[The efficacy and safety of laparoscopic radical gastrectomy after neoadjuvant chemotherapy combined with immunotherapy and targeted therapy]

Objectives: To explore the efficacy and safety of laparoscopic radical gastrectomy after neoadjuvant chemotherapy combined with immunotherapy and targeted therapy in patients with gastric cancer. Methods: A retrospective analysis of clinical and pathological data of 20 patients with locally advanced gastric cancer (clinical TNM stage T3-4aN+M0) admitted to the Cancer Hospital, Chinese Academy of Medical Sciences from July 2021 to July 2023. All patients received 3 cycles of SOX (Oxaliplatin+S-1) regimen combined with immunotherapy (Trastuzumab) and targeted therapy (Apatinib) as neoadjuvant treatment followed by laparoscopic radical gastrectomy for gastric cancer. Surgical outcomes, postoperative pathological response, and postoperative recovery were observed. Quantitative data, except for age and operation time, were expressed using Median (range). Results: Among the 20 patients, there were 18 males and 2 females, aged 41 to 73 years [(60.6±9.7) years]. All 20 patients underwent laparoscopic surgical treatment after neoadjuvant therapy, with one patient undergoing laparoscopic conversion to open total gastrectomy with partial transverse colon resection due to tumor invasion into the transverse mesocolon. Eight patients underwent totally laparoscopic radical gastrectomy, all with Billroth Ⅱ+Braun anastomosis at the distal stomach. Eleven patients underwent laparoscopic-assisted radical gastrectomy, among which total gastrectomy with Roux-en-Y anastomosis was performed in ten cases, and proximal gastrectomy with esophagogastrostomy overlap anastomosis was performed in one case. The mean operation time for the 20 patients was (165.0±34.1) minutes; intraoperative blood loss was 80 (20-100) ml; and the number of lymph nodes retrieved was 68 (21-89). Postoperative pathological TNM staging revealed stage T0N0M0 in six cases, stage Ⅰ in two cases, stage Ⅱ in three cases, and stage Ⅲ in nine cases. Six patients (30.0%) achieved pathological complete response, and nine patients (45.0%) achieved significant pathological response. The median postoperative time to flatus was 4 (1-5) days; oral intake resumed after 3 (2-5) days; and the median length of hospital stay was 13 (6-19) days. One patient developed colonic anastomotic leakage with intra-abdominal infection, and one patient developed duodenal stump leakage with intra-abdominal infection, both classified as Clavien-Dindo grade 3A complications, and improved after treatment and discharged. One patient developed gastric paresis, and two patients developed pleural effusion, classified as Clavien-Dindo grade 2 complications, and improved after treatment and discharged. There were no deaths within 30 days after discharge. Conclusions: Laparoscopic radical gastrectomy for gastric cancer after neoadjuvant treatment with the SOX regimen combined with immunotherapy and targeted therapy is safe and feasible, with satisfactory short-term efficacy. However, there is an increase in overall surgical risk and difficulty, and it is recommended to be performed in experienced gastric cancer centers.

US-based Sequential Algorithm Integrating an AI Model for Advanced Liver Fibrosis Screening

Background Noninvasive tests can be used to screen patients with chronic liver disease for advanced liver fibrosis; however, the use of single tests may not be adequate. Purpose To construct sequential clinical algorithms that include a US deep learning (DL) model and compare their ability to predict advanced liver fibrosis with that of other noninvasive tests. Materials and Methods This retrospective study included adult patients with a history of chronic liver disease or unexplained abnormal liver function test results who underwent B-mode US of the liver between January 2014 and September 2022 at three health care facilities. A US-based DL network (FIB-Net) was trained on US images to predict whether the shear-wave elastography (SWE) value was 8.7 kPa or higher, indicative of advanced fibrosis. In the internal and external test sets, a two-step algorithm (Two-step#1) using the Fibrosis-4 Index (FIB-4) followed by FIB-Net and a three-step algorithm (Three-step#1) using FIB-4 followed by FIB-Net and SWE were used to simulate screening scenarios where liver stiffness measurements were not or were available, respectively. Measures of diagnostic accuracy were calculated using liver biopsy as the reference standard and compared between FIB-4, SWE, FIB-Net, and European Association for the Study of the Liver guidelines (ie, FIB-4 followed by SWE), along with sequential algorithms. Results The training, validation, and test data sets included 3067 (median age, 42 years [IQR, 33-53 years]; 2083 male), 1599 (median age, 41 years [IQR, 33-51 years]; 1124 male), and 1228 (median age, 44 years [IQR, 33-55 years]; 741 male) patients, respectively. FIB-Net obtained a noninferior specificity with a margin of 5% (P < .001) compared with SWE (80% vs 82%). The Two-step#1 algorithm showed higher specificity and positive predictive value (PPV) than FIB-4 (specificity, 79% vs 57%; PPV, 44% vs 32%) while reducing unnecessary referrals by 42%. The Three-step#1 algorithm had higher specificity and PPV compared with European Association for the Study of the Liver guidelines (specificity, 94% vs 88%; PPV, 73% vs 64%) while reducing unnecessary referrals by 35%. Conclusion A sequential algorithm combining FIB-4 and a US DL model showed higher diagnostic accuracy and improved referral management for all-cause advanced liver fibrosis compared with FIB-4 or the DL model alone. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Ghosh in this issue.

[Design of an improved percutaneous transhepatic cholangio drainage tube based on MRCP imaging data]

Objective: Quantified MRCP imaging data was used as a reference for design and preparation of a modified percutaneous transhepatic cholangio drainage (PTCD) tube. Methods: 3.0 T upper abdominal MR and MRCP imaging data of 2 300 patients treated from July 2015 to July 2020 at the Department of Radiology of the Affiliated Cancer Hospital of Zhengzhou University were screened and a total of 381 patients diagnosed with biliary duct structures were identified. Causative etiologies among these patients included pancreatic adenocarcinoma (pancreatic head), cholangiocarcinoma, ampullary carcinoma, as well as intrahepatic and/or extrahepatic bile duct dilation. An improved PTCD tube was designed based on MRCP quantification of left and right hepatic and common hepatic duct length. Results: In the setting of biliary obstruction caused by malignancy, the distance of the left hepatic duct from its origin to the point of left and right hepatic duct confluence was 15.9±3.8 mm, while the distance of the right hepatic duct from its origin to the point of left and right hepatic duct confluence was 12.4±3.2 mm; the length of the bile duct from its origin to the point of left and right hepatic duct confluence was 34.0±8.1 mm. The improved PTCD tube design incorporated an altered length of the drainage orifice. Conclusion: MRCP imaging of the biliary tract is effective for measuring biliary tract length in the setting of pathological dilation. Based on our biliary tract measurements, a modified PTCD tube was designed to more effectively meet drainage requirements and manage biliary obstruction caused by Bismuth-Corlette type Ⅱ and Ⅲ malignancies.

Collaborative Enhancement of Consistency and Accuracy in US Diagnosis of Thyroid Nodules Using Large Language Models

Background Large language models (LLMs) hold substantial promise for medical imaging interpretation. However, there is a lack of studies on their feasibility in handling reasoning questions associated with medical diagnosis. Purpose To investigate the viability of leveraging three publicly available LLMs to enhance consistency and diagnostic accuracy in medical imaging based on standardized reporting, with pathology as the reference standard. Materials and Methods US images of thyroid nodules with pathologic results were retrospectively collected from a tertiary referral hospital between July 2022 and December 2022 and used to evaluate malignancy diagnoses generated by three LLMs-OpenAI's ChatGPT 3.5, ChatGPT 4.0, and Google's Bard. Inter- and intra-LLM agreement of diagnosis were evaluated. Then, diagnostic performance, including accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC), was evaluated and compared for the LLMs and three interactive approaches: human reader combined with LLMs, image-to-text model combined with LLMs, and an end-to-end convolutional neural network model. Results A total of 1161 US images of thyroid nodules (498 benign, 663 malignant) from 725 patients (mean age, 42.2 years ± 14.1 [SD]; 516 women) were evaluated. ChatGPT 4.0 and Bard displayed substantial to almost perfect intra-LLM agreement (κ range, 0.65-0.86 [95% CI: 0.64, 0.86]), while ChatGPT 3.5 showed fair to substantial agreement (κ range, 0.36-0.68 [95% CI: 0.36, 0.68]). ChatGPT 4.0 had an accuracy of 78%-86% (95% CI: 76%, 88%) and sensitivity of 86%-95% (95% CI: 83%, 96%), compared with 74%-86% (95% CI: 71%, 88%) and 74%-91% (95% CI: 71%, 93%), respectively, for Bard. Moreover, with ChatGPT 4.0, the image-to-text-LLM strategy exhibited an AUC (0.83 [95% CI: 0.80, 0.85]) and accuracy (84% [95% CI: 82%, 86%]) comparable to those of the human-LLM interaction strategy with two senior readers and one junior reader and exceeding those of the human-LLM interaction strategy with one junior reader. Conclusion LLMs, particularly integrated with image-to-text approaches, show potential in enhancing diagnostic medical imaging. ChatGPT 4.0 was optimal for consistency and diagnostic accuracy when compared with Bard and ChatGPT 3.5. © RSNA, 2024 Supplemental material is available for this article.

