Use of a radiology tool for the diagnosis of pulmonary fibrosis.

OBJECTIVE: The purpose of this paper was to perform an exploratory reader study to assess the utility of a web-based application in assisting non-chest radiologist in correctly diagnosing the radiographic pattern of pulmonary fibrosis. METHODS: Three non-chest radiologists with 5 to 20 years of experience individually reviewed 3 rounds of randomly chosen chest CT scans (round 1: 100 scans, round 2: 50 scans, round 3: 25 scans) from a list of patients with established diagnosis of pulmonary fibrosis. In round 1, radiologists were asked to directly record their diagnosis for the pattern of fibrosis. In round 2 and 3 they were asked to review for features provided in a web-based application and provide diagnosis based on the most likely predicted diagnosis from the application. There was an approximate 1-month interval and relevant tutorials were provided between each round. Diagnosis accuracy is reported by readers at each round. RESULTS: The overall accuracy increased from 63 % (n = 188/299) in round 1 to 74 % in round 3 (n = 52/70) (p = 0.0265). Difficulty in recognition of mosaic attenuation and homogeneous has led to misdiagnosis. Refining the definition for feature homogeneous increased the diagnosis accuracy of NSIP from 42 % (n = 20/48) in round 2 to 65 % (n = 24/37) in round 3(p = 0.0179). The Fleiss Kappa across readers varied from Round 1 to Round 3 with values 0.36 to 0.42. CONCLUSIONS: Using the web-based application with refined definition for feature homogeneous helps to improve the non-subspecialty radiologist's accuracy in diagnosing different types of fibrosis.

Breast Collagen Organization: Variance by Patient Age and Breast Quadrant.

Breast density is an important marker for increased breast cancer risk, but the ideal marker would be more specific. Breast compactness, which reflects the focal density of collagen fibers, parallels breast cancer occurrence being highest in the upper outer quadrants of the breast. In addition, it peaks during the same time frame as breast cancer in women. Improved biomarkers for breast cancer risk could pave the way for patient-specific preventive strategies.

Surgical management of pleural complications in lymphangioleiomyomatosis.

OBJECTIVE: Lymphangioleiomyomatosis (LAM) is a rare cystic lung disease occurring primarily in women. Pneumothorax and chylothorax are common pleural complications in LAM. We aim to explore various options in the surgical management of pleural disease in LAM. METHODS: A retrospective chart review of all patients at the Center for LAM and Rare Lung Diseases at Columbia University was performed, and date, type, and indication for surgical procedure were collected. All patients with any cystic lung disease seen between January 1, 2000, and March 1, 2023, were included in the database. RESULTS: The charts for 326 patients with possible LAM were reviewed, including 213 with confirmed LAM and 113 women with cystic lung disease consistent suspected to be LAM were reviewed. A total of 40.5% underwent surgical procedures at our institution or at referring hospitals. A total of 15.6% of patients underwent surgical lung biopsies. A total of 16.6% had a history of pneumothoraces, of whom 79.6% underwent chemical and/or mechanical pleurodesis, 14.8% required pleurectomy, and 7.4% were discharged with tunneled indwelling pleural catheters. We found that 5.6% of confirmed LAM patients have history of chylothorax, with thoracic duct ligation, thoracic duct embolization, pleurodesis, and pleurodesis with long-term tunneled indwelling pleural catheter placement all used as treatment strategies. CONCLUSIONS: Here we demonstrate the significant burden of pleural disease in patients with LAM. It is imperative that thoracic surgeons understand the high incidence of pneumothorax in this patient population. Tunneled indwelling pleural catheters are underutilized but provide long-term options for chylous management with long-term mechanical pleurodesis and a decrease in hospital length of stay.

Radiology of fibrosis. Part I: Thoracic organs.

