The Effectiveness of ChatGPT in Temporomandibular Joint Pathologies and Sequence Determination in Magnetic Resonance Imaging

Gözde Serindere; Ceren Aktuna Belgin; Kaan Gündüz

Makale detayları

The Effectiveness of ChatGPT in Temporomandibular Joint Pathologies and Sequence Determination in Magnetic Resonance Imaging

Yazarlar:

Gözde Serindere | Ceren Aktuna Belgin | Kaan Gündüz

Yayıncı:

Marmara University

Ana Başlıklar:

Oral and Maxillofacial Radiology | Dentistry (Other)

Dergi:

European Journal of Research in Dentistry Vol.9 Issue 2, pp.98-103

Belge Tipi:

Makale

Yayın Tarihi:

8/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001357114

pISSN:

2630-6247

Anahtar kelimeler:

Özet:

 Objectives: Temporomandibular joint TMJ pathologies is a general term for pain and dysfunction of the TMJ complex and masticatory muscles. Magnetic resonance imaging MRI is the gold standard for evaluating the TMJ complex, disc-condylar relationship and disc displacement. The aim of this study was to evaluate the effectiveness of ChatGPT version 4.0 ChatGPT-V4 in identifying TMJ pathologies, slice plane and sequence in MR images. Materials and Methods: One hundred MR images of patients with bilateral TMJ pathology 200 TMJs were recorded. TMJ pathologies, slice plane, sequence of the MR images and ChatGPT responses were evaluated. The subheadings in the ChatGPT-V4 answers were recorded as true if present in the image and false if not. The slice plane was categorized as true-false and the sequence as true-false-missing. Results: In all images, ChatGPT-V4 correctly recognized the slice plane. The correct MR sequence recognition rate was 81.5. Missing sequence recognition rate was 12 on both sides. It failed to identify the fat-suppressed sequences. ChatGPT-V4 misidentified the sequence in 6.5 of the images. The accuracy of ChatGPT-V4 in identifying TMJ pathologies remained at 50.7. ChatGPT-V4 achieved the highest accuracy in the diagnosis of anterior disc dislocation and osteoarthritis. Conclusions: ChatGPT-V4 can be relied upon to control the slice plane and sequence of MR images. The results show that ChatGPT-V4 is currently limited in its ability to produce responses related to TMJ pathologies on MR images. Therefore, ChatGPT cannot replace a dentist and physicians should be aware of this limitation during their use of chatGPT to check for TMJ pathologies.

 Objectives: Temporomandibular joint TMJ pathologies is a general term for pain and dysfunction of the TMJ complex and masticatory muscles. Magnetic resonance imaging MRI is the gold standard for evaluating the TMJ complex, disc-condylar relationship and disc displacement. The aim of this study was to evaluate the effectiveness of ChatGPT version 4.0 ChatGPT-V4 in identifying TMJ pathologies, slice plane and sequence in MR images. Materials and Methods: One hundred MR images of patients with bilateral TMJ pathology 200 TMJs were recorded. TMJ pathologies, slice plane, sequence of the MR images and ChatGPT responses were evaluated. The subheadings in the ChatGPT-V4 answers were recorded as true if present in the image and false if not. The slice plane was categorized as true-false and the sequence as true-false-missing. Results: In all images, ChatGPT-V4 correctly recognized the slice plane. The correct MR sequence recognition rate was 81.5. Missing sequence recognition rate was 12 on both sides. It failed to identify the fat-suppressed sequences. ChatGPT-V4 misidentified the sequence in 6.5 of the images. The accuracy of ChatGPT-V4 in identifying TMJ pathologies remained at 50.7. ChatGPT-V4 achieved the highest accuracy in the diagnosis of anterior disc dislocation and osteoarthritis. Conclusions: ChatGPT-V4 can be relied upon to control the slice plane and sequence of MR images. The results show that ChatGPT-V4 is currently limited in its ability to produce responses related to TMJ pathologies on MR images. Therefore, ChatGPT cannot replace a dentist and physicians should be aware of this limitation during their use of chatGPT to check for TMJ pathologies.

 Objectives: Temporomandibular joint TMJ pathologies is a general term for pain and dysfunction of the TMJ complex and masticatory muscles. Magnetic resonance imaging MRI is the gold standard for evaluating the TMJ complex, disc-condylar relationship and disc displacement. The aim of this study was to evaluate the effectiveness of ChatGPT version 4.0 ChatGPT-V4 in identifying TMJ pathologies, slice plane and sequence in MR images. Materials and Methods: One hundred MR images of patients with bilateral TMJ pathology 200 TMJs were recorded. TMJ pathologies, slice plane, sequence of the MR images and ChatGPT responses were evaluated. The subheadings in the ChatGPT-V4 answers were recorded as true if present in the image and false if not. The slice plane was categorized as true-false and the sequence as true-false-missing. Results: In all images, ChatGPT-V4 correctly recognized the slice plane. The correct MR sequence recognition rate was 81.5. Missing sequence recognition rate was 12 on both sides. It failed to identify the fat-suppressed sequences. ChatGPT-V4 misidentified the sequence in 6.5 of the images. The accuracy of ChatGPT-V4 in identifying TMJ pathologies remained at 50.7. ChatGPT-V4 achieved the highest accuracy in the diagnosis of anterior disc dislocation and osteoarthritis. Conclusions: ChatGPT-V4 can be relied upon to control the slice plane and sequence of MR images. The results show that ChatGPT-V4 is currently limited in its ability to produce responses related to TMJ pathologies on MR images. Therefore, ChatGPT cannot replace a dentist and physicians should be aware of this limitation during their use of chatGPT to check for TMJ pathologies.

