A scoring system combining clinical, radiological, and histopathological examinations for differential diagnosis between lipoma and atypical lipomatous tumor/well-differentiated liposarcoma

AbstractThis study evaluated the diagnostic accuracy of clinical, radiological, and histopathological examinations for differential diagnosis between atypical lipomatous tumor (ALT)/well-differentiated liposarcoma (WDLS) and lipoma, and aimed to develop a new combined scoring system for the preoperative diagnosis of ALT/WDLS. Eighty-nine lipomas and 56 ALT/WDLS were included and their clinical characteristics, magnetic resonance imaging (MRI) findings, histological findings by hematoxylin and eosin (HE) staining were investigated. Then, univariate and multivariate logistic regression analyses were performed for the findings, and a combined scoring system consisted of predictive factors of ALT/WDLS was developed. The univariate and multivariate logistic regression analyses revealed that tumor location (lower extremity), deep site, size (> 11 cm), thick septa (> 2 mm), enhancement of septa or nodular lesions, and lipoblasts were significantly different for the diagnosis of ALT/WDLS. We developed a combined scoring system based on the six predictive factors (total 0–16 points, the cutoff was 9 points). The area under the curve was 0.945, and sensitivity was 87.6% and specificity was 91.1% by the receiver operating characteristics curve. This combined scoring system does not require special equipment and reagents such as fluorescence in situ hybridization (FISH), and anyone can use it easily in many medical institutions with high diagnostic accuracy.

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A Scoring System Combining Clinical, Radiological, And Histopathological Examinations For Differential Diagnosis Between Lipoma And Atypical Lipomatous Tumor/Well-Differentiated Liposarcoma

10.21203/rs.3.rs-279121/v2 ◽

2021 ◽

Author(s):

Yohei Asano ◽

Shinji Miwa ◽

Norio Yamamoto ◽

Katsuhiro Hayashi ◽

Akihiko Takeuchi ◽

...

Keyword(s):

Logistic Regression ◽

Differential Diagnosis ◽

Diagnostic Accuracy ◽

Predictive Factors ◽

Scoring System ◽

Regression Analyses ◽

Multivariate Logistic Regression ◽

Atypical Lipomatous Tumor ◽

Lipomatous Tumor ◽

Well Differentiated

Abstract This study evaluated the diagnostic accuracy of clinical, radiological, and histopathological examinations for differential diagnosis between atypical lipomatous tumor (ALT)/well-differentiated liposarcoma (WDLS) and lipoma, and aimed to develop a new combined scoring system for the preoperative diagnosis of ALT/WDLS. Eighty-nine ALT/WDLS and 56 lipomas were included and their clinical characteristics, magnetic resonance imaging (MRI) findings, histological findings by hematoxylin and eosin (HE) staining were investigated. Then, univariate and multivariate logistic regression analyses were performed for the findings, and a combined scoring system consisted of predictive factors of ALT/WDLS was developed. The univariate and multivariate logistic regression analyses revealed that tumor location (lower extremity), deep site, size (>11cm), thick septa (>2mm), enhancement of septa or nodular lesions, and lipoblasts were significantly different for the diagnosis of ALT/WDLS. We developed a combined scoring system based on the six predictive factors (total 0–16 points, the cutoff was 9 points). The area under the curve was 0.945, and sensitivity was 87.6% and specificity was 91.1% by the receiver operating characteristics curve. This combined scoring system does not require special equipment and reagents such as fluorescence in situ hybridization (FISH), and anyone can use it easily in many medical institutions with high diagnostic accuracy.

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A scoring system combining clinical, radiological, and histopathological examinations for differential diagnosis between lipoma and atypical lipomatous tumor/well-differentiated liposarcoma

10.21203/rs.3.rs-279121/v1 ◽

2021 ◽

Author(s):

Yohei Asano ◽

Shinji Miwa ◽

Norio Yamamoto ◽

Katsuhiro Hayashi ◽

Akihiko Takeuchi ◽

...

Keyword(s):