Sustained injury from factors such as hypoxia, infection, or physical damage may provoke improper tissue repair and the anomalous deposition of connective tissue that causes fibrosis. This phenomenon may take place in any organ, ultimately leading to their dysfunction and eventual failure. Tissue fibrosis has also been found to be central in both the process of carcinogenesis and cancer progression. Thus, its prompt diagnosis and regular monitoring is necessary for implementing effective disease-modifying interventions aiming to reduce mortality and improve overall quality of life. While significant research has been conducted on these subjects, a comprehensive understanding of how their relationship manifests through modern imaging techniques remains to be established. This work intends to provide a comprehensive overview of imaging technologies relevant to the detection of fibrosis affecting thoracic organs as well as to explore potential future advancements in this field.

Radiology of fibrosis part II: abdominal organs.

Fibrosis is the aberrant process of connective tissue deposition from abnormal tissue repair in response to sustained tissue injury caused by hypoxia, infection, or physical damage. It can affect almost all organs in the body causing dysfunction and ultimate organ failure. Tissue fibrosis also plays a vital role in carcinogenesis and cancer progression. The early and accurate diagnosis of organ fibrosis along with adequate surveillance are helpful to implement early disease-modifying interventions, important to reduce mortality and improve quality of life. While extensive research has already been carried out on the topic, a thorough understanding of how this relationship reveals itself using modern imaging techniques has yet to be established. This work outlines the ways in which fibrosis shows up in abdominal organs and has listed the most relevant imaging technologies employed for its detection. New imaging technologies and developments are discussed along with their promising applications in the early detection of organ fibrosis.

Combined expert-in-the-loop-random forest multiclass segmentation U-net based artificial intelligence model: evaluation of non-small cell lung cancer in fibrotic and non-fibrotic microenvironments.

BACKGROUND: The tumor microenvironment (TME) plays a key role in lung cancer initiation, proliferation, invasion, and metastasis. Artificial intelligence (AI) methods could potentially accelerate TME analysis. The aims of this study were to (1) assess the feasibility of using hematoxylin and eosin (H&E)-stained whole slide images (WSI) to develop an AI model for evaluating the TME and (2) to characterize the TME of adenocarcinoma (ADCA) and squamous cell carcinoma (SCCA) in fibrotic and non-fibrotic lung. METHODS: The cohort was derived from chest CT scans of patients presenting with lung neoplasms, with and without background fibrosis. WSI images were generated from slides of all 76 available pathology cases with ADCA (n = 53) or SCCA (n = 23) in fibrotic (n = 47) or non-fibrotic (n = 29) lung. Detailed ground-truth annotations, including of stroma (i.e., fibrosis, vessels, inflammation), necrosis and background, were performed on WSI and optimized via an expert-in-the-loop (EITL) iterative procedure using a lightweight [random forest (RF)] classifier. A convolution neural network (CNN)-based model was used to achieve tissue-level multiclass segmentation. The model was trained on 25 annotated WSI from 13 cases of ADCA and SCCA within and without fibrosis and then applied to the 76-case cohort. The TME analysis included tumor stroma ratio (TSR), tumor fibrosis ratio (TFR), tumor inflammation ratio (TIR), tumor vessel ratio (TVR), tumor necrosis ratio (TNR), and tumor background ratio (TBR). RESULTS: The model's overall classification for precision, sensitivity, and F1-score were 94%, 90%, and 91%, respectively. Statistically significant differences were noted in TSR (p = 0.041) and TFR (p = 0.001) between fibrotic and non-fibrotic ADCA. Within fibrotic lung, statistically significant differences were present in TFR (p = 0.039), TIR (p = 0.003), TVR (p = 0.041), TNR (p = 0.0003), and TBR (p = 0.020) between ADCA and SCCA. CONCLUSION: The combined EITL-RF CNN model using only H&E WSI can facilitate multiclass evaluation and quantification of the TME. There are significant differences in the TME of ADCA and SCCA present within or without background fibrosis. Future studies are needed to determine the significance of TME on prognosis and treatment.

Radiology of fibrosis part III: genitourinary system.