ADMNet: Adaptive-Weighting Dual Mapping for Online Tracking With Respiratory Motion Estimation in Contrast-Enhanced Ultrasound

Lesion localization and tracking are critical for accurate, automated medical imaging analysis. Contrast-enhanced ultrasound (CEUS) significantly enriches traditional B-mode ultrasound with contrast agents to provide high-resolution, real-time images of blood flow in tissues and organs. However, many trackers, designed primarily for natural RGB or B-mode ultrasound images, underutilize the extensive data from dual-screen enhanced images and fail to account for respiratory motion, thus facing challenges in achieving accurate target tracking. To address the existing challenges, we propose an adaptive-weighted dual mapping (ADMNet), an online tracking framework tailored for CEUS. Firstly, we introduced a novel Multimodal Atrous Attention Fusion (MAAF) module, innovatively designed to adapt the weightage between B-mode and enhanced images in dual-screen CEUS, reflecting the clinician's dynamic focus shifts between screens. Secondly, we proposed a Respiratory Motion Compensation (RMC) module to correct motion trajectory interferences due to respiratory motion, effectively leveraging temporal information. We utilized two newly established CEUS datasets, totaling 35,082 frames, to benchmark the ADMNet against various advanced B-mode ultrasound trackers. Our extensive experiments revealed that ADMNet achieves new state-of-the-art performance in CEUS tracking. Ablation studies and visualizations further underline the effectiveness of MAAF and RMC modules, demonstrating the promising potential of ADMNet in clinical CEUS tracing, thus providing novel research avenues in this field.

Integration of Artificial Intelligence Decision Aids to Reduce Workload and Enhance Efficiency in Thyroid Nodule Management

Importance

To optimize the integration of artificial intelligence (AI) decision aids and reduce workload in thyroid nodule management, it is critical to incorporate personalized AI into the decision-making processes of radiologists with varying levels of expertise.

Objective

To develop an optimized integration of AI decision aids for reducing radiologists' workload while maintaining diagnostic performance compared with traditional AI-assisted strategy.

Design, Setting, and Participants

In this diagnostic study, a retrospective set of 1754 ultrasonographic images of 1048 patients with 1754 thyroid nodules from July 1, 2018, to July 31, 2019, was used to build an optimized strategy based on how 16 junior and senior radiologists incorporated AI-assisted diagnosis results with different image features. In the prospective set of this diagnostic study, 300 ultrasonographic images of 268 patients with 300 thyroid nodules from May 1 to December 31, 2021, were used to compare the optimized strategy with the traditional all-AI strategy in terms of diagnostic performance and workload reduction. Data analyses were completed in September 2022.

Main Outcomes and Measures

The retrospective set of images was used to develop an optimized integration of AI decision aids for junior and senior radiologists based on the selection of AI-assisted significant or nonsignificant features. In the prospective set of images, the diagnostic performance, time-based cost, and assisted diagnosis were compared between the optimized strategy and the traditional all-AI strategy.

Results

The retrospective set included 1754 ultrasonographic images from 1048 patients (mean [SD] age, 42.1 [13.2] years; 749 women [71.5%]) with 1754 thyroid nodules (mean [SD] size, 16.4 [10.6] mm); 748 nodules (42.6%) were benign, and 1006 (57.4%) were malignant. The prospective set included 300 ultrasonographic images from 268 patients (mean [SD] age, 41.7 [14.1] years; 194 women [72.4%]) with 300 thyroid nodules (mean [SD] size, 17.2 [6.8] mm); 125 nodules (41.7%) were benign, and 175 (58.3%) were malignant. For junior radiologists, the ultrasonographic features that were not improved by AI assistance included cystic or almost completely cystic nodules, anechoic nodules, spongiform nodules, and nodules smaller than 5 mm, whereas for senior radiologists the features that were not improved by AI assistance were cystic or almost completely cystic nodules, anechoic nodules, spongiform nodules, very hypoechoic nodules, nodules taller than wide, lobulated or irregular nodules, and extrathyroidal extension. Compared with the traditional all-AI strategy, the optimized strategy was associated with increased mean task completion times for junior radiologists (reader 11, from 15.2 seconds [95% CI, 13.2-17.2 seconds] to 19.4 seconds [95% CI, 15.6-23.3 seconds]; reader 12, from 12.7 seconds [95% CI, 11.4-13.9 seconds] to 15.6 seconds [95% CI, 13.6-17.7 seconds]), but shorter times for senior radiologists (reader 14, from 19.4 seconds [95% CI, 18.1-20.7 seconds] to 16.8 seconds [95% CI, 15.3-18.3 seconds]; reader 16, from 12.5 seconds [95% CI, 12.1-12.9 seconds] to 10.0 seconds [95% CI, 9.5-10.5 seconds]). There was no significant difference in sensitivity (range, 91%-100%) or specificity (range, 94%-98%) between the 2 strategies for readers 11 to 16.

Conclusions and Relevance

This diagnostic study suggests that an optimized AI strategy in thyroid nodule management may reduce diagnostic time-based costs without sacrificing diagnostic accuracy for senior radiologists, while the traditional all-AI strategy may still be more beneficial for junior radiologists.

Shear-wave elastography combined with contrast-enhanced ultrasound algorithm for noninvasive characterization of focal liver lesions

PURPOSE

To establish shear-wave elastography (SWE) combined with contrast-enhanced ultrasound (CEUS) algorithm (SCCA) and improve the diagnostic performance in differentiating focal liver lesions (FLLs).

MATERIAL AND METHODS

We retrospectively selected patients with FLLs between January 2018 and December 2019 at the First Affiliated Hospital of Sun Yat-sen University. Histopathology was used as a standard criterion except for hemangiomas and focal nodular hyperplasia. CEUS with SonoVue (Bracco Imaging) and SCCA combining CEUS and maximum value of elastography with < 20 kPa and > 90 kPa thresholds were used for the diagnosis of FLLs. The diagnostic performance of CEUS and SCCA was calculated and compared.

RESULTS

A total of 171 FLLs were included, with 124 malignant FLLs and 47 benign FLLs. The area under curve (AUC), sensitivity, and specificity in detecting malignant FLLs were 0.83, 91.94%, and 74.47% for CEUS, respectively, and 0.89, 91.94%, and 85.11% for SCCA, respectively. The AUC of SCCA was significantly higher than that of CEUS (P = 0.019). Decision curves indicated that SCCA provided greater clinical benefits. The SCCA provided significantly improved prediction of clinical outcomes, with a net reclassification improvement index of 10.64% (P = 0.018) and integrated discrimination improvement of 0.106 (P = 0.019). For subgroup analysis, we divided the FLLs into a chronic-liver-disease group (n = 88 FLLs) and a normal-liver group (n = 83 FLLs) according to the liver background. In the chronic-liver-disease group, there were no differences between the CEUS-based and SCCA diagnoses. In the normal-liver group, the AUC of SCCA and CEUS in the characterization of FLLs were 0.89 and 0.83, respectively (P = 0.018).

CONCLUSION

SCCA is a feasible tool for differentiating FLLs in patients with normal liver backgrounds. Further investigations are necessary to validate the universality of this algorithm.

Performance and comparison of artificial intelligence and human experts in the detection and classification of colonic polyps

OBJECTIVE

The main aim of this study was to analyze the performance of different artificial intelligence (AI) models in endoscopic colonic polyp detection and classification and compare them with doctors with different experience.

METHODS

We searched the studies on Colonoscopy, Colonic Polyps, Artificial Intelligence, Machine Learning, and Deep Learning published before May 2020 in PubMed, EMBASE, Cochrane, and the citation index of the conference proceedings. The quality of studies was assessed using the QUADAS-2 table of diagnostic test quality evaluation criteria. The random-effects model was calculated using Meta-DISC 1.4 and RevMan 5.3.

RESULTS

A total of 16 studies were included for meta-analysis. Only one study (1/16) presented externally validated results. The area under the curve (AUC) of AI group, expert group and non-expert group for detection and classification of colonic polyps were 0.940, 0.918, and 0.871, respectively. AI group had slightly lower pooled specificity than the expert group (79% vs. 86%, P < 0.05), but the pooled sensitivity was higher than the expert group (88% vs. 80%, P < 0.05). While the non-experts had less pooled specificity in polyp recognition than the experts (81% vs. 86%, P < 0.05), and higher pooled sensitivity than the experts (85% vs. 80%, P < 0.05).

CONCLUSION

The performance of AI in polyp detection and classification is similar to that of human experts, with high sensitivity and moderate specificity. Different tasks may have an impact on the performance of deep learning models and human experts, especially in terms of sensitivity and specificity.

Circulating tumour cell counts and ultrasomics signature-based nomogram for preoperative prediction of early recurrence of hepatocellular carcinoma after radical treatment

METHODS

Between December 2017 and December 2018, 153 HCC patients (134 males and 19 females; mean age, 56.0 ± 10.2 years; range, 28-78 years) treated with radical therapy were enrolled in our retrospective study and were divided into a training cohort (n = 107) and a validation cohort (n = 46). All patients underwent preoperative CTC tests and CEUS examinations before treatment. The ultrasomics signature was extracted and built from CEUS images. Univariate and multivariate logistic regression analyses were used to identify the significant variables related to ER, which were then combined to build a predictive nomogram. The performance of the nomogram was evaluated by its discrimination, calibration and clinical utility. The predictive model was further evaluated in the internal validation cohort.

RESULTS

HBV DNA, serum AFP level, CTC status, tumour size and ultrasomics score were identified as independent predictors associated with ER (all p < 0.05). Multivariable logistic regression analysis showed that the CTC status (OR = 7.02 [95% CI, 2.07 to 28.38], p = 0.003) and ultrasomics score (OR = 148.65 [95% CI, 25.49 to 1741.72], p < 0.001) were independent risk factors for ER. The nomogram based on ultrasomics score, CTC status, serum AFP level and tumour size exhibited C-indexes of 0.933 (95% CI, 0.878 to 0.988) and 0.910 (95% CI, 0.765 to 1.055) in the training and validation cohorts, respectively, fitting well in calibration curves. Decision curve analysis further confirmed the clinical usefulness of the nomogram.

