Photon-counting CT in Thoracic Imaging: Early Clinical Evidence and Incorporation Into Clinical Practice.

Photon-counting CT (PCCT) is an emerging advanced CT technology that differs from conventional CT in its ability to directly convert incident x-ray photon energies into electrical signals. The detector design also permits substantial improvements in spatial resolution and radiation dose efficiency and allows for concurrent high-pitch and high-temporal-resolution multienergy imaging. This review summarizes (a) key differences in PCCT image acquisition and image reconstruction compared with conventional CT; (b) early evidence for the clinical benefit of PCCT for high-spatial-resolution diagnostic tasks in thoracic imaging, such as assessment of airway and parenchymal diseases, as well as benefits of high-pitch and multienergy scanning; (c) anticipated radiation dose reduction, depending on the diagnostic task, and increased utility for routine low-dose thoracic CT imaging; (d) adaptations for thoracic imaging in children; (e) potential for further quantitation of thoracic diseases; and (f) limitations and trade-offs. Moreover, important points for conducting and interpreting clinical studies examining the benefit of PCCT relative to conventional CT and integration of PCCT systems into multivendor, multispecialty radiology practices are discussed.

Quantitative CT and machine learning classification of fibrotic interstitial lung diseases.

OBJECTIVES: To evaluate quantitative computed tomography (QCT) features and QCT feature-based machine learning (ML) models in classifying interstitial lung diseases (ILDs). To compare QCT-ML and deep learning (DL) models' performance. METHODS: We retrospectively identified 1085 patients with pathologically proven usual interstitial pneumonitis (UIP), nonspecific interstitial pneumonitis (NSIP), and chronic hypersensitivity pneumonitis (CHP) who underwent peri-biopsy chest CT. Kruskal-Wallis test evaluated QCT feature associations with each ILD. QCT features, patient demographics, and pulmonary function test (PFT) results trained eXtreme Gradient Boosting (training/validation set n = 911) yielding 3 models: M1 = QCT features only; M2 = M1 plus age and sex; M3 = M2 plus PFT results. A DL model was also developed. ML and DL model areas under the receiver operating characteristic curve (AUC) and 95% confidence intervals (CIs) were compared for multiclass (UIP vs. NSIP vs. CHP) and binary (UIP vs. non-UIP) classification performances. RESULTS: The majority (69/78 [88%]) of QCT features successfully differentiated the 3 ILDs (adjusted p ≤ 0.05). All QCT-ML models achieved higher AUC than the DL model (multiclass AUC micro-averages 0.910, 0.910, 0.925, and 0.798 and macro-averages 0.895, 0.893, 0.925, and 0.779 for M1, M2, M3, and DL respectively; binary AUC 0.880, 0.899, 0.898, and 0.869 for M1, M2, M3, and DL respectively). M3 demonstrated statistically significant better performance compared to M2 (∆AUC: 0.015, CI: [0.002, 0.029]) for multiclass prediction. CONCLUSIONS: QCT features successfully differentiated pathologically proven UIP, NSIP, and CHP. While QCT-based ML models outperformed a DL model for classifying ILDs, further investigations are warranted to determine if QCT-ML, DL, or a combination will be superior in ILD classification. KEY POINTS: • Quantitative CT features successfully differentiated pathologically proven UIP, NSIP, and CHP. • Our quantitative CT-based machine learning models demonstrated high performance in classifying UIP, NSIP, and CHP histopathology, outperforming a deep learning model. • While our quantitative CT-based machine learning models performed better than a DL model, additional investigations are needed to determine whether either or a combination of both approaches delivers superior diagnostic performance.

Quantitative CT Analysis of Diffuse Lung Disease.

Quantitative analysis of thin-section CT of the chest has a growing role in the clinical evaluation and management of diffuse lung diseases. This heterogeneous group includes diseases with markedly different prognoses and treatment options. Quantitative tools can assist in both accurate diagnosis and longitudinal management by improving characterization and quantification of disease and increasing the reproducibility of disease severity assessment. Furthermore, a quantitative index of disease severity may serve as a useful tool or surrogate endpoint in evaluating treatment efficacy. The authors explore the role of quantitative imaging tools in the evaluation and management of diffuse lung diseases. Lung parenchymal features can be classified with threshold, histogram, morphologic, and texture-analysis-based methods. Quantitative CT analysis has been applied in obstructive, infiltrative, and restrictive pulmonary diseases including emphysema, cystic fibrosis, asthma, idiopathic pulmonary fibrosis, hypersensitivity pneumonitis, connective tissue-related interstitial lung disease, and combined pulmonary fibrosis and emphysema. Some challenges limiting the development and practical application of current quantitative analysis tools include the quality of training data, lack of standard criteria to validate the accuracy of the results, and lack of real-world assessments of the impact on outcomes. Artifacts such as patient motion or metallic beam hardening, variation in inspiratory effort, differences in image acquisition and reconstruction techniques, or inaccurate preprocessing steps such as segmentation of anatomic structures may lead to inaccurate classification. Despite these challenges, as new techniques emerge, quantitative analysis is developing into a viable tool to supplement the traditional visual assessment of diffuse lung diseases and to provide decision support regarding diagnosis, prognosis, and longitudinal evaluation of disease. ©RSNA, 2019.