Fibrosis is a pathological process involving the abnormal deposition of connective tissue, resulting from improper tissue repair in response to sustained injury caused by hypoxia, infection, or physical damage. It can impact any organ, leading to their dysfunction and eventual failure. Additionally, tissue fibrosis plays an important role in carcinogenesis and the progression of cancer.Early and accurate diagnosis of organ fibrosis, coupled with regular surveillance, is essential for timely disease-modifying interventions, ultimately reducing mortality and enhancing quality of life. While extensive research has already been carried out on the topics of aberrant wound healing and fibrogenesis, we lack a thorough understanding of how their relationship reveals itself through modern imaging techniques.This paper focuses on fibrosis of the genito-urinary system, detailing relevant imaging technologies used for its detection and exploring future directions.

TGF-ß signaling: critical nexus of fibrogenesis and cancer.

The transforming growth factor-beta (TGF-ß) signaling pathway is a vital regulator of cell proliferation, differentiation, apoptosis, and extracellular matrix production. It functions through canonical SMAD-mediated processes and noncanonical pathways involving MAPK cascades, PI3K/AKT, Rho-like GTPases, and NF-κB signaling. This intricate signaling system is finely tuned by interactions between canonical and noncanonical pathways and plays key roles in both physiologic and pathologic conditions including tissue homeostasis, fibrosis, and cancer progression. TGF-ß signaling is known to have paradoxical actions. Under normal physiologic conditions, TGF-ß signaling promotes cell quiescence and apoptosis, acting as a tumor suppressor. In contrast, in pathological states such as inflammation and cancer, it triggers processes that facilitate cancer progression and tissue remodeling, thus promoting tumor development and fibrosis. Here, we detail the role that TGF-ß plays in cancer and fibrosis and highlight the potential for future theranostics targeting this pathway.

Can Hounsfield units on chest CT characterize breast nodules as cystic or solid?

We report the results of our retrospective analysis of the ability of standard chest computed tomography (CT) scans to correctly differentiate cystic from solid lesions. MModal Catalyst identified 27 women who had an ultrasound of the breast that was recommended because of a chest CT finding between January 1, 2010, and December 31, 2017. All images were reviewed by a radiologist fellowship trained in both breast imaging and cardiothoracic radiology (MS). Ultrasound characterization of lesion density as cystic or solid was considered the gold standard for this study. Analysis of CT scans was performed to identify lesions of interest corresponding to ultrasound abnormality; average, minimum, and maximum Hounsfield units (HUs) were measured. If masses had any solid component, they were considered solid. Twenty masses were solid, and 7 masses were cystic on ultrasound. Thirteen studies were performed without contrast and 14 were performed with contrast. On non-contrast studies, the average HU for cystic lesions was 19 compared to 38 HU for solid (P=0.007). On contrast studies, the average HU for cystic lesions was 16 compared to 53 HU for solid (P=0.002). Cystic lesions did not change with contrast significantly. Solid lesions enhanced with contrast; average HU 38 without contrast to 53 HU with contrast. Chest CT accurately diagnosed breast masses as cystic or solid with or without contrast.

Exploring breast cancer screening fear through a psychosocial lens.

Breast cancer screening is crucial for early detection and treatment. Yet, underutilization persists due to various psychosocial factors. This manuscript delves into the multifaceted fears that hinder screening adherence. The literature provides a framework categorizing breast cancer screening fears into generalized cancer fear, fear of screening components, and fear of screening outcomes. In this review, we explore fear of screening components (concerns regarding radiation, discomfort, and pain) and fear of screening outcomes (disability and mortality apprehension, treatment fears, obligation anxiety, and financial concerns) as undesirable, and potentially addressable, aspects of breast cancer screening fear. False-positive results exacerbate these anxieties, prolonging distress and impacting patients' lives beyond the screening process. Addressing these concerns requires reframing current screening approaches to prioritize patient comfort, cultural sensitivity, and accessibility. To address current psychosocial challenges in breast cancer screening, this manuscript advocates for modifying breast cancer screening methods to improve adherence and patient well-being.