Logistic Regression ◽

Differential Diagnosis ◽

Predictive Factors ◽

Scoring System ◽

Regression Analyses ◽

Multivariate Logistic Regression ◽

Special Equipment ◽

Atypical Lipomatous Tumor ◽

Lipomatous Tumor ◽

Well Differentiated

Abstract Background: Preoperative differential diagnosis between atypical lipomatous tumor (ALT)/well-differentiated liposarcoma (WDLS) and lipoma is important to determine the appropriate resection margin. However, since their radiological and histopathological findings are similar, it may be difficult to make a differential diagnosis. In this study, we evaluated the diagnostic accuracies of clinical, radiological, and histopathological examinations for diagnosing ALT/WDLS and developed a new combined scoring system.Methods: Eighty-nine ALT/WDLS and 56 lipomas were included and their clinical characteristics, magnetic resonance imaging (MRI) findings, histological findings by hematoxylin and eosin (HE) staining were investigated, and compared between ALT/WDLS and lipoma. Then, univariate analyses and multivariate logistic regression analyses were performed for the findings, and a combined scoring system consisted of predictive factors of ALT/WDLS was developed. Results: The univariate and multivariate logistic regression analyses revealed that tumor location (lower extremity), deep site, and size (>11cm), thick septa (>2mm), enhancement of septa or nodular lesions on MRI, and lipoblasts in HE staining were significantly different for the diagnosis of ALT/WDLS. Based on the six predictive factors, we developed a combined scoring system (total 0–16 points, the cutoff was 9 points). The mean score of ALT/WDLS was significantly higher than lipoma (11.9 vs. 5.6, p<0.0001). The area under the curve was 0.945, and sensitivity was 87.6% and specificity was 91.1% by the receiver operating characteristics curve.Conclusions: We developed a new combined scoring system based on comprehensive examinations that excluded examination which requires special equipment and reagents such as fluorescence in situ hybridization (FISH), and this can be used in many medical institutions. The diagnostic accuracy of ALT/WDLS was high and it may be useful for preoperative diagnosis and surgical plan.

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Prevalence and Predictive Factors of Sexual Dysfunction in Iranian Women: Univariate and Multivariate Logistic Regression Analyses

Korean Journal of Family Medicine ◽

10.4082/kjfm.2016.37.5.293 ◽

2016 ◽

Vol 37 (5) ◽

pp. 293 ◽

Cited By ~ 2

Author(s):

Ashraf Direkvand-Moghadam ◽

Zainab Suhrabi ◽

Malihe Akbari ◽

Azadeh Direkvand-Moghadam

Keyword(s):

Logistic Regression ◽

Sexual Dysfunction ◽

Predictive Factors ◽

Regression Analyses ◽

Iranian Women ◽

Multivariate Logistic Regression

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Differential diagnosis of atypical lipomatous tumor/well-differentiated liposarcoma and dedifferentiated liposarcoma: utility of p16 in combination with MDM2 and CDK4 immunohistochemistry

Human Pathology ◽

10.1016/j.humpath.2016.08.009 ◽

2017 ◽

Vol 59 ◽

pp. 34-40 ◽

Cited By ~ 36

Author(s):

Solène-Florence Kammerer-Jacquet ◽

Sixte Thierry ◽

Florian Cabillic ◽

Morgane Lannes ◽

Florence Burtin ◽

...

Keyword(s):

Differential Diagnosis ◽

Dedifferentiated Liposarcoma ◽

Atypical Lipomatous Tumor ◽

Lipomatous Tumor ◽

Well Differentiated

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Differential diagnosis of lipoma and atypical lipomatous tumor/well‐differentiated liposarcoma by cytological analysis

Diagnostic Cytopathology ◽

10.1002/dc.24928 ◽

2022 ◽

Author(s):

Kana Sugiyama ◽

Kota Washimi ◽

Shinya Sato ◽

Toru Hiruma ◽

Mai Sakai ◽

...

Keyword(s):

Differential Diagnosis ◽

Cytological Analysis ◽

Atypical Lipomatous Tumor ◽

Lipomatous Tumor ◽

Well Differentiated

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Differential Diagnosis of Lipoma and Atypical Lipomatous Tumor/Well-Differentiated Liposarcoma by Cytological Analysis

10.21203/rs.3.rs-900482/v1 ◽

2021 ◽

Author(s):

Kana Sugiyama ◽

Kota Washimi ◽

Shinya Sato ◽

Toru Hiruma ◽

Mai Sakai ◽

...

Keyword(s):

Differential Diagnosis ◽

Detection Accuracy ◽

Atypical Cell ◽

Tissue Samples ◽

Atypical Lipomatous Tumor ◽

Lipomatous Tumor ◽

Multinucleated Cells ◽

Adipocytic Tumors ◽

Atypical Cells ◽

Well Differentiated

Abstract Background: Adipocytic tumors are the most common soft tissue tumors, with lipomas and atypical lipomatous tumor/well-differentiated liposarcomas (ALT/WDL) comprising the majority of cases. Preoperative differential diagnosis of lipoma or ALT/WDL can provide important information for decisions regarding treatment. We evaluated the cytological findings of 20 cases of lipoma and ALT/WDL.Methods: Fluorescence in situ hybridization (FISH) was performed on formalin-fixed paraffin-embedded specimens (FFPE) to examine mouse double minute 2 homolog (MDM2) amplification in all cases. Tissue samples were collected from the center of the surgical materials, stained with Papanicolaou, and evaluated for 12 cytological parameters by six cytotechnologists.Results: The findings regarding large atypical cells, multinucleated cells, and nuclear pleomorphism were highly concordant among the cytotechnologists and were associated with MDM2 amplification. Large atypical cells, considered a highly specific feature of ALT/WDL, were not observed in the lipoma cases. However, the sensitivity of the large atypical cell findings was not high (67%), and therefore, comprehensive evaluation of multinucleated cells and pleomorphism is crucial for predicting the diagnosis of ALT/WDL. FISH of MDM2 on Papanicolaou-stained specimens was performed in four cases. In two cases, the results were similar to those of MDM2 FISH performed on FFPE sections and were reproducible, whereas in two other cases, the signal could not be evaluated because of the strong background coloration. Conclusions: Cytology specimens may be useful for preoperative diagnosis of adipocytic tumors, particularly if the FISH conditions for Papanicolaou-stained specimens and the detection accuracy of MDM2 amplification can be improved.