CONCLUSION

The nomogram incorporating CTC, ultrasomics features and independent clinical risk factors achieved satisfactory preoperative prediction of ER in HCC patients after radical treatment.

ADVANCES IN KNOWLEDGE

1. CTC status and ultrasomics score were identified as independent predictors associated with ER of HCC after radical treatment. 2. The nomogram constructed by ultrasomics score generated by 17 ultrasomics features, combined with CTCs and independent clinical risk factors such as AFP and tumour size. 3. The nomogram exhibited satisfactory discriminative power, and could be clinically useful in the preoperative prediction of ER after radical treatment in HCC patients.

Contrast-Enhanced Ultrasound-Based Nomogram: A Potential Predictor of Individually Postoperative Early Recurrence for Patients With Combined Hepatocellular-Cholangiocarcinoma

PURPOSES

To evaluate the postsurgical prognostic implication of contrast-enhanced ultrasound (CEUS) for combined hepatocellular-cholangiocarcinoma (CHC). To build a CEUS-based early recurrence prediction classifier for CHC, in comparison with tumor-node-metastasis (TNM) staging.

METHODS

The CEUS features and clinicopathological findings of each case were analyzed, and the Liver Imaging Reporting and Data System categories were assigned. The recurrence-free survival associated factors were evaluated by Cox proportional hazard model. Incorporating the independent factors, nomograms were built to estimate the possibilities of 3-month, 6-month, and 1-year recurrence and whose prognostic value was determined by time-dependent receiver operating characteristics, calibration curves, and hazard layering efficiency validation, comparing with TNM staging system.

RESULTS

In the multivariable analysis, the levels of carbohydrate antigen 19-9, prothrombin time and total bilirubin, and tumor shape, the Liver Imaging Reporting and Data System category were independent factors for recurrence-free survival. The LR-M category showed longer recurrence-free survival than did the LR-4/5 category. The 3-month, 6-month, and 1-year area under the curves of the CEUS-clinical nomogram, clinical nomogram, and TNM staging system were 0.518, 0.552, and 0.843 versus 0.354, 0.240, and 0.624 (P = .048, .049, and .471) vs. 0.562, 0.545, and 0.843 (P = .630, .564, and .007), respectively. The calibration curves of the CEUS-clinical model at different prediction time pionts were all close to the ideal line. The CEUS-clinical model effectively stratified patients into groups of high and low risk of recurrence in both training and validation set, while the TNM staging system only works on the training set.

CONCLUSIONS

Our CEUS-clinical nomogram is a reliable early recurrence prediction tool for hepatocellular-cholangiocarcinoma and helps postoperative risk stratification.

Application of the CT/MRI LI-RADS Treatment Response Algorithm to Contrast-Enhanced Ultrasound: A Feasibility Study

Purpose

The contrast-enhanced ultrasound (CEUS) Liver Imaging Reporting and Data System (LI-RADS) treatment response algorithm (TRA) is still in development. The aim of this study was to explore whether the CT/MRI LI-RADS TRA features were applicable to CEUS in evaluating the liver locoregional therapy (LRT) response.

Patients and Methods

This study was a retrospective review of a prospectively maintained database of patients with hepatocellular carcinoma undergoing ablation between July 2017 and December 2018. The standard criteria for a viable lesion were a histopathologically confirmed or typical viable appearance in the follow-up CT/MRI. Performance of the LI-RADS TRA assessing tumor viability was then compared between CEUS and CT/MRI. Inter-reader association was calculated.

Results

A total of 244 patients with 389 treated observations (118 viable) were evaluated. The sensitivity and specificity of the CEUS TRA and CT/MRI LI-RADS TRA viable categories for predicting viable lesions were 55.0% (65/118) versus 56.8% (67/118) (P = 0.480) and 99.3% (269/271) versus 96.3% (261/271) (P = 0.013), respectively. The PPV of CEUS was higher than that of CT/MRI (97.0% vs 87.0%). Subgroup analysis showed that the sensitivity was low in the 1-month assessment for both CEUS (38.1%, 16/42) and CT/MR (47.6%, 20/42) and higher in the 2–6-month assessment for both CEUS (65.7%, 23/35) and CT/MR (62.9%, 22/35). Interobserver agreements were substantial for both CEUS TRA and CT/MRI LI-RADS TRA (κ, 0.74 for both).

Conclusion

The CT/MRI LI-RADS TRA features were applicable to CEUS TRA for liver locoregional therapy. The CEUS TRA for liver locoregional therapy has sufficiently high specificity and PPV to diagnose the viability of lesions after ablation.

Reproducibility of radiomics features from ultrasound images: influence of image acquisition and processing

OBJECTIVES

To systematically assess the reproducibility of radiomics features from ultrasound (US) images during image acquisition and processing.

MATERIALS AND METHODS

A standardized phantom was scanned to obtain US images. Reproducibility of radiomics features from US images, also known as ultrasomics features, was explored via (a) intra-US machine: changing the US acquisition parameters including gain, focus, and frequency; (b) inter-US machine: comparing three different scanners; (c) changing segmentation locations; and (d) inter-platform: comparing features extracted by the Ultrasomics and PyRadiomics algorithm platforms. Reproducible ultrasomics features were selected based on coefficients of variation.

RESULTS

A total of 108 US images from three scanners were obtained; 5253 ultrasomics features including seven categories of features were extracted and evaluated for each US image. From intra-US machine analysis, 37.0-38.8% of features showed good reproducibility. From inter-US machine analysis, 42.8% (2248/5253) of features exhibited good reproducibility. From segmentation location analysis, 55.7-57.6% of features showed good reproducibility. No significant difference in the normalized feature ranges was found between the 100 features extracted by the Ultrasomics and PyRadiomics platforms with the same algorithm (p = 0.563). A total of 1452 (27.6%) ultrasomics features were reproducible whenever intra-/inter-US machine or segmentation location were changed, most of which were wavelet and shearlet features.

CONCLUSIONS

Different acquisition parameters, US scanners, segmentation locations, and feature extraction platforms affected the reproducibility of ultrasomics features. Wavelet and shearlet features showed the best reproducibility across all procedures.

KEY POINTS

• Different acquisition parameters, US scanners, segmentation locations, and feature extraction platforms affected the reproducibility of ultrasomics features. • A total of 1452 (27.6%) ultrasomics features were reproducible whenever intra-/inter-US machine or segmentation location were changed. • Wavelet and shearlet features showed the best reproducibility across all procedures.

Using new criteria to improve the differentiation between HCC and non-HCC malignancies: clinical practice and discussion in CEUS LI-RADS 2017

PURPOSE

Using contrast-enhanced ultrasound (CEUS) to evaluate the diagnostic performance of liver imaging reporting and data system (LI-RADS) version 2017 and to explore potential ways to improve the efficacy.

METHODS

A total of 315 nodules were classified as LR-1 to LR-5, LR-M, and LR-TIV. New criteria were applied by adjusting the early washout onset (< 45 s) and the time of marked washout (within 3 min). Two subgroups of the LR-M nodules were recategorized as LR-5, respectively. The diagnostic performance was evaluated by calculating the accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).

RESULTS

By adjusting early washout onset to < 45 s, the LR-5 as a standard for diagnosing HCC had an improved sensitivity (74.1% vs. 56.1%, P < 0.001) without significant change in PPV (93.3% vs. 96.1%, P = 0.267), but the specificity was decreased (48.3% vs. 78.5%, P = 0.018). The LR-M as a standard for the diagnosis of non-HCC malignancies had an increase in specificity (89.2% vs. 66.2%, P < 0.001) but a decrease in sensitivity (31.5% vs. 68.4%, P = 0.023). After reclassification according to the time of marked washout, the sensitivity of the LR-5 increased (80% vs. 56.1%, P < 0.001) without a change in PPV (94.9% vs. 96.1%, P = 0.626) and specificity (80% vs. 78.5%, P = 0.879). For reclassified LR-M nodules, the specificity increased (87.5% versus 66.2%, P < 0.001) with a non-significant decrease in sensitivity (47.3% vs. 68.4%, P = 0.189).

CONCLUSIONS

The CEUS LI-RADS showed good confidence in diagnosing HCC while tended to misdiagnose HCC as non-HCC malignancies. Adjusting the marked washout time within 3 min would reduce the possibility of this misdiagnosis.

RGB Three-Channel SWE-Based Ultrasomics Model: Improving the Efficiency in Differentiating Focal Liver Lesions

Objective

To explore a new method for color image analysis of ultrasomics and investigate the efficiency in differentiating focal liver lesions (FLLs) by Red, Green, and Blue (RGB) three-channel SWE-based ultrasomics model.

Methods

One hundred thirty FLLs were randomly divided into training set (n = 65) and validation set (n = 65). The RGB three-channel and direct conversion methods were applied to the same color SWE images. Ultrasomics features were extracted from the preprocessing images establishing two feature data sets. The least absolute shrinkage and selection operator (LASSO) logistic regression model was applied for feature selection and model construction. Two models, named RGB model (based on RGB three-channel conversion) and direct model (based on direct conversion), were used to differentiate FLLs. The diagnosis performance of the two models was evaluated by area under the curve (AUC), calibration curves, decision curves, and net reclassification index (NRI).

Results

In the validation cohort, the AUC of the direct model and RGB model in characterization on FLLs were 0.813 and 0.926, respectively (p = 0.038). Calibration curves and decision curves indicated that the RGB model had better calibration efficiency and provided greater clinical benefits. NRI revealed that the RGB model correctly reclassified 7% of malignant cases and 25% of benign cases compared to the direct model (p = 0.01).

