TRAVMATİK OLMAYAN AKUT BATIN VAKALARINDA BİLGİSAYARLI TOMOGRAFİ KULLANIMI: KLİNİK GEREKLİLİK, YAPAY ZEKA VE ETİK SINIRLAR

Öz

Amaç: Bu çalışmada, travmatik olmayan akut karın olgularında bilgisayarlı tomografinin (BT) gerekliliği ve sınırlılıkları, klinik endikasyonlar, potansiyel komplikasyonlar ve hassas hasta gruplarında aşırı kullanımın etik sonuçlarına odaklanarak değerlendirilmiştir. Gereç ve Yöntem: Bu teorik derleme, kontrastlı BT'nin travmatik olmayan akut abdominal durumların tanısındaki rolünü değerlendiren güncel literatüre dayanmaktadır. Hasta risk tabakalandırması, kontrasta bağlı nefropati, radyasyona maruz kalma ve yapay zekanın (YZ) radyolojik değerlendirmeye entegrasyonuna özellikle vurgu yapılmaktadır. Bulgular: BT, akut apandisit, divertikülit, epiploik apandisit, omental enfarktüs ve mezenterik iskemi gibi durumların teşhisinde bir köşe taşı olmaya devam etmektedir. Bununla birlikte, yaşlı ve komorbid hastalarda uygulanması kontrast kaynaklı nefropati riski taşır. Son çalışmalar, hidrasyon protokollerinin ve riske dayalı seçim kriterlerinin uygulanmasının bu tür komplikasyonları azaltabileceğini göstermektedir. Ayrıca, teknik ve etik sınırlamalar devam etse de, yapay zeka destekli görüntüleme, tanısal doğruluğu artırma ve gereksiz taramaları azaltma konusunda umut vaat etmektedir. Tartışma: Acil servislerde BT'ye artan güven, görüntülemenin genellikle yeterli klinik gerekçe olmaksızın önleyici olarak istendiği bir “BT refleksine” yol açmıştır. BT, özellikle atipik sunumlarda tanısal güveni artırabilirken, gelişigüzel kullanım etik ilkelerle, özellikle de primum non nocere ilkesiyle çelişmektedir. Gelişmekte olan yapay zeka teknolojileri karar vermeyi destekleyebilir, ancak özellikle karmaşık veya yüksek riskli popülasyonlarda klinik yargının yerini tam olarak alamaz. Sonuç Travmatik olmayan akut batında BT kullanımı hasta merkezli, klinik olarak gerekçelendirilmiş ve etik olarak sorumlu olmalıdır. Uygun olduğunda ultrasonografi gibi alternatiflere öncelik verilmeli ve yüksek riskli hastalarda komplikasyonları en aza indirmek için önleyici tedbirler alınmalıdır. BT, acil abdominal görüntülemede gerekli ancak otomatik olmayan bir araç olmaya devam etmelidir.

Anahtar Kelimeler

• Akut karın
• Bilgisayarlı tomografi
• Kontrast nefropatisi

THE USE OF COMPUTED TOMOGRAPHY IN NON-TRAUMATIC ACUTE ABDOMEN CASES: CLINICAL NECESSITY, ARTIFICIAL INTELLIGENCE AND ETHICAL LIMITS

Öz

Aim: This study aims to evaluate the necessity and limitations of computed tomography (CT) in non-traumatic acute abdomen cases, focusing on clinical indications, potential complications, and the ethical implications of overuse in vulnerable patient groups. Material And Method: This theoretical review is based on current literature evaluating the role of contrast-enhanced CT in diagnosing non-traumatic acute abdominal conditions. Particular emphasis is placed on patient risk stratification, contrast-induced nephropathy, radiation exposure, and the integration of artificial intelligence (AI) in radiological assessment. Results: CT remains a cornerstone in diagnosing conditions such as acute appendicitis, diverticulitis, epiploic appendagitis, omental infarction, and mesenteric ischemia. However, its application in elderly and comorbid patients carries risks of contrast-induced nephropathy. Recent studies show that implementing hydration protocols and risk-based selection criteria can mitigate such complications. Moreover, AI-supported imaging has shown promise in improving diagnostic accuracy and reducing unnecessary scans, although technical and ethical limitations persist. Discussion: The increasing reliance on CT in emergency departments has led to a “CT reflex,” where imaging is often ordered preemptively without adequate clinical justification. While CT can improve diagnostic confidence, especially in atypical presentations, indiscriminate use contradicts ethical principles, particularly the tenet of primum non nocere. Emerging AI technologies may support decision-making, yet cannot fully replace clinical judgment, especially in complex or high-risk populations. Conclusion: The use of CT in non-traumatic acute abdomen should be patient-centered, clinically justified, and ethically responsible. Alternatives such as ultrasonography should be prioritized when appropriate, and preventive measures must be taken to minimize complications in high-risk patients. CT should remain an essential, but not automatic, tool in emergency abdominal imaging.