Improved pulmonary function and exercise tolerance despite persistent pulmonary fibrosis over 1 year after severe COVID-19 infection.

We conducted a prospective single-centre cohort study of 104 multi-ethnic severe COVID-19 survivors from the first wave of the pandemic 15 months after hospitalisation. Of those who were assessed at 4 and 15 months, improvement of ground glass opacities correlated with worsened fibrotic reticulations. Despite a high prevalence of fibrotic patterns (64%), pulmonary function, grip strength, 6 min walk distance and frailty normalised. Overall, dyspnoea, cough and exhaustion did not improve and were not correlated with pulmonary function or radiographic fibrosis at 15 months, suggesting non-respiratory aetiologies. Monitoring persistent, and often subclinical, fibrotic interstitial abnormalities will be needed to determine their potential for future progression.

Lung nodule malignancy classification with associated pulmonary fibrosis using 3D attention-gated convolutional network with CT scans.

BACKGROUND: Chest Computed tomography (CT) scans detect lung nodules and assess pulmonary fibrosis. While pulmonary fibrosis indicates increased lung cancer risk, current clinical practice characterizes nodule risk of malignancy based on nodule size and smoking history; little consideration is given to the fibrotic microenvironment. PURPOSE: To evaluate the effect of incorporating fibrotic microenvironment into classifying malignancy of lung nodules in chest CT images using deep learning techniques. MATERIALS AND METHODS: We developed a visualizable 3D classification model trained with in-house CT dataset for the nodule malignancy classification task. Three slightly-modified datasets were created: (1) nodule alone (microenvironment removed); (2) nodule with surrounding lung microenvironment; and (3) nodule in microenvironment with semantic fibrosis metadata. For each of the models, tenfold cross-validation was performed. Results were evaluated using quantitative measures, such as accuracy, sensitivity, specificity, and area-under-curve (AUC), as well as qualitative assessments, such as attention maps and class activation maps (CAM). RESULTS: The classification model trained with nodule alone achieved 75.61% accuracy, 50.00% sensitivity, 88.46% specificity, and 0.78 AUC; the model trained with nodule and microenvironment achieved 79.03% accuracy, 65.46% sensitivity, 85.86% specificity, and 0.84 AUC. The model trained with additional semantic fibrosis metadata achieved 80.84% accuracy, 74.67% sensitivity, 84.95% specificity, and 0.89 AUC. Our visual evaluation of attention maps and CAM suggested that both the nodules and the microenvironment contributed to the task. CONCLUSION: The nodule malignancy classification performance was found to be improving with microenvironment data. Further improvement was found when incorporating semantic fibrosis information.

Comparison of lung cancer occurring in fibrotic versus non-fibrotic lung on chest CT.

PURPOSE: Evaluate the behavior of lung nodules occurring in areas of pulmonary fibrosis and compare them to pulmonary nodules occurring in the non-fibrotic lung parenchyma. METHODS: This retrospective review of chest CT scans and electronic medical records received expedited IRB approval and a waiver of informed consent. 4500 consecutive patients with a chest CT scan report containing the word fibrosis or a specific type of fibrosis were identified using the system M*Model Catalyst (Maplewood, Minnesota, U.S.). The largest nodule was measured in the longest dimension and re-evaluated, in the same way, on the follow-up exam if multiple time points were available. The nodule doubling time was calculated. If the patient developed cancer, the histologic diagnosis was documented. RESULTS: Six hundred and nine patients were found to have at least one pulmonary nodule on either the first or the second CT scan. 274 of the largest pulmonary nodules were in the fibrotic tissue and 335 were in the non-fibrotic lung parenchyma. Pathology proven cancer was more common in nodules occurring in areas of pulmonary fibrosis compared to nodules occurring in areas of non-fibrotic lung (34% vs 15%, p < 0.01). Adenocarcinoma was the most common cell type in both groups but more frequent in cancers occurring in non-fibrotic tissue. In the non-fibrotic lung, 1 of 126 (0.8%) of nodules measuring 1 to 6 mm were cancer. In contrast, 5 of 49 (10.2%) of nodules in fibrosis measuring 1 to 6 mm represented biopsy-proven cancer (p < 0.01). The doubling time for squamous cell cancer was shorter in the fibrotic lung compared to non-fibrotic lung, however, the difference was not statistically significant (p = 0.24). 15 incident lung nodules on second CT obtained ≤ 18 months after first CT scan was found in fibrotic lung and eight (53%) were diagnosed as cancer. CONCLUSIONS: Nodules occurring in fibrotic lung tissue are more likely to be cancer than nodules in the nonfibrotic lung. Incident pulmonary nodules in pulmonary fibrosis have a high likelihood of being cancer.

