Robustness assessment of an automated AI-based white blood cell morphometric analysis system using different smear preparation methods.

INTRODUCTION: Numerous AI-based systems are being developed to evaluate peripheral blood (PB) smears, but the feasibility of these systems on different smear preparation methods has not been fully understood. In this study, we assessed the impact of different smear preparation methods on the robustness of the deep learning system (DLS). METHODS: We collected 193 PB samples from patients, preparing a pair of smears for each sample using two systems: (1) SP50 smears, prepared by the DLS recommended fully automated slide preparation with double fan drying and staining (May-Grunwald Giemsa, M-G) system using SP50 (Sysmex) and (2) SP1000i smears, prepared by automated smear preparation with single fan drying by SP1000i (Sysmex) and manually stained with M-G. Digital images of PB cells were captured using DI-60 (Sysmex), and the DLS performed cell classification. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were used to evaluate the performance of the DLS. RESULTS: The specificity and NPV for all cell types were 97.4%-100% in both smear sets. The average sensitivity and PPV were 88.9% and 90.1% on SP50 smears, and 87.0% and 83.2% on SP1000i smears, respectively. The lower performance on SP1000i smears was attributed to the intra-lineage misclassification of neutrophil precursors and inter-lineage misclassification of lymphocytes. CONCLUSION: The DLS demonstrated consistent performance in specificity and NPV for smears prepared by a system different from the recommended method. Our results suggest that applying an automated smear preparation system optimized for the DLS system may be important.

Assessment of drainage vein of focal nodular hyperplasia using contrast-enhanced ultrasound.

PURPOSE: Identification of drainage vessels is useful for differential diagnosis of hepatic tumors. Direct drainage to the hepatic vein has been reported to occur in focal nodular hyperplasia (FNH), but studies evaluating the drainage veins of FNH are limited. We aimed to investigate the detection rate of the FNH drainage vein and the factors related to visualization of the drainage vein on contrast-enhanced ultrasound (CEUS). METHODS: Fifty consecutive patients with 50 FNH lesions were retrospectively evaluated in this study. We calculated and compared the detection rate of the FNH drainage vein on CEUS, contrast-enhanced magnetic resonance imaging (CEMRI), and contrast-enhanced computed tomography (CECT), and identified the factors correlated with visualization of the FNH drainage vein on CEUS by using multivariate logistic regression analyses. RESULTS: Visualization of the drainage vein was confirmed in 31 of 50 lesions (62%) using CEUS, three of 44 lesions (6.8%) using CEMRI, and one of 18 lesions (5.6%) using CECT. The detection rate of the FNH drainage vein on CEUS was significantly higher than that on CEMRI and CECT (p < 0.001). Multivariate analysis identified lesion size (≥ 25 mm) and detection of the spoke-wheel pattern on Doppler US as independent factors for drainage vein detection in FNH. CONCLUSION: Our study showed that rapid FNH drainage to the hepatic vein was observed at a relatively high rate on CEUS, suggesting that CEUS focusing on detection of drainage veins is important for diagnosing FNH.

Evaluation of cell count and classification capabilities in body fluids using a fully automated Sysmex XN equipped with high-sensitive Analysis (hsA) mode and DI-60 hematology analyzer system.

The XN series automated hematology analyzer has been equipped with a body fluid (BF) mode to count and differentiate leukocytes in BF samples including cerebrospinal fluid (CSF). However, its diagnostic accuracy is not reliable for CSF samples with low cell concentration at the border between normal and pathologic level. To overcome this limitation, a new flow cytometry-based technology, termed "high sensitive analysis (hsA) mode," has been developed. In addition, the XN series analyzer has been equipped with the automated digital cell imaging analyzer DI-60 to classify cell morphology including normal leukocytes differential and abnormal malignant cells detection. Using various BF samples, we evaluated the performance of the XN-hsA mode and DI-60 compared to manual microscopic examination. The reproducibility of the XN-hsA mode showed good results in samples with low cell densities (coefficient of variation; % CV: 7.8% for 6 cells/µL). The linearity of the XN-hsA mode was established up to 938 cells/µL. The cell number obtained using the XN-hsA mode correlated highly with the corresponding microscopic examination. Good correlation was also observed between the DI-60 analyses and manual microscopic classification for all leukocyte types, except monocytes. In conclusion, the combined use of cell counting with the XN-hsA mode and automated morphological analyses using the DI-60 mode is potentially useful for the automated analysis of BF cells.

