Search

BackgroundMicrovascular invasion is a major histopathological risk factor of postoperative recurrence in patients with hepatocellular carcinoma. This study aimed to develop and validate a digital biopsy model using imaging features to predict microvascular invasion before hepatectomy.MethodsA total of 217 consecutive patients who underwent hepatectomy for resectable hepatocellular carcinoma were enrolled at two tertiary-care reference centers. An imaging-based digital biopsy model was developed and internally validated using logistic regression analysis with adjustments for age, sex, etiology of disease, size and number of lesions.ResultsThree imaging features, i.e., non-smoothness of lesion margin (OR = 16.40), ill-defined pseudocapsula (OR = 4.93), and persistence of intratumoral internal artery (OR = 10.50), were independently associated with microvascular invasion and incorporated into a prediction model. A scoring system with 0 - 3 points was established for the prediction model. Internal validation confirmed an excellent calibration of the model. A cutoff of 2 points indicates a high risk of microvascular invasion (area under the curve 0.87). The overall survival and recurrence-free survival stratified by the risk model was significantly shorter in patients with high risk features of microvascular invasion compared to those patients with low risk of microvascular invasion (overall survival: median 35 vs. 75 months, P = 0.027; recurrence-free survival: median 17 vs. 38 months, P < 0.001)).ConclusionA preoperative assessment of microvascular invasion by digital biopsy is reliable, easily applicable, and might facilitate personalized treatment strategies.

Abstract To examine the comparative robustness of computed tomography (CT)-based conventional radiomics and deep-learning convolutional neural networks (CNN) to predict overall survival (OS) in HCC patients. Retrospectively, 114 HCC patients with pretherapeutic CT of the liver were randomized into a development (n = 85) and a validation (n = 29) cohort, including patients of all tumor stages and several applied therapies. In addition to clinical parameters, image annotations of the liver parenchyma and of tumor findings on CT were available. Cox-regression based on radiomics features and CNN models were established and combined with clinical parameters to predict OS. Model performance was assessed using the concordance index (C-index). Log-rank tests were used to test model-based patient stratification into high/low-risk groups. The clinical Cox-regression model achieved the best validation performance for OS (C-index [95% confidence interval (CI)] 0.74 [0.57–0.86]) with a significant difference between the risk groups (p = 0.03). In image analysis, the CNN models (lowest C-index [CI] 0.63 [0.39–0.83]; highest C-index [CI] 0.71 [0.49–0.88]) were superior to the corresponding radiomics models (lowest C-index [CI] 0.51 [0.30–0.73]; highest C-index [CI] 0.66 [0.48–0.79]). A significant risk stratification was not possible (p > 0.05). Under clinical conditions, CNN-algorithms demonstrate superior prognostic potential to predict OS in HCC patients compared to conventional radiomics approaches and could therefore provide important information in the clinical setting, especially when clinical data is limited.

Abstract Background The aim of this study was to assess the usefulness of adding thoracic CT to abdominal CT in intensive care unit (ICU) patients with signs of infection after abdominopelvic surgery. Methods 143 thoracoabdominal CTs of ICU patients with signs of infection after abdominopelvic surgery were retrospectively reviewed for thoracic pathologies. It was determined if pathologic findings were visible only on thoracic CT above the diaphragmatic dome or also on abdominal CT up to the diaphragmatic dome. All thoracic pathologies visible only above the diaphragmatic dome were retrospectively analyzed by an ICU physician in terms of clinical relevance. Diagnostic and therapeutic efficacy of thoracic CT were assessed with regard to an infectious focus and to other pathologic findings. Results 297 pathologic thoracic findings were recorded. 26 of the 297 findings could only be detected on images obtained above the diaphragmatic dome (in 23 of 143 CTs). A change in patient management was initiated due to only one of the 26 supradiaphragmatic findings. Diagnostic efficacy of thoracic CT in addition to abdominal CT to identify an infectious focus was 3.5% (95%-CI: 0.5–6.5%) and therapeutic efficacy was 0.7% (95%-CI: 0–2.1%). With regard to all pathologic thoracic findings, diagnostic efficacy was 16.1% (95%-CI: 10.1–22.1%) and therapeutic efficacy remained at 0.7%. Conclusions Additional thoracic CT to detect an infectious focus in ICU patients after abdominopelvic surgery leads to identification of the focus in only 3.5% and to changes in patient management in only 0.7%. Other relevant findings are more common (16.1%), but very rarely affect patient management.

