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Armocida D, Zancana G, Bianconi A, Cofano F, Pesce A, Ascenzi BM, Bini P, Marchioni E, Garbossa D, Frati A. Brain metastases: Comparing clinical radiological differences in patients with lung and breast cancers treated with surgery. World Neurosurg X 2024; 23:100391. [PMID: 38725976 PMCID: PMC11079529 DOI: 10.1016/j.wnsx.2024.100391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Revised: 04/26/2024] [Accepted: 04/29/2024] [Indexed: 05/12/2024] Open
Abstract
Purpose Brain metastases (BMs) most frequently originate from the primary tumors of the lung and breast. Survival in patients with BM can improve if they are detected early. No studies attempt to consider all potential surgical predictive factors together by including clinical, radiological variables for their recognition. Methods The study aims to simultaneously analyze all clinical, radiologic, and surgical variables on a cohort of 314 patients with surgically-treated BMs to recognize the main features and differences between the two histotypes. Results The two groups consisted of 179 BM patients from lung cancer (Group A) and 135 patients from breast cancer (Group B). Analysis showed that BMs from breast carcinoma are more likely to appear in younger patients, tend to occur in the infratentorial site and are frequently found in patients who have other metastases outside of the brain (46 %, p = 0.05), particularly in bones. On the other hand, BMs from lung cancer often occur simultaneously with primitive diagnosis, are more commonly cystic, and have a larger edema volume. However, no differences were found in the extent of resection, postoperative complications or the presence of decreased postoperative performance status. Conclusion The data presented in this study reveal that while the two most prevalent forms of BM exhibit distinctions with respect to clinical onset, age, tumor location, presence of extra-cranial metastases, and lesion morphology from a strictly surgical standpoint, they are indistinguishable with regard to outcome, demonstrating comparable resection rates and a low risk of complications.
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Affiliation(s)
- Daniele Armocida
- Experimental Neurosurgery Unit, IRCCS “Neuromed”, via Atinense 18, 86077, Pozzilli, IS, Italy
- Department of Neuroscience “Rita Levi Montalcini”, Neurosurgery Unit, University of Turin, Via cherasco 15, 10126, Turin, TO, Italy
| | - Giuseppa Zancana
- Human Neurosciences Department Neurosurgery Division “La Sapienza” University, Policlinico Umberto 6 I, viale del Policlinico 155, 00161, Rome, RM, Italy
| | - Andrea Bianconi
- Department of Neuroscience “Rita Levi Montalcini”, Neurosurgery Unit, University of Turin, Via cherasco 15, 10126, Turin, TO, Italy
| | - Fabio Cofano
- Department of Neuroscience “Rita Levi Montalcini”, Neurosurgery Unit, University of Turin, Via cherasco 15, 10126, Turin, TO, Italy
| | - Alessandro Pesce
- Neurosurgery Unit Department, Santa Maria Goretti Hospital, Via Guido Reni, 04100, Latina, LT, Italy
| | - Brandon Matteo Ascenzi
- Independent Neuroresearcher Member of Marie Curie Alumni Association (MCAA), Via Dante Alighieri 103, 03012, Anagni, FR, Italy
| | - Paola Bini
- IRCCS foundation Istituto Neurologico Nazionale Mondino, Via Mondino, 2, 27100, Pavia, Italy
| | - Enrico Marchioni
- IRCCS foundation Istituto Neurologico Nazionale Mondino, Via Mondino, 2, 27100, Pavia, Italy
| | - Diego Garbossa
- Department of Neuroscience “Rita Levi Montalcini”, Neurosurgery Unit, University of Turin, Via cherasco 15, 10126, Turin, TO, Italy
| | - Alessandro Frati
- Experimental Neurosurgery Unit, IRCCS “Neuromed”, via Atinense 18, 86077, Pozzilli, IS, Italy
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Wang R, Zhou R, Sun S, Yang Z, Chen H. Histograms of computed tomography values in differential diagnosis of benign and malignant osteogenic lesions. Acta Radiol 2024; 65:625-631. [PMID: 38213126 DOI: 10.1177/02841851231225418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2024]
Abstract
BACKGROUND The use of histogram analysis of computed tomography (CT) values is a potential method for differentiating between benign osteoblastic lesions (BOLs) and malignant osteoblastic lesions (MOLs). PURPOSE To explore the diagnostic efficacy of histogram analysis in accurately distinguishing between BOLs and MOLs based on CT values. MATERIAL AND METHODS A total of 25 BOLs and 25 MOLs, which were confirmed through pathology or imaging follow-up, were included in this study. FireVoxel software was used to process the lesions and obtain various histogram parameters, including mean value, standard deviation, variance, coefficient of variation, skewness, kurtosis, entropy value, and percentiles ranging from 1st to 99th. Statistical tests, such as two independent-sample t-tests and the Mann-Whitney U test with Bonferroni correction, were employed to compare the differences in histogram parameters between BOLs and MOLs. A receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic efficacy of each parameter. RESULTS Significant differences were observed in several histogram parameters between BOLs and MOLs, including the mean value, coefficient of variation, skewness, and various percentiles. Notably, the 25th percentile demonstrated the highest diagnostic efficacy, as indicated by the largest area under the curve in the ROC curve analysis. CONCLUSION Histogram analysis of CT values provides valuable diagnostic information for accurately differentiating between BOLs and MOLs. Among the different parameters, the 25th percentile parameter proves to be the most effective in this discrimination process.
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Affiliation(s)
- Ruiqing Wang
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao City, PR China
| | - Ruizhi Zhou
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao City, PR China
| | - Shiqing Sun
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao City, PR China
| | - Zhitao Yang
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao City, PR China
| | - Haisong Chen
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao City, PR China
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