Conclusion

The RGB model generated by RGB three-channel method yielded better diagnostic efficiency than the direct model established by direct conversion method. The RGB three-channel method may be promising on ultrasomics analysis of color images in clinical application.

Tumor size-based validation of contrast-enhanced ultrasound liver imaging reporting and data system (CEUS LI-RADS) 2017 for hepatocellular carcinoma characterizing

OBJECTIVES

To validate the efficacy of contrast-enhanced ultrasound Liver Imaging Reporting and Data System (CEUS LI-RADS) and its major features in diagnosing hepatocellular carcinoma (HCC) of different sizes in high-risk patients.

METHODS

Between January 2014 and December 2015, a total of 545 untreated liver nodules were included. These liver nodules were divided into two groups (<20 mm and ≥20 mm). Each nodule was classified based on CEUS LI-RADS. The diagnostic performance comparison was assessed by the chi-square test, with pathology results as the golden criterion.

RESULTS

The accuracy, sensitivity, specificity, and positive predictive value (PPV) of CEUS LR-5 criteria in <20 mm group vs ≥20 mm group in diagnosing HCC were 60.5% vs 59.8%, 55.6% vs 57.6%, 85.7% vs 88.6 and 95.2% vs 98.5%, respectively, without significant difference (all p > 0.05). The accuracy, sensitivity and PPV of LR5/M for malignancy in <20 mm group were lower than in ≥20 mm group, with values of 79.1% vs 95.0%, 84.2% vs 95.7 and 91.4% vs 99.2%, respectively (p < 0.05).

CONCLUSIONS

The CEUS LI-RADS has a comparable performance for diagnosing HCC between lesions ≥ 20 mm and <20 mm. For diagnosing malignancy including HCC, it has a higher efficacy for lesions ≥ 20 mm than <20 mm.

ADVANCES IN KNOWLEDGE

1.For diagnosing HCC, CEUS LI-RADS has comparable performances between lesions ≥ 20 mm and <20 mm.2. For diagnosing malignancy including HCC, CEUS LI-RADS has a higher efficacy for lesions ≥ 20 mm than <20 mm.

Preoperative Pathological Grading of Hepatocellular Carcinoma Using Ultrasomics of Contrast-Enhanced Ultrasound

RATIONALE AND OBJECTIVES

To develop an ultrasomics model for preoperative pathological grading of hepatocellular carcinoma (HCC) using contrast-enhanced ultrasound (CEUS).

MATERIAL AND METHODS

A total of 235 HCCs were retrospectively enrolled, including 65 high-grade and 170 low-grade HCCs. Representative images of four-phase CEUS were selected from the baseline sonography, arterial, portal venous, and delayed phase images. Tumor ultrasomics features were automatically extracted using Ultrasomics-Platform software. Models were built via the classifier support vector machine, including an ultrasomics model using the ultrasomics features, a clinical model using the clinical factors, and a combined model using them both. Model performances were tested in the independent validation cohort considering efficiency and clinical usefulness.

RESULTS

A total of 1502 features were extracted from each image. After the reproducibility test and dimensionality reduction, 25 ultrasomics features and 3 clinical factors were selected to build the models. In the validation cohort, the combined model showed the best predictive power, with an area under the curve value of 0.785 (95% confidence interval [CI] 0.662-0.909), compared to the ultrasomics model of 0.720 (95% CI 0.576-0.864) and the clinical model of 0.665 (95% CI 0.537-0.793). Decision curve analysis suggested that the combined model was clinically useful, with a corresponding net benefit of 0.760 compared to the other two models.

CONCLUSION

We presented an ultrasomics-clinical model based on multiphase CEUS imaging and clinical factors, which showed potential value for the preoperative discrimination of HCC pathological grades.

Articles That Use Artificial Intelligence for Ultrasound: A Reader's Guide

Artificial intelligence (AI) transforms medical images into high-throughput mineable data. Machine learning algorithms, which can be designed for modeling for lesion detection, target segmentation, disease diagnosis, and prognosis prediction, have markedly promoted precision medicine for clinical decision support. There has been a dramatic increase in the number of articles, including articles on ultrasound with AI, published in only a few years. Given the unique properties of ultrasound that differentiate it from other imaging modalities, including real-time scanning, operator-dependence, and multi-modality, readers should pay additional attention to assessing studies that rely on ultrasound AI. This review offers the readers a targeted guide covering critical points that can be used to identify strong and underpowered ultrasound AI studies.

Machine Learning-Based Ultrasomics Improves the Diagnostic Performance in Differentiating Focal Nodular Hyperplasia and Atypical Hepatocellular Carcinoma

Background

The typical enhancement patterns of hepatocellular carcinoma (HCC) on contrast-enhanced ultrasound (CEUS) are hyper-enhanced in the arterial phase and washed out during the portal venous and late phases. However, atypical variations make a differential diagnosis both challenging and crucial. We aimed to investigate whether machine learning-based ultrasonic signatures derived from CEUS images could improve the diagnostic performance in differentiating focal nodular hyperplasia (FNH) and atypical hepatocellular carcinoma (aHCC).

Patients and Methods

A total of 226 focal liver lesions, including 107 aHCC and 119 FNH lesions, examined by CEUS were reviewed retrospectively. For machine learning-based ultrasomics, 3,132 features were extracted from the images of the baseline, arterial, and portal phases. An ultrasomics signature was generated by a machine learning model. The predictive model was constructed using the support vector machine method trained with the following groups: ultrasomics features, radiologist’s score, and combination of ultrasomics features and radiologist’s score. The diagnostic performance was explored using the area under the receiver operating characteristic curve (AUC).

Results

A total of 14 ultrasomics features were chosen to build an ultrasomics model, and they presented good performance in differentiating FNH and aHCC with an AUC of 0.86 (95% confidence interval [CI]: 0.80, 0.89), a sensitivity of 76.6% (95% CI: 67.5%, 84.3%), and a specificity of 80.5% (95% CI: 70.6%, 85.9%). The model trained with a combination of ultrasomics features and the radiologist’s score achieved a significantly higher AUC (0.93, 95% CI: 0.89, 0.96) than that trained with the radiologist’s score (AUC: 0.84, 95% CI: 0.79, 0.89, P < 0.001). For the sub-group of HCC with normal AFP value, the model trained with a combination of ultrasomics features, and the radiologist’s score remain achieved the highest AUC of 0.92 (95% CI: 0.87, 0.96) compared to that with the ultrasomics features (AUC: 0.86, 95% CI: 0.74, 0.89, P < 0.001) and radiologist’s score (AUC: 0.86, 95% CI: 0.79, 0.91, P < 0.001).

Conclusions

Machine learning-based ultrasomics performs as well as the staff radiologist in predicting the differential diagnosis of FNH and aHCC. Incorporating an ultrasomics signature into the radiologist’s score improves the diagnostic performance in differentiating FNH and aHCC.

Preliminary investigation of the diagnostic value of shear wave elastography in evaluating the testicular spermatogenic function in patients with azoospermia

To assess the diagnostic value of shear wave elastography (SWE) for evaluating the histological spermatogenic function of azoospermic males, 91 patients with azoospermia who underwent standardised greyscale ultrasound and SWE examinations followed by testicular biopsy were retrospectively recruited. Spermatogenic function was classified by biopsy as normal testicular spermatogenesis (n = 61), hypospermatogenesis (n = 18), spermatogenesis arrest (n = 6) and Sertoli cell-only syndrome (n = 6). Significant differences in testicular size and SWE values were observed between these 4 groups (p < .01). The mean SWE value had good discrimination power (AUC = 0.79) with a cut-off value of 1.55 KPa, a sensitivity of 0.58, specificity of 0.85, positive predictive value (PPV) of 0.36 and negative predictive value (NPV) of 0.93. Testicular volume had an AUC of 0.75. With a cut-off value of 8.41 ml, the testicular volume had a sensitivity of 0.58, specificity of 0.92, PPV of 0.54 and NPV of 0.93. The mean SWE value and testicular volume efficiently discriminated patients with normal spermatogenesis and hypospermatogenesis from patients with Sertoli cell-only syndrome and spermatogenesis arrest.

Inter-reader agreement of CEUS LI-RADS among radiologists with different levels of experience

OBJECTIVES

To investigate the inter-reader agreement of contrast-enhanced ultrasound (CEUS) of Liver Imaging Reporting and Data System version 2017 (LI-RADS v2017) categories among radiologists with different levels of experience.

MATERIALS AND METHODS

From January 2014 to December 2014, a total of 326 patients at high risk of hepatocellular carcinoma (HCC) who underwent CEUS were included in this retrospective study. All lesions were classified according to LI-RADS v2017 by six radiologists with different levels of experiences: two residents, two fellows, and two specialists. Kappa coefficient was used to assess consistency of LI-RADS categories and major features among radiologists with different levels of experience. The diagnostic performance of HCC was described by accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the curve (AUC).

RESULTS

Inter-reader agreement among radiologists of different experience levels was substantial agreement for arterial phase hyperenhancement, washout appearance, and early or late washout. Inter-reader agreement for LI-RADS categories was moderate to substantial. When LR-5 was used as criteria to determinate HCC, the AUC of LI-RADS for HCC was 0.67 for residents, 0.72 for fellows, and 0.78 for specialist radiologists. When compared between residents and specialists, accuracy, sensitivity, and AUC were significantly different (all p < 0.05). However, there were no significant differences in specificity, PPV, and NPV between the two groups.

CONCLUSION

CEUS LI-RADS showed good diagnostic consistency among radiologists with different levels of experience, and consistency increased with experience levels.

