scholarly journals Novel Insights of T2-Weighted Imaging: Significance for Discriminating Lung Cancer from Benign Pulmonary Nodules and Masses

Cancers ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 3713
Author(s):  
Katsuo Usuda ◽  
Shun Iwai ◽  
Aika Yamagata ◽  
Yoshihito Iijima ◽  
Nozomu Motono ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Pulmonary Nodule ◽  
Predictive Value ◽  
Signal Intensity ◽  
Diffusion Weighted Imaging ◽  
Contrast Ratio ◽  
Pulmonary Nodules ◽  
Cutoff Value ◽  
Lung Cancers ◽  
Diagnostic Capability

Diffusion-weighted imaging is useful for discriminating lung cancer from benign pulmonary nodules and masses (BPNMs), however the diagnostic capability is not perfect. The aim of this research was to clarify whether T2-weighted imaging (T2WI) is efficient in discriminating lung cancer from BPNMs, especially from pulmonary abscesses. A T2 contrast ratio (T2 CR) for a pulmonary nodule is defined as the ratio of T2 signal intensity of a pulmonary nodule divided by the T2 signal intensity of the rhomboid muscle. There were 52 lung cancers and 40 inflammatory BPNMs (mycobacteria disease 12, pneumonia 13, pulmonary abscess 9, other 6) and seven non-inflammatory BPNMs. The T2 CR (2.14 ± 0.63) of lung cancers was significantly lower than that (2.68 ± 1.04) of BPNMs (p = 0.0021). The T2 CR of lung cancers was significantly lower than that (2.93 ± 0.26) of pulmonary abscesses (p = 0.011). When the optical cutoff value of T2 CR was set as 2.44, the sensitivity was 0.827 (43/52), the specificity 0.596 (28/47), the accuracy 0.717 (71/99), the positive predictive value 0.694 (43/62), and the negative predictive value 0.757 (28/37). T2 CR of T2WI is useful in discriminating lung cancer from BPNMs. Pulmonary abscesses, which show strong restricted diffusion in DWI, can be differentiated from lung cancers using T2WI.

scholarly journals Combination Assessment of Diffusion-Weighted Imaging and T2-Weighted Imaging Is Acceptable for the Differential Diagnosis of Lung Cancer from Benign Pulmonary Nodules and Masses

Cancers ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1551
Author(s):  
Katsuo Usuda ◽  
Masahito Ishikawa ◽  
Shun Iwai ◽  
Yoshihito Iijima ◽  
Nozomu Motono ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Differential Diagnosis ◽  
Diffusion Coefficient ◽  
Diffusion Weighted Imaging ◽  
Contrast Ratio ◽  
Pulmonary Nodules ◽  
Diagnostic Ability ◽  
Lung Cancers ◽  
Apparent Diffusion ◽  
Diagnosis Of Lung Cancer

The purpose of this study is to determine whether the combination assessment of DWI and T2-weighted imaging (T2WI) improves the diagnostic ability for differential diagnosis of lung cancer from benign pulmonary nodules and masses (BPNMs). The optimal cut-off value (OCV) for differential diagnosis was set at 1.470 × 10−3 mm2/s for apparent diffusion coefficient (ADC), and at 2.45 for T2 contrast ratio (T2 CR). The ADC (1.24 ± 0.29 × 10−3 mm2/s) of lung cancer was significantly lower than that (1.69 ± 0.58 × 10−3 mm2/s) of BPNM. The T2 CR (2.01 ± 0.52) of lung cancer was significantly lower than that (2.74 ± 1.02) of BPNM. As using the OCV for ADC, the sensitivity was 83.9% (220/262), the specificity 63.4% (33/52), and the accuracy 80.6% (253/314). As using the OCV for T2 CR, the sensitivity was 89.7% (235/262), the specificity 61.5% (32/52), and the accuracy 85.0% (267/314). In 212 PNMs which were judged to be malignant by both DWI and T2WI, 203 PNMs (95.8%) were lung cancers. In 33 PNMs which were judged to be benign by both DWI and T2WI, 23 PNMs (69.7%) were BPNMs. The combined assessment of DWI and T2WI could judge PNMs more precisely and would be acceptable for differential diagnosis of PNMs.

