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DOI 10.3348/kjr.2018.0555

Медицинская библиотека · Korean journal of radiology · 2019

Learning Curve of C-Arm Cone-beam Computed Tomography Virtual Navigation-Guided Percutaneous Transthoracic Needle Biopsy.

Ahn Su Yeon, Park Chang Min, Yoon Soon Ho, Kim Hyungjin, Goo Jin Mo

СтатьяПоддержка исследования: вне правительства СШАПеревод пока не подготовлен

Аннотация

OBJECTIVE

To evaluate the learning curve for C-arm cone-beam computed tomography (CBCT) virtual navigation-guided percutaneous transthoracic needle biopsy (PTNB) and to determine the amount of experience needed to develop appropriate skills for this procedure using cumulative summation (CUSUM).

MATERIALS AND

METHODS

We retrospectively reviewed 2042 CBCT virtual navigation-guided PTNBs performed by 7 novice operators between March 2011 and December 2014. Learning curves for CBCT virtual navigation-guided PTNB with respect to its diagnostic performance and the occurrence of biopsy-related pneumothorax were analyzed using standard and risk-adjusted CUSUM (RA-CUSUM). Acceptable failure rates were determined as 0.06 for diagnostic failure and 0.25 for PTNB-related pneumothorax.

RESULTS

Standard CUSUM indicated that 6 of the 7 operators achieved an acceptable diagnostic failure rate after a median of 105 PTNB procedures (95% confidence interval [CI], 14-240), and 6 of the operators achieved acceptable pneumothorax occurrence rate after a median of 79 PTNB procedures (95% CI, 27-155). RA-CUSUM showed that 93 (95% CI, 39-142) and 80 (95% CI, 38-127) PTNB procedures were required to achieve acceptable diagnostic performance and pneumothorax occurrence, respectively.

CONCLUSION

The novice operators' skills in performing CBCT virtual navigation-guided PTNBs improved with increasing experience over a wide range of learning periods.

Для цитирования: Ahn Su Yeon, Park Chang Min, Yoon Soon Ho, Kim Hyungjin, Goo Jin Mo. Learning Curve of C-Arm Cone-beam Computed Tomography Virtual Navigation-Guided Percutaneous Transthoracic Needle Biopsy.. Korean journal of radiology. 2019. DOI: 10.3348/kjr.2018.0555.

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