Evidence map›Paper›PMID 36467572›Full record

ArticleEuropean journal of radiology open2022

Quantitative assessment of renal obstruction in multi-phase CTU using automatic 3D segmentation of the renal parenchyma and renal pelvis: A proof of concept.

Chanoch Kahn, Isaac Leichter, Richard Lederman, Jacob Sosna, Mordechai Duvdevani, Talia Yeshua

Open access · goldAbstract read
In one paragraph

Article in European journal of radiology open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 43% of its field
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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
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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

6 authors at 2 institutions in 1 country.

Chanoch KahnDepartment of Applied Physics, The Jerusalem Collage of Technology, 21 HaVa'ad HaLeumi St, Jerusalem, Israel.
Isaac LeichterDepartment of Applied Physics, The Jerusalem Collage of Technology, 21 HaVa'ad HaLeumi St, Jerusalem, Israel.
Richard LedermanDepartment of Radiology, Hadassah Medical Center, 1 Kalman Man St, Jerusalem, Israel.
Jacob SosnaDepartment of Radiology, Hadassah Medical Center, 1 Kalman Man St, Jerusalem, Israel.
Mordechai DuvdevaniDepartment of Urology, Hadassah Medical Center, 1 Kalman Man St, Jerusalem, Israel.
Talia YeshuaDepartment of Applied Physics, The Jerusalem Collage of Technology, 21 HaVa'ad HaLeumi St, Jerusalem, Israel.
Hadassah Medical Center · ILJerusalem College of Technology · IL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Quantitative evaluation of renal obstruction is crucial for preventing renal atrophy. This study presents a novel method for diagnosing renal obstruction by automatically extracting objective indicators from routine multi-phase CT Urography (CTU). Material and methods: The study included multi-phase CTU examinations of 6 hydronephrotic kidneys and 24 non-hydronephrotic kidneys (23,164 slices). The developed algorithm segmented the renal parenchyma and the renal pelvis of each kidney in each CTU slice. Following a 3D reconstruction of the parenchyma and renal pelvis, the algorithm evaluated the amount of the contrast media in both components in each phase. Finally, the algorithm evaluated two indicators for assessing renal obstruction: the change in the total amount of contrast media in both components during the CTU phases, and the drainage time, "T Results: The algorithm segmented the parenchyma and renal pelvis with an average dice coefficient of 0.97 and 0.92 respectively. In all the hydronephrotic kidneys the total amount of contrast media did not decrease during the CTU examination and the T Conclusions: The novel algorithm enables accurate 3D segmentation of the renal parenchyma and pelvis and estimates the amount of contrast media in multi-phase CTU examinations. This serves as a proof-of-concept for the ability to extract from routine CTU indicators that alert to the presence of renal obstruction and estimate its severity.

Indexed as

3D kidney segmentationCT urographyRenal obstructionUrine drainage rate

Identifiers

PMID36467572
PMCPMC9709111
OpenAlexW4310779051

What OpenQuestion holds

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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.