Can MRI contribute to pulmonary nodule analysis?

BACKGROUND: There is no accurate method distinguishing different types of pulmonary nodules. PURPOSE: To investigate whether multiparametric 3T MRI biomarkers can distinguish malignant from benign pulmonary nodules, differentiate different types of neoplasms, and compare MRI-derived measurements with values from commonly used noninvasive imaging modalities. STUDY TYPE: Prospective. SUBJECTS: Sixty-eight adults with pulmonary nodules undergoing resection. SEQUENCES: Respiratory triggered diffusion-weighted imaging (DWI), periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) fat saturated T2 -weighted imaging, T1 -weighted 3D volumetric interpolated breath-hold examination (VIBE) using CAIPIRINHA (controlled aliasing in parallel imaging results in a higher acceleration). ASSESSMENT/STATISTICS: Apparent diffusion coefficient (ADC), T1 , T2 , T1 and T2 normalized to muscle (T1 /M and T2 /M), and dynamic contrast enhancement (DCE) values were compared with histology to determine whether they could distinguish malignant from benign nodules and discern primary from secondary malignancies using logistic regression. Predictability of primary neoplasm types was assessed using two-sample t-tests. MRI values were compared with positron emission tomography / computed tomography (PET/CT) to examine if they correlated with standardized uptake value (SUV) or CT Hounsfield unit (HU). Intra- and interreader agreements were assessed using intraclass correlations. RESULTS: Forty-nine of 74 nodules were malignant. There was a significant association between ADC and malignancy (odds ratio 4.47, P < 0.05). ADC ≥1.3 µm2 /ms predicted malignancy. ADC, T1 , and T2 together predicted malignancy (P = 0.003). No MRI parameter distinguished primary from metastatic neoplasms. T2 predicted PET positivity (P = 0.016). T2 and T1 /M correlated with SUV (P < 0.05). Of 18 PET-negative malignant nodules, 12 (67%) had an ADC ≥1.3 µm2 /ms. With the exception of T2 , all noncontrast MRI parameters distinguished adenocarcinomas from carcinoid tumors (P < 0.05). T1 , T2 , T1 /M, and T2 /M correlated with HU and therefore can predict nodule density. Combined with ADC, washout enhancement, arrival time (AT), peak enhancement intensity (PEI), Ktrans , Kep , Ve collectively were predictive of malignancy (P = 0.012). Combined washin, washout, time to peak (TTP), AT, and PEI values predicted malignancy (P = 0.043). There was good observer agreement for most noncontrast MRI biomarkers. DATA CONCLUSION: MRI can contribute to pulmonary nodule analysis. Multiparametric MRI might be better than individual MRI biomarkers in pulmonary nodule risk stratification. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018.

Lung Adenocarcinoma: Correlation of Quantitative CT Findings with Pathologic Findings.

Purpose To identify the ability of computer-derived three-dimensional (3D) computed tomographic (CT) segmentation techniques to help differentiate lung adenocarcinoma subtypes. Materials and Methods This study had institutional research board approval and was HIPAA compliant. Pathologically classified resected lung adenocarcinomas (n = 41) with thin-section CT data were identified. Two readers independently placed over-inclusive volumes around nodules from which automated computer measurements were generated: mass (total mass) and volume (total volume) of the nodule and of any solid portion, in addition to the solid percentage of the nodule volume (percentage solid volume) or mass (percentage solid mass). Interobserver agreement and differences in measurements among pathologic entities were evaluated by using t tests. A multinomial logistic regression model was used to differentiate the probability of three diagnoses: invasive non-lepidic-predominant adenocarcinoma (INV), lepidic-predominant adenocarcinoma (LPA), and adenocarcinoma in situ (AIS)/minimally invasive adenocarcinoma (MIA). Results Mean percentage solid volume of INV was 35.4% (95% confidence interval [CI]: 26.2%, 44.5%)-higher than the 14.5% (95% CI: 10.3%, 18.7%) for LPA (P = .002). Mean percentage solid volume of AIS/MIA was 8.2% (95% CI: 2.7%, 13.7%) and had a trend toward being lower than that for LPA (P = .051). Accuracy of the model based on total volume and percentage solid volume was 73.2%; accuracy of the model based on total mass and percentage solid mass was 75.6%. Conclusion Computer-assisted 3D measurement of nodules at CT had good reproducibility and helped differentiate among subtypes of lung adenocarcinoma. (©) RSNA, 2016.

