In situ split plus portal vein ligation (ISLT) - a salvage procedure following inefficient portal vein embolization to gain adequate future liver remnant volume prior to extended liver resection.

BACKGROUND: Right extended liver resection is frequently required to achieve tumor-free margins. Portal venous embolization (PVE) of the prospective resected hepatic segments for conditioning segments II/III does not always induce adequate hypertrophy in segments II and III (future liver remnant volume (FLRV)) for extended right-resection. Here, we present the technique of in situ split dissection along segments II/III plus portal disruption to segments IV-VIII (ISLT) as a salvage procedure to overcome inadequate gain of FLRV after PVE. METHODS: In eight patients, FLRV was further pre-conditioned following failed PVE prior to hepatectomy (ISLT-group). We compared FLRV changes in the ISLT group with patients receiving extended right hepatectomy following sufficient PVE (PVEres-group). Survival of the ISLT-group was compared to PVEres patients and PVE patients with insufficient FLRV gain or tumor progress who did not receive further surgery (PVEnores-group). RESULTS: Patient characteristics and surgical outcome were comparable in both groups. The mean FLRV-to-body-weight ratio in the ISLT group was smaller than in the PVEres-group pre- and post-PVE. One intraoperative mortality due to a coronary infarction was observed for an ISLT patient. ISLT was successfully completed in the remaining seven ISLT patients. Liver function and 2-year survival of ~ 50% was comparable to patients with extended right hepatectomy after efficient PVE. Patients who received a PVE but who were not subsequently resected (PVEnores) demonstrated no survival beyond 4 months. CONCLUSION: Despite extended embolization of segments I and IV-VIII, ISLT should be considered if hypertrophy was not adequate. Liver function and overall survival after ISLT was comparable to patients with trisectionectomy after efficient PVE.

Development of size-specific institutional diagnostic reference levels for computed tomography protocols in neck imaging.

PURPOSE: To develop size-specific institutional diagnostic reference levels (DRLs) for computed tomography (CT) protocols used in neck CT imaging (cervical spine CT, cervical CT angiography (CTA) and cervical staging CT) and to compare institutional to national DRLs. MATERIALS AND METHODS: Cervical CT examinations (spine, n = 609; CTA, n = 505 and staging CT, n = 184) performed between 01/2016 and 06/2017 were included in this retrospective study. For each region and examination, the volumetric CT dose index (CTDIvol) and dose-length product (DLP) were determined and binned into size bins according to patient water-equivalent diameter (dw). Linear regression analysis was performed to calculate size-specific institutional DRLs for CTDIvol and DLP, applying the 75th percentile as the upper limit for institutional DRLs. The mean institutional CTDIvol and DLP were compared to national DRLs (CTDIvol 20 mGy for cervical spine CT (DLP 300 mGycm) and cervical CTA (DLP 600 mGycm), and CTDIvol 15 mGy for cervical staging CT (DLP 330 mGycm)). RESULTS: The mean CTDIvol and DLP (±standard deviation) were 15.2 ± 4.1 mGy and 181.5 ± 88.3 mGycm for cervical spine CT; 8.1 ± 4.3 mGy and 280.2 ± 164.3 mGycm for cervical CTA; 8.6 ± 1.9 mGy and 162.8 ± 85.0 mGycm for cervical staging CT. For all CT protocols, there was a linear increase in CTDIvol and DLP with increasing dw. For the CTDIvol, size-specific institutional DRLs increased with dw from 14 to 29 mGy for cervical spine CT, from 5 to 17 mGy for cervical CTA and from 8 to 13 mGy for cervical staging CT. For the DLP, size-specific institutional DRLs increased with dw from 130 to 510 mGycm for cervical spine CT, from 140 to 640 mGycm for cervical CTA and from 140 to 320 mGycm for cervical staging CT. Institutional DRLs were lower than national DRLs by 81% and 67% for cervical spine CT (dw = 17.8 cm), 43% and 51% for cervical CTA (dw = 19.5 cm) and 59% and 53% for cervical staging CT (dw = 18.8 cm) for CTDIvol and DLP, respectively. CONCLUSION: Size-specific institutional DRLs were generated for neck CT examinations. The mean institutional CTDIvol and DLP values were well below national DRLs.

