{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T14:02:39Z","timestamp":1791295359796,"version":"4.1.0"},"reference-count":95,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T00:00:00Z","timestamp":1791244800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Med."],"abstract":"<jats:p>Subsolid pulmonary nodules (SSNs), including pure ground-glass nodules (pGGNs) and part-solid nodules (PSNs), span transient inflammatory abnormalities and adenocarcinoma-spectrum lesions with widely different management implications. This critical narrative review treats CT reconstruction as part of the quantitative biomarker definition and asks whether targeted or high-spatial-resolution reconstruction provides stable, task-specific information beyond standardized thin-section CT. Evidence was synthesized across direct SSN reconstruction-domain studies, technical robustness studies, and clinical prediction studies. Direct imaging studies support improved depiction of selected fine structures, while same-scan GGN evidence demonstrates substantial pixel-size dependence of radiomic features and model composition. However, most clinical models were not evaluated in paired reconstruction domains, external validation with calibration remains uncommon, and no prospective study demonstrating management or patient benefit from reconstruction-aware radiomics in SSNs was identified in the literature reviewed. Persistent pGGNs provide a biological and technical rationale for investigating incremental quantitative information, but greater benefit than in PSNs has not been demonstrated. In PSNs, any model must add value beyond solid-component measurements, consolidation-to-tumor ratio, morphology, and longitudinal growth. Translation therefore requires reconstruction and segmentation robustness testing, strong conventional comparators, external calibration, prespecified thresholds, and prospective decision-linked evaluation. Until such benefit and safety are demonstrated, reconstruction-aware radiomics should remain investigational or confined to governed, domain-checked decision-support pathways.<\/jats:p>","DOI":"10.3389\/fmed.2026.1955926","type":"journal-article","created":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T13:47:29Z","timestamp":1791294449000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Reconstruction-aware radiomics for risk stratification of subsolid pulmonary nodules: technical evidence, clinical limits, and translation priorities"],"prefix":"10.3389","volume":"13","author":[{"given":"Yujian","family":"Liu","sequence":"first","affiliation":[{"name":"Department of Radiology, Zigong First People\u2019s Hospital","place":["Zigong, Sichuan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu","family":"Peng","sequence":"additional","affiliation":[{"name":"Department of Radiology, Zigong First People\u2019s Hospital","place":["Zigong, Sichuan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Feng","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Radiology, Zigong First People\u2019s Hospital","place":["Zigong, Sichuan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jie","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Radiology, Zigong First People\u2019s Hospital","place":["Zigong, Sichuan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jie","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Radiology, Zigong First People\u2019s Hospital","place":["Zigong, Sichuan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianquan","family":"Zhong","sequence":"additional","affiliation":[{"name":"Department of Radiology, Zigong First People\u2019s Hospital","place":["Zigong, Sichuan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,10,6]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"395","DOI":"10.1056\/NEJMoa1102873","article-title":"Reduced lung-cancer mortality with low-dose computed tomographic screening","volume":"365","year":"2011","journal-title":"N Engl J Med"},{"key":"B2","doi-asserted-by":"publisher","first-page":"503","DOI":"10.1056\/NEJMoa1911793","article-title":"Reduced lung-cancer mortality with volume CT screening in a randomized trial","volume":"382","author":"de Koning","year":"2020","journal-title":"N Engl J Med"},{"key":"B3","doi-asserted-by":"publisher","first-page":"980","DOI":"10.1136\/thoraxjnl-2020-215107","article-title":"Lung cancer probability and clinical outcomes of baseline and new subsolid nodules detected on low-dose CT screening","volume":"76","author":"Kim","year":"2021","journal-title":"Thorax"},{"key":"B4","doi-asserted-by":"publisher","first-page":"1176","DOI":"10.2214\/AJR.16.16043","article-title":"CT screening for lung cancer: part-solid nodules in baseline and annual repeat rounds","volume":"207","author":"Henschke","year":"2016","journal-title":"AJR Am J Roentgenol"},{"key":"B5","doi-asserted-by":"publisher","first-page":"441","DOI":"10.1148\/radiol.2019190905","article-title":"Cancer risk in subsolid nodules in the national lung screening trial","volume":"293","author":"Hammer","year":"2019","journal-title":"Radiology"},{"key":"B6","doi-asserted-by":"publisher","first-page":"3884","DOI":"10.1007\/s00330-020-07450-z","article-title":"Natural history of pathologically confirmed pulmonary subsolid nodules with deep learning-assisted nodule segmentation","volume":"31","author":"Qi","year":"2021","journal-title":"Eur Radiol"},{"key":"B7","doi-asserted-by":"publisher","first-page":"55","DOI":"10.3390\/diagnostics10020055","article-title":"What\u2019s new on quantitative CT analysis as a tool to predict growth in persistent pulmonary subsolid nodules? 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