Anahtar Kelimeler

• Acute abdomen
• Computed tomography
• Contrast nephropathy

Destekleyen Kurum

No funding.

Etik Beyan

This study is a theoretical review based solely on previously published literature. It does not involve any human participants, animal subjects, or the use of patient data. Therefore, ethical approval from an institutional review board was not required.

Kaynakça

1. 1. Barai KP, Knight BC. Diagnosis and management of idiopathic omental infarction: a case report. Int J Surg Case Rep 2011;2(6):138–40.
2. 2.Singh AK, Gervais DA, Hahn PF, Sagar P, Mueller PR, Novelline RA. Acute epiploic appendagitis and its mimics. Radiographics 2005;25(6):1521–34.
3. 3. Kamaya A, Federle MP, Desser TS. Imaging manifestations of abdominal fat necrosis and its mimics. Radiographics 2011;31(7):2021–34.
4. 4. Goti F, Hollmann R, Stieger R, Lange J. Idiopathic segmental infarction of the greater omentum successfully treated by laparoscopy: report of case. Surg Today 2000;30(5):451–3.
5. 5. Nubi A, McBride W, Stringel G. Primary omental infarct: conservative vs operative management in the era of ultrasound, computerized tomography, and laparoscopy. J Pediatr Surg 2009;44(5):953–6.
6. 6. Pereira JM, Sirlin CB, Pinto PS, Jeffrey RB, Stella DL, Casola G. Disproportionate fat stranding: a helpful CT sign in patients with acute abdominal pain. Radiographics 2004;24(3):703–15.
7. 7. Gans SL, Pols MA, Stoker J, Boermeester MA; expert steering group. Guideline for the diagnostic pathway in patients with acute abdominal pain. Dig Surg. 2015;32(1):23-31.
8. 8. Mehran R, Aymong ED, Nikolsky E, Lasic Z, Iakovou I, Fahy M, et al. A simple risk score for prediction of contrast-induced nephropathy after percutaneous coronary intervention: development and initial validation. J Am Coll Cardiol. 2004;44(7):1393-1399.

