Computed tomography-based radiomics improves non-invasive diagnosis of Pneumocystis jirovecii pneumonia in non-HIV patients: a retrospective study

被引:3
作者
Yu, Hang [1 ]
Yang, Zhen [2 ]
Wei, Yuanhui [1 ]
Shi, Wenjia [1 ]
Zhu, Minghui [3 ]
Liu, Lu [4 ]
Wang, Miaoyu [1 ]
Wang, Yueming [1 ]
Zhu, Qiang [2 ]
Liang, Zhixin [2 ]
Zhao, Wei [2 ]
Chen, Liang-an [2 ]
机构
[1] Chinese Peoples Liberat Army, Dept Resp & Crit Care Med, Med Sch, Beijing, Peoples R China
[2] Chinese Peoples Liberat Army Gen Hosp, Dept Resp & Crit Care Med, Med Ctr 8, Beijing, Peoples R China
[3] Wuhan Univ, Zhongnan Hosp, Dept Pulm & Crit Care Med, Wuhan, Hubei, Peoples R China
[4] Chinese Peoples Liberat Army Gen Hosp, Dept Nutr, Med Ctr 1, Beijing, Peoples R China
关键词
Pneumocystis Jirovecii Pneumonia; Computed tomography; Radiomics; Diagnostic tests; ECIL GUIDELINES; PCR DIAGNOSIS;
D O I
10.1186/s12890-023-02827-4
中图分类号
R56 [呼吸系及胸部疾病];
学科分类号
摘要
Background Pneumocystis jirovecii pneumonia (PCP) could be fatal to patients without human immunodeficiency virus (HIV) infection. Current diagnostic methods are either invasive or inaccurate. We aimed to establish an accurate and non-invasive radiomics-based way to identify the risk of PCP infection in non-HIV patients with computed tomography (CT) manifestation of pneumonia.Methods This is a retrospective study including non-HIV patients hospitalized for suspected PCP from January 2010 to December 2022 in one hospital. The patients were randomized in a 7:3 ratio into training and validation cohorts. Computed tomography (CT)-based radiomics features were extracted automatically and used to construct a radiomics model. A diagnostic model with traditional clinical and CT features was also built. The area under the curve (AUC) were calculated and used to evaluate the diagnostic performance of the models. The combination of the radiomics features and serum beta-D-glucan levels was also evaluated for PCP diagnosis.Results A total of 140 patients (PCP: N = 61, non-PCP: N = 79) were randomized into training (N = 97) and validation (N = 43) cohorts. The radiomics model consisting of nine radiomic features performed significantly better (AUC = 0.954; 95% CI: 0.898-1.000) than the traditional model consisting of serum beta-D-glucan levels (AUC = 0.752; 95% CI: 0.597-0.908) in identifying PCP (P = 0.002). The combination of radiomics features and serum beta-D-glucan levels showed an accuracy of 95.8% for identifying PCP infection (positive predictive value: 95.7%, negative predictive value: 95.8%).Conclusions Radiomics showed good diagnostic performance in differentiating PCP from other types of pneumonia in non-HIV patients. A combined diagnostic method including radiomics and serum beta-D-glucan has the potential to provide an accurate and non-invasive way to identify the risk of PCP infection in non-HIV patients with CT manifestation of pneumonia.
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共 40 条
  • [1] ECIL guidelines for the diagnosis of Pneumocystis jirovecii pneumonia in patients with haematological malignancies and stem cell transplant recipients
    Alanio, Alexandre
    Hauser, Philippe M.
    Lagrou, Katrien
    Melchers, Willem J. G.
    Helweg-Larsen, Jannik
    Matos, Olga
    Cesaro, Simone
    Maschmeyer, Georg
    Einsele, Hermann
    Donnelly, J. Peter
    Cordonnier, Catherine
    Maertens, Johan
    Bretagne, Stephane
    [J]. JOURNAL OF ANTIMICROBIAL CHEMOTHERAPY, 2016, 71 (09) : 2386 - 2396
  • [2] The Pathogenesis and Diagnosis of Pneumocystis jiroveci Pneumonia
    Apostolopoulou, Anna
    Fishman, Jay A.