scholarly journals Effect of a pulmonary nodule fact sheet on patient anxiety and knowledge: a quality improvement initiative

2018 ◽  
Vol 7 (3) ◽  
pp. e000437 ◽  
Author(s):  
Matthew T Koroscil ◽  
Mitchell H Bowman ◽  
Michael J Morris ◽  
Andrew J Skabelund ◽  
Andrew M Hersh
Keyword(s):  
Lung Cancer ◽  
Quality Improvement ◽  
Pulmonary Nodule ◽  
Early Stage ◽  
Pulmonary Nodules ◽  
Low Risk ◽  
Quality Improvement Initiative ◽  
Patient Anxiety ◽  
Patient Understanding ◽  
Fact Sheet

IntroductionThe utilisation of chest CT for the evaluation of pulmonary disorders, including low-dose CT for lung cancer screening, is increasing in the USA. As a result, the discovery of both screening-detected and incidental pulmonary nodules has become more frequent. Despite an overall low risk of malignancy, pulmonary nodules are a common cause of emotional distress among adult patients.MethodsWe conducted a multi-institutional quality improvement (QI) initiative involving 101 participants to determine the effect of a pulmonary nodule fact sheet on patient knowledge and anxiety. Males and females aged 35 years or older, who had a history of either screening-detected or incidental solid pulmonary nodule(s) sized 3–8 mm, were included. Prior to an internal medicine or pulmonary medicine clinic visit, participants were given a packet containing a pre-fact sheet survey, a pulmonary nodule fact sheet and a post-fact sheet survey.ResultsOf 101 patients, 61 (60.4%) worried about their pulmonary nodule at least once per month with 18 (17.8%) worrying daily. The majority 67/101 (66.3%) selected chemotherapy, chemotherapy and radiation, or radiation as the best method to cure early-stage lung cancer. Despite ongoing radiographic surveillance, 16/101 (15.8%) stated they would not be interested in an intervention if lung cancer was diagnosed. Following review of the pulmonary nodule fact sheet, 84/101 (83.2%) reported improved anxiety and 96/101 (95.0%) reported an improved understanding of their health situation. Patient understanding significantly improved from 4.2/10.0 to 8.1/10.0 (p<0.01).ConclusionThe incorporation of a standardised fact sheet for subcentimeter solid pulmonary nodules improves patient understanding and alleviates anxiety. We plan to implement pulmonary nodule fact sheets into the care of our patients with low-risk subcentimeter pulmonary nodules.

scholarly journals Malignant melanoma without primary, presenting as solitary pulmonary nodule: a case report

2021 ◽  
Vol 15 (1) ◽  
Author(s):  
George Tsaknis ◽  
Muhammad Naeem ◽  
Advitya Singh ◽  
Siddharth Vijayakumar
Keyword(s):  
Lung Cancer ◽  
Malignant Melanoma ◽  
Pulmonary Nodule ◽  
Solitary Pulmonary Nodule ◽  
Past History ◽  
White Male ◽  
Pulmonary Nodules ◽  
Metastatic Malignant Melanoma ◽  
Unknown Primary ◽  
Solitary Pulmonary Nodules

Abstract Background Solitary pulmonary nodules are the most common incidental finding on chest imaging. Their management is very well defined by several guidelines, with risk calculators for lung cancer being the gold standard. Solitary intramuscular metastasis combined with a solitary pulmonary nodule from malignant melanoma without a primary site is rare. Case presentation A 57-year-old white male was referred to our lung cancer service with solitary pulmonary nodule. After positron-emission tomography, we performed an ultrasound-guided core needle biopsy of an intramuscular solitary lesion, not identified on computed tomography scan, and diagnosed metastatic malignant melanoma. The solitary pulmonary nodule was resected and also confirmed metastatic melanoma. There was no primary skin lesion. The patient received oral targeted therapy and is disease-free 5 years later. Conclusions Clinicians dealing with solitary pulmonary nodules must remain vigilant for other extrathoracic malignancies even in the absence of obvious past history. Lung metastasectomy may have a role in metastatic malignant melanoma with unknown primary.