 Amaç: Temporomandibular eklem TME patolojileri, TME kompleksi ve çiğneme kaslarının ağrı ve işlev bozukluğu için kullanılan genel bir terimdir. Manyetik rezonans görüntüleme MRG, TME kompleksini, disk-kondiler ilişkiyi ve disk deplasmanını değerlendirmek için altın standarttır. Bu çalışmanın amacı ChatGPT versiyon 4.0ın ChatGPT-V4 TME patolojilerini, kesit düzlemini ve MR görüntülerindeki sekansı belirlemedeki etkinliğini değerlendirmektir. Gereç ve Yöntemler: Bilateral TME patolojisi olan hastaların yüz MR görüntüsü 200 TME kaydedildi. TME patolojileri, kesit düzlemi, MR görüntülerinin sırası ve ChatGPT yanıtları değerlendirildi. ChatGPT-V4 yanıtlarındaki alt başlıklar görüntüde varsa doğru, yoksa yanlış olarak kaydedildi. Kesit düzlemi doğru-yanlış ve sekans doğru-yanlış-eksik olarak kategorize edildi. Bulgular: Tüm görüntülerde ChatGPT-V4 kesit düzlemini doğru şekilde tanıdı. Doğru MR sekansını belirleme oranı 81,5ti. Eksik sekans tanıma oranı her iki tarafta da 12 idi. Yağ baskılı sekansları tanımlamada başarısız oldu. ChatGPT-V4 görüntülerin 6,5inde sekansı yanlış tanımladı. ChatGPT-V4ün TME patolojilerini tanımlama doğruluğu 50,7de kalmıştır. ChatGPT-V4, anterior disk dislokasyonu ve osteoartrit tanısında en yüksek doğruluğu elde etti. Sonuç: ChatGPT-V4e MR görüntülerinin kesit düzlemini ve sekansını kontrol etmek için güvenilebilir. Sonuçlar ChatGPT-V4ün şu anda MR görüntülerinde TME patolojileriyle ilgili yanıtlar üretme kabiliyetinin sınırlı olduğunu göstermektedir. Bu nedenle ChatGPT bir diş hekiminin yerini alamaz ve hekimler TME patolojilerini kontrol etmek için chatGPTyi kullanırken bu sınırlamanın farkında olmalıdır.

Makale detayları

The Effectiveness of ChatGPT in Temporomandibular Joint Pathologies and Sequence Determination in Magnetic Resonance Imaging

Yazarlar:

Gözde Serindere | Ceren Aktuna Belgin | Kaan Gündüz

Yayıncı:

Marmara University

Ana Başlıklar:

Oral and Maxillofacial Radiology | Dentistry (Other)

Dergi:

European Journal of Research in Dentistry Vol.9 Issue 2, pp.98-103

Belge Tipi:

Makale

Yayın Tarihi:

8/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001357114

pISSN:

2630-6247

Artificial intelligence

Magnetic resonance imaging

Temporomandibular jointYapay zeka

Manyetik rezonans görüntüleme

Temporomandibular eklem

Sayı

Makale detayları

The Effectiveness of ChatGPT in Temporomandibular Joint Pathologies and Sequence Determination in Magnetic Resonance Imaging

Yazarlar: Gözde Serindere | Ceren Aktuna Belgin | Kaan Gündüz

Yayıncı: Marmara University

Ana Başlıklar: Oral and Maxillofacial Radiology | Dentistry (Other)

Dergi: European Journal of Research in Dentistry Vol.9 Issue 2, pp.98-103

Belge Tipi: Makale

Yayın Tarihi: 8/2025

Belge Dili: İngilizce

Document ID (Org No.): 2001357114

pISSN: 2630-6247

Artificial intelligence

Magnetic resonance imaging

Temporomandibular jointYapay zeka

Manyetik rezonans görüntüleme

Temporomandibular eklem

Sayı

Yazarlar:

Gözde Serindere | Ceren Aktuna Belgin | Kaan Gündüz

Yayıncı:

Marmara University

Ana Başlıklar:

Oral and Maxillofacial Radiology | Dentistry (Other)

Dergi:

European Journal of Research in Dentistry Vol.9 Issue 2, pp.98-103

Belge Tipi:

Makale

Yayın Tarihi:

8/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001357114

pISSN:

2630-6247