KEY POINTS

• The inter-reader agreement for LI-RADS categories was moderate to substantial agreement (κ, 0.60-0.80). • When compared between residents and specialists, accuracy, sensitivity, and AUC showed significantly different (all p < 0.05). However, there were no significant differences for specificity, PPV, and NPV between these two groups. • Among the radiologists with more than 1 year of experience, there was no significant difference in the diagnostic performance of HCC, suggesting that CEUS LI-RADS is a good standardized categorization system for high-risk patients.

Pathological considerations of CEUS LI-RADS: correlation with fibrosis stage and tumour histological grade

OBJECTIVES

To evaluate the influence of pathological factors, such as fibrosis stage and histological grade, on the Liver Imaging Reporting and Data System (LI-RADS) v2017 category of contrast-enhanced ultrasonography (CEUS) in patients with high risk of hepatocellular carcinoma (HCC).

MATERIALS AND METHODS

Between June 2015 and December 2016, 441 consecutive patients at high risk of HCC with 460 pathologically proven HCCs were enrolled in this retrospective study. All patients underwent a CEUS examination. The major features (arterial phase hyperenhancement, late and mild washout) were assessed, and LI-RADS categories were assigned according to CEUS LI-RADS v2017. CEUS LI-RADS categories and major features were compared in different histological grades and fibrosis stages.

RESULTS

The CEUS LR-5 category was more frequently assigned in the low-grade group (151/280) than in the high-grade group (66/159) (p = 0.013), whereas the LR-TIV category was more frequently assigned in the high-grade group (36/159) than in the low-grade group (40/280) (p = 0.035). CEUS LI-RADS category was not significantly different among different fibrosis stages (p ≥ 0.05). Arterial phase hyperenhancement (APHE) and the hepatic fibrosis stage showed a significant correlation in HCCs ≥ 2 cm and the low-grade group (p = 0.027 and p = 0.003, respectively). No major features of CEUS LI-RADS showed statistically significant differences between the low- and high-grade groups (p ≥ 0.05).

CONCLUSION

Hepatic fibrosis stage can influence APHE but showed no impact on the CEUS LI-RADS classification, whereas the histological grade of HCC influenced the LR-5 and LR-TIV categories.

KEY POINTS

• Histological grade influenced CEUS LR-5 and LR-TIV category (p = 0.013 and p = 0.035 respectively). Low-grade HCCs occurred more frequently in LR-5 category whereas high-grade HCCs occurred more frequently in LR-TIV category. • Fibrosis stage shows significant influence on APHE on HCCs of the size ≥ 2 cm and low-grade group (p = 0.027 and p = 0.003, respectively). • Hepatic fibrosis stage and HCC histological grade exhibited limited impact on CEUS LI-RADS. CEUS LI-RADS may be feasible for diagnosing HCC in patients regardless of histological grade and fibrosis stage.

Shear wave elastography-based ultrasomics: differentiating malignant from benign focal liver lesions

PURPOSE

Ultrasomics is a radiomics technique that extracts high-throughput quantitative data from ultrasound imaging. The aim of this study was to differentiate malignant from benign focal liver lesions (FLLs) using two-dimensional shear wave elastography (2D-SWE)-based ultrasomics.

METHODS

A total of 175 FLLs in 169 patients were prospectively analyzed. The study population was divided into a training cohort (n = 122) and a validation cohort (n = 53). The maxima, minima, mean, and standard deviation of 2D-SWE measurements were expressed in kilopascals (E_max, E_min, E_mean, and E_SD). The ultrasonics technique was used to extract the features from the 2D-SWE images. Support vector machine was used to establish two prediction models: the ultrasomics score (ultrasomics features only) and the combined score (SWE measurements and ultrasomics features). The diagnostic performance of the models in differentiating FLLs was analyzed.

RESULTS

A total of 1044 features were extracted and 15 features were selected. The AUC for the combined score, ultrasomics score, E_max, E_mean, E_min and E_SD were 0.94, 0.91, 0.92, 0.89, 0.67, and 0.89, respectively. The combined score had the best diagnostic performance. The sensitivity, specificity, PPV, NPV, +LR, LR of the combined score were 92.59%, 87.50%, 94.59%, 82.50%, 7.35%, and 0.09%, respectively. The decision curve analysis results showed that when the threshold probability was > 29%, the combined score showed improved benefits for patients compared to using the ultrasomics score and 2D-SWE measurements.

CONCLUSION

The results of this study demonstrated that the combined score had good diagnostic accuracy in differentiating malignant from benign FLLs.

Testicular quantitative ultrasound: A noninvasive monitoring method for evaluating spermatogenic function in busulfan-induced testicular injury mouse models

Busulfan-induced testicular injury mouse models are commonly used for experiments on spermatogonial stem cell transplantation, treatments for azoospermia due to spermatogenic failure and preserving male fertility after chemotherapy. Here, we investigated the value of testicular quantitative ultrasound for evaluating spermatogenic function in this model. In this study, testicular ultrasound was performed on mice from day 0 to 126 after busulfan treatment (n = 48), and quantitative data, including the testicular volume, mean pixel intensity and pixel uniformity, were analysed. The results revealed that from day 0 to 36, the testicular volume was positively associated with the testicle-to-body weight ratio (r = .92). On day 63, the pixel uniformity, which remained stable from day 0 to 36, declined significantly compared with that on day 36 (p < .01). On day 126, when the whole progression of spermatogenesis could be observed in most tubules, the mean pixel intensity also returned to normal (p > .05). In conclusion, testicular quantitative ultrasound could be used as a noninvasive and accurate monitoring method for evaluating spermatogenic function in busulfan-induced testicular injury mouse models.

Malignancy risk stratification and FNA recommendations for thyroid nodules: A comparison of ACR TI-RADS, AACE/ACE/AME and ATA guidelines

OBJECTIVE

To compare diagnostic performance and malignancy risk stratification among guidelines set forth by the American Thyroid Association (ATA) in 2015, the American Association of Clinical Endocrinologists (AACE), the American College of Endocrinology (ACE) and the Association Medici Endocrinologi (AME) in 2016, and the American College of Radiology (ACR) in 2017.

METHODS

The retrospective study was approved by the hospital ethics committee, and the informed consent requirement was waived. From October 2015 to March 2016, a total of 230 patients with 230 consecutive thyroid nodules were enrolled in this study. Each nodule was classified by one junior and one senior radiologist separately according to ACR TI-RADS, AACE/ACE/AME and ATA guidelines. The malignancy diagnostic performance and the number of FNA recommendations were pairwise compared among three guidelines using chi-square tests.

RESULTS

Of the 230 thyroid nodules, 137 were malignant, and 93 were benign. However, 19.6% of the nodules (45 of 230) did not match any pattern using the ATA guidelines but with a high risk of malignancy (68.9%). The ACR TI-RADS derived the highest diagnostic performance, from both junior radiologist (AUC 0.815) and senior radiologist (AUC 0.864). The ACR guidelines also showed the greatest level of sensitivity (junior: 86.1%, senior: 94.9%), compared with AACE/ACE/AME and ATA guidelines. The number of thyroid nodules recommended to fine-needle aspiration (FNA) was the lowest (37.8%, 40.4%) by ACR TI-RADS, and meanwhile, the malignant detection rate within these nodules was highest (64.4%, 68.8%).

CONCLUSIONS

The ACR guidelines present a higher level of diagnostic indicators and may offer a meaningful reduction in FNA recommendations with a higher malignancy detection rate.

Differential diagnosis between hepatic alveolar echinococcosis and intrahepatic cholangiocarcinoma with conventional ultrasound and contrast-enhanced ultrasound

BACKGROUND

Misclassifications of hepatic alveolar echinococcosis (HAE) as intrahepatic cholangiocarcinoma (ICC) may lead to inappropriate treatment strategies. The aim of this study was to explore the differential diagnosis with conventional ultrasound and contrast-enhanced ultrasound (CEUS).

METHODS

Sixty HAE lesions with 60 propensity score-matched ICC lesions were retrospectively collected. The 120 lesions were randomly divided into a training set (n = 80) and a testing set (n = 40). In the training set, the most useful independent conventional ultrasound and CEUS features was selected for differentiating between HAE and ICC. Then, a simplified US scoring system for diagnosing HAE was constructed based on selected features with weighted coefficients. The constructed US score for HAE was validated in both the training set and the testing set, and diagnostic performance was evaluated.

RESULTS

Compared with ICC lesions, HAE lesions were mostly located in the right lobe and had mixed echogenicity, a pseudocystic appearance and foci calcifications on conventional ultrasound. On CEUS, HAE lesions showed more regular rim-like enhancement than ICC lesions and had late washout with a long enhancement duration. The simplified US score consisted of echogenicity, pseudocystic/calcification, bile duct dilatation, enhancement pattern, enhancement duration, and marked washout. In the testing set, the sensitivity, specificity, LR+, LR- and the area under the ROC curve for the score to differentiate HAE from ICC were 80.0, 81.3%, 4.27, 0.25 and 0.905, respectively.

CONCLUSIONS

The US score based on typical features from both conventional ultrasound and CEUS could accurately differentiate HAE from ICC.

CT-based radiomics scores predict response to neoadjuvant chemotherapy and survival in patients with gastric cancer

BACKGROUND

Neoadjuvant chemotherapy is a promising treatment option for potential resectable gastric cancer, but patients' responses vary. We aimed to develop and validate a radiomics score (rad_score) to predict treatment response to neoadjuvant chemotherapy and to investigate its efficacy in survival stratification.