Implementation of Institutional Size-Specific Diagnostic Reference Levels for CT Angiography.

RATIONALE AND OBJECTIVES: To generate institutional size-specific diagnostic reference levels (DRLs) for computed tomography angiography (CTA) examinations and assess the potential for dose optimization compared to size-independent DRLs. MATERIALS AND METHODS: CTA examinations of the aorta, the pulmonary arteries and of the pelvis/lower extremity performed between January 2016 and January 2017 were included in our retrospective study. Water equivalent diameter (Dw) was automatically calculated for each patient. The relationship between Dw and computed tomography dose index (CTDIvol) was analyzed and the 75th percentile was chosen as the upper limit for institutional DRLs. Size-specific institutional DRLs were compared to national size-independent DRLs from Germany and the UK. RESULTS: A total of 1344 examinations were included in our study (n = 733 aortic CTA, n = 406 pulmonary CTA, n = 205 pelvic/lower extremity CTA). Mean Dw was 26 ± 9 cm and mean CTDIvol was 7.0 ± 4.6 mGy. For all CTA protocols, there was a linear progression of CTDIvol with increasing Dw with an R²â€¯= 0.95 in aortic CTA, R²â€¯= 0.94 in pulmonary CTA and R²â€¯= 0.93 in pelvic/lower extremity CTA. Median CTDIvol increased by 0.57 mGy per additional cm Dw in aortic CTA, by 1.1 mGy in pulmonary CTA and by 0.31 mGy in pelvic/lower extremity CTA. Institutional DRLs were lower than national DRLs for average size patients (aortic CTA: Dw 28.2 cm, CTDIvol 7.6 mGy; pulmonary CTA, Dw 27.9 cm, CTDIvol 11.8 mGy; pelvic/lower extremity CTA, Dw 20.0 cm, CTDIvol 6.4 mGy). More dose outliers in small patients were detected with size-specific DRLs compared to national size-independent DRLs (56.4% vs 16.2%). CONCLUSION: We implemented institutional size-specific DRLs for CTA examinations which enabled a more precise analysis compared to national sizeindependent DRLs.

Potential of a machine-learning model for dose optimization in CT quality assurance.

OBJECTIVES: To evaluate machine learning (ML) to detect chest CT examinations with dose optimization potential for quality assurance in a retrospective, cross-sectional study. METHODS: Three thousand one hundred ninety-nine CT chest examinations were used for training and testing of the feed-forward, single hidden layer neural network (January 2016-December 2017, 60% male, 62 ± 15 years, 80/20 split). The model was optimized and trained to predict the volumetric computed tomography dose index (CTDIvol) based on scan patient metrics (scanner, study description, protocol, patient age, sex, and water-equivalent diameter (DW)). The root mean-squared error (RMSE) was calculated as performance measurement. One hundred separate, consecutive chest CTs were used for validation (January 2018, 60% male, 63 ± 16 years), independently reviewed by two blinded radiologists with regard to dose optimization, and used to define an optimal cutoff for the model. RESULTS: RMSE was 1.71, 1.45, and 1.52 for the training, test, and validation dataset, respectively. The scanner and DW were the most important features. The radiologists found dose optimization potential in 7/100 of the validation cases. A percentage deviation of 18.3% between predicted and actual CTDIvol was found to be the optimal cutoff: 8/100 cases were flagged as suboptimal by the model (range 18.3-53.2%). All of the cases found by the radiologists were identified. One examination was flagged only by the model. CONCLUSIONS: ML can comprehensively detect CT examinations with dose optimization potential. It may be a helpful tool to simplify CT quality assurance. CT scanner and DW were most important. Final human review remains necessary. A threshold of 18.3% between the predicted and actual CTDIvol seems adequate for CT quality assurance. KEY POINTS: • Machine learning can be integrated into CT quality assurance to improve retrospective analysis of CT dose data. • Machine learning may help to comprehensively detect dose optimization potential in chest CT, but an individual review of the results by an experienced radiologist or radiation physicist is required to exclude false-positive findings.

Tailoring CT Dose to Patient Size: Implementation of the Updated 2017 ACR Size-specific Diagnostic Reference Levels.

