脾脏血管性病变与淋巴瘤CT鉴别诊断

目的 运用CT区分脾脏血管性病变与淋巴瘤。方法 回顾性分析20例经手术、穿刺病理学检查证实的脾脏病变的发病年龄、性别、脾脏指数、病变大小、数目、有无液化、钙化、强化幅度、强化方式等特征,并进行统计学分析。结果 20例脾脏病变中,11例血管性病变(6例海绵状血管瘤,3例窦岸细胞血管瘤,2例硬化性血管瘤样结节性转化),9例淋巴瘤;两组间发病年龄、病变大小、数目、有无液化、钙化等差异无统计学意义;两组间脾脏指数、动脉期强化幅度差异具有统计学意义(P＜0.05)。5例海绵状血管瘤呈不均匀性强化,1例呈渐进性填充式强化,2例窦岸细胞血管瘤呈“雀斑征”,1例硬化性血管瘤样结节性转化呈“辐轮征”;9例淋巴瘤实质部分均呈均匀、轻中度强化。结论 脾脏血管性病变与淋巴瘤CT表现不同,CT有助于明确诊断。     

Diagnosing pulmonary thromboembolism: Concerns and controversies

Pulmonary thromboembolism (PTE) is an important cause of mortality/morbidity even today despite advancement in clinical understanding as well as diagnostic facilities. Clinical diagnosis of PTE is often challenging because of nonspecific sign/symptoms. Adherence to clinical decision-making protocols and appropriate use of diagnostic modalities like computed tomography pulmonary angiography can resolve the diagnostic dilemma in most cases and help in the overall management of PTE. This article deals with various concerns as well as controversies surrounding accurate diagnosis of PTE as on date.     

A Proposal for an Alternative Approach to Particle Size Method Development During Early-Stage Small Molecule Pharmaceutical Development

Particle size analysis in the pharmaceutical industry has long been a source of debate regarding how best to define measurement accuracy; the degree to which the result of a measurement or calculation conforms to the true value. Defining a “true” value for the size of a particle can be challenging as the output of its measurement will differ because of variations in measurement approaches, instrumental differences and calculation methods. Consequently, for “real” particles, a universal “true” value does not exist and accuracy is therefore not a definable characteristic. Accordingly, precision is then a measure of the ability to reproducibly achieve a measurement of unknown relevance.This article proposes, in place of accuracy, a means to define the “appropriateness” of a measurement in line with the critical quality attributes (CQA) of the material being characterized. The decision as to whether the measurement is correct should involve a link to the CQA; that is, correlation should be demonstrated, without which the measured particle size cannot be defined as a critical material attribute.Correspondingly, methods should also be able to provide sufficient precision to demonstrate discrimination relating to variation in the CQA. The benefits and challenges of this approach are discussed.     

Abdominal lymph node recurrence from colorectal cancer: Resection should be considered as a curative treatment in patients with controlled disease

BackgroundLymph node recurrences (LNR) from colorectal cancer (CRC) still represent a therapeutic challenge, as standardized recommendations have yet to be established. The aim of this study was to analyze short- and long-term oncological outcomes following resection of LNR from CRC.MethodsAll patients with previously resected CRC who underwent histopathologically confirmed LNR resection in 3 tertiary referral centers between 2010 and 2017 were reviewed. Short- and long-term outcomes were analyzed, mainly recurrence-free and overall survival. Further recurrences following LNR resection were also analyzed.ResultsOverall, 18 patients were included. Primary CRC was left-sided in 16 (89%) patients, staged T3-4 in 15 (83%), N+ in 14 (78%) and presented with synchronous metastases in 8 (43%). Median time interval between primary CRC and LNR resections was 31 months. Performed lymphadenectomies were aortocaval (n = 10), pelvic (n = 7), in hepatic pedicle (n = 3) and mesenteric (n = 1). Four patients had associated liver metastases resection. Three (17%) presented with postoperative complications, of which one Clavien-Dindo 3. Fourteen (78%) patients presented with further recurrences after a mean delay of 9 months, with 36% of patients presenting with early (<6 months) recurrence. Five (36%) patients could undergo secondary recurrence resection and 3 (21%) patients radiotherapy. Median overall survival following LNR resection reached 44 months.ConclusionsCurrent results suggest that LNR resection is feasible and associated with improved survival, in selected patients. Longer time interval between primary CRC resection and LNR occurrence appeared to be a favorable prognostic factor whereas multisite recurrence appeared to be associated with impaired long-term survival.     

Outcomes after neoadjuvant or adjuvant chemotherapy for cT2-4N0-1 non–small cell lung cancer: A propensity-matched analysis

Objective

Comparative survival between neoadjuvant chemotherapy and adjuvant chemotherapy for patients with cT2-4N0-1M0 non–small cell lung cancer has not been extensively studied.

Limited benefit of CT scans in tuberculosis contact tracing

ObjectiveThe detection of abnormal findings on computed tomography (CT) scans of tuberculosis contacts combined with normal plain radiographs contributes to the early detection of tuberculosis. However, the benefit of the early detection of abnormalities for the prevention of active tuberculosis during follow-up requires evaluation.MethodWe conducted retrospective comparison of the existence of CT scans of tuberculosis contacts without findings of active tuberculosis on plain radiographs at a hospital in Japan. Results: Among 243 contacts without CT scans, five developed tuberculosis during follow-up. Among 229 contacts with CT scans, 24 were judged as targets of multi-drug therapy since their CT findings were suggestive of active tuberculosis at the time of the CT screening. Among 205 contacts judged as having latent tuberculous infection with CT screening, three developed tuberculosis diseases during follow-up. Conclusion: CT scans detected abnormal findings among contacts without abnormalities of plain radiographs but there were some contacts that developed tuberculosis diseases among those with contact investigation including CT scan. The value of CT is equivocal considering the balance of true treatment, overtreatment and harm of radiation.     

