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Folly Beach Library
9 a.m. - 5:30 p.m.
Phone: (843) 588-2001
Edgar Allan Poe/Sullivan's Island Library
Closed for renovations
Phone: (843) 883-3914
West Ashley Library
9 a.m. – 7 p.m.
Phone: (843) 766-6635
Wando Mount Pleasant Library
9 a.m. – 8 p.m.
Phone: (843) 805-6888
Village Library
9 a.m. - 6 p.m.
Phone: (843) 884-9741
St. Paul's/Hollywood Library
9 a.m. – 8 p.m.
Phone: (843) 889-3300
Otranto Road Library
9 a.m. – 8 p.m.
Phone: (843) 572-4094
Mt. Pleasant Library
9 a.m. – 8 p.m.
Phone: (843) 849-6161
McClellanville Library
9 a.m. - 6 p.m.
Phone: (843) 887-3699
Keith Summey North Charleston Library
9 a.m. – 8 p.m.
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John's Island Library
9 a.m. – 8 p.m.
Phone: (843) 559-1945
Hurd/St. Andrews Library
9 a.m. – 8 p.m.
Phone: (843) 766-2546
Miss Jane's Building (Edisto Library Temporary Location)
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Dorchester Road Library
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Phone: (843) 552-6466
John L. Dart Library
9 a.m. – 7 p.m.
Phone: (843) 722-7550
Baxter-Patrick James Island
9 a.m. – 8 p.m.
Phone: (843) 795-6679
Main Library
9 a.m. – 8 p.m.
Phone: (843) 805-6930
Bees Ferry West Ashley Library
9 a.m. – 8 p.m.
Phone: (843) 805-6892
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9 a.m. - 5 p.m.
Phone: (843) 805-6909
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Stepwise algorithm using computed tomography and magnetic resonance imaging for differential diagnosis of fat‐poor angiomyolipoma in small renal masses: A prospective validation study.
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- Author(s): Toide, Masahiro (AUTHOR); Tanaka, Hajime (AUTHOR); Kobayashi, Masaki (AUTHOR); Fujiwara, Motohiro (AUTHOR); Nakamura, Yuki (AUTHOR); Fukuda, Shohei (AUTHOR); Kimura, Koichiro (AUTHOR); Waseda, Yuma (AUTHOR); Yoshida, Soichiro (AUTHOR); Tateishi, Ukihide (AUTHOR); Fujii, Yasuhisa (AUTHOR)
- Source:
International Journal of Urology. Jul2024, Vol. 31 Issue 7, p778-784. 7p. - Source:
- Additional Information
- Subject Terms:
- Abstract: Objectives: To validate the diagnostic accuracy of a stepwise algorithm to differentiate fat‐poor angiomyolipoma (fp‐AML) from renal cancer in small renal masses (SRMs). Methods: We prospectively enrolled 223 patients with solid renal masses <4 cm and no visible fat on unenhanced computed tomography (CT). Patients were assessed using an algorithm that utilized the dynamic CT and MRI findings in a stepwise manner. The diagnostic accuracy of the algorithm was evaluated in patients whose histology was confirmed through surgery or biopsy. The clinical course of the patients was further analyzed. Results: The algorithm classified 151 (68%)/42 (19%)/30 (13%) patients into low/intermediate/high AML probability groups, respectively. Pathological diagnosis was made for 183 patients, including 10 (5.5%) with fp‐AML. Of these, 135 (74%)/36 (20%)/12 (6.6%) were classified into the low/intermediate/high AML probability groups, and each group included 1 (0.7%)/3 (8.3%)/6 (50%) fp‐AMLs, respectively, leading to the area under the curve for predicting AML of 0.889. Surgery was commonly opted in the low and intermediate AML probability groups (84% and 64%, respectively) for initial management, while surveillance was selected in the high AML probability group (63%). During the 56‐month follow‐up, 36 (82%) of 44 patients initially surveyed, including 13 of 18 (72%), 6 of 7 (86%), and 17 of 19 (89%) in the low/intermediate/high AML probability groups, respectively, continued surveillance without any progression. Conclusions: This study confirmed the high diagnostic accuracy for differentiating fp‐AMLs. These findings may help in the management of patients with SRMs. [ABSTRACT FROM AUTHOR]
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