RATIONALE AND OBJECTIVES: To use an automatic computed tomography (CT) dose monitoring system to analyze the institutional chest and abdominopelvic CT dose data as regards the updated 2017 American College of Radiology (ACR) diagnostic reference levels (DRLs) based on water-equivalent diameter (Dw) and size-specific dose estimates (SSDE) to detect patient-size subgroups in which CT dose can be optimized. MATERIALS AND METHODS: All chest CT examinations performed between July 2016 and April 2017 with and without contrast material, CT of the pulmonary arteries, and abdominopelvic CT with and without contrast material were included in this retrospective study. Dw and SSDE were automatically calculated for all scans using a previously validated in-house developed Matlab software and stored into our CT dose monitoring system. CT dose data were analyzed as regards the updated ACR DRLs (size groups: 21-25 cm, 25-29 cm, 29-33 cm, 33-37 cm, 37-41 cm). SSDE and volumetric computed tomography dose index (CTDIvol) were used as CT dose parameter. RESULTS: Overall, 30,002 CT examinations were performed in the study period, 3860 of which were included in the analysis (mean age 62.1 ± 16.4 years, Dw 29.0 ± 3.3 cm; n = 577 chest CT without contrast material, n = 628 chest CT with contrast material, n = 346 CT of chest pulmonary, n = 563 abdominopelvic CT without contrast material, n = 1746 abdominopelvic CT with contrast material). Mean SSDE and CTDIvol relative to the updated DRLs were 43.3 ± 26.4 and 45.1 ± 27.9% for noncontrast chest CT, 52.3 ± 23.1 and 52.0 ± 23.1% for contrast-enhanced chest CT, 68.8 ± 29.5 and 70.0 ± 31.0% for CT of pulmonary arteries, 41.9 ± 29.2 and 43.3 ± 31.3% for noncontrast abdominopelvic CT, and 56.8 ± 22.2 and 58.8 ± 24.4% for contrast-enhanced abdominopelvic CT. Lowest dose compared to the DRLs was found for the Dw group of 21-25 cm in noncontrast abdominopelvic CT (SSDE 30.4 ± 21.8%, CTDIvol 30.8 ± 21.4%). Solely the group of patients with a Dw of 37-41 cm undergoing noncontrast abdominopelvic CT exceeded the ACR DRL (SSDE 100.3 ± 59.0%, CTDIvol 107.1 ± 63.5%). CONCLUSIONS: On average, mean SSDE and CTDIvol of our institutional chest and abdominopelvic CT protocols were lower than the updated 2017 ACR DRLs. Size-specific subgroup analysis revealed a wide variability of SSDE and CTDIvol across CT protocols and patient size groups with a transgression of DRLs in noncontrast abdominopelvic CT of large patients (Dw 37-41 cm).

Institutional computed tomography diagnostic reference levels based on water-equivalent diameter and size-specific dose estimates.

Size-specific institutional diagnostic reference levels (DRLs) were generated for chest and abdominopelvic computed tomography (CT) based on size-specific dose estimates (SSDEs) and depending on patients' water-equivalent diameter (Dw). 1690 CT examinations were included in the IRB-approved retrospective study. SSDEs based on the mean water-equivalent diameter of the entire scan volume were calculated automatically. SSDEs were analyzed for different patient sizes and institutional DRLs (iDRLS; 75% percentiles) based on Dw and SSDEs were generated. iDRLs were compared to the national DRLs. Mean volumetric computed tomography dose index (CTDIvol), Dw and SSDEs for all 1690 CT examinations were 7.2 ± 4.0 mGy (0.84-47.9 mGy), 29.0 ± 3.4 cm and 8.5 ± 3.8 mGy (1.2-37.7 mGy), respectively. Overall, the mean SSDEs of all CT examinations were higher than the CTDIvol in chest CT, abdominopelvic CT and upper abdominal CT, respectively (p < 0.001 for all). There was a strong linear correlation between Dw and SSDEs in chest (R2 = 0.66), abdominopelvic (R2 = 0.98) and upper abdominal CT (R2 = 0.96) allowing for the implementation of size-specific institutional DRLs based on SSDEs and patients' Dw. We generated size-specific, Dw-dependent institutional DRLs based on SSDEs, which allow for easier and more comprehensive analyses of CT radiation exposure. Our results indicate that implementation of SSDEs into national DRLs may be beneficial.