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Radiology Study Simulator is not intended for clinical diagnosis and does not provide medical advice. It is designed as a safe learning environment for students, researchers, volunteers, and educators to practice simulating the way radiologists think and structure their reports. While it cannot replace the judgment of a licensed physician, it can serve as a tool for self-learning and understanding radiology and medical reporting language, especially for those in under-resourced or remote areas. By practicing with it, users become more familiar with the language, logic, and reasoning of radiology reports, which helps them communicate more effectively with healthcare professionals.

Worldwide, there is a significant gap between imaging examinations and the availability of structured reports. According to the World Health Organization and GE Healthcare, nearly two-thirds (≈66%) of the global population lacks access to basic imaging diagnostic services. In the United States, only 21% of extremely disadvantaged communities have access to CT, and only 19% have access to MRI. Even when imaging is available, interpretation is inconsistent: daily radiology practice shows 3%–5% error or discrepancy rates, and retrospective studies have found misdiagnosis rates as high as 30%. In teaching hospitals, preliminary reports by junior residents often differ from attending radiologists’ final reports, sometimes leading to recalls or changes in patient management.

Delays and incomplete reporting are also widespread. In some hospitals, as many as 40% of studies remain unreported at certain times. Even when reports are issued, follow-up recommendations are often not acted upon: 14–15% of actionable findings are not completed within the recommended timeframe, and some studies show that more than half (55%) of patients fail to complete their follow-up imaging.

In Asia, similar challenges are evident. In Taiwan, the Ministry of Health has acknowledged that administrative bottlenecks and limited radiologist capacity can result in patients not receiving written reports; even when reports are issued, patients often find them too technical to understand, such as in the case of mammography reports. In Japan, radiologists face extremely high workloads, averaging more than four times the global reporting volume per physician; the Japanese College of Radiology has even identified unread reports as a growing social issue. In Hong Kong, persistent shortages and attrition among radiologists have left the territory with only about 2.16 doctors per 1,000 population, significantly lower than international benchmarks, adding to delays and backlogs in reporting. Across Southeast Asia, while imaging equipment is increasingly available, the lack of trained personnel, report-writing capacity, and follow-up systems often means that scans do not translate into actionable reports. Early deployments of teleradiology have also faced difficulties in generating and returning reports in a timely manner.

Taken together, these observations point to a global reality: “having an imaging study without receiving a timely or understandable report” is not an exception, but a systemic issue. In this context, an education-focused tool such as the Radiology Study Simulator demonstrates clear value. It helps learners and the general public understand structured reporting, practice diagnostic reasoning, and bridge the knowledge gap that often leaves patients confused when faced with real reports.

Because delays, unread reports, and incomprehensible findings are common worldwide, learning how to interpret and practice structured radiology reporting has become an essential educational need. The Radiology Study Simulator was created with this goal in mind: to provide a safe, non-clinical environment where users can walk through the entire process from entering case details to generating structured reports. Below, we explain step by step how the app works.                            

Now that we’ve seen why reporting gaps and delays exist worldwide, let’s walk through how the Radiology Study Simulator works in practice. The app guides you through a structured four-step workflow—Step 0 to Step 4—so that learners can experience the full process of entering case details, uploading imaging, and generating study-style reports.

The first step is Step 0: Choose Case Purpose.

As shown below, you can select one of four modes, and this choice shapes the entire report output:

• A. Initial study – First-time interpretation; produces a ranked differential and suggested next steps.

• B. Follow-up study – Focuses only on describing changes in size, density, or location, without assigning benign vs malignant probability.

• C. Pre-/Post-treatment study – Highlights treatment response and complications.

• D. Emergency-style case – Uses a triage tone, emphasizes urgency, and recommends immediate next actions. 

Step 1 | Enter Basic Case Information (Required)

After selecting the case purpose in Step 0, the next step is to provide the essential details that set the context for the report. These inputs are straightforward but crucial, because they guide how the app frames its interpretation:

• Body part (required): Chest / Brain / Abdomen & Pelvis / Limbs / Other

• Imaging type: X-ray / CT (with or without contrast) / MRI (with sequence if known)

• Study date (optional): YYYY-MM-DD

• Comparison study (optional): Indicate whether an old study is available for side-by-side review (Yes/No)

This stage ensures that every simulated report has a clear anatomical focus, imaging modality, and—when applicable—comparative context.                                                            

Step 2 | Add Background Information (Optional)

To make the simulation more realistic, you can provide additional case background. While not required, these details help the report generation mimic the reasoning process of real radiologists:

• Reported symptoms: e.g., cough, fever, hemoptysis, weight loss

• History notes: e.g., smoking, tuberculosis, cancer, immunosuppression

• Family background: optional but useful for hereditary risk factors

• Lab results or physician notes: typed formats only (such as blood test reports, typed hospital summaries, structured lab sheets).

⚠️ Important: The app can read structured text and numbers, but not scanned handwriting, embedded images, or raw DICOM files inside PDFs.

By adding context such as symptoms or lab values, you get a study-style report that better mirrors real-world decision-making.

Step 3 | Add Other Data (Optional)

At this stage, you can provide additional lab or pathology information to refine the impression. While optional, these inputs help the simulator mimic how radiologists incorporate clinical context:

• Lab-style summaries: e.g., WBC count, CRP, tumor markers, LDH

• Sputum or pathology results (if available): e.g., AFB smear, cytology, biopsy findings

• Previous lab or pathology summaries: typed only; handwritten or image-only scans are not supported

This step is not required, but when included, it enhances the realism of the simulated report by combining imaging findings with clinical and laboratory clues—just like in actual multidisciplinary practice.