9. 9. Moore A, Dickerson E, Dillman JR, Vummidi D, Kershaw DB, Khalatbari S, et al. Incidence of nonconfounded post-computed tomography acute kidney injury in hospitalized patients with stable 88 renal function receiving intravenous iodinated contrast material. Curr Probl Diagn Radiol. 2014;43(5):237-241.
10. 10. Huang MK, Hsu TF, Chiu YH, Chiang SC, Kao WF, Yen DH, et al. Risk factors for acute kidney injury in the elderly undergoing contrast- enhanced computed tomography in the emergency department. J Chin Med Assoc. 2013;76(5):271-276.
11. 11. Feldkamp T, Kribben A. Contrast media induced nephropathy: definition, incidence, outcome, pathophysiology, risk factors and prevention. Minerva Med. 2008; 99(2): 177-96.
12. 12. Parfrey PS, Griffiths SM, Barrett BJ, Paul MD, Genge M, Withers J, et al. Contrast material-induced renal failure in patients with diabetes mellitus, renal insufficiency, or both. A prospective controlled study. N Engl J Med. 1989;320(3):143-149.
13. 13. Reginelli A, Russo A, Pinto A, Stanzione F, Martiniello C, Cappabianca S, et al. The role of computed tomography in the preoperative assessment of gastrointestinal causes of acute abdomen in elderly patients. Int J Surg. 2014;12 Suppl 2:S181-S186.
14. 14. Al Hariri M, Al Hassan S, Khalifeh M, Tamim H, El Majzoub I, El Zahran T. Factors associated with contrast-associated acute kidney injury in an emergency department: A cohort study in Lebanon. PLoS One. 2025;20(3):e0316604.
15. 15. De Simone B, Ansaloni L, Sartelli M, Gaiani F, Leandro G, De' Angelis GL, et al. Is the risk of contrast-induced nephropathy a real contraindication to perform intravenous contrast enhanced Computed Tomography for non-traumatic acute abdomen in Emergency Surgery Department?. Acta Biomed. 2018;89(9-S):158-172.
16. 16. Tuncal S, Ünal Y. Computed tomography trend in acute appendicitis: retrospective cross-sectional analysis. Turkiye Klinikleri J Med Sci. 2022;42(2):111-8.
17. 17. Kim M, Kim JS, Lee C, Kang BK. Detection of pneumoperitoneum in the abdominal radiograph images using artificial neural networks. Eur J Radiol Open. 2021;8:100316.
18. 18. Holmer C, Mallmann CA, Musch MA, Kreis ME, Grone J. Surgical management of iatrogenic perforation of the gastrointestinal tract: 15 years of experience in a single center. World J Surg. 2017;41(8):1961-1965.
19. 19. Brejnebøl MW, Nielsen YW, Taubmann O, Eibenberger E, Muller FC. Artificial Intelligence based detection of pneumoperitoneum on CT scans in patients presenting with acute abdominal pain: a clinical diagnostic test accuracy study. Eur J Radiol. 2022;150:110216.
20. 20. Vanderbecq Q, Ardon R, De Reviers A, Ruppli C, Dallongeville A, Boulay-Coletta I, et al. Adhesion-related small bowel obstruction: deep learning for automatic transition-zone detection by CT. Insights Imaging. 2022;13(1):13.
21. 21. Rajpurkar P, Park A, Irvin J, Chute C, Bereket M, Mastrodicasa D, et al. AppendiXNet: Deep Learning for Diagnosis of Appendicitis from A Small Dataset of CT Exams Using Video Pretraining. Sci Rep. 2020;10(1):3958.
22. 22. Hayashi K, Ishimaru T, Lee J, Hirai S, Ooke T, Hosokawa T, et al. Identification of appendicitis using ultrasound with the aid of machine learning. J Laparoendosc Adv Surg Tech A. 2021;31(12):1412- 1419.
23. 23 Kim SW, Cheon JE, Choi YH, Hwang JY, Shin SM, Cho YJ, et al. Feasibility of a deep learning artificial intelligence model for the diagnosis of pediatric ileocolic intussusception with grayscale ultrasonography. Ultrasonography. 2024;43(1):57-67.
24. 24 Yu CJ, Yeh HJ, Chang CC, Tang JH, Kao WY, Chen WC, et al. Lightweight deep neural networks for cholelithiasis and cholecystitis detection by point-of-care ultrasound. Comput Methods Programs Biomed. 2021;211:106382.
25. 25 Yao J, Chu LC, Patlas M. Applications of Artificial Intelligence in Acute Abdominal Imaging. Canadian Association of Radiologists Journal. 2024;75(4):761-770.
26. 26. Mashayekhi R, Parekh VS, Faghih M, Singh VK, Jacobs MA, Zaheer A. Radiomic features of the pancreas on CT imaging accurately differentiate functional abdominal pain, recurrent acute pancreatitis, and chronic pancreatitis. Eur J Radiol. 2020;123:108778.
27. 27 Chaudhari H, Mahendrakar S, Baskin SE, Reddi AS. Contrast-Induced Acute Kidney Injury: Evidence in Support of Its Existence and a Review of Its Pathogenesis and Management. Int J Nephrol Renovasc Dis. 2022 Oct 11;15:253-266.
28. 28. Expert Panel on Gastrointestinal Imaging:, Scheirey CD, Fowler KJ, et al. ACR Appropriateness Criteria® Acute Nonlocalized Abdominal Pain. J Am Coll Radiol. 2018;15(11S):S217-S231.