Abstract Background The prognosis of pancreatic ductal adenocarcinoma (PDAC) is one of the most dismal of all cancers and the median survival of PDAC patients is only 6–8 months after diagnosis. While decades of research effort have been focused on early diagnosis and understanding of molecular mechanisms, few clinically useful markers have been universally applied. To improve the treatment and management of PDAC, it is equally relevant to identify prognostic factors for optimal therapeutic decision-making and patient survival. Compelling evidence have suggested the potential use of extracellular vesicles (EVs) as non-invasive biomarkers for PDAC. The aim of this study was thus to identify non-invasive plasma-based EV biomarkers for the prediction of PDAC patient survival after surgery. Methods Plasma EVs were isolated from a total of 258 PDAC patients divided into three independent cohorts (discovery, training and validation). RNA sequencing was first employed to identify differentially-expressed EV mRNA candidates from the discovery cohort (n = 65) by DESeq2 tool. The candidates were tested in a training cohort (n = 91) by digital droplet polymerase chain reaction (ddPCR). Cox regression models and Kaplan–Meier analyses were used to build an EV signature which was subsequently validated on a multicenter cohort (n = 83) by ddPCR. Results Transcriptomic profiling of plasma EVs revealed differentially-expressed mRNAs between long-term and short-term PDAC survivors, which led to 10 of the top-ranked candidate EV mRNAs being tested on an independent training cohort with ddPCR. The results of ddPCR enabled an establishment of a novel prognostic EV mRNA signature consisting of PPP1R12A, SCN7A and SGCD for risk stratification of PDAC patients. Based on the EV mRNA signature, PDAC patients with high risk displayed reduced overall survival (OS) rates compared to those with low risk in the training cohort (p = 0.014), which was successfully validated on another independent cohort (p = 0.024). Interestingly, the combination of our signature and tumour stage yielded a superior prognostic performance (p = 0.008) over the signature (p = 0.022) or tumour stage (p = 0.016) alone. It is noteworthy that the EV mRNA signature was demonstrated to be an independent unfavourable predictor for PDAC prognosis. Conclusion This study provides a novel and non-invasive prognostic EV mRNA signature for risk stratification and survival prediction of PDAC patients.

PurposeThe use of inner-branch aortic stent grafts in the treatment of complex aortic pathologies aims at broad applicability and stable bridging stent sealing compared to other endovascular technologies. The objective of this study was to evaluate the early outcomes with a single manufacturer custom-made and off-the-shelf inner-branched endograft in a mixed patient cohort.MethodsThis retrospective, monocentric study between 2019 and 2022 included 44 patients treated with inner-branched aortic stent grafts (iBEVAR) as custom-made device (CMD) or off-the-shelf device (E-nside) with at least four inner branches. The primary endpoints were technical and clinical success.ResultsOverall, 77% (n = 34) and 23% (n = 10) of the patients (mean age 77 ± 6.5 years, n = 36 male) were treated with a custom-made iBEVAR with at least four inner branches and an off-the-shelf graft, respectively. Treatment indications were thoracoabdominal pathologies in 52.2% (n = 23), complex abdominal aneurysms in 25% (n = 11), and type Ia endoleaks in 22.7% (n = 10). Preoperative spinal catheter placement was performed in 27% (n = 12) of patients. Implantation was entirely percutaneous in 75% (n = 33). Technical success was 100%. Target vessel success manifested at 99% (178/180). There was no in-hospital mortality. Permanent paraplegia developed in 6.8% (n = 3) of patients. The mean follow-up was 12 months (range 0–52 months). Three late deaths (6.8%) occurred, one related to an aortic graft infection. Kaplan–Meier estimated 1-year survival manifested at 95% and branch patency at 98% (177/180). Re-intervention was necessary for a total of six patients (13.6%).ConclusionsInner-branch aortic stent grafts provide a feasible option for the treatment of complex aortic pathologies, both elective (custom-made) and urgent (off-the-shelf). The technical success rate is high with acceptable short-term outcomes and moderate re-intervention rates comparable to existing platforms. Further follow-up will evaluate long-term outcomes.