METHODS

A total of 106 patients with neoadjuvant chemotherapy before gastrectomy were included (training cohort: n = 74; validation cohort: n = 32). Radiomics features were extracted from the pre-treatment portal venous-phase CT. After feature reduction, a rad_score was established by Randomised Tree algorithm. A rad_clinical_score was constructed by integrating the rad_score with clinical variables, so was a clinical score by clinical variables only. The three scores were validated regarding their discrimination and clinical usefulness. The patients were stratified into two groups according to the score thresholds (updated with post-operative clinical variables), and their survivals were compared.

RESULTS

In the validation cohort, the rad_score demonstrated a good predicting performance in treatment response to the neoadjuvant chemotherapy (AUC [95% CI] =0.82 [0.67, 0.98]), which was better than the clinical score (based on pre-operative clinical variables) without significant difference (0.62 [0.42, 0.83], P = 0.09). The rad_clinical_score could not further improve the performance of the rad_score (0.70 [0.51, 0.88], P = 0.16). Based on the thresholds of these scores, the high-score groups all achieved better survivals than the low-score groups in the whole cohort (all P < 0.001).

CONCLUSION

The rad_score that we developed was effective in predicting treatment response to neoadjuvant chemotherapy and in stratifying patients with gastric cancer into different survival groups. Our proposed strategy is useful for individualised treatment planning.

[Surgical treatment strategy for digestive system malignancies during the outbreak of COVID-19]

The outbreak of COVID-19 occurred in Wuhan, Hubei province of China, at the end of 2019, and spread rapidly across the country. After the outbreak of this disease, the overwhelming majority of cities have launched the "first level response" and the regular diagnosis and treatment of cancer patients are greatly affected. The digestive systemic cancer is the most common malignancy. Most patients are diagnosed in the advanced stage with poor prognosis. The epidemic of COVID-19 poses new challenges to diagnosis and treatment of the patients with digestive system malignancies. Based on the fully understanding of the characteristics of digestive system tumors, we should change the treatment strategy and adopt more reasonable treatment strategy timely during the epidemic period to minimize the adverse effects of the epidemic of COVID-19 on the treatment.

CT-based radiomics for preoperative prediction of early recurrent hepatocellular carcinoma: technical reproducibility of acquisition and scanners

PURPOSE

To test the technical reproducibility of acquisition and scanners of CT image-based radiomics model for early recurrent hepatocellular carcinoma (HCC).

METHODS

We included primary HCC patient undergone curative therapies, using early recurrence as endpoint. Four datasets were constructed: 109 images from hospital #1 for training (set 1: 1-mm image slice thickness), 47 images from hospital #1 for internal validation (sets 2 and 3: 1-mm and 10-mm image slice thicknesses, respectively), and 47 images from hospital #2 for external validation (set 4: vastly different from training dataset). A radiomics model was constructed. Radiomics technical reproducibility was measured by overfitting and calibration deviation in external validation dataset. The influence of slice thickness on reproducibility was evaluated in two internal validation datasets.

RESULTS

Compared with set 1, the model in set 2 indicated favorable prediction efficiency (the area under the curve 0.79 vs. 0.80, P = 0.47) and good calibration (unreliability statistic U: P = 0.33). However, in set 4, significant overfitting (0.63 vs. 0.80, P < 0.01) and calibration deviation (U: P < 0.01) were observed. Similar poor performance was also observed in set 3 (0.56 vs. 0.80, P = 0.02; U: P < 0.01).

CONCLUSIONS

CT-based radiomics has poor reproducibility between centers. Image heterogeneity, such as slice thickness, can be a significant influencing factor.

Comparison of Real-Time Two-Dimensional and Three-Dimensional Contrast-Enhanced Ultrasound to Quantify Flow in an In Vitro Model: A Feasibility Study

BACKGROUND This feasibility study aimed to compare real-time two-dimensional contrast-enhanced ultrasound (2D-CEUS) and three-dimensional contrast-enhanced ultrasound (3D-CEUS) to quantify flow in an in vitro model. MATERIAL AND METHODS Five polyvinyl chloride (PVC) tubes were used for the perfusion models and used SonoVue ultrasound contrast agent with a perfusion volume ratio of 1: 2: 4: 8: 16. The contrast was injected at a constant speed to compare the raw quantitative data of 2D-CEUS and 3D-CEUS at angles of 0°, 45°, and 90°. The coefficient of variation (CV) of the peak intensity (PI) in the model were compared and the correlations between weighted PI and perfusion volume were analyzed. RESULTS In the three angles used, real-time 3D-CEUS resulted in a more comprehensive view of the spatial relationships in the perfusion model. Using real-time 2D-CEUS, the mean CV was 0.92±0.36, and the mean CV in the real-time 3D-CEUS model was significantly less at 0.48±0.32 (p<0.001). Quantitative 3D-CEUS parameters showed a good correlation with those of 2D-CEUS with an r-value of 0.93 (p=0.02). The r-value of weighted PI and the perfusion ratio using 2D-CEUS was 0.66 (p=0.23) compared with values in 3D-CEUS of 0.84 (p=0.08). CONCLUSIONS The combination of real-time 3D-CEUS and quantitative analysis identified the spatial distribution of the changes in angle in the model, which was less influenced by sectional planes, and was more representative of the perfusion volume when compared with 2D-CEUS. Quantitative real-time 3D-CEUS requires in vivo studies to evaluate the potential role in the clinical evaluation of vascular perfusion of malignant tumors.

Sorafenib versus hepatic arterial infusion chemotherapy for advanced hepatocellular carcinoma: a systematic review and meta-analysis

BACKGROUND

The clinical benefits and safety of Sorafenib versus hepatic arterial infusion chemotherapy (HAIC) for advanced hepatocellular carcinoma (HCC) are inconsistent in some studies. This meta-analysis aims to evaluate the effectiveness and safety of Sorafenib versus HAIC for patients with advanced HCC.

METHODS

An electronic search was performed from PubMed, Embase, the Cochrane Library and Web of Science to identify comparative studies evaluating Sorafenib versus HAIC for HCC. Objective response rate, disease control rate, overall survival, progression-free survival and adverse events were evaluated using meta-analytical techniques.

RESULTS

Fourteen retrospective studies with 1779 patients (Sorafenib = 773, HAIC = 1006) were included in the meta-analysis. HAIC delivered favorable outcomes in objective response rate (odds ratio 0.13; 95%CI, 0.07-0.24) and disease control rate (odds ratio 0.48; 95%CI 0.26-0.87) assessed by the Response Evaluation Criteria in Solid Tumors. The pooled hazard ratio for overall survival at 0.60 (95% CI 0.39-0.91) and the pooled hazard ratio for progression-free survival at 0.69(95% CI 0.51-0.95), further indicates that HAIC was superior to Sorafenib. There was a higher incidence of adverse events, including hypertension (odds ratio 13.07; 95% CI 2.37-71.67), fatigue (odds ratio 6.72; 95% CI 2.14-21.13), dermatological disorders (odds ratio 15.87; 95% CI 5.58-45.16) and gastrointestinal disorders (odds ratio 3.20; 95% CI 2.02-5.07) in patients receiving Sorafenib than in those receiving HAIC.

CONCLUSION

HAIC offers a safe and effective alternative to Sorafenib with better tumor response and longer overall survival and progression-free survival, hence HAIC should be recommended for the patients with advanced HCC.

Predicting Breast Cancer in Breast Imaging Reporting and Data System (BI-RADS) Ultrasound Category 4 or 5 Lesions: A Nomogram Combining Radiomics and BI-RADS

Radiomics reflects the texture and morphological features of tumours by quantitatively analysing the grey values of medical images. We aim to develop a nomogram incorporating radiomics and the Breast Imaging Reporting and Data System (BI-RADS) for predicting breast cancer in BI-RADS ultrasound (US) category 4 or 5 lesions. From January 2017 to August 2018, a total of 315 pathologically proven breast lesions were included. Patients from the study population were divided into a training group (n = 211) and a validation group (n = 104) according to a cut-off date of March 1^st, 2018. Each lesion was assigned a category (4A, 4B, 4C or 5) according to the second edition of the American College of Radiology (ACR) BI-RADS US. A radiomics score was generated from the US image. A nomogram was developed based on the results of multivariate regression analysis from the training group. Discrimination, calibration and clinical usefulness of the nomogram for predicting breast cancer were assessed in the validation group. The radiomics score included 9 selected radiomics features. The radiomics score and BI-RADS category were independently associated with breast malignancy. The nomogram incorporating the radiomics score and BI-RADS category showed better discrimination (area under the receiver operating characteristic curve [AUC]: 0.928; 95% confidence interval [CI]: 0.876, 0.980) between malignant and benign lesions than either the radiomics score (P = 0.029) or BI-RADS category (P = 0.011). The nomogram demonstrated good calibration and clinical usefulness. In conclusion, the nomogram combining the radiomics score and BI-RADS category is potentially useful for predicting breast malignancy in BI-RADS US category 4 or 5 lesions.

Clinicopathological findings and imaging features of intraductal papillary neoplasm of the bile duct: comparison between contrast-enhanced ultrasound and contrast-enhanced computed tomography

PURPOSE

Intraductal papillary neoplasms of the bile duct (IPNBs) are a group of rare lesions with uncertain clinical findings and imaging features. We aim to investigate the clinicopathological features and imaging findings of IPNBs on contrast-enhanced ultrasound (CEUS) and contrast-enhanced computed tomography (CECT).

METHODS

From February 2005 to March 2018, 30 patients with pathologically confirmed IPNBs were retrospectively identified in our hospital. Demographic, clinical, and pathological data, CEUS and CECT features and surgical strategies were analyzed.