Step 4 | Upload Imaging

The final step is to upload your imaging files. The app accepts common formats and provides flexibility for different study types:

• X-ray: Upload as JPG or PNG

• CT / MRI: Export each series as JPG/PNG or MP4

  • MP4 clips should be ≤ ~3 minutes; the app automatically samples 12–15 representative frames from each clip

• Multiple body parts: Upload them separately and label clearly (e.g., “Chest series 1–3”)

Quick DICOM conversion guide:

1. Go to dicomlibrary.com

2. Upload your DICOM or zipped folder

3. Use “View and Export” to convert to JPG/PNG

4. If you have too many images, merge them into a single MP4 (e.g., with Adobe Express: convert images to video, adjust playback speed if needed)

⚠️ Important: PDFs are read as text + embedded images only. The app does not analyze embedded DICOM files.

With this step, the setup is complete—you’re ready to generate a study-style radiology report that follows structured logic and red-flag patterns.

Note: In a separate blog essay, I’ll share a free step-by-step guide on how to convert DICOM files into JPG, PNG, or MP4, so that anyone can prepare their own study images easily.                                                                                                                                

What You Get: Study-Style Reports

Once imaging is uploaded, the simulator generates structured, study-style reports that follow radiology logic.

X-ray Reports (9-Step Structure)

Every X-ray study is summarized in a 9-step report, designed to help learners practice systematic interpretation:

1. Key finding (TL;DR)

2. Global scan findings

3. Key clues (location, morphology, signs)

4. Other possibilities (ranked)

5. Next steps (study suggestion)

6. Small lesion safeguard

7. Red-flag alerts

8. Confidence & limitations

9. Regional checklist

This mirrors how radiologists structure their thought process—balancing main impressions, differentials, and cautionary notes.

CT/MRI Reports (Per-Series + Final Integration)

For cross-sectional imaging, the app produces per-series reports using the same 9-step framework. Afterward, it generates a Final Integrated Impression that consolidates all series:

• Key finding (TL;DR)

• Integrated impression (combined across series)

• Other possibilities (ranked)

• Next steps (study suggestion)

• Confidence & limitations

• Red-flag alerts 

🔎 Extra Note: Don’t Skip the Background Step

While you can technically generate a report after entering only the imaging (Step 4), leaving out key background information (e.g., smoking, alcohol use, prior disease history) may significantly change the impression ranking. In some cases, the simulator may prompt you again at Step 4 with a question like “Do you also want to add history?” — but this doesn’t always happen.

To get the most realistic and educational output, it’s best to enter clinical history fully at Step 2 (Case Background). This reflects how real radiologists think: missing background can lead to different interpretations, and in real-world practice, incomplete information can even affect outcomes in critical settings (e.g., court reviews, medical audits).

1. Example Lesson: Background Changes Everything

In our example, the first report (without smoking history) leaned toward infection as the top possibility. When we re-ran the same X-ray but added smoking history, the report shifted—now highlighting central lung cancer as a higher-priority concern.

This demonstrates a core teaching point: the same image can lead to different impressions once clinical background is considered. That’s why entering history at Step 2 (Case Background) is so important. Without it, the report may underestimate risk; with it, the ranking better reflects real-world reasoning.

⚠️ Pro Tip: If you also include lab reports, typed physician notes, or pathology snippets in Step 2 and Step 3, the report becomes even more accurate and realistic. Just like in real radiology, combining imaging with bloodwork or pathology improves confidence and helps prioritize the right differentials.                                        

FAQs

Can it read DICOM directly?
No. Please export your DICOM files into JPG, PNG, or MP4 before uploading. Embedded DICOM files inside PDFs are not analyzed.

How long can my MP4 be?
Each MP4 should be kept to about ≤ ~3 minutes. The app automatically samples 12–15 representative frames from each clip.

Is this for clinical use?
To be clear, ChatGPT is not permitted to provide medical advice or clinical opinions. This app is strictly limited to academic study and self-learning purposes. It does not make clinical judgments, nor does it speculate about patient care.

What languages are supported?
The default output is in English, but reports can also be generated in Chinese on request.

Can I upload multiple regions in one scan?
Yes. Please upload and label each region separately (e.g., Chest, Abdomen, Pelvis). Each region will receive its own per-series report, and when applicable, an integrated conclusion will be generated.

What kind of PDFs can I upload?
You can upload PDFs containing typed text and numbers (e.g., lab reports, structured physician notes, hospital summaries). However, scanned handwritten notes, embedded images, or DICOM files inside PDFs are not supported.

How do you improve the accuracy of the simulator?
We continuously build a backend “analysis file library.” Cases where ChatGPT-5’s interpretation was less accurate are collected and stored for further review. This helps refine the educational value of the simulator.

Can users contribute if they find inaccuracies?
Yes. If you notice outputs that seem inaccurate, you can share them with us. Selected anonymized cases will be added to the backend analysis files, so that the simulator continues to improve and provide more useful study examples over time.

Although it is called the Radiology Study Simulator, it is not a medical assistant and does not replace professional reporting. Instead, it serves as an educational case-study tool. Users can upload de-identified imaging (X-ray, CT, MRI) and, when available, complement it with medical reports such as typed lab summaries or physician notes.

The purpose is not to provide diagnosis, but to let learners practice structured reporting and understand how clinical context (like lab data or prior reports) changes interpretation. In this way, the simulator functions as a training environment—helping students and educators explore how imaging and case information interact, without making clinical decisions.

Appendix

How to Convert DICOM to JPG/PNG/MP4 for Study:

https://www.ensoulai.com/blogs/blog/how-to-convert-dicom-to-jpg-png-mp4-for-study

References:

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