    [J]. JOURNAL OF FUNGI, 2022, 8 (11)
  • [3] Diagnosis of severe respiratory infections in immunocompromised patients
    Azoulay, Elie
    Russell, Lene
    Van de Louw, Andry
    Metaxa, Victoria
    Bauer, Philippe
    Povoa, Pedro
    Montero, Jose Garnacho
    Loeches, Ignacio Martin
    Mehta, Sangeeta
    Puxty, Kathryn
    Schellongowski, Peter
    Rello, Jordi
    Mokart, Djamel
    Lemiale, Virginie
    Mirouse, Adrien
    [J]. INTENSIVE CARE MEDICINE, 2020, 46 (02) : 298 - 314
  • [4] Carmona Eva M, 2011, Ther Adv Respir Dis, V5, P41, DOI 10.1177/1753465810380102
  • [5] Diagnostic accuracy of serum (1-3)-β-D-glucan for Pneumocystis jirovecii pneumonia: a systematic review and meta-analysis
    Del Corpo, Olivier
    Butler-Laporte, Guillaume
    Sheppard, Donald C.
    Cheng, Matthew P.
    McDonald, Emily G.
    Lee, Todd C.
    [J]. CLINICAL MICROBIOLOGY AND INFECTION, 2020, 26 (09) : 1137 - 1143
  • [6] Combination of β-(1,3)-D-glucan testing in serum and qPCR in nasopharyngeal aspirate for facilitated diagnosis of Pneumocystis jirovecii pneumonia
    Desoubeaux, Guillaume
    Chesnay, Adelaide
    Mercier, Victor
    Bras-Cachinho, Jose
    Moshiri, Parastou
    Eymieux, Sebastien
    De Kyvon, Marie-Alix
    Lemaignen, Adrien
    Goudeau, Alain
    Bailly, Eric
    [J]. MYCOSES, 2019, 62 (11) : 1015 - 1022
  • [7] Revision and Update of the Consensus Definitions of Invasive Fungal Disease From the European Organization for Research and Treatment of Cancer and the Mycoses Study Group Education and Research Consortium
    Donnelly, J. Peter
    Chen, Sharon C.
    Kauffman, Carol A.
    Steinbach, William J.
    Baddley, John W.
    Verweij, Paul E.
    Clancy, Cornelius J.
    Wingard, John R.
    Lockhart, Shawn R.
    Groll, Andreas H.
    Sorrell, Tania C.
    Bassetti, Matteo
    Akan, Hamdi
    Alexander, Barbara D.
    Andes, David
    Azoulay, Elie
    Bialek, Ralf
    Bradsher, Robert W., Jr.
    Bretagne, Stephane
    Calandra, Thierry
    Caliendo, Angela M.
    Castagnola, Elio
    Cruciani, Mario
    Cuenca-Estrella, Manuel
    Decker, Catherine F.
    Desai, Sujal R.
    Fisher, Brian
    Harrison, Thomas
    Heussel, Claus Peter
    Jensen, Henrik E.
    Kibbler, Christopher C.
    Kontoyiannis, Dimitrios P.
    Kullberg, Bart-Jan
    Lagrou, Katrien
    Lamoth, Frederic
    Lehrnbecher, Thomas
    Loeffler, Jurgen
    Lortholary, Olivier
    Maertens, Johan
    Marchetti, Oscar
    Marr, Kieren A.
    Masur, Henry
    Meis, Jacques F.
    Morrisey, C. Orla
    Nucci, Marcio
    Ostrosky-Zeichner, Luis
    Pagano, Livio
    Patterson, Thomas F.
    Perfect, John R.
    Racil, Zdenek
    [J]. CLINICAL INFECTIOUS DISEASES, 2020, 71 (06) : 1367 - 1376
  • [8] CT Radiomics to Predict Macrotrabecular-Massive Subtype and Immune Status in Hepatocellular Carcinoma
    Feng, Zhichao
    Li, Huiling
    Liu, Qianyun
    Duan, Junhong
    Zhou, Wenming
    Yu, Xiaoping
    Chen, Qian
    Liu, Zhenguo
    Wang, Wei
    Rong, Pengfei
    [J]. RADIOLOGY, 2023, 307 (01)
  • [9] A deep-learning radiomics-based lymph node metastasis predictive model for pancreatic cancer: a diagnostic study
    Fu, Ningzhen
    Fu, Wenli
    Chen, Haoda
    Chai, Weimin
    Qian, Xiaohua
    Wang, Weishen
    Jiang, Yu
    Shen, Baiyong
    [J]. INTERNATIONAL JOURNAL OF SURGERY, 2023, 109 (08) : 2196 - 2203
  • [10] Risk Factors and Prevention of Pneumocystis jirovecii Pneumonia in Patients With Autoimmune and Inflammatory Diseases
    Ghembaza, Amine
    Vautier, Mathieu
    Cacoub, Patrice
    Pourcher, Valerie
    Saadoun, David
    [J]. CHEST, 2020, 158 (06) : 2323 - 2332