RESULTS

The most common clinical manifestations were abdominal pain (53.3%), jaundice (23.3%), and acute cholangitis (10.0%). Among all lesions, 5/30 (16.7%) lesions presented as dilated bile ducts only, while 13/30 (43.3%) lesions presented as dilated bile ducts with intraductal papillary masses, and 12/30 (40.0%) presented as solid masses with dilated bile ducts. For the 20 patients who underwent both CEUS and CECT, 18 lesions were hyperenhanced on CEUS, and 17 lesions were hyperenhanced on CECT in the arterial phase. In total, 16 and 18 lesions showed washout in the portal and late phases on CEUS, while the corresponding number of lesions that showed washout in the portal and late phases on CECT were 11 and 13. Twelve lesions (40.0%) showed atypical hyperplasia, while 16/30 (53.3%) lesions underwent malignant transformations.

CONCLUSIONS

There are 3 major forms of IPNBs on grayscale ultrasound, including diffusely dilated bile ducts without visible mass; focal dilated bile duct with intraductal papillary masses; and solid mass surrounded by dilated bile ducts. The enhancement patterns of IPNBs on CEUS and on CECT were consistent. IPNB has a high malignant potential, and patients should be treated with surgical resection after the diagnosis is established.

CT-based peritumoral radiomics signatures to predict early recurrence in hepatocellular carcinoma after curative tumor resection or ablation

OBJECTIVE

To construct a prediction model based on peritumoral radiomics signatures from CT images and investigate its efficiency in predicting early recurrence (ER) of hepatocellular carcinoma (HCC) after curative treatment.

MATERIALS AND METHODS

In total, 156 patients with primary HCC were randomly divided into the training cohort (109 patients) and the validation cohort (47 patients). From the pretreatment CT images, we extracted 3-phase two-dimensional images from the largest cross-sectional area of the tumor. A region of interest (ROI) was manually delineated around the lesion for tumoral radiomics (T-RO) feature extraction, and another ROI was outlined with an additional 2 cm peritumoral area for peritumoral radiomics (PT-RO) feature extraction. The least absolute shrinkage and selection operator (LASSO) logistic regression model was applied for feature selection and model construction. The T-RO and PT-RO models were constructed. In the validation cohort, the prediction efficiencies of the two models and peritumoral enhancement (PT-E) were evaluated qualitatively by receiver operating characteristic (ROC) curves, calibration curves and decision curves and quantitatively by area under the curve (AUC), the category-free net reclassification index (cfNRI) and integrated discrimination improvement values (IDI).

RESULTS

By comparing AUC values, the prediction accuracy in the validation cohort was good for the PT-RO model (0.80 vs. 0.79, P = 0.47) but poor for the T-RO model (0.82 vs. 0.62, P < 0.01), which was significantly overfitted. In the validation cohort, the ROC curves, calibration curves and decision curves indicated that the PT-RO model had better calibration efficiency and provided greater clinical benefits. CfNRI indicated that the PT-RO model correctly reclassified 47% of ER patients and 32% of non-ER patients compared to the T-RO model (P < 0.01); additionally, the PT-RO model correctly reclassified 24% of ER patients and 41% of non-ER patients compared to PT-E (P = 0.02). IDI indicated that the PT-RO model could improve prediction accuracy by 0.22 (P < 0.01) compared to the T-RO model and by 0.20 (P = 0.01) compared to PT-E.

CONCLUSION

The CT-based PT-RO model can effectively predict the ER of HCC and is more efficient than the T-RO model and the conventional imaging feature PT-E.

[Characteristics of neuromyelitis optica spectrum disorder associated with the area postrema]

Objective: To evaluate the clinical characteristics and the corresponding MRI and laboratory findings in patients with neuromyelitis optica spectrum disorder (NMOSD) associated with area postrema (AP). Methods: The study was a retrospective analysis of data from 120 NMOSD patients, and 18 cases were with AP out of these patients, The clinical presentation, MRI changes, serological markers and treatment outcome were reported. Results: AP occurred in 18 patients (15%, 18/120). AP was the onset symptom in 14 (14/18) patients and 3 days to 7 months (median 40 days) later, optic neuritis or myelitis was involved. One patient presented AP after optic neuritis. Three patients (3/18) had AP and myelitis or optic neuritis simultaneously. AP symptom presented as intractable nausea and vomiting, hiccups. Compared to the patients without AP (n=102), the patients with AP (n=18) had shorter duration and fewer numbers of optic neuritis(P<0.05). There was no statistical difference in sex, onset age, course of disease (relapsing or monophasic) and EDSS scores (P>0.05). The MRI revealed flake or linear lesions in medulla. Twelve patients had cervical cord lesions extending to medulla lesions (12/18). Eleven patients had long cord lesions extending more than 3 spinal cords. The AQP4-antibody did not differ in patients with or without AP (14/18 vs 75/102). The symptom of AP was successfully relieved with methylprednisolone. Conclusion: AP symptoms/signs are common in patients with NMOSD. Vomiting and hiccups can be the first symptoms. The medulla lesions and the lesions extending to upper cervical cord are unique to NMOSD. Awareness of AP presentations is helpful for early diagnosis and proper treatment to prevent further disability.

Peritumoral tissue on preoperative imaging reveals microvascular invasion in hepatocellular carcinoma: a systematic review and meta-analysis

BACKGROUND

Histologic microvascular invasion (MVI) substantially worsens the prognosis of patients with hepatocellular carcinoma, and can only be diagnosed postoperatively. Preoperative assessment of MVI by imaging has been focused on tumor-related features, while peritumoral imaging features have been indicated elsewhere to be more accurate. The aim of the present study is to evaluate the association between peritumoral imaging features and MVI.

METHODS

Literature search was performed using the PubMed, Embase, and Cochrane Library databases. Summary results of the association between peritumoral imaging features and MVI were presented as the odds ratio (OR) and the 95% confidence interval. Meta-regression and subgroup analyses were performed when heterogeneity was detected. Diagnostic accuracy analysis was also conducted for identified features.

RESULTS

Ten studies were included in the analysis. Moderate and low heterogeneities were found among the seven studies on peritumoral enhancement and four studies on peritumoral hypointensity on HBP, respectively. Summary results revealed a significant association between MVI and peritumoral enhancement (OR 4.04 [2.23, 7.32], p < 0.05), and peritumoral hypointensity on HBP (OR 10.62 [5.31, 21.26], p < 0.05). Diagnostic accuracy analysis revealed high specificity (0.90-0.94) but low sensitivity (0.29-0.40) for both features to assess MVI.

CONCLUSION

The two peritumoral imaging features are significantly associated with MVI. The two features highly suggest MVI only when present with a high false negative rate. Promotion of their diagnostic efficiency can be a worthwhile task for future research.

Thermal Field Distributions of Ablative Experiments Using Cyst-mimicking Phantoms: Comparison of Microwave and Radiofrequency Ablation

RATIONALE AND OBJECTIVES

The objective of this study was to explore the thermal field distribution of cystic lesions undergoing microwave ablation (MWA) and radiofrequency ablation (RFA) using in vitro phantoms.

MATERIALS AND METHODS

Cyst-mimicking lesions filled with sodium chloride (NaCl) solution in acrylamide phantoms were treated with MWA and RFA in vitro. The radiofrequency electrodes or MWA antennas were implanted in the centers of the artificial cystic lesions. We used temperature fields located 5, 15, and 25 mm from the electrode or the antenna to plot the temperature-rise curves. Solid phantoms without cysts were also fabricated as controls.

RESULTS

The temperature within cysts increased faster and reached a higher maximum temperature during MWA than during RFA, and this result was independent of the NaCl solution concentration. RFA treatment caused the temperatures within the lesion to increase significantly faster in the cysts containing 0.9% NaCl than in those containing 5.0% NaCl. However, the MWA temperature-rise curves were only weakly affected by the ionic concentration. The median temperature difference values between the 5- and 15-mm points were markedly lower in the 0.9% NaCl cyst-mimicking phantom (P <0.001) than in the solid phantom after either MWA or RFA.

CONCLUSIONS

Our data indicate that MWA is a more effective technique for focal cystic lesions than RFA and has higher overall energy utilization. MWA was also less affected by the ionic concentration of the cystic fluid.

[Value of split hand in the differential diagnosis of amyotrophic lateral sclerosis and cervical spondylotic amyotrophy]

Objective: To investigate the value of split hand in the differential diagnosis of amyotrophic lateral sclerosis(ALS) and cervical spondylotic amyotrophy (CSA). Methods: A total of 62 ALS patients, 57 CSA patients and 65 normal controls who visited the Neurology and Spine Department of Beijing Jishuitan Hospital from May 2013 to June 2017 were enrolled into this study.The amplitudes of compound muscle action potentials (CMAP) were recorded from abductor digiti minimi (ADM) and abductor pollicis brevis (APB). Moreover, the ratio of CMAP amplitude between ADM and APB (ADM/APB) was calculated. Results: The ADM/APB of the ALS group (1.93±1.97)was significantly higher than that of the normal control group (0.92±0.22)(P<0.05); the ADM/APB of the CSA group (0.74±0.32)was significantly lower than that of the normal control group (0.92±0.22)(P<0.05); the ADM/APB of the ALS group (1.93±1.97)was significantly higher than that of the CSA group(0.74±0.32)(P<0.05); the areas under receiver operator characteristic curve in patients with ALS was 0.843, the diagnostic sensitivity and specificity for ALS were 75.8% and 83.1% with the cutoff value of ADM/APB=1.077; the areas under receiver operator characteristic curve in patients with CSA was 0.737, the diagnostic sensitivity and specificity for CSA were 64.9% and 87.1% with the cutoff value of ADM/APB=0.739. Conclusion: The ADM/APB has certain clinical value for the differentiation of ALS and CSA.