Evaluation of Patient Tolerance and Small-Bowel Distention With a New Small-Bowel Distending Agent for Enterography.

OBJECTIVE: The objective of our study was to compare a flavored beverage containing a thickening agent for enterography with a low-Hounsfield-value barium suspension for side effects, taste, subjects' willingness to repeat the drinking protocol, and small-bowel distention. SUBJECTS AND METHODS: The following five drinking protocols were administered to 10 volunteers: 1000 mL of flavored beverage followed by 350 mL of water, 1500 mL of flavored beverage, 900 mL of low-Hounsfield-value barium suspension followed by 450 mL of water, 1350 mL of low-Hounsfield-value barium suspension followed by 150 mL of water, and 1500 mL of water. MR images were obtained 50 and 60 minutes after initiation of drinking. Subjects completed a questionnaire evaluating the side effects, the taste of the drink, and their willingness to repeat the drinking protocol. Reviewers assigned scores evaluating small-bowel distention and ranked the examinations in order of preference. RESULTS: There was no significant difference in nausea or vomiting among the protocols (p = 0.20 and 0.42, respectively), but larger volumes of flavored beverage and low-Hounsfield-value barium suspension resulted in more cramping and diarrhea (p = 0.001 and 0.002, respectively). The taste of the low-Hounsfield-value barium suspension was rated the worst (p < 0.0001). The subjects' willingness to repeat the drinking protocol was highest for the 1000 mL of flavored beverage or water alone (p < 0.05). There were no significant differences in subjective small-bowel distention except that water was rated the worst by two of the three readers (p < 0.02). There was no significant difference in the diameter of the most dis-tended small bowel for any segment or reader (p > 0.23). CONCLUSION: A flavored beverage containing a thickening agent has a similar side effect profile and results in equivalent small-bowel distention compared with a low-Hounsfield-value barium suspension, but subjects rate taste and their willingness to repeat the drinking protocol higher for this new agent.

Imaging of Solid Pulmonary Nodules.

Early detection with accurate classification of solid pulmonary nodules is critical in reducing lung cancer morbidity and mortality. Computed tomography (CT) remains the most widely used imaging examination for pulmonary nodule evaluation; however, other imaging modalities, such as PET/CT and MRI, are increasingly used for nodule characterization. Current advances in solid nodule imaging are largely due to developments in machine learning, including automated nodule segmentation and computer-aided detection. This review explores current multi-modality solid pulmonary nodule detection and characterization with discussion of radiomics and risk prediction models.

Long-term prognosis analysis of surgical therapy for bilateral synchronous multiple primary lung cancer: a follow-up of 293 cases.

Background: Bilateral synchronous multiple primary lung cancer (BSMPLC) presents significant clinical challenges due to its unique characteristics and prognosis. Understanding the risk factors that influence overall survival (OS) and recurrence-free survival (RFS) is crucial for optimizing therapeutic strategies for BSMPLC patients. Methods: We retrospectively analyzed clinical characteristics and treatment outcomes of 293 patients with BSMPLC who underwent surgical treatment between January 2010 and July 2017. Results: The 10-year OS and RFS rates were 96.1% and 92.8%, respectively. Preoperative forced expiratory volume in 1 second (FEV1) ≥70% [hazard ratio (HR), 0.214; 95% confidence interval (CI): 0.053 to 0.857], identical pathology types (HR, 9.726; 95% CI: 1.886 to 50.151), largest pT1 (HR, 7.123; 95% CI: 2.663 to 19.055), and absence of lymphovascular invasion (LVI; HR, 7.021; 95% CI: 1.448 to 34.032) emerged as independent predictors of improved OS. Moreover, the sum of tumor sizes less than or equal to 3 cm (HR, 6.229; 95% CI: 1.411 to 27.502) and absence of pleural invasion (HR, 3.442; 95% CI: 1.352 to 8.759) were identified as independent predictors of enhanced RFS. The presence or absence of residual nodules after bilateral surgery did not influence patients' OS (P=0.987) and RFS (P=0.054). Conclusions: Patients with BSMPLC who underwent surgery generally had a favorable prognosis. Whether or not to remove all nodules bilaterally does not affect the patient's long-term prognosis, suggesting the need for an individualized surgical approach.