Radiological reporting errors have a direct negative impact on patient treatment. The purpose of this study was to investigate the contribution of clinical information (CI) in radiological reporting of oncological imaging and the dependence on the radiologists’ experience level (EL). Sixty-four patients with several types of carcinomas and twenty patients without tumors were enrolled. Computed tomography datasets acquired in primary or follow-up staging were independently analyzed by three radiologists (R) with different EL (R1: 15 years; R2: 10 years, R3: 1 year). Reading was initially performed without and 3 months later with CI. Overall, diagnostic accuracy and sensitivity for primary tumor detection increased significantly when receiving CI from 77% to 87%; p = 0.01 and 73% to 83%; p = 0.01, respectively. All radiologists benefitted from CI; R1: 85% vs. 92%, p = 0.15; R2: 77% vs. 83%, p = 0.33; R3: 70% vs. 86%, p = 0.02. Overall, diagnostic accuracy and sensitivity for detecting lymphogenous metastases increased from 80% to 85% (p = 0.13) and 42% to 56% (p = 0.13), for detection of hematogenous metastases from 85% to 86% (p = 0.61) and 46% to 60% (p = 0.15). Specificity remained stable (>90%). Thus, CI in oncological imaging seems to be essential for correct radiological reporting, especially for residents, and should be available for the radiologist whenever possible.

Purpose: To evaluate the effect of contrast timing, contrast volume, and contrast flow rate on the image quality of pulmonary arteries in computed tomography angiography (CTA) and to assess if bolus-tracking region of interest (ROI) positioning in the left atrium, which is used for triple-rule-out CTA, allows for sufficient depiction of the pulmonary arteries., Methods: In this retrospective single-center study, data were collected for patients who underwent thoracic CTA during a specific period. Two groups of 121 patients each were created based on bolus-tracking ROI positioning in the main pulmonary artery or left atrium using propensity score matching. Image quality of the pulmonary arteries was evaluated using quantitative and qualitative scores. Subgroups were formed to examine the influence of contrast volume and flow rate. Two radiologists determined if pulmonary embolism was present, if pulmonary embolism could be excluded with certainty, and from which level pulmonary embolism could be excluded with certainty. Interrater reliability also was evaluated., Results: ROI positioning in the main pulmonary artery scored significantly higher compared with the left atrium. There was no significant difference in subgroups of patients who were examined with 60 mL or more contrast volume and less than 4 mL/s flow rate; scores were similar or better than in the overall study population. Pulmonary embolism was not able to be excluded with certainty for each 1 patient in these subgroups compared with a high percentage in the overall study population., Discussion: ROI positioning in the left atrium in combination with the 60 mL or more contrast volume and less than 4 mL/s flow rate does not adversely affect depiction of the pulmonary arteries compared with conventional ROI positioning in the main pulmonary artery., Conclusion: When using 60 mL or more contrast volume and less than 4 mL/s flow rate, ROI positioning in the left atrium, which is used in triple-rule-out CTA, is sufficient for the assessment of pulmonary arteries., (© 2023 American Society of Radiologic Technologists.)