Insights Into Imaging

25/07/2025

This study evaluated MRI (dMRI) vs. cone beam CT (CBCT) for measuring periodontal bone loss in 253 lesions across 19 patients with severe periodontitis.

📌 Key Findings:
dMRI (T1W + C & T2W) showed strong correlation with CBCT (rs = 0.86-0.91)
dMRI overestimated bone lesion volumes by 19–55%
A novel T2W-mismatch pattern (seen in 44.1% of lesions) correlated with clinical inflammation

💡 While CBCT remains more accurate for bone loss measurement, dMRI offers added value in detecting active inflammation, especially in high-risk patients. (Arne Lauer et al.)



https://insightsimaging.springeropen.com/articles/10.1186/s13244-025-02004-7

24/07/2025

The authors developed a high-performance ML model to classify NSCLC 🫁, granulomatous inflammation, and benign using CT + clinical data from 3,030 patients.

🧠 Key Results:
✔️ Test accuracy: 81%
✔️ External validation accuracy: 79%
✔️ Demonstrated strong clinical utility through decision and calibration curve analysis (Zhenyu Cao et al.)



https://insightsimaging.springeropen.com/articles/10.1186/s13244-025-02020-7

23/07/2025

The false-positive rate associated with MRI scans in cases of deep infiltrating is 23%, which can result in misdiagnosis. T2-hypointense lesions are primarily the result of anatomical variations, fibrous connective tissue, benign and malignant tumours, faeces, surgical material, and post-treatment scars. This paper aims to help the radiologist acknowledge MRI pitfalls and the differential diagnosis of deep pelvic infiltrating endometriosis to reduce false-positive results. (Edouard Ruaux et al.)



https://insightsimaging.springeropen.com/articles/10.1186/s13244-023-01588-2

23/07/2025

🏥 Measuring radiology's value goes beyond outcomes - it includes patient experience, safety, and service quality.

💡By listening and acting on feedback, departments can drive continuous improvement and deliver truly value-based care. (Andrea Rockall et al.)



https://insightsimaging.springeropen.com/articles/10.1186/s13244-025-02002-9

22/07/2025

🔍 Understanding Pelvic Nerve Involvement in Endometriosis

🎯This article provides a comprehensive review of the pathophysiology of neural , proposes an optimized protocol tailored for the evaluation of pelvic nerves, and highlights key landmarks crucial for the accurate detection and of each nerve. (Justine Bourg et al.)



https://insightsimaging.springeropen.com/articles/10.1186/s13244-025-02005-6

21/07/2025

Mass-forming intrahepatic cholangiocarcinomas (MF-ICCs) can be subclassified into biliary and parenchymal types using (US) - this reveals key differences in behavior and prognosis.

📌 Biliary MF-ICCs (bMF-ICCs) were linked to:

Higher rates of lymph node metastasis & bile duct invasion

Worse overall survival

Strong alignment with large duct pathology

💡 This US-based subclassification could offer critical pre-surgical insight into tumor biology and guide treatment strategies. (Cong-Jian Wen et al.)



https://insightsimaging.springeropen.com/articles/10.1186/s13244-025-02019-0

18/07/2025

📊 How Good Is Research in Bone ?

This review assessed 18 radiomics studies using METRICS and RQS scoring systems.

🔍 Findings:
Adherence rates: METRICS 37.3-94.8%, RQS 2.8-44.4%
All studies were retrospective
MRI was the most used imaging modality
Excellent scoring reliability (ICC > 0.96)

🚩 Key gaps: limited use of deep learning, lack of external validation, and poor adherence to open science. (Salvatore Gitto et al.)



https://insightsimaging.springeropen.com/articles/10.1186/s13244-025-02016-3

17/07/2025

🔬 Can Localization Microscopy (ULM) Help Diagnose Breast Lesions?

This study shows that ULM can effectively distinguish between benign and malignant breast lesions using microvasculature patterns and flow metrics.

✅ Chaotic pattern = more likely malignant
✅ Largest vessel diameter had the highest diagnostic accuracy (AUC: 0.962)
✅ Excellent operator reliability (ICC > 0.90)

ULM offers promising potential for noninvasive breast diagnosis.



(Jia Li et al.)

https://insightsimaging.springeropen.com/articles/10.1186/s13244-025-02013-6

16/07/2025

Improving the image quality of prostate MRIs is fundamental, and this can be achieved by addressing factors not covered in the PI-RADSv2.1 technical recommendation. (Linda C. P. Thijssen et al.)



https://insightsimaging.springeropen.com/articles/10.1186/s13244-025-01960-4

16/07/2025

🎨 Color Maps in : Time for Standards

The International Society of Magnetic Resonance in Medicine's Quantitative MR Group, is working to standardize color schemes for safer, clearer imaging.

Opinion Open access Published: 17 June 2025 Colour map displays Nandita M. deSouza ORCID: orcid.org/0000-0003-4232-476X1,2, Miha Fuderer3, Nico Sollmann4,5, Barbara Daria Wichtmann6 & …Xavier Golay7,8,9 Show authors Insights into Imaging volume 16, Article number: 127 (2025) Cite this article 456 ...

15/07/2025

Solitary Re**al Ulcer Syndrome (SRUS) can mimic re**al cancer on , but their management is completely different - misdiagnosis can lead to unnecessary treatment.

📌 Xie et al. reviewed scans from 30 SRUS patients and compared them with 120 early-stage re**al patients.

🔍 Key MRI features that helped differentiate SRUS from cancer included:
Unrestricted diffusion
Hypo- or mixed high-low intensity on T2-weighted imaging
Layered enhancement or submucosal edema



https://insightsimaging.springeropen.com/articles/10.1186/s13244-025-01979-7

14/07/2025

🔍 Can Help Predict ’s Disease Treatment Response?

Researchers developed a deep learning model using baseline intestinal ultrasound (IUS) images and clinical data to predict mucosal healing after one year of treatment.

📊 The model showed promising performance:
✅ AUC: 0.73
✅ PPV: 80%

💡 This approach could help tailor treatment strategies earlier - but further validation with larger, real-world data is needed. (Li Ma et al.)



https://insightsimaging.springeropen.com/articles/10.1186/s13244-025-02014-5