Recent Advancements in Computed Tomography Assessment of Fibrotic Interstitial Lung Diseases.

Interstitial lung disease (ILD) is a heterogeneous group of disorders with complex and varied imaging manifestations and prognosis. High-resolution computed tomography (HRCT) is the current standard-of-care imaging tool for ILD assessment. However, visual evaluation of HRCT is limited by interobserver variation and poor sensitivity for subtle changes. Such challenges have led to tremendous recent research interest in objective and reproducible methods to examine ILDs. Computer-aided CT analysis to include texture analysis and machine learning methods have recently been shown to be viable supplements to traditional visual assessment through improved characterization and quantification of ILDs. These quantitative tools have not only been shown to correlate well with pulmonary function tests and patient outcomes but are also useful in disease diagnosis, surveillance and management. In this review, we provide an overview of recent computer-aided tools in diagnosis, prognosis, and longitudinal evaluation of fibrotic ILDs, while outlining some of the pitfalls and challenges that have precluded further advancement of these tools as well as potential solutions and further endeavors.

Combined Pulmonary Fibrosis and Emphysema: A Narrative Review.

Combined pulmonary fibrosis and emphysema (CPFE) syndrome refers to co-occurrence of two disease processes in the lung that can be difficult to diagnose but is associated with high morbidity and mortality burden. Diagnosis of CPFE is challenging because the two diseases can counterbalance respective impairments resulting in deceivingly normal-appearing chest radiography and spirometry in a dyspneic patient. Although an international committee published the terminology and definitions of CPFE in 2022, consensus on exact diagnostic criteria and optimal management strategy is yet to be determined. Herein, we provide a narrative review summarizing the literature on CPFE from 1990 to 2022, including historical background, epidemiology, pathogenesis, clinical features, imaging and pulmonary function findings, diagnosis, prognosis, complications, and treatment. Although CPFE was initially conceived as a variant presentation of idiopathic pulmonary fibrosis, it has been recognized to occur in patients with a wide variety of interstitial lung diseases, including connective tissue disease-associated interstitial lung diseases, and hypersensitivity pneumonitis. The affected patients have a heightened risk for pulmonary hypertension and lung cancer. Clinicians need to recognize the characteristic presenting features of CPFE along with prognostic implications of this entity.

Anatomic Approach to Common and Uncommon Manifestations of Thoracic Leukemias with Radiologic-Pathologic Correlation.

Leukemias are hematopoietic malignancies characterized by the production of abnormal leukocytes in the bone marrow. Clinical manifestations arise from either bone marrow suppression or leukemic organ infiltration. Lymphadenopathy is the most common direct manifestation of intrathoracic leukemia. However, leukemic cells may also infiltrate the lungs, pleura, heart, bones, and soft tissues. Pulmonary complications in patients with leukemia typically include pneumonia, hemorrhage, pulmonary edema, and sequelae of leukemia treatment. However, pulmonary abnormalities can also be related directly to leukemia, including leukemic pulmonary infiltration. The direct, non-treatment-related effects of leukemia on intrathoracic structures will be the focus of this imaging essay. Given the typical anatomic approach for image interpretation, an organ-based depiction of common and less common intrathoracic findings directly caused by leukemic involvement is presented, emphasizing imaging findings with pathologic correlations. Keywords: Leukemia, Pulmonary, Thorax, Soft Tissues/Skin, Hematologic, Bone Marrow © RSNA, 2023.

The dynamic contrast enhanced-magnetic resonance imaging and diffusion-weighted imaging features of alveolar soft part sarcoma.