scholarly journals Mobile Low-Dose Computed Tomographic (LDCT) Scanning combined with Remote Reading: a feasible approach to lung cancer screening among rural population

2021 ◽  
Author(s):  
Bojiang Chen ◽  
Jun Shao ◽  
Jinghong Xian ◽  
Pengwei Ren ◽  
Wenxin Luo ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Screening ◽  
Rural Areas ◽  
Pulmonary Nodules ◽  
Lung Cancer Screening ◽  
Western China ◽  
Control Group ◽  
Local Hospital ◽  
Lung Cancers ◽  
Computed Tomographic

Abstract BackgroundLow-dose computed tomographic (LDCT) screening has been proven to be powerful in detecting lung cancers in early stage. However, it’s hard to carry out in less-developed regions in lacking of facilities and professionals. The feasibility and efficacy of mobile LDCT scanning combined with remote reading by experienced radiologists from superior hospital for lung cancer screening in deprived areas was explored in this study.MethodsA prospective cohort was conducted in rural areas of western China. Residents over 40 years old were invited for lung cancer screening by mobile LDCT scanning combined with remote image reading or local hospital-based LDCT screening. Rates of positive pulmonary nodules and detected lung cancers in the baseline were compared between the two groups.ResultsAmong 8073 candidates with preliminary response, 7251 eligibilities were assigned to the mobile LDCT with remote reading (n = 4527) and local hospital-based LDCT screening (n = 2724) for lung cancer. Basic characteristics of the subjects were almost similar in the two cohorts except that the mean age of participants in mobile group was relatively older than control (61.18 vs. 59.84 years old, P < 0.001). 1778 participants with mobile LDCT scans with remote reading (39.3%) revealed 2570 pulmonary nodules or mass, and 352 subjects in the control group (13.0%) were detected 472 ones (P < 0.001). Proportions of nodules less than 8 mm or subsolid were both more frequent in the mobile LDCT group (83.3% vs. 76.1%, 32.9% vs. 29.8%, respectively; both P < 0.05). In the baseline screening, 26 cases of lung cancer were identified in the mobile LDCT scanning with remote reading cohort, with a lung cancer detection rate of 0.57% (26/4527), which was significantly higher than control (4/2724 = 0.15%, P = 0.006). Moreover, 80.8% (21/26) of lung cancer patients detected by mobile CT with remote reading were in stage I, remarkedly higher than that of 25.0% in control (1/4, P = 0.020).ConclusionMobile LDCT combined with remote reading is probably a potential mode for lung cancer screening in rural areas.Trial registrationNo. of registration trial was ChiCTR-DDD-15007586 (http://www.chictr.org).

scholarly journals Clinically Applicable Deep Learning Strategy for Pulmonary Nodule Risk Prediction: Insights into HONORS

2020 ◽  
Author(s):  
Wenhui Lv ◽  
Yang Wang ◽  
Changsheng Zhou ◽  
Sheng Huang ◽  
Xiangming Fang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Deep Learning ◽  
Medical Errors ◽  
Pulmonary Nodule ◽  
Large Scale ◽  
Learning Algorithm ◽  
Pulmonary Nodules ◽  
Youden Index ◽  
List Type ◽  
Clinical Scenarios

