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Record W4292403456 · doi:10.1111/bju.15869

Radiological features characterising indeterminate testes masses: a systematic review and meta‐analysis

2022· review· en· W4292403456 on OpenAlexaff
Michael Ager, Sarah Donegan, Luca Boeri, J. Mayor de Castro, James F. Donaldson, Muhammad Imran Omar, Konstantinos Dimitropoulos, Tharu Tharakan, Florian Janisch, Tim Muilwijk, Catrin Tudur Smith, Rien J.M. Nijman, Christian Radmayr, Andrea Salonia, M. Pilar Laguna Pes, Suks Minhas

Bibliographic record

VenueBritish Journal of Urology · 2022
Typereview
Languageen
FieldMedicine
TopicTesticular diseases and treatments
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineMalignancyIndeterminateRadiological weaponMeta-analysisMagnetic resonance imagingRadiologySystematic reviewHistopathologyNuclear medicineMEDLINEPathology

Abstract

fetched live from OpenAlex

CONTEXT: The use of scrotal ultrasonography (SUS) has increased the detection rate of indeterminate testicular masses. Defining radiological characteristics that identify malignancy may reduce the number of men undergoing unnecessary radical orchidectomy. OBJECTIVE: To define which SUS or scrotal magnetic resonance imaging (MRI) characteristics can predict benign or malignant disease in pre- or post-pubertal males with indeterminate testicular masses. EVIDENCE ACQUISITION: This systematic review was conducted in accordance with Cochrane Collaboration guidance. Medline, Embase, Cochrane controlled trials and systematic reviews databases were searched from (1970 to 26 March 2021). Benign and malignant masses were classified using the reported reference test: i.e., histopathology, or 12 months progression-free radiological surveillance. Risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool (QUADAS-2). EVIDENCE SYNTHESIS: A total of 32 studies were identified, including 1692 masses of which 28 studies and 1550 masses reported SUS features, four studies and 142 masses reported MRI features. Meta-analysis of different SUS (B-mode) values in post-pubertal men demonstrated that a size of ≤0.5 cm had a significantly lower odds ratio (OR) of malignancy compared to masses of >0.5 cm (P < 0.001). Comparison of masses of 0.6-1.0 cm and masses of >1.5 cm also demonstrated a significantly lower OR of malignancy (P = 0.04). There was no significant difference between masses of 0.6-1.0 and 1.1-1.5 cm. SUS in post-pubertal men also had a statistically significantly lower OR of malignancy for heterogenous masses vs homogenous masses (P = 0.04), hyperechogenic vs hypoechogenic masses (P < 0.01), normal vs increased enhancement (P < 0.01), and peripheral vs central vascularity (P < 0.01), respectively. There were limited data on pre-pubertal SUS, pre-pubertal MRI and post-pubertal MRI. CONCLUSIONS: This meta-analysis identifies radiological characteristics that have a lower OR of malignancy and may be of value in the management of the indeterminate testis mass.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.028
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.015
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.028
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0150.022
Bibliometrics0.0060.007
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.054
GPT teacher head0.343
Teacher spread0.289 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations14
Published2022
Admission routes1
Has abstractyes

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