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Predictors of thermal increase in magnetic resonance–guided focused ultrasound treatment for essential tremor: histogram analysis of skull density ratio values for 1024 elements

Journal of Neurosurgery ◽

10.3171/2021.5.jns21669 ◽

2021 ◽

pp. 1-6

Author(s):

Ken Iijima ◽

Hajime Yokota ◽

Toshio Yamaguchi ◽

Masayuki Nakano ◽

Takahiro Ouchi ◽

...

Keyword(s):

Logistic Regression ◽

Operating Characteristic ◽

Focused Ultrasound ◽

Characteristic Curve ◽

Density Ratio ◽

Predictive Ability ◽

Curve Analysis ◽

Regression Analyses ◽

Multivariate Logistic Regression ◽

Operating Characteristic Curve

OBJECTIVE Sufficient thermal increase capable of generating thermocoagulation is indispensable for an effective clinical outcome in patients undergoing magnetic resonance–guided focused ultrasound (MRgFUS). The skull density ratio (SDR) is one of the most dominant predictors of thermal increase prior to treatment. However, users currently rely only on the average SDR value (SDRmean) as a screening criterion, although some patients with low SDRmean values can achieve sufficient thermal increase. The present study aimed to examine the numerical distribution of SDR values across 1024 elements to identify more precise predictors of thermal increase during MRgFUS. METHODS The authors retrospectively analyzed the correlations between the skull parameters and the maximum temperature achieved during unilateral ventral intermediate nucleus thalamotomy with MRgFUS in a cohort of 55 patients. In addition, the numerical distribution of SDR values was quantified across 1024 elements by using the skewness, kurtosis, entropy, and uniformity of the SDR histogram. Next, the authors evaluated the correlation between the aforementioned indices and a peak temperature > 55°C by using univariate and multivariate logistic regression analyses. Receiver operating characteristic curve analysis was performed to compare the predictive ability of the indices. The diagnostic performance of significant factors was also assessed. RESULTS The SDR skewness (SDRskewness) was identified as a significant predictor of thermal increase in the univariate and multivariate logistic regression analyses (p < 0.001, p = 0.013). Moreover, the receiver operating characteristic curve analysis indicated that the SDRskewness exhibited a better predictive ability than the SDRmean, with area under the curve values of 0.847 and 0.784, respectively. CONCLUSIONS The SDRskewness is a more accurate predictor of thermal increase than the conventional SDRmean. The authors suggest setting the SDRskewness cutoff value to 0.68. SDRskewness may allow for the inclusion of treatable patients with essential tremor who would have been screened out based on the SDRmean exclusion criterion.

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Middle Cerebral Artery-to-Uterine Artery Pulsatility Index Ratio Independently Predicts Adverse Perinatal Outcome in Pregnancies at Term

10.21203/rs.3.rs-51822/v1 ◽

2020 ◽

Author(s):

Sufen Zhou ◽

Hongyan Guo ◽

Heng Liu ◽

Mingqun Li

Keyword(s):

Risk Factors ◽

Logistic Regression ◽

Middle Cerebral Artery ◽

Perinatal Outcome ◽

Pulsatility Index ◽

Uterine Artery ◽

Regression Analyses ◽

Multivariate Logistic Regression ◽

Adverse Perinatal Outcome ◽

Independent Risk Factors

Abstract Background: This study aimed to investigate potential predictors, including cerebroplacental ratio (CPR), middle cerebral artery (MCA)/uterine artery pulsatility index (PI) ratio, for adverse perinatal outcome in pregnancies at term.Methods: This was an observational, prospective study of recruited pregnancies at term. An adverse perinatal outcome was set as the primary observational endpoint. The receiver operating characteristic (ROC) curve was plotted to investigate the predictive and cut-off values of risk factors for adverse perinatal outcome. Independent risk factors (maternal, neonatal, prenatal ultrasound and Doppler variables) for adverse perinatal outcome were evaluated by the univariate and multivariate logistic regression analyses.Results: A total of 392 pregnancies at term were included and 19.4% of them had suffered adverse perinatal outcome. CPR (OR: 0.42, 95%CI: 0.20-0.93, P=0.032) and MCA/uterine artery PI ratio (OR: 0.25, 95%CI: 0.16-0.42, P=0.032) were two independent risk factors for adverse perinatal outcome by univariate and multivariate logistic regression analyses.Conclusions: MCA/uterine artery PI ratio is a good predictor of adverse perinatal outcome in pregnancies at term.

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