Developing radiology diagnostic tools for pulmonary fibrosis using machine learning methods.

BACKGROUND: Accurate and prompt diagnosis of the different patterns for pulmonary fibrosis is essential for patient management. However, accurate diagnosis of the specific pattern is challenging due to overlapping radiographic characteristics. MATERIALS AND METHODS: We conducted a retrospective chart review utilizing two machine learning methods, classification and regression tree and Bayesian additive regression tree, to select the most important radiographic features for diagnosing the three most common fibrosis patterns and created an online diagnostic app for convenient implementation. RESULTS: Four hundred patients (median age of 67 with inter quartile range 58-73; 200 males) were included in the study. Peripheral distribution, homogeneity, lower lobe predominance and mosaic attenuation of fibrosis are the four most important features identified. Bayesian additive regression tree demonstrates better performance than classification and regression tree in diagnosis prediction and provides the predicted probability of each diagnosis with uncertainty intervals for each combination of features. CONCLUSION: The model and app built with Bayesian additive regression tree can be used as an effective tool in assisting radiologists in the diagnostic process of pulmonary fibrosis pattern recognition.

Integrating [18F]-Fluorodeoxyglucose Positron Emission Tomography with Computed Tomography with Radiation Therapy and Immunomodulation in Precision Therapy for Solid Tumors.

[18F]-FDG positron emission tomography with computed tomography (PET/CT) imaging is widely used to enhance the quality of care in patients diagnosed with cancer. Furthermore, it holds the potential to offer insight into the synergic effect of combining radiation therapy (RT) with immuno-oncological (IO) agents. This is achieved by evaluating treatment responses both at the RT and distant tumor sites, thereby encompassing the phenomenon known as the abscopal effect. In this context, PET/CT can play an important role in establishing timelines for RT/IO administration and monitoring responses, including novel patterns such as hyperprogression, oligoprogression, and pseudoprogression, as well as immune-related adverse events. In this commentary, we explore the incremental value of PET/CT to enhance the combination of RT with IO in precision therapy for solid tumors, by offering supplementary insights to recently released joint guidelines.

Defining the pathway to timely diagnosis and treatment of interstitial lung disease: a US Delphi survey.

INTRODUCTION: Timely diagnosis of interstitial lung disease (ILD) is limited by obstacles in the current patient pathway. Misdiagnosis and delays are common and may lead to a significant burden of diagnostic procedures and worse outcomes. This Delphi survey aimed to identify consensus on the key steps that facilitate the patient journey to an accurate ILD diagnosis and appropriate management in the US. METHODS: A modified Delphi analysis was conducted, comprising three online surveys based on a comprehensive literature search. The surveys spanned five domains (guidelines, community screening, diagnosis, management and specialist referral) and were completed by a panel of US physicians, including primary care physicians and pulmonologists practising in community or academic settings. A priori definitions of consensus agreement were median scores of 2-3 (agree strongly/agree), with an IQR of 0-1 for questions on a 7-point Likert scale from -3 to 3, or ≥80% agreement for binary questions. RESULTS: Forty-nine panellists completed the surveys and 62 statements reached consensus agreement. There was consensus agreement on what should be included in the primary care evaluation of patients with suspected ILD and the next steps following workup. Regarding diagnosis in community pulmonology care, consensus agreement was reached on the requisition and reporting of high-resolution CT scans and the appropriate circumstances for holding multidisciplinary discussions. Additionally, there was consensus agreement on which symptoms and comorbidities should be monitored, the frequency of consultations and the assessment of disease progression. Regarding specialist referral, consensus agreement was reached on which patients should receive priority access to ILD centres and the contents of the referral package. CONCLUSIONS: These findings clarify the most common issues that should merit further evaluation for ILD and help define the steps for timely, accurate diagnosis and appropriate collaborative specialty management of patients with ILD.