AbstractBackground and PurposeLimited optimization was clinically applicable for reducing missed diagnosis, misdiagnosis and inter-reader variability in pulmonary nodule diagnosis. We aimed to propose a deep learning-based algorithm and a practical strategy to better stratify the risk of pulmonary nodules, thus reducing medical errors and optimizing the clinical workflow.Materials and MethodsA total of 2,348 pulmonary nodules (1,215 with lung cancer) containing screened nodules from National Lung Cancer Screening Trial (NLST) and incidentally detected nodules from Jinling Hospital (JLH) were used to train and evaluate a deep learning algorithm, Filter-guided pyramid network (FGP-NET). Internal and external test of FGP-NET were performed on two independent datasets (n=542). The performance of FGP-NET at Youden point which maximizing the Youden index was compared with 126 board-certificated radiologists. We further proposed Hierarchical Ordered Network ORiented Strategy (HONORS), which manipulates the emphasis either on sensitivity or specificity to target risk-stratified clinical scenarios, directly making decisions for some patients.ResultsFGP-NET achieved a high area under the curve (AUC) of 0.969 and 0.855 for internal and external testing, and was comparable or even outperformed the radiologists when considering sensitivity. HONORS-guided FGP-NET identified benign nodules with a high sensitivity (95.5%) in the screening scenario, and demonstrated satisfactory performance for the rest ambiguous nodules with 0.945 of AUC by the Youden point. FGP-NET also detected lung cancer with a high specificity of 94.5% in routine diagnostic scenario; an AUC of 0.809 was achieved for the rest nodules.ConclusionThe combination of HONORS and FGP-NET provides well-organized stratification for pulmonary nodules and also offers the potential for reducing medical errors.HighlightsPulmonary nodules were managed for both screening and diagnostic scenariosProposal of a hierarchical strategy for targeting risk-stratified clinical scenariosA large scale Human-deep learning contest for reliable performance evaluation

Diffusion-weighted imaging (DWI) signal intensity and distribution represent the amount of cancer cells and their distribution in primary lung cancer

2013 ◽  
Vol 37 (2) ◽  
pp. 265-272 ◽  
Author(s):  
Katsuo Usuda ◽  
Xi-Tong Zhao ◽  
Motoyasu Sagawa ◽  
Hirokazu Aikawa ◽  
Masakatsu Ueno ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Cells ◽  
Signal Intensity ◽  
Diffusion Weighted Imaging ◽  
Primary Lung Cancer ◽  
Diffusion Weighted

scholarly journals Whole-Lesion Apparent Diffusion Coefficient Histogram Analysis: Significance for Discriminating Lung Cancer from Pulmonary Abscess and Mycobacterial Infection

Cancers ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2720
Author(s):  
Katsuo Usuda ◽  
Shun Iwai ◽  
Aika Yamagata ◽  
Yoshihito Iijima ◽  
Nozomu Motono ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Pulmonary Nodules ◽  
Mycobacterial Infection ◽  
Resonance Imaging ◽  
Lung Cancers ◽  
Mycobacterial Infections ◽  
Single Slice ◽  
Apparent Diffusion ◽  
Weighted Magnetic Resonance Imaging

Diffusion-weighted magnetic resonance imaging (DWI) can differentiate malignant from benign pulmonary nodules. However, it is difficult to differentiate pulmonary abscesses and mycobacterial infections (PAMIs) from lung cancers because PAMIs show restricted diffusion in DWI. The study purpose is to establish the role of ADC histogram for differentiating lung cancer from PAMI. There were 41 lung cancers (25 adenocarcinomas, 16 squamous cell carcinomas), and 19 PAMIs (9 pulmonary abscesses, 10 mycobacterial infections). Parameters more than 60% of the area under the ROC curve (AUC) were ADC, maximal ADC, mean ADC, median ADC, most frequency ADC, kurtosis of ADC, and volume of lesion. There were significant differences between lung cancer and PAMI in ADC, mean ADC, median ADC, and most frequency ADC. The ADC (1.19 ± 0.29 × 10−3 mm2/s) of lung cancer obtained from a single slice was significantly lower than that (1.44 ± 0.54) of PAMI (p = 0.0262). In contrast, mean, median, or most frequency ADC of lung cancer which was obtained in the ADC histogram was significantly higher than the value of each parameter of PAMI. ADC histogram could discriminate PAMIs from lung cancers by showing that AUCs of several parameters were more than 60%, and that several parameters of ADC of PAMI were significantly lower than those of lung cancer. ADC histogram has the potential to be a valuable tool to differentiate PAMI from lung cancer.