Background: Alveolar soft part sarcoma (ASPS) is a rare type of soft tissue sarcoma that predominantly affects adolescents and young adults. Early diagnosis of ASPS is crucial for optimal therapeutic planning and improving prognosis, but its diagnostic features are not well delineated. This study aimed to retrospectively analyze the imaging features of ASPS with an emphasis on the dynamic contrast-enhanced-magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI) findings to identify imaging findings that might suggest the diagnosis to radiologists. Methods: The imaging features of 34 patients with pathologically proven limb ASPS were retrospectively analyzed. A total of 23 underwent DCE-MRI, and 12 underwent DWI. Results: Among the 34 cases of ASPS, 31 tumors were in the lower extremities, and 3 were in the upper extremities. The maximum tumor diameters ranged from 3.0 to 19.4 cm (mean, 8.7±3.96 cm). A total of 28 cases had well-defined borders. The masses demonstrated heterogeneous high signal intensity on T2-weighted imaging (T2WI) and the fat-suppressed (FS) T2WI sequence and slight hyperintensity on T1-weighted imaging (T1WI). A total of 25 lesions had thin hypointense bands on T1WI and T2WI. Intra- and peri-tumoral tubular areas of flow void were exhibited on both T1WI and T2WI in all cases. A total of 12 cases showed a high signal on DWI, and the mean apparent diffusion coefficient (ADC) value was (0.86±0.07)×10-3 mm2/s [range, (0.6-1.4)×10-3 mm2/s]. Persistent remarkable enhancement of the lesion was displayed on contrast-enhanced scans. The time-intensity curves (TICs) of 23 masses showed early arterial enhancement and slow washout of contrast. Conclusions: ASPS most commonly presents in the lower extremities of adolescents or young adults. Hyperintense T1WI, T2WI, and DWI signals, low ADC, flow voids, early arterial enhancement are frequent MRI features.

DIPNECH: pragmatic approach, uncertainties, notable associations, and a proposal for an improved definition.

Diffuse idiopathic pulmonary neuroendocrine cell hyperplasia (DIPNECH) is a rare, but increasingly recognized entity that primarily affects middle-aged and elderly women. It is characterized by abnormal proliferation of pulmonary neuroendocrine cells (PNECs) and is considered a preinvasive lesion for carcinoid tumorlets/tumors. Sometimes, DIPNECH is accompanied by constrictive bronchiolitis which usually manifests as chronic cough and/or dyspnea, along with airflow limitation on spirometry. The telltale imaging sign of DIPNECH is the presence of multiple noncalcified pulmonary nodules and mosaic attenuation on CT. However, these clinico-radiologic features of DIPNECH are characteristic but nonspecific; thus, histopathologic confirmation is usually necessary. DIPNECH has an indolent course and only rarely leads to respiratory failure or death; progression to overt neuroendocrine tumor (carcinoid) of the lung occurs in a minority of patients. Of available therapies, somatostatin analogs and mechanistic target of rapamycin inhibitors are the most promising. In this review, we provide an update regarding the diagnosis and management of DIPNECH and describe critical gaps in our understanding of this entity, including the central terms 'diffuse' and 'idiopathic.' We also summarize the inconsistencies in definitions employed by recent studies and discuss the pitfalls of the DIPNECH definitions proposed by the World Health Organization in 2021. In this context, we propose an objective and reproducible radio-pathologic case definition intended for implementation in the research realm and seeks to enhance homogeneity across cohorts. Furthermore, we discuss aspects of PNECs biology which suggest that PNEC hyperplasia may contribute to the pathogenesis of phenotypes of lung disease aside from constrictive bronchiolitis and carcinoid tumorlets/tumors. Finally, we steer attention to some of the most pressing and impactful research questions awaiting to be unraveled.

Improved efficiency of CT interpretation using an automated lung nodule matching program.

OBJECTIVE: The purpose of this study was to assess the impact of an automated program on improvement in lung nodule matching efficiency. MATERIALS AND METHODS: Four thoracic radiologists independently reviewed two serial chest CT examinations from each of 57 patients. Each radiologist performed timed manual lung nodule matching. After 6 weeks, all radiologists independently repeated the timed matching portion using an automated nodule matching program. The time required for manual and automated matching was compared. The impact of nodule size and number on matching efficiency was determined. RESULTS: An average of 325 (range, 244-413) noncalcified solid pulmonary nodules was identified. Nodule matching was significantly faster with the automated program irrespective of the interpreting radiologist (p < 0.0001 for each). The maximal time saved with automated matching was 11.4 minutes (mean, 2.3 ± 2.0 minutes). Matching was faster in 56 of 57 cases (98.2%) for three readers and in 46 of 57 cases (80.7%) for one reader. There were no differences among readers with respect to the mean time saved per matched nodule (p > 0.5). The automated program achieved 90%, 90%, 79%, and 92% accuracy for the four readers. The improvement in efficiency for a given patient using the automated technique was proportional to the number of matched nodules (p < 0.0001) and inversely proportional to nodule size (p < 0.05). CONCLUSION: Use of the automated lung nodule matching program significantly improves diagnostic efficiency. The time saved is proportionate to the number of nodules identified and inversely proportional to nodule size. Adoption of such a program should expedite CT examination interpretation and improve report turnaround time.