Establishing quantitative radiographic criteria for the diagnosis of pleuroparenchymal fibroelastosis.

PURPOSE: Pleuroparenchymal Fibroelastosis (PPFE) is a type of pulmonary fibrosis most commonly occurring at the apices. Patients with PPFE have an increased risk of adverse effects from lung biopsy and in the post-surgical setting. Here, we investigated simple and reproducible measurements on chest CT to evaluate their predictive value in diagnosing PPFE. METHODS: We analyzed a cohort of patients with histologically-proven PPFE and compared them to a cohort of patients diagnosed with "biapical scarring" (BAS) on chest CT. We measured plueuroparenchymal thickness using several independent parameters on chest CT. We also assessed other radiologic and clinical characteristics to identify if any were predictive of PPFF. RESULTS: Our analysis demonstrated the average greatest apical thickness with a cut off of 4.5 mm yielded a sensitivity of 94.4% and a specificity of 88.9%, and an area under the curve of 97.2%. Single greatest apical thickness with a cut off of 7.5 mm had a sensitivity of 100% and a specificity of 88.9%, with the area under the curve of 97.8%. Average greatest upper lobe thickness with a cut off of 8.0 mm had a sensitivity of 88.9% and a specificity of 100%, with an area under the curve of 98.2%. Single greatest upper lobe thickness with a cut off of 8.5 yielded both a sensitivity and specificity of 94.4% and an area under the curve of 94.3%. CONCLUSION: Measurements described above are highly sensitive and specific for the diagnosis of PPFE and warrant investigation with a larger cohort of patients.

Radiographic grading system for usual interstitial pneumonia correlates with mortality and may serve as a surrogate endpoint in clinical trials.

PURPOSE: Usual interstitial pneumonia (UIP)/ idiopathic pulmonary fibrosis (IFP) is a relentlessly progressive lung disease with outcomes similar to cancer. We have previously established a radiologic grading system for UIP and demonstrated that it correlates with pulmonary function tests; here we test the hypothesis that it correlates with mortality. Validating a correlation with mortality will demonstrate the utility of this system for monitoring progression over time clinically and in trials of anti-fibrotic agents. METHODS: We searched the radiology record system "Catalyst" to identify cases and reviewed each case to confirm the diagnosis. 94 patients met the inclusion criteria for further assessment. Chest CT grade was determined by consensus of two cardiothoracic radiologists. Data was analyzed to identify the interval between chest CT and death. This interval was correlated with CT grade using Spearman correlation analysis. RESULTS: For all cases, chest CT grade and mortality demonstrated a positive correlation of rs = 0.37732, 2-tailed p = 0.00018. We also employed subgroup analysis; for the subgroup with intervals less than or equal to 100 days, there was a positive correlation, rs = 0.48339, 2-tailed p = 0.03602; for the subgroup with an interval greater than 100 days between imaging and death there was a positive correlation, rs = 0.302, 2-tailed p = 0.00846. CONCLUSION: These data support use of this system for monitoring clinical progression and as a surrogate endpoint for clinical trials. Future work building upon the data presented here will evaluate its utility in clinical trials and develop automated grading.