORCID http://orcid.org/0000-0001-9206-739X
Satomi KawamotoThe Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD, 21287, USA.
Elliot K FishmanThe Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD, 21287, USA.ORCID http://orcid.org/0000-0002-2567-1658

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Emphysematous cystitis, also known as 'cystitis emphysematosa,' is a rare complicated urinary tract infection characterized by gas within the bladder wall. Most cases are mild and detected incidentally; however, delayed management can lead to significant morbidity and mortality, particularly when infection extends to the upper urinary tract. With increasing use of cross-sectional imaging, radiologists are encountering this condition more frequently. This pictorial review presents 20 cases of emphysematous cystitis from our institution, illustrating the range of CT imaging patterns and clinical features from representative cases. We identified three distinct patterns of gas distribution: loculated or curvilinear focal collections (40% of cases), single layer of cobblestone/beaded necklace pattern (30% of cases), and circumferential dissection of the bladder wall with multilayered gas (30% of cases). Diabetes is the most common predisposing factor. Other risk factors included neurogenic bladder, long-term urinary catheters, immunosuppression, chemotherapy, recurrent urinary stones, and frequent urologic procedures. The clinical presentation ranges from incidental detection on imaging to symptomatic patients presenting with acute abdomen and dysuria in the emergency department (ED). Treatment primarily consists of antibiotic therapy, with surgical intervention required only in select severe cases. Understanding these CT patterns along with the associated clinical features and risk factors allows radiologists to accurately diagnose emphysematous cystitis and guide timely clinical management.

Indexed as

Bladder gasComputed tomography (CT)Emphysematous cystitisIntramural bladder gas Complicated urinary tract infectionUrinary tract infection

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Registered trials

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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.