A non-smooth tumor margin on preoperative imaging assesses microvascular invasion of hepatocellular carcinoma: A systematic review and meta-analysis

Microvascular invasion (MVI) is rarely diagnosed preoperatively in hepatocellular carcinoma (HCC). The aim of this meta-analysis is to assess the diagnostic power of a non-smooth tumor margin on preoperative imaging for MVI. We performed a literature search using the PubMed, Embase and Cochrane Library databases, and 11 studies were included involving 618 MVI-positive cases and 1030 MVI-negative cases. Considerable heterogeneity was found, and was indicated to be attributable to the mean patient ages in the included studies. In subgroups of studies with a mean patient age older than 60 years and studies with computed tomography (CT) as the imaging method (as opposed to magnetic resonance imaging (MRI)), heterogeneity was low, and the diagnostic odds ratio (DOR) of the single two-dimensional imaging feature for MVI was 21.30 (95% CI [12.52, 36.23]) and 28.78 (95% CI [13.92, 59.36]), respectively; this power was equivalent to or greater than that of certain multivariable-based scoring systems. In conclusion, a non-smooth tumor margin on preoperative imaging is of great value for MVI assessment and should be considered for inclusion in future scoring systems.

NDM-1-Producing Citrobacter freundii, Escherichia coli, and Acinetobacter baumannii Identified from a Single Patient in China

We identified New Delhi metallo-β-lactamase (NDM-1)-producing Citrobacter freundii GB032, Escherichia coli GB102, and Acinetobacter baumannii GB661 in urine and stool samples from a single patient in China. Plasmid profiling and Southern blotting indicated that blaNDM-1 from GB032 and that from GB102 were likely located on the same plasmid, while blaNDM-1 from GB661 was located on a very large (>400-kb) plasmid. This case underscores the broad host range of blaNDM-1 and its potential to spread between members of the family Enterobacteriaceae and A. baumannii.

[Human DNA polymorphism of HaeIII system in Chinese oriental, Han population]

DNA typing by restriction fragment length polymorphism (RFLP) analysis was an extremely important technique used in forensic science identification, paternity test and gene diagnosis. While RFLP testing was a highly informative method, it traditionally had several disadvantages. It was time consuming and involved in working with radioactive phosphorus. A chemiluminescent detection of RFLP technique that was faster and safer than isotopic detection. The chemiluminescent system had a good sensitivity of detecting 3-25 ng sample DNA. The development of direct alkaline phosphatase (AP) conjugated probes and improved chemiluminescent substrates provided a non-isotopic detection method that equaled or surpassed 32P detection systems. Population genetic studies were performed using direct alkaline phosphatase (AP) conjugated oligonucleotide probes (AL1874, YNH24, TBQ7, VI) that recognized four hypervariable number of tandem repeats regions (D2S92, D2S44, D10S28, D17S79 loci) respectively in the human genome. DNA from approximately 480 unrelated individuals, subdivided into oriental group were digested with HaeIII enzyme and were successively hybridized to each DNA probe. The number of distinct DNA fragments identified for each of these regions varies from 37 to more than 78. An allele frequency distribution was determined for each locus with the computer and digitizer. The results showed significant differences between different races (American-blacks, Caucasians, and Orientals), in the pattern of distributions as well as in the relative frequency of the most common alleles of D2S92, D2S44, D10S28, and D17S79. The results showed that the analysis of these loci had useful applications in genetics and in forensic identity.

[HLA-DRB alleles polymorphism in Han, Hui, Uygur and Tibetan populations in northwestern China]

According to the 11th THW standard, we designed a pair of primers by which a segment of 256bp of HLA-DRB1, B3, B4, and B5 could be amplified simultaneously. Twenty-seven oligonucleotide probes were designed and synthesized for 39 loci on DRB1, 3 on DRB3, 1 on DRB4 and 3 on DRB5. A PCR-SSO DNA typing protocol was built, which met the standard of HLA class II DNA typing in 11th IHW. With this method, 186 of Chinese (Han) in Xi'an, 169 of Hui in Ningxia, 200 of Uygur in Xinjiang, and 188 of Tibetan in Tibet were detected with a comparison study. The genetic distribution of 46 loci of DRB in four ethnic healthy populations were surveyed. No diversity has been found between Han and Hui in DRB. DRB1 * 02(16.9%), DRB1 * 07 (13.1%), and DRB1 * 09(12.0%) were the higher frequent loci in Han. More DRB loci were detected in Tibetan but without higher loci as in Han and Hui. The DRB polymorphism of Uygur population was similar to Caucasian. A discriminative highest frequency of DRB1 * 07(23.8%) was found in Uygur, which implied a selection happened.

Prenatal and molecular diagnosis of hemophilia B

Prenatal diagnosis was carried out on a woman who had previously given birth to a son with a spontaneous mutation of C-->T transition at nt 31133 of the factor IX (F.IX) gene. The diagnosis was performed on chorionic villi sampling by the method of amplification-created restriction site (ACRS). It revealed a female fetus with a normal F.IX gene, as confirmed by DNA sequencing after delivery. Meanwhile, a survey using the ACRS method to evaluate the inheritance of 63 individuals from 8 hemophilia B families was done. A different single-point mutation in each family was proved by DNA sequencing. One individual had a mutation with a naturally-created restriction site. In each of the remaining patients, we were able to show an enzyme-cutting site in their DNA amplification product for ACRS with the designed mutagenesis primers. All patients and carriers could be diagnosed accurately by comparing ACRS results with clinical and laboratory findings. There were new novel mutations among the patients.

Speech synthesis by glottal excited linear prediction

This paper describes a linear predictive (LP) speech synthesis procedure that resynthesizes speech using a 6th-order polynomial waveform to model the glottal excitation. The coefficients of the polynomial model form a vector that represents the glottal excitation waveform for one pitch period. A glottal excitation code book with 32 entries for voiced excitation is designed and trained using two sentences spoken by different speakers. The purpose for using this approach is to demonstrate that quantization of the glottal excitation waveform does not significantly degrade the quality of speech synthesized with a glottal excitation linear predictive (GELP) synthesizer. This implementation of the LP synthesizer is patterned after both a pitch-excited LP speech synthesizer and a code excited linear predictive (CELP) speech coder. In addition to the glottal excitation codebook, we use a stochastic codebook with 256 entries for unvoiced noise excitation. Analysis techniques are described for constructing both codebooks. The GELP synthesizer, which resynthesizes speech with high quality, provides the speech scientist a simple speech synthesis procedure that uses established analysis techniques, that is able to reproduce all speed sounds, and yet also has an excitation model waveform that is related to the derivative of the glottal flow and the integral of the residue. It is conjectured that the glottal excitation codebook approach could provide a mechanism for quantitatively comparing the differences in glottal excitation codebooks for male and female speakers and for speakers with vocal disorders and for speakers with different voice types such as breathy and vocal fry voices. Conceivably, one could also convert the voice of a speaker with one voice type, e.g., breathy, to the voice of a speaker with another voice type, e.g., vocal fry, by synthesizing speech using the vocal tract LP parameters for the speaker with the breathy voice excited by the glottal excitation codebook trained for vocal fry.

Isolated extramedullary relapse of acute lymphoblastic leukemia presenting as an intraspinal mass

Leptomeningeal relapse is a common finding in acute lymphoblastic leukemia (ALL), but a solid intraspinal mass with cord compression as the sole site of extramedullary relapse is unusual. We report an adult patient with ALL, after 2 years of complete remission, who developed a spinal cord compression due to an intraspinal mass as a first manifestation of extramedullary relapse. Manifestation of first relapse in ALL presenting as an intraspinal mass is rare and may be added to other unusual extramedullary sites of relapse.

DAE (daunorubicin, Ara-C, and etoposide) and intermediate dose Ara-C for remission induction and consolidation treatment of adult patients with acute myeloid leukemia

Fifty-one patients (age 18-73 years) with acute myeloid leukemia were treated with daunorubicin, cytarabine, and etoposide in an age-adjusted protocol, with patients older than 50 receiving fewer days of therapy. Complete remission (CR) occurred in 66% of the patients (34 of 51 patients). Patients 50 years of age and younger achieved a 74% CR rate (23 of 31 patients) compared to a 55% CR rate (11 of 20 patients) in older patients. Of the 34 complete responders, 11 (32%) refused consolidation therapy and received traditional Chinese herbal medicine. All of these 11 patients relapsed after a short remission duration (median, 3.8 months) and died. The median remission duration and median overall survival of 23 complete responders receiving at least two courses of consolidation therapy were 10.1 and 19.8 months, respectively. The actuarial 3-year disease-free survival for these 23 complete responders was 21 +/- 9%. Myelosuppression was the major toxicity, and nonhematological side effects were acceptable. The regimen appeared to have acceptable toxicity, and its efficacy was comparable with that of standard regimens with long-term maintenance therapy.

[Effects of castration and testosterone-replacement on hypothalamic and plasma luteinizing hormone-releasing hormone levels in the aged male rat]

Hypothalamic and plasma luteinizing hormone-releasing hormone (LHRH) levels following orchidectomy (ORDX) and testosterone (T)-replacement were compared between young (2-3 months old) and aged (24-26 months old) male rats by radioimmunoassay. Plasma T level and hypothalamic LHRH content are markedly decreased in the aged rat as compared to those of the young rat, whereas plasma LHRH levels are similar in the two groups. Following ORDX and ORDX plus T-replacement, plasma T levels in both groups are about the same, whereas the rates of variation of hypothalamic and plasma LHRH levels in the aged rat are significantly lower than those in the young rat. These results suggest that the negative feedback mechanism of the hypothalamic LHRHergic system is impaired in the aged rat, which may be one of the important reasons causing age-dependent deterioration of the functional control of hypothalamic-pituitary-testicular axis.