Novel flowcytometry-based approach of malignant cell detection in body fluids using an automated hematology analyzer.

Morphological microscopic examinations of nucleated cells in body fluid (BF) samples are performed to screen malignancy. However, the morphological differentiation is time-consuming and labor-intensive. This study aimed to develop a new flowcytometry-based gating analysis mode "XN-BF gating algorithm" to detect malignant cells using an automated hematology analyzer, Sysmex XN-1000. XN-BF mode was equipped with WDF white blood cell (WBC) differential channel. We added two algorithms to the WDF channel: Rule 1 detects larger and clumped cell signals compared to the leukocytes, targeting the clustered malignant cells; Rule 2 detects middle sized mononuclear cells containing less granules than neutrophils with similar fluorescence signal to monocytes, targeting hematological malignant cells and solid tumor cells. BF samples that meet, at least, one rule were detected as malignant. To evaluate this novel gating algorithm, 92 various BF samples were collected. Manual microscopic differentiation with the May-Grunwald Giemsa stain and WBC count with hemocytometer were also performed. The performance of these three methods were evaluated by comparing with the cytological diagnosis. The XN-BF gating algorithm achieved sensitivity of 63.0% and specificity of 87.8% with 68.0% for positive predictive value and 85.1% for negative predictive value in detecting malignant-cell positive samples. Manual microscopic WBC differentiation and WBC count demonstrated 70.4% and 66.7% of sensitivities, and 96.9% and 92.3% of specificities, respectively. The XN-BF gating algorithm can be a feasible tool in hematology laboratories for prompt screening of malignant cells in various BF samples.

[Comparison of Cormack/Lehane classification grades decided by novice residents and those by board certified anesthesiologists].

BACKGROUND: Tracheal intubation training is one of the most important ones in anesthesia training. But it is difficult to evaluate from the outside whether the laryngeal view obtained with the laryngoscope is appropriate or not. METHODS: We chose a total of 389 cases of tracheal intubation performed by 12 novice residents in 2 months, and compared the grades of Cormack/Lehane classification of the same patients decided by novice residents and board certified anesthesiologists. RESULTS: During the 2-month period, the average number of tracheal intubation performed by a novice resident was 32 +/- 12 cases (mean +/- SD). A significant difference was found between Cormack/Lehane classification (P<0.05) decided by novice residents and those by board certified anesthesiologists. When the number of intubation performed by a novice resident was fewer than 30, the grade was grade II > III > I > IV. On the contrary, when it was more than 30, the ratio of grades I and II (appropriate laryngeal view) increased and the distribution changed to grade II > I >III > IV. CONCLUSIONS: We considered it useful in the tracheal intubation training that certified anesthesiologists evaluate patients' Cormack/Lehane classification grades before novice residents do, because we can obtain necessary information on laryngeal view and intubation difficulty in advance.

[Study of analgestic efficacy of ropivacaine-fentanyl patient-controlled epidural analgesia after upper abdominal gynecological surgery].

BACKGROUND: Most of the patients who undergo radical or subradical hysterectomy with paraaortic lymphadenectomy suffer from postoperative pain for upper abdominal incision. They also complain of postoperative nausea and vomiting (PONV) frequently, which are increased by opioids. METHODS: Reducing total fentanyl dose to 0.6 mg, frequency of moving pain complaints increased gradually. Therefore, we introduced patient-controlled epidural analgesia (PCEA) for suppressing pain on moving. We investigated analgestic efficacy of 0.2% ropivacaine-fentanyl PCEA in twelve patients undergoing upper abdominal gynecological surgery. Postoperative analgesic effects were evaluated by visual analogue scale (VAS) at rest and on moving, times of bolus infusion, side effects, and degrees of satisfication by patient's self-assessments. Continuous epidural infusion of 0.6 mg fentanyl in 288 ml 0.2% ropivacaine was started at a rate of 4 ml x hr(-1) with a bolus dose of 2 ml. RESULTS: VAS was maintained below 20 mm at rest but was elevated to the maximum of 45 mm on moving with few bolus requests. Ninty-two percents of the patients answered satisfied but fifty percents of them had PONV. CONCLUSIONS: We conclude that ropivacaine-fentanyl PCEA is effective after upper abdominal gynecological surgery, and we can decrease the dose of fentanyl by explaining PCEA system more effectively to the patients for suppressing the pain on moving and PONV.