Deep learning with biopsy whole slide images for pretreatment prediction of pathological complete response to neoadjuvant chemotherapy in breast cancer：A multicenter study

IntroductionPredicting pathological complete response (pCR) for patients receiving neoadjuvant chemotherapy (NAC) is crucial in establishing individualized treatment. Whole-slide images (WSIs) of tumor tissues reflect the histopathologic information of the tumor, which is important for therapeutic response effectiveness. In this study, we aimed to investigate whether predictive information for pCR could be detected from WSIs.Materials and methodsWe retrospectively collected data from four cohorts of 874 patients diagnosed with biopsy-proven breast cancer. A deep learning pathological model (DLPM) was constructed to predict pCR using biopsy WSIs in the primary cohort, and it was then validated in three external cohorts. The DLPM could generate a deep learning pathological score (DLPs) for each patient; stromal tumor-infiltrating lymphocytes (TILs) were selected for comparison with DLPs.ResultsThe WSI feature-based DLPM showed good predictive performance with the highest area under the curve (AUC) of 0.72 among the cohorts. Alternatively, the combination of the DLPM and clinical characteristics offered a better prediction performance (AUC >0.70) in all cohorts. We also evaluated the performance of DLPM in three different breast subtypes with the best prediction for the triple-negative breast cancer (TNBC) subtype (AUC: 0.73). Moreover, DLPM combined with clinical characteristics and stromal TILs achieved the highest AUC in the primary cohort (AUC: 0.82) and validation cohort 1 (AUC: 0.80).ConclusionOur study suggested that WSIs integrated with deep learning could potentially predict pCR to NAC in breast cancer. The predictive performance will be improved by combining clinical characteristics. DLPs from DLPM can provide more information compared to stromal TILs for pCR prediction.     

Differentiating autoimmune pancreatitis from pancreatic ductal adenocarcinoma with CT radiomics features

PurposeThe purpose of this study was to determine whether computed tomography (CT)-based machine learning of radiomics features could help distinguish autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma (PDAC).Materials and MethodsEighty-nine patients with AIP (65 men, 24 women; mean age, 59.7 ± 13.9 [SD] years; range: 21–83 years) and 93 patients with PDAC (68 men, 25 women; mean age, 60.1 ± 12.3 [SD] years; range: 36–86 years) were retrospectively included. All patients had dedicated dual-phase pancreatic protocol CT between 2004 and 2018. Thin-slice images (0.75/0.5 mm thickness/increment) were compared with thick-slices images (3 or 5 mm thickness/increment). Pancreatic regions involved by PDAC or AIP (areas of enlargement, altered enhancement, effacement of pancreatic duct) as well as uninvolved parenchyma were segmented as three-dimensional volumes. Four hundred and thirty-one radiomics features were extracted and a random forest was used to distinguish AIP from PDAC. CT data of 60 AIP and 60 PDAC patients were used for training and those of 29 AIP and 33 PDAC independent patients were used for testing.ResultsThe pancreas was diffusely involved in 37 (37/89; 41.6%) patients with AIP and not diffusely in 52 (52/89; 58.4%) patients. Using machine learning, 95.2% (59/62; 95% confidence interval [CI]: 89.8–100%), 83.9% (52:67; 95% CI: 74.7–93.0%) and 77.4% (48/62; 95% CI: 67.0–87.8%) of the 62 test patients were correctly classified as either having PDAC or AIP with thin-slice venous phase, thin-slice arterial phase, and thick-slice venous phase CT, respectively. Three of the 29 patients with AIP (3/29; 10.3%) were incorrectly classified as having PDAC but all 33 patients with PDAC (33/33; 100%) were correctly classified with thin-slice venous phase with 89.7% sensitivity (26/29; 95% CI: 78.6–100%) and 100% specificity (33/33; 95% CI: 93–100%) for the diagnosis of AIP, 95.2% accuracy (59/62; 95% CI: 89.8–100%) and area under the curve of 0.975 (95% CI: 0.936–1.0).ConclusionsRadiomic features help differentiate AIP from PDAC with an overall accuracy of 95.2%.     

Pediatric cardiac computed tomography angiography: Expert consensus from the Filiale de Cardiologie Pédiatrique et Congénitale (FCPC) and the Société Française d’Imagerie Cardiaque et Vasculaire diagnostique et interventionnelle (SFICV)

This article was designed to provide a pediatric cardiac computed tomography angiography (CCTA) expert panel consensus based on opinions of experts of the Société Française d’Imagerie Cardiaque et Vasculaire diagnostique et interventionnelle (SFICV) and of the Filiale de Cardiologie Pédiatrique Congénitale (FCPC). This expert panel consensus includes recommendations for indications, patient preparation, CTA radiation dose reduction techniques, and post-processing techniques. The consensus was based on data from available literature (original papers, reviews and guidelines) and on opinions of a group of specialists with extensive experience in the use of CT imaging in congenital heart disease. In order to reach high potential and avoid pitfalls, CCTA in children with congenital heart disease requires training and experience. Moreover, pediatric cardiac CCTA protocols should be standardized to acquire optimal images in this population with the lowest radiation dose possible to prevent unnecessary radiation exposure. We also provided a suggested structured report and a list of acquisition protocols and technical parameters in relation to specific vendors.