BackgroundAfter extended liver resection, a remnant liver that is too small can lead to postresection liver failure. To reduce this risk, preoperative evaluation of the future liver remnant volume (FLRV) is critical. The open-source OsiriX® PAC software system can be downloaded for free and used by nonradiologists to calculate liver volume using a stand-alone Apple computer. The purpose of this study was to assess the accuracy of OsiriX® CT volumetry for predicting liver resection volume and FLVR in patients undergoing partial hepatectomy.MethodsPreoperative contrast-enhanced liver CT scans of patients who underwent partial hepatectomy were analyzed by three observers. Two surgical trainees measured the total liver volume, resection volume, and tumor volume using OsiriX®, and a radiologist measured these volumes using CT scanner-linked Aquarius iNtuition® software. Resection volume was correlated with prospectively determined resection weight, and differences in the measured liver volumes were analyzed. Interobserver variability was assessed using Bland–Altman plots.Results25 patients (M/F ratio: 13/12) with a median age of 61 (range, 34–77) years were included. There were significant correlations between the weight and volume of the resected specimens (Pearson’s correlation coefficient: R2 = 0.95). There were no major differences in total liver volumes, resection volumes, or tumor volumes for observers 1, 2, and 3. Bland–Altman plots showed a small interobserver variability. The mean time to complete liver volumetry for one patient using OsiriX® was 19 ± 3 min.ConclusionsOsiriX® liver volumetry performed by surgeons is an accurate and time-efficient method for predicting resection volume and FLRV.

BackgroundA small remnant liver volume is an important risk factor for posthepatectomy liver failure. ImageJ and OsiriX® are both free, open-source image processing software packages. The aim of the present study was to compare ImageJ and OsiriX® in performing prospective computed tomography (CT) volumetric analysis of the liver on a personal computer (PC) in patients undergoing major liver resection.MethodsPatients scheduled for a right hemihepatectomy were eligible for inclusion. Two surgeons and one surgical trainee measured volumes of total liver, tumor, and future resection specimen prospectively with ImageJ and OsiriX®. A radiologist also measured these volumes with CT scanner-linked Aquarius iNtuition® software. Resection volumes were compared with the actual weights of the liver specimens removed during surgery, and differences between the measured liver volumes were analyzed.ResultsA total of 15 patients (8 men, 7 women) with a median age of 63 years (48–79 years) were included. There was a significant correlation between the measured weights of resection specimens and the volumes calculated prospectively with ImageJ and OsiriX® (r = 0.89; r = 0.83, respectively). There was also a significant correlation between the volumes measured with radiological software iNtuition® and the volumes measured with ImageJ and OsiriX® (r = 0.93; r = 0.95, respectively).ConclusionsThere were no major differences in total liver volumes, resection volumes, or tumour volumes for these three software packages. Prospective hepatic CT volumetry with ImageJ or OsiriX® is reliable and can be accurately used on a PC by nonradiologists. ImageJ and OsiriX® yield results comparable to the radiological software iNtuition®.

Contrast-enhanced mammography (CEM) has shown to be superior to full-field digital mammography (FFDM), but current results are dominated by studies performed on systems by one vendor. Information on diagnostic accuracy of other CEM systems is limited. Therefore, we aimed to evaluate the diagnostic performance of CEM on an alternative vendor’s system. We included all patients who underwent CEM in one hospital in 2019, except those with missing data or in whom CEM was used as response monitoring tool. Three experienced breast radiologists scored the low-energy images using the BI-RADS classification. Next, the complete CEM exams were scored similarly. Histopathological results or a minimum of one year follow-up were used as reference standard. Diagnostic performance and AUC were calculated and compared between low-energy images and the complete CEM examination, for all readers independently as well as combined. Breast cancer was diagnosed in 23.0% of the patients (35/152). Compared to low-energy images, overall CEM sensitivity increased from 74.3 to 87.6% (p < 0.0001), specificity from 87.8 to 94.6% (p = 0.0146). AUC increased from 0.872 to 0.957 (p = 0.0001). Performing CEM on the system tested, showed that, similar to earlier studies mainly performed on another vendor’s systems, both sensitivity and specificity improved when compared to FFDM.