Diffusion-weighted imaging in evaluating the efficacy of concurrent chemoradiotherapy in the treatment of non-small cell lung cancer

2018 ◽  
Vol 104 (3) ◽  
pp. 188-195 ◽  
Author(s):  
Hai-Dong Xu ◽  
Yu-Qin Zhang ◽  
Wei-Yu Shen ◽  
Zheng-Chun Mao
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Predictive Value ◽  
Diffusion Weighted Imaging ◽  
Concurrent Chemoradiotherapy ◽  
Tumor Regression ◽  
Small Cell ◽  
Small Cell Lung ◽  
Short Term ◽  
Term Efficacy

Objective: To explore the predictive value of diffusion-weighted imaging (DWI) in evaluating the short-term efficacy of concurrent chemoradiotherapy (CCRT) in the treatment of patients with non-small cell lung cancer (NSCLC). Methods: A total of 192 patients with NSCLC were selected and treated with CCRT. Dynamic contrast-enhanced magnetic resonance imaging combined with DWI was performed on all patients before and after CCRT treatment. Correspondingly, apparent diffusion coefficient (ADC) values were recorded before treatment (ADCpre), during treatment (ADCmid), and after treatment (ADCpost). Tumor response was evaluated as complete response (CR), partial response (PR), stable disease (SD), or progressive disease (PD). Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic power of quantitative DWI parameters in predicting the short-term efficacy of CCRT for patients with NSCLC. Results: There were 21 patients with CR, 82 with PR, 77 with SD, and 12 with PD. The ADCpre was negatively correlated with tumor regression rate, whereas ADCmid, ADCpost, and their respective change rates ∆ADCmid and ∆ADCpost were positively related to tumor regression rate. The ROC curve analysis suggested ADCpre = 1.38 × 10−3 mm2/s, ∆ADCmid = 14.14%, and ∆ADCpost = 20.39% as thresholds to predict the short-term efficacy of CCRT, with corresponding areas under the curve of 0.637, 0.743, and 0.752, respectively. Conclusions: These findings indicate that DWI provides promising predictive value in evaluating the short-term efficacy of CCRT in the treatment of patients with NSCLC.

Application “Lung Nodule" Software With Lungrads On Early Detection And Follow Up The Pulmonary Nodules By Lung Low Dose CT Findings

2020 ◽  
Author(s):  
Ha Hoang Thi Ngoc
Keyword(s):  
Lung Cancer ◽  
Early Detection ◽  
Pulmonary Nodule ◽  
Low Dose ◽  
False Negative ◽  
Lung Nodule ◽  
Pulmonary Nodules ◽  
Lung Cancer Mortality ◽  
Smoking History ◽  
Low Dose Ct

Background: A pulmonary nodule is defined as a rounded or irregular opacity, well or poorly defined, measuring up to 3 cm in diameter. Early detection the malignancy of nodules has a significant role in decreasing the mortality, increasing the survival time and consider as early diagnosis lung cancer. Content: The main risk factors are those of current or former smokers, aged 55 to 74 years with a smoking history of at least 1 pack-day. Low dose CT: Screening individuals with high risk of lung cancer by low dose CT scans could reduce lung cancer mortality by 20 percent compared to chest X-ray. Radiation dose has to maximum reduced but respect the rule of ALARA (As Low as Resonably Archivable). ACR-LungRADS 2014: Classification of American College of Radiology, LungRADS, is a newly application but showed many advantages in comparison with others classification such as increasing positive predict value (PPV), no result of false negative and cost effectiveness. “Lung nodule” was applied as a smart phone application in order to have a quickly evaluation, especially the malignancy and management face on a pulmonary nodule.

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